THOMPSON RIVERS UNIVERSITY

First Nation Government Investing Policy and Community Wellbeing

by

Shawn Blankinship

A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
Masters of Business Administration
KAMLOOPS, BRITISH COLUMBIA

APRIL, 2021

Committee Members:
Dr. Laura Lamb (Supervisor)
Dr. Hasnat Dewan
Dr. Randall Kimmel

© Shawn Blankinship, 2021

ABSTRACT

This study provides deeper insight into the relationship between First Nation
government investing policy and community wellbeing in Canada, and evaluates how
geographic remoteness and population level influence this relationship. Community
wellbeing is measured by Census data and investing policy is measured by First Nation
government financial statements. This study utilizes descriptive statistics, Pearson
correlational analysis, and linear regression. The findings demonstrate that own-source
revenue maintain positive associations with most community wellbeing measures. A negative
association is identified between most community wellbeing measures and higher ratios of
both trust fund assets and tangible capital assets. Transfer revenue from Indigenous
organizations have greater community wellbeing outcomes compared to direct transfers from
the federal/provincial governments. Geographic remoteness is associated with lower
education levels, lower housing conditions, and higher Indigenous language knowledge.
These new insights can inform Indigenous leaders as they shape policy development for the
benefit of First Nations people.

Keywords: First Nation, Indigenous, community wellbeing, investing, policy, regression,
correlation, financial

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ACKNOWLEDGEMENTS

I would like to thank Dr. Laura Lamb for providing support, guidance, and supervision
throughout this study. Her knowledge and expertise were invaluable throughout the research
process and in the writing of this manuscript. I would also like to thank my thesis committee
members Dr. Hasnat Dewan and Dr. Randall Kimmel for their insight, feedback, and
contribution to this study.
I express my thanks to all of the staff at Thompson Rivers University for providing
guidance and assistance through the Masters of Business Administration program and thesis
work. I also thank my former professional colleagues from the firms MNP LLP and KPMG
LLP for the experience and technical knowledge I gained during my time in accounting
public practice.
I also thank my parents, family, friends, and the Ashcroft Indian Band for their support
and encouragement throughout the research process. This achievement would not have been
possible without all of their support.

iii

TABLE OF CONTENTS
Abstract ..................................................................................................................................... ii
Acknowledgements .................................................................................................................. iii
Table of Contents ..................................................................................................................... iv
List of Tables .......................................................................................................................... vii
Introduction ................................................................................................................................1
Chapter 1: Literature Review .....................................................................................................2
Foreign Country Studies of Local Government .................................................................... 2
Financial Indicator Analysis in Local Government .............................................................. 6
Trust Fund Studies ................................................................................................................ 7
First Nation Wellbeing Studies ............................................................................................. 8
First Nation Tangible Capital Asset (TCA) Studies............................................................ 10
First Nation Business and Own-Source Revenue Studies................................................... 11
Other First Nations Studies ................................................................................................. 14
Literature Review – Concluding Statements ....................................................................... 16
Chapter 2: Methodology and Hypotheses ................................................................................18
Definitions ........................................................................................................................... 18
Population Definition .......................................................................................................... 19
Data Source – 2016 First Nation Audited Financial Statements......................................... 20
Data Source – 2016 Census of First Nation Communities ................................................. 22
Categories of Financial Indicators....................................................................................... 22
Subgroup Matrix Based on Population and Geographic Remoteness ................................ 23
Descriptive Statistics and Comparative Analysis ............................................................... 24
Pearson Correlation Coefficient (r) Analysis and Hypotheses............................................ 24
Multiple Linear Regression ................................................................................................. 29
Methodologies and Hypotheses – Concluding Statements ................................................. 31
Chapter 3: Descriptive Statistics and Comparative Analysis ..................................................32
Descriptive Statistics of All Communities .......................................................................... 34
Descriptive Statistics by Population.................................................................................... 39
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Descriptive Statistics by Geographic Remoteness .............................................................. 49
Descriptive Statistics and Comparative Analysis – Concluding Statements ...................... 59
Chapter 4: Pearson Correlation Coefficient (r) Analysis and Hypotheses ..............................60
R Results and Discussion Amongst Demographic Indices ................................................. 62
R Results and Discussion Between Financial Indicators and Demographic Indices .......... 69
Pearson Correlation Coefficient (r) Analysis and Hypotheses – Concluding Statements .. 85
Chapter 5: Multiple Linear Regression ....................................................................................86
Multiple Linear Regression Results Table .......................................................................... 87
Multiple Linear Regression Results Discussion.................................................................. 88
Relationship of the Language Index with the Nation Wellness Index ................................ 91
Multiple Linear Regression – Concluding Statements........................................................ 94
Chapter 6: Conclusion..............................................................................................................95
Strengths and Limitations of the Research Methodologies ................................................. 95
Discussion of Results .......................................................................................................... 97
Areas for Future Research ................................................................................................. 110
Concluding Statements...................................................................................................... 113
Appendix A – Summary of Financial Indicators ....................................................................A1
Appendix B – Summary of Demographic Indices ..................................................................A4
Appendix C – Subgroups of First Nation Communities .........................................................A7
Appendix D – Descriptive Statistics of Demographic Indices with Breakdown Between
Subgroups ...............................................................................................................................A8
Appendix E – Descriptive Statistics of Financial Indicators with Breakdown Between
Subgroups .............................................................................................................................A11
Appendix F – T-test Statistic Details ....................................................................................A35
Appendix G – Descriptive Statistics Analysis and T-test Results by Population and
Geography ...........................................................................................................................A143
Appendix H – Descriptive Statistics Analysis and T-test Results of Demogrpahic Indices by
Subgroup .............................................................................................................................A149
Appendix I – Descriptive Statistics Analysis and T-test Results of Financial Indicators by
Subgroup .............................................................................................................................A155
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Appendix J – R Results Between Business Activity Indicators and Demographic Indices
.............................................................................................................................................A186
Appendix K – R Results Between Government Business Entity (GBE) Activity Indicators
and Demographic Indices ..................................................................................................A191
Appendix L – R Results Between Trust Activity Indicators and Demographic Indices ...A196
Appendix M – R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices ......................................................................................................... A199
Appendix N – R Results Between Other Activity Indicators and Demographic Indices .. A203
Appendix O – Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups ..................................................................... A208
Appendix P – Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population ......................................... A216
Appendix Q – Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups .................................................... A222
Appendix R – Correlational Instance Scatterplots and Line of Best Fit Graphs ............... A233
Appendix S – Relationship of the Language Index with the Nation Wellness Index........ A324
Appendix T – Professional Experience of Author ............................................................. A333
Appendix U – Stratified Trust Activity Correlational Analysis ........................................ A334

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LIST OF TABLES
Table 1: Terms and Definitions .............................................................................................. 18
Table 2: Number of First Nation Communities in Study........................................................ 20
Table 3: Summary and Mnemonic Labels of Subgroups........................................................ 24
Table 4: Demographic Indices Correlational Hypotheses ...................................................... 26
Table 5: Underlying Investment Policies by Financial Indicator Category and Correlational
Hypotheses .............................................................................................................................. 27
Table 6: Correlation Hypotheses Summary ............................................................................ 29
Table 7: Linear Regression Models ........................................................................................ 30
Table 8: Description of Independent Variables ...................................................................... 31
Table 9: Appendices Relating to Descriptive Statistics and Comparative Analysis Chapter . 33
Table 10: Descriptive Statistics of All Communities - Business Activity Indicators ............. 34
Table 11: Descriptive Statistics of All Communities – Government Business Entity (GBE)
Indicators................................................................................................................................. 35
Table 12: Descriptive Statistics of All Communities - Trust Indicators ................................. 36
Table 13: Descriptive Statistics of All Communities - Tangible Capital Asset (TCA)
Indicators................................................................................................................................. 36
Table 14: Descriptive Statistics of All Communities - Other Indicators ................................ 37
Table 15: Descriptive Statistics of All Communities - Demographic Indices ........................ 38
Table 16: Descriptive Statistics by Population - Business Activity Indicators ...................... 39
Table 17: Descriptive Statistics by Population - Government Business Entity (GBE)
Indicators................................................................................................................................. 41
Table 18: Descriptive Statistics by Population - Trust Indicators .......................................... 42
Table 19: Descriptive Statistics by Population - Tangible Capital Asset (TCA) Indicators .. 43
Table 20: Descriptive Statistics by Population - Other Indicators (Part 1)............................. 45
Table 21: Descriptive Statistics by Population - Other Indicators (Part 2)............................. 46
Table 22: Descriptive Statistics by Population - Demographic Indices ................................. 48
Table 23: Descriptive Statistics by Geographic Remoteness - Business Activity Indicators . 50
Table 24: Descriptive Statistics by Geographic Remoteness – GBE Indicators .................... 51

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Table 25: Descriptive Statistics by Geographic Remoteness - Trust Indicators ..................... 52
Table 26: Descriptive Statistics by Geographic Remoteness - Tangible Capital Asset (TCA)
Indicators................................................................................................................................. 53
Table 27: Descriptive Statistics by Geographic Remoteness - Other Indicators (Part 1) ....... 55
Table 28: Descriptive Statistics by Geographic Remoteness - Other Indicators (Part 2) ....... 56
Table 29: Descriptive Statistics by Geographic Remoteness - Demographic Indices ............ 58
Table 30: Appendices Relating to Pearson Correlation Chapter ............................................ 61
Table 31: R Summary Between Demographic Indices - Total Population ............................. 62
Table 32: R Summary Between Demographic Indices - Subgroup SC .................................. 62
Table 33: R Summary Between Demographic Indices - Subgroup SM ................................. 63
Table 34: R Summary Between Demographic Indices - Subgroup SR .................................. 63
Table 35: R Summary Between Demographic Indices - Subgroup MC ................................. 63
Table 36: R Summary Between Demographic Indices - Subgroup MM ................................ 64
Table 37: R Summary Between Demographic Indices - Subgroup MR ................................. 64
Table 38: R Summary Between Demographic Indices - Subgroup LC .................................. 64
Table 39: R Summary Between Demographic Indices - Subgroup LM ................................. 65
Table 40: R Summary Between Demographic Indices - Subgroup LR .................................. 65
Table 41: R Summary Between Business Activity Financial Indicators and Demographic
Indices – Total Population ...................................................................................................... 69
Table 42: R Summary Between Government Business Entity (GBE) Activity Financial
Indicators and Demographic Indices – Total Population ........................................................ 70
Table 43: R Summary Between Trust Activity Financial Indicators and Demographic Indices
– Total Population ................................................................................................................... 74
Table 44: R Summary Between TCA Financial Indicators and Demographic Indices – Total
Population ............................................................................................................................... 78
Table 45: R Summary Between Other Financial Indicators and Demographic Indices – Total
Population ............................................................................................................................... 81
Table 46: Multiple Linear Regression – Average Marginal Effects of Variables with
Demographic Indices .............................................................................................................. 87
Table 47: Strengths and Limitations of Descriptive Statistics and Comparative Analysis
Methodology ........................................................................................................................... 95
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Table 48: Strengths and Limitations of Pearson Correlation Coefficient (r) Analysis ........... 96
Table 49: Strengths and Limitations of Multiple Linear Regression ...................................... 97
Table 50: Education, Housing, and Language Indices by Affected Subgroup ..................... 107

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Introduction
This thesis will provide deeper insight into the relationship between First Nation
government investing policy and First Nation community wellbeing in Canada. New insights
will be gained to assist community leaders in the development of sound investing policy for
local First Nation governments. The insights will be applicable not just to a specific
government or organization, but to community leaders, policy makers, and First Nation
people across Canada.
The first research objective is to determine the relationship between First Nation
government investing policies and First Nation community wellbeing. The second research
objective is to evaluate how geographic remoteness and population levels influence this
relationship. By utilizing both community demographic data from Statistics Canada and First
Nation government financial statements, new insights will be gained to inform First Nation
leaders in policy development.
The strengths of this study include the ability to analyze data from over 400 First
Nation governments, the high level of detail available in the audited financial statements, the
use of clearly defined and objective quantitative measures, and the ability to correlate First
Nation government financial indicators with community demographic indices. There has
been limited research utilizing First Nation financial statement data when evaluating
community wellbeing. This cross-sectional correlation study will fill an important
information gap with the goal of providing insight to improve the lives of First Nation people
across Canada.

1

Chapter 1: Literature Review
Due to the uniqueness of this study, a broad literature review has been conducted to tie
in multiple disciplines and academic foundations. Key areas of focus include First Nation
wellbeing studies in Canada, applicable foreign country studies, the use of ratio analysis in
local government, trust fund studies, tangible capital asset studies of First Nations, First
Nation business and own-source revenue studies, and other First Nation studies. The
following sub-sections provide an overview of the literature for each area of focus, and
provide valuable insight into the research of this study.
A key research objective of this thesis is to understand the relationship between First
Nation government investing policy and community wellbeing. This literature review lays
the academic foundation for this objective by evaluating existing research in the distinct
areas of First Nation government investing policy and First Nation community wellbeing.
The literature has strong insights in the factors affecting First Nations wellbeing. These
insights can be used to develop hypotheses that can be tested empirically in this manuscript.
Likewise, the current literature evaluating own-source revenue, tangible capital assets, and
trust funds provide a framework for how these investing activities may impact First Nation
communities. This manuscript then expands on the existing literature to statistically test the
relationship between these investing policies and First Nation community wellbeing. The
other literature topics also provide insights from international studies, issues around local
economic development, and the effects of land/property regimes in Canadian First Nation
communities. The topics in this thesis are a natural extension of the existing literature.

Foreign Country Studies of Local Government
Local governments around the world often address similar issues and concerns, many
of which are shared with Canada’s First Nation governments. By evaluating foreign country
studies of local government, the shared issues can provide insight and possible policy
solutions for First Nation governments in Canada. Literature will be reviewed from Russian,
Chinese, and Japanese studies.
Eugenievna & Yakovlevna (2014) evaluated municipal financing policy in Russia’s far
north communities. A common theme surfaced that many of these communities received
significantly less own-source revenue compared to their more southern and urban municipal
counterparts. This resulted in less autonomy, and the inability to implement their own long2

term investing policies. Critical investing decisions would then be made by federal/regional
government officials without a direct understanding of the local needs. Key capital
expenditures noted in this study include housing, municipal infrastructure, and communal
services. An exception to federal/regional reliance was communities with strong business
activities within their municipalities. The local business was able to provide additional
municipal revenue in the forms of taxation and land lease fees (from municipal owned land).
There are notable similarities between Russia’s far north municipalities and remote
First Nation communities in Canada. Both have a strong reliance on federal/regional revenue
transfers, and both are responsible for key capital infrastructure. Eugenievna & Yakovlevna
(2014) demonstrate that communities with a stronger business presence are in a better
financial position to provide much needed capital investment within their communities. For
Canada’s First Nation communities, the local government is often a key player in local
business activities. Due to the similarities between Canada’s First Nation communities and
those municipalities noted in this Russian study, many of the findings from Eugenievna &
Yakovlevna have relevance when evaluating First Nation governments in Canada.
Su & Tao (2017) studied the economic development of local Chinese governments, and
how they developed over the past several decades. This study notes that many local
governments in China started as business owners (state owned), and would thus be motivated
to give preferential treatment to their own businesses. In the 2000’s, many local Chinese
governments made a transformation from business owners to tax collectors. Three main
sources of local government revenue came from land lease fees, sales tax, and business tax
(Su & Tao). The local Chinese governments often had exclusive rights to the local land, a
situation that is mirrored by many First Nation communities in Canada. Utilizing local land
for development purposes became a strong source of revenue for local Chinese governments.
It is possible that a similar strategy could be utilized by Canadian First Nations. Success in
this area has already been seen by communities such as the Westbank First Nation (WFN),
where commercial development on its lands has provided a strong source of funding for
economic development. According to the WFN website, over 450 businesses operate on
WFN lands, along with numerous residential developments (Westbank First Nation, 2020).
Su & Tao’s study suggests that providing taxation and land-use autonomy to local
governments can lead to innovation in developing local economies and obtaining needed
3

revenue sources for local government. This principle of tax autonomy and greater selfdetermination over lands can also be applied to Canadian First Nation governments in their
pursuit to improve the lives of their First Nations people.
Shirai (2005) evaluates the relationship between local governments in Japan and the
federal Japanese government. This study finds that local Japanese governments do not have
sufficient autonomy in establishing a local tax base. The tax structure in Japan makes local
governments reliant on federal transfers. This has led to inequitable transfer payments based
on federally controlled transfer metrics. An issue noted in this study is how low-income
governments receive a higher portion of transfers, which has led to waste and inefficient
spending. This also leaves other governments with a lower proportion of federal transfers.
The issue of inequitable transfer payments also exists for First Nation governments in
Canada.
Herrmann-Pillath & Xingyuan (2004) studied the fiscal arrangements of Chinese local
governments and the impact of land usage on the government’s finances. This study found
that investment financing often came from non-budget sources. A key non-budget source
noted in the study includes the use of public lands. Local governments in China often have
exclusive rights to the use of public lands, and can receive revenues via rent, lease, property
tax, and capital gains on non-agricultural land (Herrmann-Pillath & Xingyuan, 2004). Note
that due to the communist environment in China, collective land ownership has been the de
facto norm in the past. Property rights have developed over the past several decades in China,
and provided a new source of revenue for local Chinese governments. There are several
parallels when considering local First Nation governments in Canada. First Nation land
(reserve land) is often controlled by the First Nation government, albeit in trust via the
federal government. Note that some exceptions can exist, where certificates of possession are
granted to individual First Nation members. The study of Chinese local government suggests
that the development of sound legal property rights can provide significant own-source
revenue for local government. This same principle could be applied to Canadian First Nation
governments through the development of a formal property rights system for reserve lands.
Such a system is already present in some First Nations communities, such as the Westbank
First Nation (2020).

4

De Soto (2000) discusses capital and private property ownership and the common
difficulties when developing nations try to implement legal systems of private property. In
the absence of a legal private property system, informal and extralegal systems will already
be in place. Even if informal private property arrangements do not have legal authority, they
can often have the social consensus of the people involved. De Soto emphasizes the need to
closely consider these informal systems when attempting to implement private property
reforms. This situation is applicable to many First Nation communities across Canada when
private property rights on reserve lands are not currently in place. While legal reform would
be required to implement private property rights in many First Nation communities, de Soto
stresses that this type of reform must be led through political reform. Local political
leadership is a prerequisite for the successful transition to a formal and legally recognized
system of private property. Local Indigenous leaders must play a critical role if private
property systems are to be implemented in First Nation communities across Canada.
Li et al. (2019) evaluated the strategy of co-production in local Chinese communities.
This study defines co-production as a cooperative approach to provide public goods and
services, with an emphasis on grassroots participation in this service delivery. The formal
structure of how this takes place varies, and often includes several entities such as
community organizations, non-profit organizations (NPO), private business, or local/regional
government to name a few. This study found that most of the government funded coproduction was towards infrastructure projects (such as public housing or sewage upgrades).
Key benefits of a co-production approach can include items such as hearing local suggestions
via local community organizations, the ability to gain consensus at the local level prior to
starting major projects, the ability to harness volunteers to complete the projects, and a
unique blending of private, public, and NPO entities to complete projects. This type of
approach may be appropriate for First Nations communities in Canada, many of whom seek
to gain stronger local representation in key infrastructure projects.
Many of Canada’s First Nation communities seek to gain greater independence from
the federal and provincial governments, and strive for the goals of self-determination and
greater autonomy. The international studies demonstrate that these concerns of Canadian
First Nations are shared with communities around the world. Many of the policy solutions
observed around the world can be applied to Canada’s First Nation communities to improve
5

their wellbeing. Common themes that have been explored are finding methods to bolster
own-source revenue to reduce reliance on centralized governments, increasing taxation
flexibility at the local level to allow innovative tax policy to meet local governments’
revenue requirements, and developing co-production capacity to provide a greater voice for
local communities in infrastructure and development projects.

Financial Indicator Analysis in Local Government
Formal methods to evaluate local government financial performance and policy
implementation have long been used within governments. This section reviews common
financial analysis techniques that can provide meaningful insight for policy makers and local
leaders.
Rivenbark & Roenigk (2011) developed a model to make municipal financial
statements more applicable for policy decision making. Two key steps are involved in this
model, and include utilizing ratio analysis to determine relationships between financial
figures and using comparative analysis either over time or between different governments.
Rivenbark & Roenigk (2011) identify a capital asset condition ratio, which can be interpreted
as the degree of government investment in capital assets. This provides a link between a
capital asset financial indicator and an investing policy. Rivenbark & Roenigk (2011) also
identify a dependency financial indicator that measures the extent of dependence on
federal/regional governments. These are examples of direct links between financial indicators
and the underlying policies in play within local government.
Groves et al. (1981) utilized a technique called indicator analysis. This technique takes
data from a variety of sources, including financial statements, census demographics data, and
census economic data. This technique analyzes the data via ratios and indices, and then
compares these ratios/indices amongst each other to identify relationships. These
relationships can then be compared amoung multiple local governments. As outlined by
Groves et al. (1981), legislative policies can have a multitude of goals. Some may relate to
revenue growth, expanded public expenditures, or replenishment of public capital assets to
name a few. Many of these policies have relating financial indicators, which can be used as a
measure of the underlying policy.
These studies demonstrate that financial indicator analysis and comparative analysis
can provide valuable insight into the operations and effectiveness of municipal governments.
6

This insight can now be applied to Canada’s First Nation communities, as First Nation
government financial statements started being prepared and became publicly available in
2014.

Trust Fund Studies
Trust funds can be used by governments to smooth income over time, but require a
strong governance structure to be effective. This section evaluates how trust funds can be
utilized by governments to provide an inter-generational benefit over the long-term.
Angelo et al. (2016) study the use of intergenerational trust funds by Pacific island
nations. These trust funds are often funded by foreign nations or private donors. The goal of
these trust funds is to provide a stable source of income for the Pacific island governments
that will last over the long-term. While the situation for the Pacific island nations is unique,
there are some similarities with Canadian First Nation governments. Both governments seek
to provide a stable long-term income, and use a trust fund structure to accomplish the task.
For these trust funds to be successful, four core principles were discussed (Angelo et al.,
2016). First is to establish a strong legal structure, second is to establish competent
management, third is to develop clearly defined investment policy and oversight, and fourth
is to set up a strong accountability system, such as requiring third-party audits. As many First
Nation communities are utilizing intergenerational trust funds, these four principles should be
followed to ensure that the trust funds continue to provide value for the First Nation
communities.
Rodon et al. (2018) study revenue allocation strategies of impact benefit agreements
(IBAs) on community development in Canadian First Nation communities. IBAs are a
common mechanism for local First Nation governments to receive financial benefits from
natural resource development on their lands. IBAs are common within mining, forestry, and
other natural resource agreements made with First Nation governments. This type of revenue
is often unevenly disbursed, so there is a desire to provide a more even distribution of the
benefit over multiple years. Trust funds can be an effective structure for accomplishing this.
Rodon et al. (2018) discuss how trust funds can provide inter-generational equity, and can
provide a buffer between the funds and the local government (if the trust governance is set up
appropriately). This can provide a much more sustainable approach, and avoids the bustboom cycle present in many natural resource industries. A disadvantage of trust funds is that
7

not all the funds are spent immediately, which may limit the ability to address the immediate
needs of the community. Rodon et al.’s study suggests that First Nations utilizing trusts funds
may have a more stable level of community wellbeing.
Trust funds have been used by Canadian First Nation communities to normalize
income from impact benefit agreements and land claim settlements. Similar trust structures
have been used internationally by several Pacific island nations. These trust structures can be
effective tools to smooth income over multiple years, and provide a benefit to future
generations. In order for these trust funds to be successful, several principles must be in
place, and include a sound legal structure, competent management, strong investment policy,
and strong accountability.

First Nation Wellbeing Studies
Numerous studies have been conducted that assess the wellbeing of First Nations
people in Canada, and evaluate wellbeing from a holistic perspective. The traditional
measures of employment, income, education, and housing are evaluated. An expanded array
of factors is also considered, which include indicators for health, social capital, and
connection to traditional culture. The importance of these factors is reviewed, along with
common research methodologies in First Nation wellbeing studies.
A common methodology used in First Nations wellbeing studies research is regression
analysis. Hossain & Lamb (2012) utilize regression analysis when evaluating the impact of
social capital on Aboriginal employment income. Another method discussed by Peck (2013)
is the utilization of predicted endogenous subgroups. Establishing meaningful subgroups can
allow the researcher to avoid the “average treatment effect” (Peck, 2013, p. 232) and provide
a deeper understanding of statistical relationships that are unique to given subgroups.
The existing body of wellbeing research of Aboriginal populations indicate strong links
between education levels and outcomes such as income and employment. Hossain & Lamb
(2012) found support for a causal link indicating that good health and social capital have an
impact on employment income of the Canadian Aboriginal population. This insight can
provide policy makers with new strategies for closing the income gap for Aboriginal peoples.
An Australian study of urban Aboriginal populations found that successful social outcomes
are interlinked with outcomes in other areas (Reeve & Bradford, 2014). This suggests that a
holistic approach is required to increase the social wellbeing of Aboriginal peoples.
8

Hossain and Lamb (2019A) evaluated the relationship between cultural attachment and
psychological wellbeing for Canadian Indigenous people, and found a strong relationship
between these two variables. This correlation was particularly notable for Indigenous
populations living in rural areas. Cultural attachment was measured by knowledge of
Indigenous language and level of involvement in traditional activities. This provides an
indication that Indigenous culture plays an important role for the wellbeing of rural
Indigenous peoples. Hossain and Lamb (2019B) also found statistically significant
relationships between economic security and Indigenous psychological wellbeing. The key
factors of economic security used in the study include employment, food security, and the
state of residential housing. This demonstrates that meeting physiological needs is important
in ensuring Indigenous wellbeing.
Axelsson et al. (2016) consider Indigenous wellbeing in the context of the colonial past
that Indigenous peoples had to endure. Issues such as self-determination and autonomy are
emphasized. A very practical issue brought up by Axelsson is the lack of data available for
many Indigenous populations. This limits the ability of policy makers and community leaders
to make informed decisions for Indigenous populations.
Kant et al. (2014) conducted a case study of two Canadian First Nation communities,
and found that overall wellbeing is very complex and is impacted by numerous factors.
While traditional economic factors (such as employment or income) do have an impact on
wellbeing, other factors such as social ties, cultural attachment, and connection with
traditional land are also essential to the wellbeing of First Nations communities. This
emphasizes that First Nation wellbeing must take a holistic approach to improve the lives of
First Nations people.
Finlay et al. (2010) discuss an approach utilized by the organization Mamow-Sha-waygi-kay-win, a charitable organization that seeks to build partnerships between First Nation
communities, government organizations, and private charitable donors. Two key principles
of this organization are to establish long-term commitments and to actively encourage
learning between First Nation communities. The long-term focus allows for measurable
metrics to be observed over time, and provides a feedback mechanism to determine if
specific goals are met. The learning between First Nations encourages community members
who have successfully achieved goals in their community to be involved in the goal setting
9

for similar projects in newly identified First Nation communities. This allows for the sharing
of knowledge, and the building of new networks that can improve the likelihood of success.
The concept of wellbeing for First Nation communities is very complex, and is
influenced by many varying factors. The studies reviewed demonstrate that a holistic
approach is required to properly understand wellbeing from a First Nations perspective. The
traditional wellbeing factors of income, employment, educational attainment, and housing are
important, but these cannot be the only considerations. Existing research of Canada’s
Indigenous population has shown strong relationships between wellbeing and cultural
attachment, traditional land usage, and self-determination. This study considers a unique
approach, and seeks to better understand the relationship between First Nation government
investing policy and its impact on community wellbeing. By better understanding the many
factors of wellbeing, policy makers will have more tools and insight to improve the
conditions for their communities.

First Nation Tangible Capital Asset (TCA) Studies
First Nation governments are often responsible for key capital infrastructure within
their communities, and include such items as water/sewer infrastructure, housing,
government/community buildings, or business owned capital assets to name a few. The
following studies evaluate how capital asset investment can impact local First Nation
communities, and common issues that can affect capital asset policy.
Clatworthy (2009) identifies a key distinction of on-reserve First Nation housing – the
reality that most First Nation communities’ housing is collectively owned and does not
mirror a free real estate market. A significant portion of on-reserve housing is owned by the
local First Nation government. As a de facto landlord for its members, these governments are
responsible for providing housing units that meet the needs of the community. Clatworthy
(2009) discusses that further capital investment in housing is required to bring the housing
standard of First Nations communities up to the national average. Note that this study was
based on 2001 housing data. In 2001, the total percentage of housing requiring major repairs
was 36.0% (Clatworthy, 2009). In 2016, the percentage of housing requiring major repairs
was reported as 39.5% (Indigenous Services Canada, 2019). Note that both sources utilized
housing metrics as reported by Statistics Canada. This trend is concerning, as housing
conditions play an important role in Indigenous wellbeing.
10

Mignone & Henley (2009) studied the impact of information and communications
technology (ICT) on social capital in Canadian First Nation communities. The study finds
that access to broadband internet has a positive effect on First Nations, particularly in the
areas of business opportunities, education, employment, income, and health. Some First
Nations have created and invested in regional telecommunication companies that provide
ICT services, such as internet and telephone. The investment would often take the form of a
corporation, and would be operated as a government business entity (GBE or Nation owned
business that operates independently from the Nation government). Mignone & Henley
(2009) found that ICT investment in remote communities significantly increased the potential
benefit to the community.
O’Gorman & Penner (2018) studied the impact of water infrastructure spending on
First Nation wellbeing. This study found a number of First Nation communities where
members do not have access to residential running water and flush toilets. This study found
that on-reserve First Nations without running water or flush toilets were four times more
likely to report an illness. This study also found that those required to haul water were 63%
more likely to report missing school or work due to a waterborne illness (O’Gorman &
Penner, 2018). This suggests that higher levels of TCA indicators would be positively
correlated with higher education, workforce, and income levels.
First Nation governments are tasked with providing capital infrastructure for their
communities. Some of the major categories of TCAs are water/sewer infrastructure,
community/government buildings, social housing, or capital assets of Nation owned
businesses (excluding GBEs). The studies reviewed demonstrate that this capital
infrastructure is crucial for the continued wellbeing of First Nation communities. This
infrastructure is particularly important for remote communities that may not be able to rely
on infrastructure from other levels of government or private utility companies. It follows that
higher levels of capital infrastructure would provide a higher degree of wellbeing for First
Nation communities.

First Nation Business and Own-Source Revenue Studies
First Nation governments have the ability to generate own-source revenue, which often
comes in the form of Nation owned businesses. The following studies evaluate the impact

11

that own-source revenue can have on First Nation communities, and how specific social
outcomes may be affected.
Boyd & Trosper (2010) conducted a case study of two forestry joint ventures (JVs) that
were pursued by two different First Nations in British Columbia. The JVs were with nonAboriginal for-profit companies. Two items noted in this study were the impact of the JV on
local First Nation employment and training/education. Both First Nations studied found
significant employment opportunities for local First Nation members. One JV had 100% First
Nation employees, while the other maintained 30% First Nation employees. While both JVs
did provide some educational opportunities, the benefit was not significant and was not
ongoing. These businesses generally preferred to hire employees that already had the
required education.
Richards & Krass (2015) published a commentary on how First Nations spend their
own source revenue. This commentary concluded by stating that a “disturbing result of our
analysis is the large incremental impact of own-source revenue on band administration in
general.” (Richards & Krass, 2015, p. 9). This seems to imply an increase in general
administration expenses. Upon further review of what was included in this band
administration expense, this includes spending on band owned businesses (such as cost of
sales or general business expenses) that are not development corporations (Richards & Krass,
2015). Effectively, this means that there are business expenses included in this study’s
definition of band administration in general. It is expected that business expenses would
increase when own-source revenue is present. The conclusion reached by Richards & Krass
could be misleading for readers. This demonstrates the importance of closely evaluating the
source and definition of all statistical figures.
Simpson et al. (2007) studied methods to close the economic gap for First Nations in
northern Manitoba. Two key findings were that long-term employment was not always
achieved due to the short-term nature of some resource development industries, and the lack
of relevant skills found in the local First Nation workforce. This suggests that economic
development activities can only increase the workforce and income indices when relevant
education levels are already present within a community. An emphasis is put on the “already
present” aspect of the education levels. Simpson et al. (2007) stress the need for a long-term

12

educational plan that is part of a larger capacity development strategy. This emphasizes the
importance of education for successful increases to the workforce and income indices.
Dylan et al. (2013) conducted a case study of Moose Cree First Nation (MCFN),
located in northern Ontario. MCFN entered into agreements with De Beers for a mining
operation, and with Ontario Power Generation for the redevelopment of power dams. The
study conducted a series of interviews with local community members and leaders. Out of
the 17 individuals interviewed, 14 were in favour of the resource development agreements. A
key reason cited in the study was employment opportunities, especially for the youth of the
community. The assumption that many of the community members had was that the
economic development would generate employment and income opportunities for
community members. This suggests that greater business activities would result in higher
workforce and income indices.
Vining & Richards (2016) evaluated the relationship between own-source income and
the community wellbeing index (per Statistics Canada). The study found a modest correlation
between these two variables. While a statistical correlation was found, it was not substantial.
Other factors that were discussed to improve community wellbeing included better
organization and funding for key services such as education (Vining & Richards, 2016).
Mahoney (2018) evaluated an educational fund settlement, and noted a link between
educational funding and increased employment prospects. By enabling First Nation members
to pursue higher education, this can result in more meaningful employment and income
potential.
First Nation governments can seek out business development opportunities as an
additional source of revenue, and to provide its members with employment and training
opportunities. The additional revenue can be used to provide needed services within the
community that in turn boost the community’s wellbeing. Likewise, new employment
opportunities for Nation members can provide numerous personal and social benefits within
the community. The studies reviewed demonstrate that business development has the
potential to improve conditions within the community, particularly when training
opportunities are provided along with employment.

13

Other First Nations Studies
The issues of land management, property rights, and economic leakage can
significantly impact the wellbeing of First Nation communities. Another important factor
impacting First Nation wellbeing is knowledge of Indigenous language. The following
studies highlight these topics and how they relate to Canadian First Nation communities.
Fligg & Robinson (2020) reviewed the relationship between First Nation land
management regimes and community wellbeing. The three regimes discussed are the Indian
Act land management (IALM), the First Nations land management (FNLM), and selfgovernment land management (SGLM). A common difficulty cited for the IALM is the
inability to use land as leverage when obtaining financing. Without the land, many
commercial financial institutions will not provide financing to First Nation governments, or
to members who would otherwise be able to obtain financing against home equity. This
greater availability of financing could be used to finance possible entrepreneurial activities,
and thus boost the local economy. FNLM and SGLM provide provisions that allow for such
financing. Fligg & Robinson (2020) found that communities using the IALM regime had on
average the lowest community wellbeing index.
Mirzaei et al. (2020) studied the impact of economic leakage from First Nation
communities in Saskatchewan. The study found that the economic leakage rates for the First
Nation economies studied is 90% - meaning that 90% of all good and services purchased by
First Nations members and governments were spent off of the reserve. This leakage
compounds due to a multiplier effect; a local business would often require support services
and provide local employment. This multiplier effect is provided off of the reserve, and
supports the surrounding regional economy instead of the local First Nation community.
Mirzaei et al. (2020) provide a list of recommendations to prevent this economic leakage.
Some of the items discussed are to develop local entrepreneurship to promote local economic
development, to seek out strategic partnerships to foster business development, and to
establish final consumer businesses on reserve.
The system of land management has been shown to impact the wellbeing of the First
Nation communities. Communities using the Indian Act land management system have the
lowest average community wellbeing. Another issue affecting First Nation wellbeing is
economic leakage, where economic and business opportunities are lost within First Nation
14

communities. This occurs when a large portion of goods/services are purchased outside of the
local community, and thus results in lost business and employment opportunities for Nation
members. Establishing strong local businesses and initiating land management reforms may
be able to boost local First Nation wellbeing.
Jewell (2016) evaluates the perceptions of urban Indigenous people in Canada towards
the importance of Indigenous language. Jewell conducted a multiple linear regression with
the importance of language as the dependent variable. The study found that language
exposure in the home and outside the home maintained the strongest link to perceptions of
the importance of Indigenous language. This link is intuitive, and Jewell provided statistical
evidence of this connection. While exposure to language resulted in a positive relation,
higher education levels resulted in a negative relation as demonstrated by the negative
coefficient. This latter finding is unexpected and is somewhat troubling. It is important not to
jump to a causal conclusion regarding this connection, as the dynamics of the relationship are
likely very complex. Regardless, Jewell provides greater insight into how urban Indigenous
people in Canada perceive the importance of Indigenous language and the factors that
influence this perception.
McIvor & Ball (2019) consider Indigenous language revitalization policies in Canada
and provide international examples of how non-dominant languages have been successfully
incorporated into formal educational institutions. This paper notes that there is no national
infrastructure in place to support Indigenous language within formal educational institutions.
While there are local examples of Indigenous language immersion schools, these institutions
often have to create the infrastructure and curriculum solely at a local level. McIvor & Ball
propose the creation of an Indigenous led organization that networks First Nation
communities together to share knowledge and resources to facilitate new and successful
language renewal programs. This organization could also present a united voice to the federal
and provincial governments in Canada to promote Indigenous language renewal across the
country.
Gomashie (2019) studied the language revitalization efforts of the Kanien’keha and
Mohawk peoples in Canada. Gomashie emphasizes the importance of Indigenous language to
Indigenous identify, particularly as language is a facet for cultural heritage, traditions,
philosophies, and worldviews. An important issue to consider is why knowledge of
15

Indigenous languages is currently low in many communities. The residential school system
in Canada forced many Indigenous children from their homes, and also forced the dominant
culture onto these Indigenous children. Gomashie discusses how Indigenous children would
be punished for practicing their traditional culture, or for speaking their Indigenous language.
Historically, education systems in Canada were used to forcibly destroy knowledge of
Indigenous language amoung younger generations. The residential school system forced an
involuntary loss of Indigenous language on the First Nations people across Canada in a very
brutal manner. Due to this, there are multiple generations of First Nations people that could
not learn their native languages. Even though the residential school system has ceased
operating, the cultural damage has already been done. A key question brought up by
Gomashie is: how can Indigenous languages be renewed when entire generations of
Indigenous people have little or no knowledge of the native languages?
Gomashie discusses the Kanien’keha’s school immersion program, where elementary
and secondary schools are taught in a bilingual method of English and Kanien’keha. This
program has been very successful at increasing the number of fluent people who can speak
Kanien’keha, especially amoung the younger generation. Children are often apt to learn
languages at young ages, and the bilingual school provides an environment for the younger
generation to actively use the language. This allows for a very rich passing on of
Kanien’keha cultural identity to new generations. Implementing these types of programs now
are important, as many fluent Indigenous language speakers are elderly. Utilizing their
knowledge of the language now is very important for the survival and renewal of Indigenous
language.

Literature Review – Concluding Statements
This chapter has reviewed key First Nations studies relating to investing policies,
community wellbeing, own-source revenue, and economic development. This provides a
strong framework for understanding the factors impacting Canada’s Indigenous population,
and for developing the hypotheses outlined in the following chapter. By building upon the
existing research, this study will take a new approach by evaluating the relationship between
First Nation government investing policies and demographic wellbeing measures. Several
studies about the role of Indigenous language to cultural identify have been reviewed, which
demonstrate the importance of Indigenous language to First Nations wellbeing.
16

Foreign country studies were also reviewed, and demonstrate that many of the issues
faced by Canadian First Nation governments have also arisen in other parts of the world. By
studying how these issues were addressed elsewhere, First Nation policy can be better
informed to meet and overcome these common challenges. Finally, this section evaluated the
various land management systems used in Canada’s First Nations, and the issue of economic
leakage. Land usage is often an important component of economic development and potential
own-source revenue, which is a key subject evaluated in this manuscript. Likewise, policies
that boost entrepreneurial activities and business development within First Nation
communities are expected to have a meaningful relationship with community wellbeing.
These relationships will be closely evaluated, as outlined in the hypotheses in the following
chapter.

17

Chapter 2: Methodology and Hypotheses
As the methodologies are discussed, it is helpful to recall the research objectives of this
thesis. As stated in the introduction, the objectives are to determine the relationship between
First Nation government investing policies and First Nation community wellbeing, and to
evaluate how geographic remoteness and population levels influence this relationship. This
section discusses the quantitative analysis that will be utilized, and the data sources used. The
key topics discussed are definitions, population definition, data sources, financial indicator
categories, subgroups used in comparative analysis, descriptive statistics and comparative
analysis, Pearson correlation analysis and hypotheses, and multiple linear regression.

Definitions
For ease of discussion, Table 1 provides definitions for terms used throughout this
manuscript. The comparative analysis evaluates communities based on geographic
remoteness and population level, so the following definitions will be important for the reader.
Note that Indigenous Services Canada (n.d.b) classifies each First Nation community in a
geography zone from 1 to 4. These geography zones are used to establish geographic
categories in this study. Definitions are also provided in reference to the financial indicators.
Table 1: Terms and Definitions
Term
Geographically close
Geographically medium
Geographically remote

Small population
Medium population
Large population
Financial indicators
Ratios
Capita measures

Statistical significance

Definition
Refer to communities in geography zone 1, or within 50km of
a service centre with year-round road access
Refers to communities in geography zone 2, or between 50km
and 350km of a service centre with year-round road access
Refers to communities in geography zone 3 (community
located over 350km to service centre with year-round road
access) or geography zone 4 (no year-round road access to a
service centre)
Community with a population less than or equal to 200
Community with a population between 201 and 999
Community with a population greater than or equal to 1,000
Financial figures from the First Nation government financial
statements, and can include both ratios and capita measures
Accounting ratios (e.g. gross business revenue/total revenue)
Indicators measured on a per capita basis (e.g. gross business
revenue/community population). For the sake of brevity, this
manuscript refers to per capita measures as capita measures.
Statistical significance is assessed at the 5% level
18

Throughout this study, statistical significance is evaluated at the 5% level. This
threshold level is widely used in the academic disciplines being studied to guard against
making conclusions that are due to chance. Vining & Richards (2016) report statistical
significance at the 5% level when conducting regression analysis on First Nation community
wellbeing. Hossain & Lamb (2012) report findings at the 5% level when conducting an
instrumental variable ordered probit study evaluating Aboriginal employment income.
Likewise, O’Gorman & Penner (2018) present regression results of the effects of water
infrastructure on health and social measures in First Nation communities at the 5% level.
Aligned with the academic practice as noted in the existing literature, this manuscript
presents statistical test results using the 5% threshold for statistical significance.

Population Definition
The population evaluated in this study is First Nation communities in Canada that
maintain a distinct land-based territory with at least 50 people living on this land-based
territory. For purposes of this study, this is defined as First Nation communities that have
specific land set aside as either reserve land or crown land designated for use of the First
Nation members. This can be measured by evaluating the registered population levels per
Indigenous Services Canada (ISC), which provides a breakdown of the community
population living “on own reserve” or “on own crown land.” An example of this for the
Ashcroft Indian Band can be found via the ISC website (n.d.d). The number of First Nations
listed on the ISC website is 637. Of these First Nations, 583 have at least 50 people living
“on own reserve,” or “on own crown land” as per the ISC registry information. Of these, 446
First Nations have usable demographic data (from Statistics Canada) and financial data
(audited financial statements).
The validity of the Census data relies on adequate responses from community
members. Communities with very small populations are more prone to data quality issues.
While response rates to the Census are generally high, some non-responsiveness does exist.
To avoid these Census data quality issues, communities with populations less than 50 will be
excluded. This population definition allows for access to both distinct and correlatable
Census demographic data and financial statement data for a large number of First Nation
communities.

19

This study evaluates 446 First Nation communities in total. See Table 2 for a
breakdown of the number of communities by population level and geographic remoteness.
Table 2: Number of First Nation Communities in Study

Small Population
Medium Population
Large Population
Subtotal by Geography

Geographically Geographically Geographically
Close
Medium
Remote
32
65
19
76
119
46
41
34
14
149
218
79

Subtotal by
Population
116
241
89
446 (Total)

Note that that the total number of communities with viable data is reduced for certain
financial indicators and a demographic index due to specific data quality issues. The specific
financial indicators and demographic index affected are listed below. Refer to Appendix A
for definitions of the financial indicators, and Appendix B for the definition of the
demographic index affected. The tangible capital asset (TCA) financial indicators evaluate
407 communities, as First Nations with qualified financial statements relating to TCA were
excluded. Government business entity (GBE) net income and equity financial indicators
evaluate 408 communities, as First Nations with incomplete GBE information were
excluded. All other GBE financial indicators evaluated 371 communities, as First Nations
with incomplete GBE information were excluded. The income index evaluates 303
communities, as Statistics Canada did not disclose income data for small and some medium
population communities due to data quality issues. If no income data was available, these
communities were excluded from the income index.

Data Source – 2016 First Nation Audited Financial Statements
The federal government of Canada introduced the First Nations Financial Transparency
Act (FNFTA) in 2013, which required most First Nation governments to submit audited
financial statements to Indigenous and Northern Affairs Canada (the federal ministry that has
since been split into Crown-Indigenous Relations and Northern Affairs Canada and
Indigenous Services Canada). The First Nation financial statements would then be published
on the federal ministry’s website for the public’s access. This legislation is still on the books
as of 2021, but the government of Prime Minister Justin Trudeau ceased enforcing the
compliance measures of the FNFTA in 2015 (Indigenous Services Canada, n.d.c).
20

Brock & Migone (2018) have conducted a review of the financial capacity of First
Nations for the period of 2014 to 2017. Even though First Nation governments are not
required to submit their audited financial statements, many First Nation governments
continue to do so. The percentage of First Nation financial statements available on the
Indigenous Services Canada website for the 2016 fiscal year is 93% (Brock & Migone,
2018). Not only this, the quality of these financial statements remains high. Brock & Migone
(2018) provide a breakdown of the financial statement audit opinions as follows: 70%
unqualified (clean), 25% qualified (often for minor issues), and 5% adverse or denial (serious
issues). The high submission rate and high quality of the financial statements make for a
valuable dataset.
The audited financial statements are available from ISC’s website in PDF format. The
financial data will be input from the PDF financial statements into a standardized financial
statement template in Microsoft Excel. The data from the Excel template will then be input
into a Microsoft Access database. Access queries and reports allow for ease of data
validation, handling, and analysis. Inputting PDF financial statements manually into an Excel
template requires a significant amount of data entry. Several procedures will be followed
during the data entry phase to minimize the risk of entry errors. First, the full set of financial
statements for each First Nation will be entered. The Statement of Financial Position (similar
to a Balance Sheet) must balance according to accounting guidelines. This provides a proof
to avoid error. Second, each major section of the financial statement has a subtotal amount.
These subtotals are present on the PDF financial statements, as well as in the Excel template
via formula-based subtotals. A proof can be obtained as data is entered by verifying that the
subtotals in the Excel template agree to the PDF financial statements. Any difference would
represent a line-item data entry error. The above proofs include verifying that the Statement
of Financial Position is balanced, and that each major section of the financial statements
subtotal correctly. The third procedure will be to conduct similar proofs in the Microsoft
Excel template, just prior to importing from Excel into the Access database. The fourth
procedure will be to conduct similar proofs after the financial data has been imported into
Microsoft Access. This will check for possible data conversion errors.

21

Data Source – 2016 Census of First Nation Communities
Indigenous Services Canada (ISC) provides publicly available demographic data for
each First Nation community. This data was collected by Statistics Canada during the 2016
Census, and was prepared for ISC. ISC provides demographic data in tabular format that is
accessible via their website (Indigenous Services Canada, n.d.a). This data will be copied
into an Excel standardized template that will then be imported into the Access database. The
demographic categories used in this study include education, income, workforce, housing,
and language. This data will be used to develop the demographic indices and general Nation
wellness index as described in Appendix B. Community population levels will also be
collected from the Census information. The First Nation registry information is also
presented on the ISC website, and will be input into the Access database. These datasets
include geographic zone and registered population figures.
Indigenous Services Canada (2019) utilizes a community wellbeing index (CWI) that
evaluates the wellbeing of First Nation communities over time, and bases the CWI on the
data sources of education, income, workforce, and housing. The methodology used by ISC to
calculate the CWI differs slightly from the index used in this study. The differences exist
because this study is cross-sectional (one year of data), while ISC’s calculation is for
longitudinal evaluation (multiple years of data). Another key difference is that this study
includes one more dataset – knowledge of Indigenous language. In addition to language, this
measure is indicative of general cultural knowledge that is passed on within a First Nation
community. This measure adds a unique Indigenous perspective to community wellness. The
index used in this study will be referred to as the Nation wellness index (NWI). Note that the
NWI is calculated by taking the arithmetic average of the education, income, workforce,
housing, and language subindices. This method assumes that each subindex maintains an
equal weight and are substitutable. This assumption may introduce a bias if a given subindex
maintains on average a lower value compared to the other subindices. While an element of
bias may be present with this method, evaluating a general Nation wellness index provides
meaningful insight to this study.

Categories of Financial Indicators
The financial indicators are derived from the audited financial statements of the First
Nation governments. As previously discussed, the financial statements have been entered
22

into a standardized financial template that allows comparability between the Nations. To
provide meaningful analysis, key financial indicators will be reviewed. The financial
indicators evaluated will be accounting ratios (e.g. earned revenue / total revenue), and capita
measures (e.g. earned revenue / community population). Refer to Appendix A for a full list of
the financial indicators to be evaluated.
The financial indicators in Appendix A are grouped by the common investing activities
of business, government business entity (e.g. Nation owned business that operate
independently), trust funds, tangible capital assets, and other. Evaluating financial indicators
demonstrate what a government has been spending its resources on. The financial indicators
are a quantifiable measure of what investing policies the government is implementing.
Effectively, the financial indicator is an indication of an underlying policy.
This study evaluates the investing policies of First Nation governments, and looks to
specific financial indicators to measure the presence of underlying investing policies. A
benefit of this approach is that proposed investing policies can be substantiated with audited
financial indicators. For example, a First Nation government may propose to invest in and
boost Nation owned business activities. The efficacy of this policy can be evaluated by
measuring the gross business sales ratio or the government business entity asset ratio to name
a few. If the financial indicator is contrary to the expected results, the First Nation leadership
has the information to take corrective action.

Subgroup Matrix Based on Population and Geographic Remoteness
As discussed in the literature review, utilizing meaningful subgroups of a population
can provide deeper insight into the statistical relationships of each subgroup. This research
design will provide more relevant information for policy makers addressing specific
community needs. This study will review nine subcategories, which are based on a matrix
between population level and geographic zone. This approach will isolate the variable effects
of population and geographic remoteness in the correlational analysis. Refer to Table 3 for a
summary and labels of the subgroups. Note that the subgroup labels use a mnemonic
abbreviation with the first letter representing the community population of small, medium or
large. The second letter represents the community geographic zone of close, medium, or
remote. Refer to Appendix C for further details and definitions.

23

Table 3: Summary and Mnemonic Labels of Subgroups

Small Population
Medium Population
Large Population

Geographically
Close
SC
MC
LC

Geographically
Medium
SM
MM
LM

Geographically
Remote
SR
MR
LR

Descriptive Statistics and Comparative Analysis
Key descriptive statistics will be reviewed to better understand the First Nation
communities evaluated in this study. Descriptive statistics of both financial indicators (as per
Appendix A) and demographic indices (as per Appendix B) will be reviewed. Comparative
analysis will also be conducted between subgroups (as per Table 3). This methodology
follows the techniques identified by Rivenbark & Roenigk (2011) and Groves et al. (1981).
The descriptive statistics that will be evaluated include the mean, median, standard
deviation, coefficient of variation, and range. These descriptive statistics will be evaluated
for the population as a whole, for the three subgroupings of population, for the three
subgroupings of geographic remoteness, and for each subgroup discussed in Table 3. Also,
the difference in the descriptive statistics will be evaluated between each
subgrouping/subgroup and the rest of the population (the total population excluding the
subgrouping/subgroup being evaluated). The information gained from this analysis will
provide a deeper understanding of the financial/demographic realities of the First Nation
communities and will highlight key differences found between the subgroups. When the
mean for a specific subgrouping/subgroup varies by 50% from the total population mean and
the coefficient of variation for the subgrouping/subgroup is less than 1.50, a t-test statistic
will be performed. Additional t-tests will be performed if relating trends have been identified.
The t-test will be between a given subgrouping/subgroup and the rest of the population. This
will determine if the difference is statistically significant.

Pearson Correlation Coefficient (r) Analysis and Hypotheses
A Pearson correlation coefficient (r) analysis will be calculated between each financial
indicator from Appendix A, and each demographic index from Appendix B. R will also be
evaluated amongst the demographic indices outlined in Appendix B. These correlation
coefficients will be calculated for the total population and for each subgroup as described in

24

Appendix C. Prior to calculating r, the expected level of correlation for each instance will be
hypothesized. This method can provide support for existing expectations, and uncover
unsupported expectations that exist in the current body of research. Five steps will be taken
in the development and testing of the hypotheses. It is important that causal conclusions are
not made from this analysis, as this study utilizes observational data. Also note that the
hypothesis testing using Pearson correlational analysis maintains the weakness of not
controlling for the effects of other impactful variables. This weakness will be addressed in
Chapter 5 through multiple linear regression, where nine independent variables are evaluated.
Key differences noted between the Pearson correlational analysis and multiple linear
regression will be evaluated in Chapter 6 of this manuscript.
First, this study will develop a hypothesis of the expected correlation between each
financial indicator category and each demographic index. Correlational hypotheses will also
be developed between the demographic indices. The hypotheses will be based on research
reviewed in the literature review and on the professional experience of the author (refer to
Appendix T). The expectation will state whether a statistically significant correlation is
expected or not at the 5% level. Note that all statistically significant correlations are expected
to be positive. Second, the study will calculate r between each financial indicator from
Appendix A and each demographic index from Appendix B, and determine if a statistically
significant correlation exists at the 5% level. Third, this study will calculate r amongst the
demographic indices from Appendix B, and determine if a statistically significant correlation
exists at the 5% level. Fourth, this study will further investigate each correlational instance
from steps 2 and 3 that is statistically significant and has an r value less than -0.40 or greater
than 0.40. The study will review a scatterplot of each relevant correlational instance and
determine if outliers exist or if a non-linear pattern exists. Fifth, the study will determine if
the hypothesized correlations agree with the results and will present the findings.
The methodologies outlined in this section provide a twofold benefit. First is evaluating
the statistical significance of the correlation between investing policies and demographic
indices, and second is identifying if certain subgroups have stronger/weaker correlations.
This twofold benefit will provide relevant and actionable information for policy makers and
community leaders when addressing the needs of local communities. Table 4 provides a
summary of the correlational hypotheses between the demographic indices.
25

Table 4: Demographic Indices Correlational Hypotheses
Demographic
Index
Education

Housing

Workforce

Income

Language
Nation wellness
index (NWI)

Notes and References
Simpson et al. (2007) suggests a statistically significant correlation
between the education index and the income/workforce indices.
Mahoney (2018) suggests a statistically significant correlation between
the education index and the income/workforce indices. Hossain &
Lamb (2012) suggest a statistically significant correlation between the
education index and the income/workforce indices.
The housing index and income index are expected to maintain a
statistically significant correlation, as additional income could be used
to improve the state of residential housing.
Simpson et al. (2007) suggests a statistically significant correlation
between the education index and the income/workforce indices.
Mahoney (2018) suggests a statistically significant correlation between
the education index and the income/workforce indices. Hossain &
Lamb (2012) suggest a statistically significant correlation between the
education index and the income/workforce indices.
Simpson et al. (2007) suggests a statistically significant correlation
between the education index and the income/workforce indices.
Mahoney (2018) suggests a statistically significant correlation between
the education index and the income/workforce indices. Hossain &
Lamb (2012) suggest a statistically significant correlation between the
education index and the income/workforce indices. The housing index
and income index are expected to maintain a statistically significant
correlation, as higher income could be spent on residential housing.
No predetermined hypotheses are present for the language index.
As the NWI is comprised of the above sub-indices, a statistically
significant correlation is expected with the other sub-indices.

Table 5 provides a summary of the correlational hypotheses between the financial
indicators and the demographic indices. It also discusses the link between the financial
indicators and the underlying investing policies. Refer to Appendix A for a detailed listing of
the financial indicators in each category. References are given to articles discussed in the
literature review. The references here provide support for the expected hypotheses in the
Pearson correlational analysis.

26

Table 5: Underlying Investment Policies by Financial Indicator Category and Correlational
Hypotheses
Category of
Financial
Indicator
Business
activities

Underlying Investment Policies, Notes, and References

The business activity financial indicators measure items such as gross
business sales, business and economic development expenses, and total
investment assets. These indicators measure how active a First Nation
government is in the business environment. Deciding to engage in business
activities requires a conscious choice by First Nation leaders, and is a policybased decision.
Eugenievna & Yakovlevna (2014) suggest a statistically significant
correlation between business activities and the housing index. Boyd &
Trosper (2010) suggest a statistically significant correlation between
business activities and the income/workforce indices, and a statistically
significant correlation between business activities and the education index.
Dylan et al. (2013) suggest a statistically significant correlation between
business activities and the income/workforce indices. Mirzaei et al. (2020)
suggest a statistically significant correlation between business activities and
the income/workforce indices. Based on the previous indices, a statistically
significant correlation between business activity and the Nation wellness
index is expected. A statistically insignificant correlation is expected with
the language index.
Government GBE activity indicators measure items such as the level of GBE assets, GBE
business
equity, GBE revenue, GBE expenses, and GBE net income. GBEs can take
entity
on several different activities, such as for-profit businesses, local utility
(GBE)
service providers, NPO service delivery, etc. A commonality of GBEs is that
activities
these entities operate independently from the First Nation government, and
would have autonomous governance of its operations. There is some overlap
between the business activity and GBE activity references, as well as with
the TCA activities.
Mirzaei et al. (2020) suggest a statistically significant correlation between
GBE activities and the income/workforce indices. Mignone & Henley (2009)
suggest a statistically significant correlation between GBE activities and the
education index, the income index, and the workforce index. Eugenievna &
Yakovlevna (2014) suggest a statistically significant correlation between
GBE activities and the housing index. Boyd & Trosper (2010) suggest a
statistically significant correlation between GBE activities and the
income/workforce indices, and a statistically significant correlation between
GBE activities and the education index. Dylan et al. (2013) suggest a
statistically significant correlation between GBE activities and the
income/workforce indices. Based on the previous indices, a statistically
significant correlation between GBE activities and the Nation wellness index
is expected. A statistically insignificant correlation is expected with the
language index.
27

Trust
activities

Tangible
capital asset
(TCA)
activities

Other
activities –
revenue
sources

Trust activity financial indicators measure the level of trust fund assets and
trust fund revenue received in the year. Many First Nation communities set
up trust funds to hold income from impact benefit agreements (e.g. income
from natural resource extraction) or treaty settlements. These sources of
revenue are non-regular, and the trust funds provide a mechanism to spread
out the benefit of these revenues over time in a more stable manner.
Choosing to set aside these funds is a policy decision made by the local
community, and can be measured by the level of assets and trust revenue
received.
Rodon et al. (2018) suggest that a statistically significant correlation exists
between trust activities and the Nation wellness index. While a statistically
significant correlation is expected for the Nation wellness index, the relation
with the specific demographic sub-indices is not predetermined.
TCA activity financial indicators measure the total level of TCA investment
and capital cash flows. Common types of TCAs include housing,
water/sewer infrastructure, community buildings, automotive/equipment, or
TCAs of First Nation businesses (not including GBEs) to name a few. The
level of investment made in TCAs can vary by community, and is
determined by the TCA policies decided by the local leaders and policy
makers.
Mignone & Henley (2009) suggest a statistically significant correlation
between TCA activities and the education index, income index, and
workforce index. Clatworthy (2009) suggests a statistically significant
correlation between TCA activities and the housing index. O’Gorman &
Penner (2018) suggest a statistically significant correlation between TCA
activities and the education index, income index, and workforce index.
Based on the previous indices, a statistically significant correlation between
TCA activities and the Nation wellness index is expected. A statistically
insignificant correlation is expected with the language index.
The other activities section includes revenues by source. The financial
indicators “earned revenue” and “earned & other revenue” include revenues
from business income, royalties, taxes, etc. As such, these financial
indicators will follow similar hypotheses to the business activity indicators.
Vining & Richards (2016) suggest a statistically significant correlation
between earned revenue and earned & other revenue and the Nation wellness
index. Many First Nations have federal/provincial transfer revenue as a large
component of the government’s revenue. Some First Nations also receive a
portion of transfer revenue from a Tribal Government or other First Nation
entity. It is generally expected that higher transfer revenues would result in
more local services, capital investment, etc. As such, it can be reasoned that
a higher level of transfer revenue would have a statistically significant
correlation with all of the demographic indices (except the language index).

Table 6 summarizes the hypothesized correlations as outlines in Tables 4 and 5. Note
that the other activities indicators are not included – refer to Table 5 for details. The language
28

index is also not included, as no statistically significant correlation is expected. Based on the
discussions in Table 4, the workforce and income indices expect to have a statistically
significant relationship, as well as between the income and housing indices. Based on this, a
statistically significant relationship is expected between the workforce and housing indices.
In a similar manner, the education index is expected to maintain a statistically significant
relationship with the workforce and income indices. It follows that a statistically significant
relationship would also exist between the education and housing indices. Note that all of the
expected statistically significant correlations in Table 4 to 6 expect positive correlations.

Table 6: Correlation Hypotheses Summary
Education
Education n/a
Housing
Statistically
significant
Workforce Statistically
significant
Income
Statistically
significant
NWI
Statistically
significant
Business
Statistically
significant
GBE
Statistically
significant
Trust
Not
statistically
significant
TCA
Statistically
significant

Housing

Workforce

Income

NWI

n/a
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
significant
Not statistically
significant
Statistically
significant

n/a
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
significant
Not
statistically
significant
Statistically
significant

n/a
Statistically
significant
Statistically
significant
Statistically
significant
Not
statistically
significant
Statistically
significant

n/a
Statistically
significant
Statistically
significant
Statistically
significant
Statistically
significant

Multiple Linear Regression
A multiple linear regression analysis will be conducted to evaluate the relation of key
variables with the demographic indices. As each demographic index is expected to have
distinct relationships with the independent variables, each demographic index will be
evaluated via multiple linear regression. The demographic indices evaluate the education
index, workforce index, language index, housing index, income index, and Nation wellness
index.
29

Nine independent variables will be utilized when conducting the multiple linear
regression. These variables consist of financial indicators that were utilized in the
correlational analysis, community population level, and level of geographic remoteness.
Refer to Table 8 for a detailed listing of the independent variables that will be utilized in this
analysis. Special care had to be taken when selecting the financial indicators to avoid the
problem of multicollinearity. Avoiding this problem was accomplished by strategically
selecting financial indicators from varying investing categories, and choosing between
financial ratio and capita indicators. A variance inflation factor test will be conducted to
determine the degree of multicollinearity amoung the independent variables. Table 7 presents
the linear regression models that will be evaluated, and the dependent variables that will be
reviewed.
Table 7: Linear Regression Models
Dependent Variable
Education Index (E)

Regression Model
E= β0E + β1EX1 + β2EX2 + β3EX3 + β4EX4 + β5EX5 + β6EX6 +
β7EX7 + β8EX8 +β9EX9 + ε
Workforce Index (W)
W= β0W + β1WX1 + β2WX2 + β3WX3 + β4WX4 + β5WX5 + β6WX6
+ β7WX7 +β8WX8 +β9WX9 + ε
Language Index (L)
L= β0L + β1LX1 + β2LX2 + β3LX3 + β4LX4 + β5LX5 + β6LX6 +
β7LX7 + β8LX8 +β9LX9 + ε
Housing Index (H)
H= β0H + β1HX1 + β2HX2 + β3HX3 + β4HX4 + β5HX5 + β6HX6
+β7HX7 +β8HX8 +β9HX9 + ε
Income Index (I)
I= β0I + β1IX1 + β2IX2 + β3IX3 + β4IX4 + β5IX5 + β6IX6 + β7IX7
+ β8IX8 + β9IX9 + ε
Nation Wellness Index (N) N= β0N + β1NX1 + β2NX2 + β3NX3 + β4NX4 + β5NX5 + β6NX6 +
β7NX7 + β8NX8 +β9NX9 + ε

30

Table 8: Description of Independent Variables
Variable
Category

Financial

Variable Name

Description of the Variable

Earned & other revenue
ratio (X1)
Federal & provincial
revenue capita (X2)
Tribal Gov't and other
First Nation entity
revenue capita (X3)
GBE expense capita (X4)

(Earned revenue + other revenue) / total
revenue 1
(Federal revenue + provincial revenue) /
community population 1, 2
(Tribal government revenue + revenue from
other FN entities) / community population 1,

Trust fund asset ratio
(X5)
TCA assets ratio (X6)

Population level

Geographic

Community population
(X7)

Geographically medium
differential (X8)
Geographically remote
differential (X9)

2

Expenses in government business entities /
community population 2, 3
Trust funds assets / total financial assets 1
Tangible capital assets / total assets 1
Population of people living on First Nation's
reserve land or associated Crown land.
Population figures are as per the 2016
Census.
If First Nation community is geographically
medium then 1; otherwise 0 4
If First Nation community is geographically
remote then 1; otherwise 0 4

Notes:
1. Financial information to calculate the financial figures are taken from the audited 2016 First
Nation financial statements. Refer to Appendix A for further details about how each financial ratio
and capita measure if calculated.
2. Community population is based off of the population of people living on the First Nation’s
reserve land or associated Crown land. These figures are taken from the 2016 Census, which are
prepared by Statistics Canada.
3. Government business entity (GBE) figures are disclosed in the notes of the financial statements.
The expense in GBEs conveys the total expenses incurred in the First Nation’s GBEs for the year.
4. Indigenous Services Canada rates the level of geographic remoteness for each First Nation
community from zones 1-4. Refer to Appendix C for detailed definitions of these zones, and the
geographic definitions used in this study.

Methodologies and Hypotheses – Concluding Statements
This chapter has reviewed the type of research to be conducted throughout this
manuscript and how the research questions will be addressed. The following chapter
evaluates the descriptive statistics and provides a detailed comparative analysis between the
major subgroups of First Nation communities.

31

Chapter 3: Descriptive Statistics and Comparative Analysis
This chapter summarizes the descriptive statistics analysis of the demographic indices
and financial indicators for First Nation communities across Canada. Usable data is available
for 446 First Nation communities. The demographic indices are based on the 2016 Census
data as prepared by Statistics Canada. The financial indicators are based on the 2016 First
Nation government audited financial statements. A goal of this analysis is to identify trends
and patterns in the data as related to population level, geographic remoteness, and the
subgroups as defined in Appendix C.
The first section presents descriptive statistics of the total population and provides a
useful overview for all First Nation communities across Canada. This information is
presented in Tables 10 - 15. The second section provides a comparative analysis by
population subgrouping. As per Table 1, small populations have 200 or fewer people,
medium populations have between 201-999 people, and large populations have 1,000 or
more people. This information is presented in Tables 16 - 22. The third section provides a
comparative analysis by geographic remoteness subgrouping. The three categories of
geographic remoteness are close, medium, and remote. Refer to Table 1 for more detailed
definitions. This information is presented in Tables 23 - 29.
Statistical analysis has been conducted to better understand the trends found in these
tables. When the mean of a specific subgrouping/subgroup varies by 50% from the total
population mean and the coefficient of variation for the subgrouping/subgroup is less than
1.50, a t-test statistic will be performed. Additional t-tests will be performed if relating trends
have been identified. This t-test will be between a given subgrouping/subgroup and the rest
of the population (total population excluding the subgrouping/subgroup being compared).
The t-test takes into consideration the means, standard deviation, and number of observations
to determine statistical significance. Detailed analysis of trends and t-test results are
presented in Appendices G for trends by population and geographic remoteness
subgroupings. The median values are also presented and discussed.
Throughout the discussion, references will be made to the matrix of subgroups as
described in Table 3. This provides a more in-depth analysis of the nine subgroups, and can
supplement the information presented in Tables 10-29. For the sake of brevity and flow, the
data tables and detailed analysis for the matrix subgroups is presented in the Appendices.
32

Refer to Table 9 for a listing of Appendices relating to the subgroups, along with other
appendices relevant to this chapter.
Table 9: Appendices Relating to Descriptive Statistics and Comparative Analysis Chapter
Appendix
Appendix A
Appendix B
Appendix C
Appendices D & E

Appendix F
Appendices G, H, & I

Appendix Description
Provides a summary of the financial indicators being analyzed.
Provides details about how the demographic indices are
calculated.
Provides details about the subgroups analyzed in this study.
Provides the summary descriptive statistics (mean, median,
standard deviation, coefficient of variation, and range) of the
demographic indices and financial indicators respectively broken
down by subgroup. Total population stats are also presented. The
data is presented via tables and graphs.
Provides details for the t-test statistic performed.
Provides descriptive statistics detailed analysis and t-test statistic
results for the following respectively: demographic indices and
financial indicators by population and geography subcategories,
demographic indices by subgroup, and financial indicators by
subgroup.

Details about the demographic indices can be found in Appendix B. The demographic
indices of education, workforce, language, housing, and income are evaluated. Also, a
composite Nation wellness index (NWI) is evaluated. The NWI is a combined average of the
demographic indices previously mentioned. For further information regarding the financial
indicators, refer to Appendix A. Both accounting ratios and per-capita measures are
reviewed. The categories of financial indicators include business activity, government
business entity (GBE) activity, trust fund activity, tangible capital asset activity, and other
activity.
General trends are discussed in the body of this section. The detailed trend analysis and
t-test results in Appendices G, H, and I provide an in-depth analysis of the patterns identified,
as well as the t-test results to determine if a statistically significant difference is identified.
These appendices make reference to appendices D, E, and F if the reader would like to delve
into further detail. The general discussion in the body of this section provides a high-level
commentary on the overall trends that are present within the demographic indices and
financial indicators. References have been left out of the discussion section for ease of
33

reading. If the reader would like further details about items in the discussion section, refer to
the corresponding appendices for further analysis.

Descriptive Statistics of All Communities
This section reviews the descriptive statistics for all of the communities. The
demographic indices and financial indicators are presented in tabular format and includes
Tables 10-15. A brief discussion of these figures is also presented. Note that more detailed
discussion will be provided in subsequent sections as comparative information will be
considered between the differing population and geographic remoteness groupings.
Table 10: Descriptive Statistics of All Communities - Business Activity Indicators
Financial Indicator
Investment Asset Ratio
Investment Asset Capita
Gross Business Sales Ratio
Gross Business Sales
Capita
Business and Ec Dev
Expense Ratio
Business and Ec Dev
Expense Capita

Mean Median
SD
0.28
0.18
0.40
14,306
2,098 48,980
0.10
0.00
0.16
4,436
0.00 10,893

CV
1.44
3.42
1.65
2.46

Min
Max
- 0.64
6.10
-132,161 586,110
0.77
- 108,670

0.13

0.06

0.16

1.19

-

0.74

5,251

1,572

9,800

1.87

-

77,479

The key figures from Table 10 indicate that the percentage of mean gross business
sales compared to total Nation revenue is 10%, and that the mean gross business sales per
capita is $4,436. Note that there is a large variation in these figures between Nations, as
demonstrated by the high coefficient of variation. Even greater variation is present when
considering the amount of investment assets held by First Nations. This variation is caused
largely by a small number of outlier Nations that maintain a significantly higher amount of
investment assets and other business activities. Note that the median values are much lower
compared to the mean values for all of the business activity indicators. The reader will notice
negative minimum values for investment asset ratio/capita, as well as similar negative values
in other affected financial indicators in subsequent tables. This largely relates to negative
values of investments in Nation owned businesses that are government business
entities/partnerships. These businesses have likely showed multiple years of losses, resulting
34

in the investment having a negative value. This is due to the modified equity method of
reporting for the investment. Note that the existence of negative value investments is rare
amoung the First Nation financial statements reviewed in this study, and as such has a
minimal impact on the analysis in this study. The financial dataset was not winsorized, as
identifying outliers can provide meaningful insight into the First Nations being reviewed.

Table 11: Descriptive Statistics of All Communities – Government Business Entity (GBE)
Indicators
Financial Indicator
GBE Asset Ratio
GBE Asset Capita
GBE Liabilities Ratio
GBE Liabilities Capita
GBE Equity Ratio
GBE Equity Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Net Income Ratio
GBE Net Income Capita

Mean Median
0.38
0.06
14,481
854
0.69
0.02
8,714
280
0.10
0.00
7,113
24
0.26
0.01
10,398
253
0.29
0.02
9,362
303
0.51
0.00
941
0

SD
0.80
59,570
3.51
30,013
0.38
39,001
0.64
55,710
0.83
48,619
9.01
14,135

CV
2.11
4.11
5.07
3.44
3.86
5.00
2.47
5.36
2.87
5.19
17.50
15.00

Min
- 0.03
- 510
- 2.13
-132,319
- 0.63
- 21,963
- 0.00
- 47
- 69.74
- 21,966

Max
7.86
751,189
45.76
328,243
5.70
578,398
6.46
805,879
10.86
819,095
132.41
278,482

Government business entities (GBEs) are Nation owned businesses that operate at
arms-length from the First Nation government. These can take the form of for-profit
businesses, not-for-profit entities, or partnerships to name a few. The mean GBE indicators
demonstrate large variation between First Nations, as indicated by a very high coefficient of
variation for all GBE financial indicators. While some Nations carry out significant GBE
activities, many have no GBE activities. This follows a similar pattern as the business
activity financial indicators, in that a few outlier Nations inflate the means upward. The
median values are much lower than the mean values for all GBE indicators. It is important to
remember this and not generalize GBE figures across all Nations.

35

Table 12: Descriptive Statistics of All Communities - Trust Indicators
Financial Indicator
Trust Fund Asset Ratio
Trust Fund Asset Capita
Trust Revenue Ratio
Trust Revenue Capita

Mean Median
SD
0.10
0.01
0.20
6,279
84 35,566
0.03
0.00
0.07
868
0 3,363

CV
1.95
5.66
2.65
3.87

Min
Max
- 0.04
0.95
- 652,801
- 0.04
0.56
- 865 49,057

The trust indicators demonstrate a relatively low amount of trust activities compared to
total financial activities of First Nations. Nations have a mean of 0.10 of trust assets
compared to total First Nation assets, and the mean of total revenues derived from trust
sources is 3%. Note also that a large variation exists between Nations, as indicated by the
high coefficient of variation. The median values for all trust financial indicators are
significantly lower than the mean values.
Table 13: Descriptive Statistics of All Communities - Tangible Capital Asset (TCA)
Indicators
Financial Indicator
TCA Ratio
TCA Capita
Gross Cash Inflow Capital
Ratio
Gross Cash Inflow Capital
Capita
Gross Cash Outflow
Capital Ratio
Gross Cash Outflow
Capital Capita
Net Cashflows Capital
Ratio
Net Cashflows Capital
Capita

Median
SD
0.71
0.23
34,008 38,167
0.00
0.24

CV
0.35
0.86
2.95

91

0

556

6.13

-

9,624

0.53

0.57

0.31

0.58

-

1.00

- 4,232

-1,937

6,694

- 1.58

- 49,267

-

0.01 252.71

- 48.00

-3,784

2,758

- 1.62

- 49,267

7,549

Mean
0.65
44,600
0.08

- 5.26
- 4,141

-1,796

6,721

Min
Max
0.01
1.25
93 392,461
1.00

The tangible capital asset (TCA) mean ratio indicates that Nations have on average
65% of their assets invested in TCA. This ratio is fairly consistent across First Nations, as
demonstrated by a relatively low coefficient of variation. Note also that the mean value of
TCA per capita is $44,600. Most of the capital cash flow financial indicators largely have

36

high coefficients of variation and significant differences between the mean and median
values. Note that the TCA ratio and capita indicators maintain a relatively low standard
deviation, and that the mean and median values are similar.

Table 14: Descriptive Statistics of All Communities - Other Indicators
Financial Indicator
Long Term Debt Ratio
Long Term Debt Capita
Net Cashflows Operating
Ratio
Net Cashflows Operating
Capita
Gross Cash Inflows
Investing Ratio
Gross Cash Inflows
Investing Capita
Gross Cash Outflows
Investing Ratio
Gross Cash Outflows
Investing Capita
Net Cashflows Investing
Ratio
Net Cashflows Investing
Capita
Earned Revenue Ratio
Earned Revenue Capita
Earned And Other Revenue
Ratio
Earned And Other Revenue
Capita
Federal and Provincial
Revenue Ratio
Federal and Provincial
Revenue Capita
Tribal Gov't & Other FN
Entity Revenue Ratio
Tribal Gov't & Other FN
Entity Revenue Capita

Mean Median
0.52
0.57
11,563
7,394
2.09
0.97

SD
CV
0.27
0.52
16,389
1.42
359.78 172.32

-5,292.26

Max
0.98
141,752
4,611.18

4,445

2,214

8,949

2.01

- 19,844

87,532

0.30

0.03

0.39

1.30

-

1.00

2,317

0

11,901

5.14

-

141,805

0.14

0.00

0.25

1.75

-

1.00

- 2,972

-16

12,838

- 4.32

- 142,249

-

14.67

0.00

187.91

12.81

- 196.16

2,961.65

- 655

0

6,367

- 9.73

- 59,882

32,893

0.20
7,982
0.34

0.15
3,262
0.30

0.20
14,615
0.22

1.02
1.83
0.66

- 0.44
- 13,313
- 0.59

0.86
143,219
1.00

13,286

6,991

21,782

1.64

- 19,140

258,109

0.57

0.59

0.23

0.40

-

1.56

16,392

14,244

12,135

0.74

-

127,652

0.07

0.03

0.11

1.63

-

0.87

1,966

659

4,577

2.33

-

72,722

Min

37

The mean long-term debt capita measure of First Nations governments is $11,563.
Variation between Nations does exist as demonstrated by the coefficient of variation of 1.42
and a lower median value of $7,394. The cash flow indicators in Table 14 maintain very high
coefficients of variation, and as such will not be further evaluated.
The First Nation government financial statements would generally indicate earned
income separately on the audited financial statements. However, some First Nations would
label such income as other revenue. While other revenue could include miscellaneous items,
the larger amounts in other income often relate to some type of earned income such as
royalties, businesses, or taxation to name a few. As such, the “earned revenue” and “earned
revenue and other revenue” are considered together in this discussion. The average mean of
earned and other revenue (compared to total Nation revenue) is 34%, while the percentage of
federal & provincial transfer revenue is 57%. The mean of transfer revenue from Tribal
Governments and other First Nation entities is 7%. Note that the coefficient of variation is
relatively lower for these financial indicators compared to other indicators previously
discussed. Likewise, the median values for earned & other revenue ratio, federal & provincial
transfer revenue ratio, and federal & provincial transfer revenue capita are very similar to the
mean values.
Table 15: Descriptive Statistics of All Communities - Demographic Indices
Demographic Index
Education Index
Workforce Index
Language Index
Housing Index
Income Index
Nation Wellness Index (NWI)

Mean Median
45.10
46.22
55.94
55.84
28.70
22.76
63.11
63.12
31.01
28.49
64.92
65.47

SD
14.54
13.20
24.28
18.14
10.31
11.53

CV
0.32
0.24
0.85
0.29
0.33
0.18

Min
3.65
13.51
5.71
17.30
32.26

Max
100.00
100.00
100.00
100.00
100.00
100.00

Table 15 presents the demographic indices for First Nations across Canada. Refer to
Appendix B for detailed definitions of how each index is calculated. Note that the range
between min and max for most of these indices is quite large – while the NWI has the lowest
range. The language index has by far the lowest index level. This indicates a low level of
Indigenous language knowledge amoung individuals living in First Nation communities. The
mean and median values for all of the demographic indices are very similar.
38

Descriptive Statistics by Population
This section reviews the descriptive statistics by population level (small, medium, and
large). This provides a useful comparative analysis between the population subgroupings.
This information is presented in Tables 16 - 22. Discussion is provided following each table,
and focuses on the trends found in the comparative analysis. Detailed analysis and t-test
statistical analysis have been conducted in Appendix G. The t-test provides statistical
evidence for statistically significant relations. For the sake of brevity and flow, the discussion
in the body of this section will focus on high level trends. Refer to Appendix G for further
analysis.
Table 16: Descriptive Statistics by Population - Business Activity Indicators
Financial
Indicator
Investment
Asset Ratio
Investment
Asset Capita
Gross
Business
Sales Ratio
Gross
Business
Sales Capita
Business and
Ec Dev
Expense
Ratio
Business and
Ec Dev
Expense
Capita

Population

Mean

Median

SD

CV

Min

Max

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

0.30
0.26
0.32
26,992
10,883
7,042
0.09
0.10
0.10
6,365
4,008
3,079
0.14
0.14
0.11

0.14
0.16
0.29
2,401
1,796
2,358
0.00
0.00
0.03
0
0
436
0.06
0.07
0.06

0.61
0.30
0.27
85,240
28,002
14,156
0.17
0.16
0.16
15,510
9,271
6,632
0.17
0.16
0.13

2.08
1.17
0.85
3.16
2.57
2.01
1.80
1.62
1.54
2.44
2.31
2.15
1.20
1.19
1.16

- 0.30
6.10
- 0.64
0.99
0.96
- 132,161 586,110
- 2,064 251,895
- 95,693
0.75
0.77
0.68
- 108,670
- 77,464
- 37,531
0.70
0.74
0.70

Small
Medium
Large

7,911
4,867
2,820

2,175
1,427
1,019

13,777
8,428
5,310

1.74
1.73
1.88

-

77,479
56,122
41,668

The investment asset ratio and capita measure demonstrate differing patterns between
the subgroupings. The mean ratio indicates that large population communities have a slightly
39

higher ratio. Note that the variation amoung small population communities is quite high as
indicated by the coefficient of variation of 2.08. Due to this, a statistically significant
difference cannot be established. When evaluating the mean capita value, the measure is
much lower for large populations ($7.0K) compared to small populations ($27K). Note that
the median measures for investment asset capita are significantly lower. A small number of
Nations maintain a very high investment asset capita measure, resulting in higher mean
values. The difference between the means and median values for investment asset ratio are
less compared to the capita measure, particularly for large population communities.
Business activity mean values are higher on a per capita basis for communities with
small populations. The business activity indicators demonstrate that communities with
smaller populations generate higher business revenue on a per capita basis. Note, however,
that the business activity ratios between the subgroupings are very similar. A small number
of Nations maintain high values for these financial indicators, which results in higher mean
values.

40

Table 17: Descriptive Statistics by Population - Government Business Entity (GBE) Indicators
Financial
Indicator
GBE Asset
Ratio
GBE Asset
Capita
GBE
Liabilities
Ratio
GBE
Liabilities
Capita
GBE Equity
Ratio
GBE Equity
Capita
GBE Revenue
Ratio
GBE Revenue
Capita
GBE Expense
Ratio
GBE Expense
Capita
GBE Net
Income Ratio
GBE Net
Income Capita

Population

Mean

Median

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

0.34
0.39
0.40
28,437
10,680
6,939
0.88
0.73
0.34
14,927
7,686
3,542
0.15
0.08
0.09
15,095
4,720
3,356
0.25
0.28
0.22
21,683
7,252
4,497
0.30
0.31
0.22
18,375
6,849
4,650
1.66
0.11
0.13
3,052
344
-147

0.00
0.08
0.23
3
854
2,174
0.00
0.02
0.10
65
262
808
0.00
0.00
0.03
0
21
862
0.00
0.01
0.08
0
263
1,283
0.00
0.02
0.09
0
290
1,477
0.00
0.00
0.00
0
0
0

SD

CV

0.99
2.92
0.81
2.06
0.45
1.15
107,390
3.78
31,151
2.92
10,621
1.53
4.78
5.42
3.43
4.69
0.67
1.96
43,138
2.89
27,302
3.55
6,068
1.71
0.61
4.18
0.22
2.77
0.31
3.56
73,310
4.86
14,612
3.10
7,221
2.15
0.75
3.06
0.66
2.41
0.32
1.45
106,400
4.91
17,680
2.44
7,980
1.77
0.89
2.96
0.93
3.01
0.32
1.43
92,493
5.03
16,543
2.42
8,124
1.75
13.15
7.91
8.00 71.86
3.19 24.14
27,544
9.02
2,474
7.18
2,297 -15.62

Min

Max

-0.03
-510
-0.44
-0.78
-2.13
-132,319
-19,911
-19,115
-0.63
-0.01
-21,963
-121
-47
-6.61
-69.74
-17.35
-21,966
-20,022
-18,934

7.86
7.73
1.67
751,189
284,081
53,305
45.76
33.99
3.27
328,243
245,667
35,312
5.70
1.34
0.78
578,398
101,374
30,976
5.64
6.46
1.86
805,879
113,136
49,031
5.78
10.86
1.90
819,095
104,832
48,386
132.41
72.85
20.10
278,482
11,247
3,125

41

There are no consistent patterns present within the mean ratios, and the level of
variation between the population groupings is low. The mean capita measures, however,
show a lower level of GBE activity for large populations. Note that the level of variation
within each subgrouping is high, as indicated by high coefficients of variation. A distinct
trend emerges from the median values. The median value for all GBE indicators (except net
income indicators) are higher for large populations. This demonstrates that a higher
proportion of large population communities maintain GBE activities. Note that for small and
medium population communities, the mean values are higher and the median values are
lower.
Table 18: Descriptive Statistics by Population - Trust Indicators
Financial
Indicator
Trust Fund
Asset Ratio
Trust Fund
Asset Capita
Trust
Revenue
Ratio
Trust
Revenue
Capita

Population

Mean

Median

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

0.09
0.10
0.12
5,281
7,115
5,315
0.02
0.03
0.02
1,231
822
521

0.01
0.01
0.00
248
81
32
0.00
0.00
0.00
0
0
0

SD

CV

Min

Max

0.16
0.20
0.23
21,893
44,836
16,837
0.07
0.07
0.07
5,262
2,452
2,078

1.89
1.92
2.01
4.15
6.30
3.17
2.80
2.46
3.15
4.27
2.98
3.99

-0.04
-0.00
-0.04
-77
-865

0.78
0.88
0.95
188,636
652,801
119,369
0.35
0.56
0.48
49,057
21,173
16,009

No statistically significant differences between are noted in the mean trust indicators
between the population subgroupings. The amounts are very similar between the
subgroupings, except for the mean of trust revenue capita. Note that the median values for all
of the trust activity indicators are 0 or nearly 0 for both ratio and capita measures. This
demonstrates that many Nations maintain little or not trust activities.

42

Table 19: Descriptive Statistics by Population - Tangible Capital Asset (TCA) Indicators
Financial
Indicator
TCA Ratio

TCA Capita

Gross Cash
Inflow
Capital Ratio
Gross Cash
Inflow
Capital
Capita
Gross Cash
Outflow
Capital Ratio
Gross Cash
Outflow
Capital
Capita
Net
Cashflows
Capital Ratio
Net
Cashflows
Capital
Capita

Population

Mean

Median

SD

CV

Min

Max

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

0.62
0.67
0.63
65,400
42,116
26,712
0.15
0.07
0.04
189
58
64

0.69
0.73
0.70
49,737
34,272
22,460
0.00
0.00
0.00
0
0
0

0.24
0.22
0.23
56,151
29,288
15,548
0.32
0.22
0.16
1,025
251
298

0.39
0.33
0.36
0.86
0.70
0.58
2.15
3.19
3.70
5.43
4.36
4.67

0.06
0.01
0.13
1,234
93
404
-

1.25
0.97
0.97
392,461
185,478
108,198
1.00
1.00
0.91
9,624
3,008
2,529

Small
Medium
Large
Small
Medium
Large

0.51
0.54
0.55
-5,729
-4,077
-2,881

0.51
0.58
0.59
-2,004
-1,991
-1,702

0.33
0.31
0.27
8,781
6,245
4,331

0.65
0.58
0.48
-1.53
-1.53
-1.50

0.03
-49,267
-44,725
-32,243

1.00
1.00
0.97
-13

Small
Medium
Large
Small
Medium
Large

1.93
1.26
-30.91
-5,540
-4,020
-2,817

0.00
-0.05
0.12
-1,721
-1,982
-1,702

16.45
32.81
553.13
8,883
6,248
4,333

8.52
25.98
-17.89
-1.60
-1.55
-1.54

-57.07
107.04
-175.92
351.78
-3,784.15 2,758.03
-49,267
7,549
-44,725
271
-31,992
938

The level of tangible capital assets (TCA) is fairly consistent between the population
subgroupings when evaluating the ratios. However, distinct patterns emerge on a per capita
basis. Communities with smaller populations have a much higher TCA per capita for both
mean and median measures. The cumulative TCA mean and median per capita is much lower
for large populations. The mean cumulative TCA per capita is much higher for small
populations that are geographically medium and remote (Appendix E, Figure A59). Some
difference is expected due to differences in economies of scale for providing services (as

43

each community requires a set amount of fixed assets to function). However, the degree of
difference for both mean and median capita measures is substantial.
Note the sharp distinction in cumulative TCA capita between the population
subgroupings. Means for small populations are $65,400, medium populations are $42,166,
and large populations are $26,712. A similar pattern emerges from the year’s gross cash
outflows from capital capita measure. Note that the per capita amount of cumulative TCA is
even lower for large population communities that are geographically remote. Appendix E,
Figure A59 shows that large population communities that are geographically remote (LR)
have a mean per capita cumulative TCA of $25,672. This is the lowest of all the subgroups.
Note that the TCA ratio and the gross cash outflow capital ratio median measures are very
similar to the mean values. The TCA capita median values are also quite similar, although
small population communities do maintain a higher degree of difference between the mean
and median.

44

Table 20: Descriptive Statistics by Population - Other Indicators (Part 1)
Financial
Indicator
Long Term
Debt Ratio
Long Term
Debt Capita
Net
Cashflows
Operating
Ratio
Net
Cashflows
Operating
Capita
Gross Cash
Inflows
Investing
Ratio
Gross Cash
Inflows
Investing
Capita
Gross Cash
Outflows
Investing
Ratio
Gross Cash
Outflows
Investing
Capita
Net
Cashflows
Investing
Ratio
Net
Cashflows
Investing
Capita

Population

Mean

Median

SD

CV

Min

Max

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

0.43
0.53
0.63
15,143
10,429
9,969
-0.83
-3.02
19.50

0.43
0.57
0.68
8,012
7,038
7,542
0.87
1.07
0.40

0.31
0.26
0.20
24,054
12,739
11,685
18.74
37.37
803.48

0.71
0.50
0.32
1.59
1.22
1.17
-22.62
-12.39
41.19

Small
Medium
Large

8,920
3,360
1,552

3,726
2,158
1,352

14,498
5,346
3,775

1.63
1.59
2.43

-12,401
-11,154
-19,844

87,532
37,146
18,561

Small
Medium
Large

0.34
0.28
0.32

0.03
0.02
0.12

0.43
0.39
0.37

1.24
1.37
1.18

-

1.00
1.00
1.00

Small
Medium
Large

2,533
2,647
1,142

0
0
87

10,699
14,214
3,721

4.22
5.37
3.26

-

103,514
141,805
22,980

Small
Medium
Large

0.18
0.12
0.14

0.00
0.00
0.03

0.30
0.23
0.22

1.65
1.87
1.56

-

0.99
1.00
0.93

Small
Medium
Large

-4,697
-2,869
-1,002

-13
-5
-85

14,795
13,981
2,541

-3.15
-4.87
-2.54

-126,494
-142,249
-14,611

-

Small
Medium
Large

0.82
4.69
59.47

0.00
0.00
0.00

22.69
38.18
412.59

27.67
8.14
6.94

-107.53
216.16
-37.54
521.57
-196.16 2,961.65

Small
Medium
Large

-2,164
-222
140

-3
0
0

9,758
4,982
2,948

-4.51
-22.47
21.04

-59,882
-43,078
-7,524

0.98
0.97
0.95
- 141,752
- 109,917
72,105
-107.51
110.42
-313.19
127.76
-5,292.26 4,611.18

32,893
22,521
22,980

45

The long-term debt mean ratio (relative to total liabilities) increases with larger
populations. On a mean per capita basis, smaller populations have a higher capita measure.
The mean and median values for long term debt ratio are very similar. The mean and median
values for long term debt capita are very different for small populations, with a lessening
difference for higher population levels. No other distinctive patterns appear regarding longterm debt amoung the subgroups. When evaluating net cash flows from operating on a per
capita basis, we can see that the capita measures vary significantly. This is demonstrated by
the high coefficient of variation.
Table 21: Descriptive Statistics by Population - Other Indicators (Part 2)
Financial
Population
Indicator
Earned
Small
Revenue Ratio Medium
Large
Earned
Small
Revenue
Medium
Capita
Large
Earned And
Small
Other
Medium
Revenue Ratio Large
Earned And
Small
Other
Medium
Revenue
Large
Capita
Federal and
Small
Provincial
Medium
Revenue Ratio Large
Federal and
Small
Provincial
Medium
Revenue
Large
Capita
Tribal Gov't & Small
Other FN
Medium
Entity
Large
Revenue Ratio

Mean

Median

SD

CV

Min

Max

0.20
0.20
0.20
12,423
7,014
4,814
0.36
0.33
0.33
20,720
11,508
8,411

0.14
0.15
0.16
4,513
3,173
2,395
0.36
0.29
0.27
10,603
6,290
5,088

0.22
0.20
0.18
21,886
11,557
7,150
0.23
0.23
0.20
27,296
20,645
12,558

1.09
1.02
0.91
1.76
1.65
1.49
0.63
0.69
0.61
1.32
1.79
1.49

-0.44
-0.28
-0.00
-13,313
-8,775
-55
-0.25
-0.59
-0.08
-19,140
-13,971
-1,088

0.86
0.79
0.73
143,219
77,464
40,042
0.91
1.00
0.89
171,477
258,109
100,299

0.53
0.57
0.60
22,662
14,780
12,584

0.53
0.60
0.63
18,312
14,045
12,238

0.23
0.23
0.21
17,986
8,077
8,393

0.44
0.40
0.35
0.79
0.55
0.67

0.04
0.11
1,510
362

1.15
1.56
1.08
127,652
53,507
71,270

0.08
0.07
0.05

0.04
0.03
0.02

0.12
0.11
0.09

1.46
1.64
1.92

-

0.87
0.69
0.57

46

Tribal Gov't & Small
Other FN
Medium
Entity
Large
Revenue
Capita

3,491
1,578
1,029

1,382
651
364

7,533
2,797
2,465

2.16
1.77
2.40

-

72,722
30,430
20,022

The revenue ratios are very consistent between most of the population subgroupings for
both mean and median measures. The revenue per capita measures do show a different
pattern; all mean revenue sources per capita are higher for smaller populations. The median
revenue indicators per capita follow a similar pattern, but the difference between the
population subgroupings is lessened. This results in larger population communities receiving
less revenue per capita, which could limit the ability of the local governments to provide
necessary services. Note that some of this difference likely relates to differences in
economies of scale between small and large populations. Small populations are on average
more remote than large population communities, which could result in higher costs and a
relating high level of transfer revenue from third-party funders.
When we evaluate earned revenue & other revenue on a per capita basis, a similar
pattern emerges. Small population communities have a higher mean capita measure of
$20,720, while large populations are $8,411. This indicates that earned and other revenue
does not scale up with increases in population. The federal and provincial transfer mean
payments on a per capita basis are much higher for small population communities at $22,662,
while large populations are $12,584. The per capita mean federal/provincial transfers can be
as much as double for small population communities compared to large population
communities. While some difference was expected, this degree of difference is unexpected.
While the median value differences between the subgroupings for these capita measures are
not as drastic, a similar pattern does exist.
First Nation government transfers includes transfers from Tribal Governments and
other First Nation entities. Small population communities maintain a higher per capita mean
measure of $3,491, while large are $1,029. Note that the mean ratio measure is higher for
small populations at 0.08, while large populations are 0.05. This demonstrate that small
population communities maintain a higher level of Indigenous entity transfer revenue. The
median values follow a similar pattern, but the overall median values are lower compared to
the mean.
47

Table 22: Descriptive Statistics by Population - Demographic Indices
Index
Education
Index
Workforce
Index
Language
Index
Housing
Index
Income Index

Nation
Wellness
Index

Population

Mean

Median

Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large
Small
Medium
Large

50.2
43.5
42.8
62.3
55.5
48.7
20.1
29.2
38.7
67.8
61.3
61.8
30.9
31.3
70.7
62.8
63.1

50.1
44.3
40.4
61.9
56.1
48.8
15.5
24.4
34.1
66.7
61.4
60.7
29.1
27.9
70.9
63.1
62.6

SD

CV

14.3
13.8
15.3
13.8
11.9
11.7
18.0
23.8
28.6
19.2
17.0
18.7
9.5
12.0
12.2
10.1
11.8

0.28
0.32
0.36
0.22
0.21
0.24
0.90
0.81
0.74
0.28
0.28
0.30
0.31
0.38
0.17
0.16
0.19

Min

Max

12.8
3.7
13.5
30.4
13.5
20.6
25.0
5.7
17.5
17.3
17.9
40.5
32.3
38.5

100.0
70.6
75.5
100.0
91.9
82.7
79.2
99.3
100.0
100.0
100.0
98.7
100.0
92.8
100.0
93.6
98.9

The mean and median values for the demographic indices are very similar. Due to this,
only the mean values will be discussed. The education index is higher for small populations
at 50.2, compared to the rest of the communities (all communities excluding the small
population communities) at 43.3. Small population communities have a higher workforce
index of 62.3, with the rest of the communities at 53.7. The language index for large
populations is 38.7, with the rest of the communities at 26.2. The housing index is
moderately higher for small population communities at 67.8, with the rest of the communities
at 61.4. All of these differences of means are statistically significant as per the t-tests in
Appendix G. No income data is available for small populations due to data quality issues.
Population at the medium and large level have nearly equal income index measures.
The Nation wellness index (NWI) provides an overall measure for a Nation’s wellness
based on the previously discussed indices. The NWI of the total population is 64.9. The NWI
is higher for small population communities with a mean of 70.7, compared to the rest of the
48

communities at 62.9. This difference is statistically significant per the t-tests in Appendix G.
As per Appendix E, Figure A111, the medium population subgroups are fairly constant with
the total population mean. However, a distinct pattern emerges for large populations. Large
populations that are geographically remote have a NWI of 68.2, large populations that are
geographically medium are 58.7, and large populations that are geographically remote are
58.5. This shows that large populations that are geographically close are slightly above the
total population index, while large populations that are geographically medium or remote
have the lowest NWI.

Descriptive Statistics by Geographic Remoteness
This section reviews the descriptive statistics by geographic remoteness level (close,
medium, and remote). This provides a useful comparative analysis between the geographic
remoteness subgroupings. This information is presented in Tables 23-29. Discussion is
provided following each table, and focuses on the trends found in the comparative analysis
between geographic zones. Detailed analysis and t-test statistical analysis has been conducted
in Appendix G. The t-tests provide statistical evidence for statistically significant relations.
For the sake of brevity and flow, the discussion in the body of this section will focus on high
level trends.

49

Table 23: Descriptive Statistics by Geographic Remoteness - Business Activity Indicators
Financial
Indicator
Investment
Asset Ratio
Investment
Asset Capita
Gross
Business
Sales Ratio
Gross
Business
Sales Capita
Business and
Ec Dev
Expense
Ratio
Business and
Ec Dev
Expense
Capita

Geographic
Zone
Close
Medium
Remote
Close
Medium
Remote
Close
Medium
Remote
Close
Medium
Remote
Close
Medium
Remote

Mean

Median

SD

CV

Min

Max

0.32
0.25
0.27
13,289
15,668
12,468
0.13
0.10
0.05
6,836
3,537
2,388
0.16
0.14
0.08

0.21
0.17
0.15
2,415
2,017
1,925
0.01
0.00
0.00
120
0
0
0.06
0.08
0.03

0.56
0.29
0.30
39,378
57,301
39,993
0.20
0.15
0.11
15,694
7,396
6,323
0.19
0.15
0.11

1.73
1.15
1.12
2.96
3.66
3.21
1.54
1.54
2.13
2.30
2.09
2.65
1.20
1.08
1.41

-0.30
-0.64
-0.05
-16,536
-132,161
-168
-

6.10
1.07
0.99
414,320
586,110
332,939
0.77
0.68
0.48
108,670
51,131
37,240
0.74
0.65
0.51

Close
Medium
Remote

6,602
4,950
3,532

1,376
1,936
554

12,977
7,733
7,437

1.97
1.56
2.11

-

77,479
48,929
45,262

The mean and median business activity financial indicators demonstrate that
geographically close communities earn a higher percentage of their total revenue from
business activities. The mean of business and economic development expenses is also higher
for geographically close communities, while the median values do not follow this pattern. A
similar pattern emerges on a per capita basis. A distinct trend is present for both investment
asset capita and business and economic development expense capita, in that the median
values are significantly lower than the mean values.

50

Table 24: Descriptive Statistics by Geographic Remoteness – GBE Indicators
Financial
Indicator
GBE
(government
business entity)
Asset Ratio
GBE Asset
Capita

Geographic
Zone
Close
Medium
Remote

Close
Medium
Remote
GBE Liabilities Close
Ratio
Medium
Remote
GBE Liabilities Close
Capita
Medium
Remote
GBE Equity
Close
Ratio
Medium
Remote
GBE Equity
Close
Capita
Medium
Remote
GBE Revenue
Close
Ratio
Medium
Remote
GBE Revenue
Close
Capita
Medium
Remote
GBE Expense
Close
Ratio
Medium
Remote
GBE Expense
Close
Capita
Medium
Remote
GBE Net
Close
Income Ratio
Medium
Remote
GBE Net
Close
Income Capita Medium
Remote

Mean

Median

SD

CV

Min

Max

0.31
0.44
0.36

0.10
0.06
0.01

0.43
1.03
0.60

1.39
2.34
1.68

-0.03
-0.00
-

2.03
7.86
3.09

8,100
17,516
19,237
0.35
1.07
0.25
4,366
12,492
6,431
0.11
0.09
0.10
5,914
6,004
12,942
0.20
0.32
0.17
5,195
12,703
14,821
0.21
0.37
0.20
4,656
12,553
9,794
0.16
0.70
0.71
668
-22
4,404

1,222
607
39
0.03
0.01
0.01
323
337
74
0.01
0.00
0.00
580
0
4
0.02
0.02
0.00
284
459
0
0.02
0.01
0.00
333
380
23
0.00
0.00
0.00
0
0
0

18,318
64,304
94,935
0.80
4.91
0.43
10,297
39,909
20,166
0.33
0.43
0.26
16,599
34,938
71,131
0.40
0.79
0.48
12,245
61,577
87,575
0.46
1.02
0.77
11,402
62,190
50,940
9.01
10.00
5.12
3,522
3,319
34,021

2.26
3.67
4.93
2.30
4.58
1.72
2.36
3.19
3.14
3.10
4.86
2.52
2.81
5.82
5.50
1.97
2.47
2.76
2.36
4.85
5.91
2.13
2.79
3.79
2.45
4.95
5.20
57.64
14.32
7.17
5.27
-147.57
7.72

-510
-2.13
-0.47
-0.18
-19,115
-132,319
-4,803
-0.01
-0.63
-121
-21,963
-0.00
-47
-69.74
-44.78
-9.69
-18,934
-21,966
-2,742

159,756
751,189
717,494
5.42
45.76
1.88
88,534
328,243
139,096
1.23
5.70
1.34
132,138
422,947
578,398
2.74
6.46
3.38
97,549
805,879
661,988
3.16
10.86
5.78
92,054
819,095
383,506
72.85
132.41
40.09
25,781
11,247
278,482

51

GBE activity means per capita amoung small population communities are divided
sharply by geographic remoteness. GBE activity means are higher for all indicators for small
populations that are geographically medium and remote (refer to Appendix E, Figures A25 –
A47). Another distinction for small populations that are geographically close is that even
though their overall GBE activity is low, the equity balance of the GBEs is quite high. It is
important to note that many of the GBE financial indicators maintain very high coefficients
of variation. Also, the median values for most GBE indicators for all geographic
subgroupings are significantly lower than the mean values; most of the median indicators
hold a value of zero. The results from the t-tests as per Appendix G and I demonstrate nonstatistically significant results between the geographic subgroupings.
Table 25: Descriptive Statistics by Geographic Remoteness - Trust Indicators
Financial
Geographic
Indicator
Zone
Trust Fund Close
Asset Ratio Medium
Remote
Trust Fund Close
Asset
Medium
Capita
Remote
Trust
Close
Revenue
Medium
Ratio
Remote
Trust
Close
Revenue
Medium
Capita
Remote

Mean

Median

SD

CV

Min

Max

0.09
0.12
0.07
5,382
4,606
12,588
0.02
0.04
0.01
522
1,332
240

0.01
0.01
0.00
113
95
30
0.00
0.00
0.00
0
0
0

0.19
0.21
0.18
21,325
14,327
75,717
0.07
0.08
0.04
1,933
4,451
1,044

2.04
1.74
2.63
3.96
3.11
6.02
3.07
2.19
4.48
3.71
3.34
4.35

-0.04
-0.04
-0.00
-865
-77
-

0.95
0.88
0.86
188,636
134,055
652,801
0.48
0.56
0.31
16,009
49,057
8,411

The mean trust activity indicators demonstrate that geographically remote communities
do not utilize trusts as much as other geographical locations. Mean trust revenues on a ratio
and per capita basis are much lower for geographically remote communities. The mean trust
fund asset ratio is lowest for geographically remote communities. While the mean trust fund
asset capita is higher for geographically remote communities, this is due to a significant
outlier. Note that trust revenue makes up a small percentage of total revenue for most First
Nations. The median values for all trust indicators are very low with a near zero value. This
52

is caused by a large number of Nations that maintain no trust activities, while a small number
of Nations maintain high levels of trust activities.
Table 26: Descriptive Statistics by Geographic Remoteness - Tangible Capital Asset (TCA)
Indicators
Financial
Indicator
Tangible
Capita Asset
(TCA) Ratio
TCA Capita

Gross Cash
Inflow
Capital Ratio
Gross Cash
Inflow
Capital
Capita
Gross Cash
Outflow
Capital Ratio
Gross Cash
Outflow
Capital
Capita
Net
Cashflows
Capital Ratio
Net
Cashflows
Capital
Capita

Geographic
Zone
Close
Medium
Remote
Close
Medium
Remote
Close
Medium
Remote
Close
Medium
Remote

Mean

Median

SD

CV

0.60
0.68
0.67
37,314
45,237
58,521
0.09
0.08
0.06
150
74
14

0.64
0.73
0.76
29,012
35,266
42,469
0.00
0.00
0.00
0
0
0

0.24
0.22
0.23
29,854
32,648
60,725
0.26
0.23
0.20
873
304
59

0.39
0.32
0.34
0.80
0.72
1.04
2.77
2.99
3.47
5.83
4.09
4.12

0.06
0.01
0.04
404
156
93
-

1.25
0.97
0.95
192,798
207,214
392,461
1.00
1.00
0.89
9,624
3,008
379

Close
Medium
Remote
Close
Medium
Remote

0.53
0.52
0.59
-3,412
-4,667
-4,647

0.61
0.52
0.66
-1,944
-1,855
-2,229

0.32
0.30
0.31
5,213
7,318
7,403

0.61
0.58
0.52
-1.53
-1.57
-1.59

-32,243
-44,725
-49,267

1.00
1.00
1.00
-

Close
Medium
Remote
Close
Medium
Remote

1.90
-13.72
6.19
-3,262
-4,593
-4,632

0.00
-0.18
0.18
-1,746
-1,796
-2,229

22.91
355.71
47.14
5,299
7,319
7,402

12.08
-25.92
7.61
-1.62
-1.59
-1.60

Min

Max

-87.84
177.59
-3,784.15 2,758.03
-56.34
351.78
-31,992
7,549
-44,725
1,333
-49,267
-

The level of mean tangible capital assets (TCA) is fairly consistent between the
geographic subgroupings when evaluating the ratios. However, distinct patterns emerge on a
mean per capita basis. Close communities maintain a mean TCA capita measure of $37,314,
while remote communities are at $58,521. A similar pattern is present for the median values;
53

however, the median values are lower for each subgrouping. This makes intuitive sense, as
the cost of building or purchasing TCA would be higher in more remote locations. Most of
the capital cash flow financial indicators maintain very high coefficients of variation, which
results in the inability to establish statistically significant differences. The median value for
TCA ratio and gross cash outflow capital ratio are very similar to the mean values.

54

Table 27: Descriptive Statistics by Geographic Remoteness - Other Indicators (Part 1)
Financial
Indicator
Long Term
Debt Ratio
Long Term
Debt Capita
Net
Cashflows
Operating
Ratio
Net
Cashflows
Operating
Capita
Gross Cash
Inflows
Investing
Ratio
Gross Cash
Inflows
Investing
Capita
Gross Cash
Outflows
Investing
Ratio
Gross Cash
Outflows
Investing
Capita
Net
Cashflows
Investing
Ratio
Net
Cashflows
Investing
Capita

Geographic
Zone
Close
Medium
Remote
Close
Medium
Remote
Close
Medium

Mean

Median

SD

CV

Min

Max

0.55
0.53
0.45
11,339
11,738
11,503
-2.01
9.65

0.62
0.57
0.46
7,887
7,500
6,205
0.79
1.27

0.27
0.27
0.28
15,386
14,849
21,670
30.29
512.53

0.49
0.50
0.63
1.36
1.26
1.88
-15.10
53.11

0.95
0.97
0.98
134,586
88,407
141,752
110.42
4,611.18

Remote
Close
Medium
Remote

-11.27
3,867
4,885
4,324

-0.17
2,156
2,472
1,537

49.82
7,121
10,172
8,462

-4.42
1.84
2.08
1.96

-281.75
5,292.26
-313.19
-6,510
-19,844
-12,401

Close
Medium
Remote

0.34
0.28
0.30

0.05
0.02
0.08

0.42
0.38
0.38

1.24
1.34
1.29

-

1.00
1.00
1.00

Close
Medium
Remote

2,828
2,531
763

3
2
0

14,676
11,861
2,201

5.19
4.69
2.88

-

141,805
121,728
12,667

Close
Medium
Remote

0.18
0.15
0.05

0.01
0.01
0.00

0.29
0.25
0.13

1.66
1.60
2.49

-

1.00
0.93
0.90

Close

-3,999

-41

16,534

-4.13

-

Medium

-3,063

-41

11,857

-3.87

Remote
Close
Medium
Remote

-784
2.57
25.42
7.61

0
0.00
0.00
0.00

4,862
21.28
265.15
59.62

-6.20
8.29
10.43
7.83

142,249
110,458
-43,078
-107.53
-196.16
-10.79

154.51
2,961.65
521.57

Close
Medium
Remote

-1,171
-531
-21

0
0
0

5,126
7,374
5,400

-4.38
-13.88
-260.82

-32,993
-59,882
-43,078

7,555
32,893
12,175

26.20
48,409
87,532
43,819

-

55

The long-term debt (LTD) indicators are very consistent amoung the geographic
subgroupings for both the mean and median measures. The mean and median values are very
similar for the LTD ratio. The LTD capita median values are lower than the mean values. No
other distinctive patterns appear amoung the other financial indicators that are statistically
significant. Note that the high coefficients of variation for these other financial indicators
result in statistically insignificant relationships.
Table 28: Descriptive Statistics by Geographic Remoteness - Other Indicators (Part 2)
Financial
Geographic
Indicator
Zone
Earned
Close
Revenue Ratio Medium
Remote
Earned
Close
Revenue
Medium
Capita
Remote
Earned And
Close
Other
Medium
Revenue Ratio Remote
Earned And
Close
Other
Medium
Revenue
Remote
Capita
Federal and
Close
Provincial
Medium
Revenue Ratio Remote
Federal and
Close
Provincial
Medium
Revenue
Remote
Capita
Tribal Gov't & Close
Other FN
Medium
Entity
Remote
Revenue Ratio
Tribal Gov't & Close
Other FN
Medium
Entity
Remote
Revenue
Capita

Mean

Median

SD

CV

Min

Max

0.28
0.17
0.11
11,130
6,211
6,932
0.41
0.32
0.26
14,552
11,911
14,694

0.22
0.14
0.04
4,172
3,635
1,068
0.40
0.30
0.19
7,206
6,967
5,918

0.24
0.16
0.17
17,998
8,367
19,502
0.23
0.20
0.21
19,210
15,862
36,006

0.84
0.94
1.52
1.62
1.35
2.81
0.57
0.65
0.82
1.32
1.33
2.45

-0.22
-0.28
-0.44
-3,330
-8,775
-13,313
-0.27
-0.59
-0.16
-5,388
-19,140
-4,014

0.86
0.75
0.73
125,403
48,251
143,219
1.00
0.87
0.99
132,086
100,299
258,109

0.51
0.57
0.67
13,720
16,905
20,014

0.52
0.59
0.73
12,445
14,835
17,840

0.22
0.22
0.24
9,818
11,684
15,805

0.43
0.38
0.35
0.72
0.69
0.79

0.00
0.00
44
441

1.18
1.56
1.11
71,270
94,492
127,652

0.06
0.08
0.07

0.02
0.03
0.03

0.09
0.11
0.13

1.59
1.51
2.00

-

0.57
0.68
0.87

1,403
2,123
2,595

369
755
703

2,475
3,214
8,836

1.76
1.51
3.40

-

20,022
23,166
72,722

56

The mean earned and other revenue ratio is higher for geographically close
communities at 0.41, while remote communities are 0.26. The median values are very
similar. The mean and median capita measure shows more consistency between the
geographic subgroupings, although the median values are much lower than the mean values.
Refer to Appendix E, Figures A81 – A84 for a further breakdown by subgroup. Mean
transfer revenue (both ratios and capita measures) from the federal/provincial government are
higher for geographically remote communities. This is expected as Indigenous Services
Canada provides supplemental funds for remote communities due to the higher costs of more
remote locations. The median for this ratio value is very similar to the mean. The median for
this capita measure is slightly lower than the mean. Refer to Appendix E, Figures A85 – A88
for a further breakdown by subgroup.
A common theme amoung the revenue source indicators are that geographically remote
and medium communities with large populations have lower per capita revenue (refer to
Appendix E, Figures A81 – A92). Having lower revenue from every source presents a
problem when these First Nation governments are required to provide many essential
services to their community members.

57

Table 29: Descriptive Statistics by Geographic Remoteness - Demographic Indices
Geographic
Zone
Education
Close
Index
Medium
Remote
Workforce
Close
Index
Medium
Remote
Language
Close
Index
Medium
Remote
Housing Index Close
Medium
Remote
Income Index Close
Medium
Remote
Nation
Close
Wellness
Medium
Index
Remote
Index

Mean

Median

SD

CV

51.7
45.2
32.4
57.4
54.5
57.3
17.9
28.1
50.7
70.2
62.2
52.0
34.2
29.4
28.9
66.5
64.0
64.4

53.6
45.9
30.3
57.8
54.1
56.2
12.5
25.0
47.8
71.4
61.9
50.4
33.5
27.0
26.5
66.8
63.8
62.6

11.9
13.1
14.6
12.0
13.8
13.6
18.3
19.9
30.2
16.7
17.7
15.8
10.9
9.7
9.3
9.9
12.3
12.0

0.23
0.29
0.45
0.21
0.25
0.24
1.02
0.71
0.60
0.24
0.28
0.30
0.32
0.33
0.32
0.15
0.19
0.19

Min
23.7
8.9
3.7
13.5
20.6
26.5
28.6
5.7
14.3
17.3
17.3
17.6
43.3
32.3
42.5

Max
81.3
100.0
75.1
90.2
100.0
100.0
98.5
99.3
100.0
100.0
100.0
100.0
92.8
100.0
56.3
98.9
100.0
97.5

The mean and median values for the demographic indices are very similar. Due to this,
only the mean values will be discussed. The education index has significant differences based
on geographic remoteness. It is worthwhile analyzing the subgroup matrix for the education
index, as very distinct patterns emerge. Refer to Appendix D, Figures A1 – A2. Note that the
education index for the total population is 45.1 Geographically remote communities with
medium populations have an education index of 28.6, and geographically remote
communities with large populations have an education index of 25.8. This significantly lower
level of educational attainment is concerning, and raises question as to why these two
subgroups are so much lower.
The language index indicates significant differences based on geographic remoteness.
Similar to the education index, it is worthwhile evaluating the subgroup matrix. Refer to
Appendix D, Figures A5 – A6. Note that the language index for the total population is 28.7.
Geographically remote communities with medium populations have a language index of
58

52.4, and geographically remote communities with large populations have a language index
of 64.5. It makes intuitive sense that communities that are more geographically remote would
have a higher knowledge of Indigenous language, as members in these communities would
have less interactions with community outsiders that may speak non-Indigenous languages.
The housing index indicates that geographically close communities have better
residential housing conditions. Similar to the education and education and language indices,
it is worthwhile evaluating the subgroup matrix in greater detail as distinct patterns emerge.
Refer to Appendix D, Figures A7 – A8. Note that the housing index for the total population
is 63.1. Geographically remote communities with medium populations have a housing index
of 51.2, while geographically remote communities with large populations have a housing
index of 43.0. For these communities, approximately half of the residential houses are in
need of major repairs. This is very distressing, and indicates that many of these communities
have widespread housing issues.
The income index has missing data for small populations. Due to data quality issues,
Statistics Canada did not release income information for small population communities. As
such, this analysis only evaluates medium and large population communities. Geographically
close communities have slightly higher income levels, which slightly declines with more
geographically remote communities. Note that the variances between subgroups is not
drastic. The workforce index is largely consistent between the geographic subgroupings, as is
the Nation wellness index.

Descriptive Statistics and Comparative Analysis – Concluding Statements
This chapter has reviewed the descriptive statistics of the investing financial indicators
and community wellbeing demographic indices of First Nation communities. The
comparative analysis performed has identified key trends for the total population as a whole,
as well as trends between the different population subgroupings and geographic remoteness
subgroupings. Both the mean and median values were evaluated. The next chapter evaluates
the Pearson correlation coefficients between the investing financial indicators and the
demographic indices. The correlation analysis is conducted for the total population as a
whole, and by the major subgroups of First Nation communities.

59

Chapter 4: Pearson Correlation Coefficient (r) Analysis and
Hypotheses
This chapter outlines the findings of the correlation analysis between the First Nations
financial indicators and the Nation wellness demographic indices. The correlational findings
are presented in two sections. The first section reviews the Pearson correlation coefficients
(r) amongst the demographic indices. The second section reviews the r between the financial
indicators and the demographic indices. The findings are presented in tabular format, with
discussion following the tables.
The Methodology and Hypotheses chapter provided the pre-established hypotheses for
the correlations that are discussed. The hypotheses proposed whether or not a statistically
significant correlation was expected. All expected statistically significant correlations in
Tables 4 – 6 expect a positive correlation. This section provides the findings as to whether
the hypotheses are supported or not supported based on the correlational analysis at a
statistical significance level of 5%. As noted in Chapter 2, a weakness of Pearson correlation
analysis is that other impactful variables are not controlled for. This weakness will be
addressed in Chapter 5 with the use of multiple linear regression. Several of the hypotheses
will be re-evaluated in this multiple linear regression, which evaluates nine independent
variables. Key differences between the Pearson correlation analysis and multiple linear
regression will be considered in Chapter 6.
This chapter makes reference to several appendices that provide further detail regarding
the analysis. Refer to Table 30 for a listing of these appendices.

60

Table 30: Appendices Relating to Pearson Correlation Chapter
Appendix
Appendix J
Appendix K
Appendix L
Appendix M
Appendix N
Appendix O
Appendix P
Appendix Q
Appendix R

Appendix Description
R Results Between Business Activity Indicators and Demographic Indices
R Results Between Government Business Entity (GBE) Activity Indicators
and Demographic Indices
R Results Between Trust Activity Indicators and Demographic Indices
R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices
R Results Between Other Activity Indicators and Demographic Indices
Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups
Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population
Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups
Correlational Instance Scatterplots and Line of Best Fit Graphs

Throughout this section and the appendices noted in Table 30, the following
presentation and markings will be used. Numbers presented in red text represent negative
correlations, highlighted cells represent r values that are greater than 0.40 or are less than
-0.40, and results with an * represent correlational amounts that are statistically significant at
the 5% level. Relevant highlighted items in Appendices J – N and Tables 31 – 45 are further
evaluated via a scatterplot and line of best fit graph in Appendix R. Statistically significant
items in Tables 31 to 45 are also evaluated via a graph in Appendix R. The line of best fit in
Appendix R is based on a fractional polynomial calculation.
The following sections present the r results amongst the demographic indices for the
total population and subgroups, and the r results between the financial indicators and
demographic indices for the total population. The results are presented in tables along with
discussion. Appendices J – N provide the financial indicator/demographic indices r results in
tabular format for the subgroups. Appendices O – Q provide further analysis, results, and
referencing to the correlational instance graphs. Finally, Appendix R provides the
correlational instance scatterplots and line of best fit graphs. For the sake of flow and brevity,
detailed appendix referencing has been left out of the general discussion. For further analysis
and detailed referencing to data charts, tables, and other appendices, refer to Appendices O Q. This provides ease of reference for readers that seek a more in-depth analysis of a given
topic.
61

R Results and Discussion Amongst Demographic Indices
This section reviews the correlations amongst the demographic indices. Recall that the
hypotheses proposed whether or not a correlation is statistically significant and positive. This
section will present the results, and discuss whether the findings support the hypotheses.
Statistical significance is evaluated at the 5% level. For the sake of brevity, detailed
referencing has been left out of this discussion section. Refer to Tables 31 – 40 for the r
result summary tables. Refer to Appendix O for further analysis and referencing to the
scatterplot and line of best fit graphs.

Table 31: R Summary Between Demographic Indices - Total Population
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.41*
-0.54*
0.44*
0.45*
0.51*

1.00
-0.23*
0.36*
0.56*
0.69*

1.00
-0.37*
-0.23*
0.09

Housing

Income

1.00
0.50*
0.66*

1.00
0.71*

Nation
Wellness

1.00

Table 32: R Summary Between Demographic Indices - Subgroup SC
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.04
-0.01
-0.07
n/a
0.39*

1.00
0.38*
0.06
n/a
0.67*

1.00
-0.29
n/a
0.44*

Housing

Income

1.00
n/a
0.51*

n/a
n/a

Nation
Wellness

1.00

62

Table 33: R Summary Between Demographic Indices - Subgroup SM
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.23
-0.26*
0.08
n/a
0.43*

1.00
0.04
0.35*
n/a
0.69*

1.00
0.06
n/a
0.36*

Housing

Income

1.00
n/a
0.75*

n/a
n/a

Nation
Wellness

1.00

Table 34: R Summary Between Demographic Indices - Subgroup SR
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.21
-0.17
-0.11
n/a
0.34

1.00
0.08
0.24
n/a
0.67*

1.00
0.06
n/a
0.58*

Housing

Income

1.00
n/a
0.54*

n/a
n/a

Nation
Wellness

1.00

Table 35: R Summary Between Demographic Indices - Subgroup MC
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.43*
-0.42*
0.50*
0.43*
0.71*

1.00
-0.11
0.05
0.34*
0.64*

1.00
-0.46*
-0.26*
-0.04

Housing

Income

1.00
0.50*
0.63*

1.00
0.68*

Nation
Wellness

1.00

63

Table 36: R Summary Between Demographic Indices - Subgroup MM
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.57*
-0.39*
0.39*
0.34*
0.57*

1.00
-0.28*
0.52*
0.54*
0.74*

1.00
-0.23*
-0.19*
0.12

Housing

Income

1.00
0.44*
0.75*

1.00
0.66*

Nation
Wellness

1.00

Table 37: R Summary Between Demographic Indices - Subgroup MR
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.44*
-0.47*
0.22
0.41*
0.24

1.00
-0.38*
0.18
0.54*
0.38*

1.00
-0.31*
-0.01
0.49*

Housing

Income

1.00
0.34*
0.34*

1.00
0.73*

Nation
Wellness

1.00

Table 38: R Summary Between Demographic Indices - Subgroup LC
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.57*
-0.69*
0.67*
0.59*
0.60*

1.00
-0.31*
0.48*
0.74*
0.77*

1.00
-0.48*
-0.31
-0.06

Housing

Income

1.00
0.56*
0.72*

1.00
0.84*

Nation
Wellness

1.00

64

Table 39: R Summary Between Demographic Indices - Subgroup LM
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.69*
-0.20
0.59*
0.44*
0.57*

1.00
-0.03
0.54*
0.78*
0.69*

1.00
-0.16
0.06
0.58*

Housing

Income

1.00
0.52*
0.58*

1.00
0.65*

Nation
Wellness

1.00

Table 40: R Summary Between Demographic Indices - Subgroup LR
Index
Education
Workforce
Language
Housing
Income
Nation Wellness

Education Workforce Language
1.00
0.64*
-0.54*
0.53
0.75*
0.31

1.00
-0.48
0.55*
0.74*
0.37

1.00
-0.09
-0.46
0.51

Housing

Income

1.00
0.49
0.70*

1.00
0.37

Nation
Wellness

1.00

The hypothesis expected the education index and workforce index to have statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a positive correlation of 0.41* for the total
population. A positive correlation is notably stronger for communities with large populations
(LC, LM, LR). The correlation is weaker for medium populations (MC, MM, MR), but is
still statistically significant. The correlation for small population communities is very weak
(SC, SM, SR), and is not statistically significant.
The hypothesis expected the education index and income index to have a statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a positive correlation of 0.45* for the total
population. Note that no income data is available for small population communities due to
data quality issues. Medium population (MC, MM, MR) and large population (LC, LM, LR)
communities demonstrate a statistically significant positive correlation. The trend also

65

emerges where the indices initially rise more steeply and then the correlation levels off as the
index levels are higher.
No hypothesis was established regarding the education index and language index.
Based on the results of Table 31, the results indicate a negative correlation of -0.54* for the
total population. Small population communities demonstrate a weaker correlation, with
subgroups SC and SR being not statistically significant. The negative correlation is generally
stronger with larger population levels, and is statistically significant for subgroups MC, MM,
MR, LC, and LR. This level of negative correlation is surprising to the author, as no
correlation was initially expected. The fact that higher levels of formal education is
negatively correlated with knowledge of Indigenous language is concerning. This may be an
indication that further efforts are required to preserve traditional Indigenous languages within
formal education systems. Note, however, that a causal conclusion cannot be made from this
analysis. There may be other factors that explain this correlation.
The hypothesis expected the education index and housing index to have a statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a statistically significant positive correlation for
the total population of 0.44*. Small population communities (SC, SM, SR) have nonstatistically significant correlations. Also, geographically remote communities (SR, MR, LR)
have non-statistically significant correlations. Medium and large population communities that
are geographically close and medium (MC, LC, MM, LM) all have statistically significant
positive correlations.
The hypothesis expected the education index and Nation wellness index to have a
statistically significant positive correlation. Based on the results of Table 31, this hypothesis
is supported for the population as a whole. The results indicate a positive correlation of 0.51*
for the total population. Communities that are geographically close (SC, MC, LC) and
medium (SM, MM, LM) all have statistically significant positive correlations. Note that
geographically remote communities (SR, MR, LR) do not maintain a statistically significant
correlation.
No hypothesis was established regarding the workforce index and language index.
Based on the results of Table 31, the results indicate a statistically significant negative

66

correlation of -0.23* for the total population. The following subgroups maintain statistically
significant correlations: SC, MM, MR, and LC.
The hypothesis expected the workforce index and housing index to have a statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a statistically significant positive correlation of
0.36*. Note that approximately half of the subgroups maintain non-statistically significant
correlations while the other half maintain statistically significant correlations. Communities
with large populations (LC, LM, LR) all have statistically significant positive correlations.
Also, all geographically medium (SM, MM, LM) communities have statistically significant
positive correlations.
The hypothesis expected the workforce index and income index to have a statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a positive correlation for the total population of
0.56*. Large population communities (LC, LM, LR) have statistically significant positive
correlations. Medium populations communities (MC, MM, MR) maintain statistically
significant positive correlations, albeit weaker than large populations. No income data is
available for small population communities.
The hypothesis expected the workforce index and Nation wellness index to have a
statistically significant correlation. Based on the results of Table 31, this hypothesis is
supported for the population as a whole. The results indicate a positive correlation for the
total population of 0.69*. Most of the community subgroups have statistically significant
positive correlations, with the exception of large population communities that are
geographically remote (LR).
No hypothesis was established regarding the language index and housing index. Based
on the results of Table 31, the results indicate a statistically significant negative correlation
for the population as a whole of -0.37*. Medium population communities (MC, MM, MR)
maintain statistically significant negative correlations, as do large population communities
that are geographically close (LC). All other subgroups do not have a statistically significant
correlation.
No hypothesis was established regarding the language index and income index. Based
on the results of Table 31, the results indicate a statistically significant negative correlation
67

for the population as a whole of -0.23*. Medium population communities that are
geographically close (MC) and medium (MM) maintain statistically significant negative
correlations. Note that no income data is available for small population communities. Large
population communities do not maintain statistically significant correlations.
The hypothesis expected the language index and Nation wellness index to have a
statistically significant correlation. Based on the results of Table 31, this hypothesis is not
supported for the population as a whole. A non-statistically significant correlation for the
total population exists of 0.09. Small population communities (SC, SM, SR) maintain
statistically significant positive correlations, as do subgroups MR and LM.
The hypothesis expected the housing index and income index to have a statistically
significant correlation. Based on the results of Table 31, this hypothesis is supported for the
population as a whole. The results indicate a positive correlation for the total population of
0.50*. No income data is available for small population communities. All other community
subgroups have a statistically significant positive correlation, except for large population
communities that are geographically remote (LR).
The hypothesis expected the housing index and Nation wellness index to have a
statistically significant correlation. Based on the results of Table 31, this hypothesis is
supported for the population as a whole. The results indicate a positive correlation of 0.66*.
All of the community subgroups maintain a statistically significant positive correlation.
The hypothesis expected the income index and Nation wellness index to have a
statistically significant correlation. Based on the results of Table 31, this hypothesis is
supported for the population as a whole. The results indicate a positive correlation of 0.71*.
Note that no income data is available for small population communities. All other community
subgroups maintain a statistically significant positive correlation, except for large population
communities that are geographically remote (LR).
This section has reviewed the correlational results amongst the demographic indices,
and presented the results of the relating hypotheses. While some of the hypotheses are not
supported, many of the hypotheses are supported by the correlational analysis that
demonstrate a statistically significant correlation at the 5% level.

68

R Results and Discussion Between Financial Indicators and Demographic Indices
This section reviews the correlation results between the financial indicators and the
demographic indices. Recall that the hypotheses proposed whether or not a correlation is
statistically significant and positive. This section will present the results and discuss whether
or not the findings support the hypotheses. Statistical significance is evaluated at the 5%
level. For the sake of brevity, detailed referencing has been left out of this discussion section.
Refer to Tables 41 – 45 and Appendices J – N for the r summary tables. Refer to Appendices
P and Q for further analysis and detailed referencing to the scatterplot and line of best fit
graphs.
R Results Between Business/GBE Activity Financial Indicators and Demographic Indices
This subsection reviews the r results between the business/GBE activity indicators and
the demographic indices. The r results for the total population are presented in Tables 41 –
42, which is followed by discussion. Supplementary information regarding the subgroup
correlational results is provided throughout the discussion section. Note that the r results for
the subgroups can be found in Appendices J – K.
Table 41: R Summary Between Business Activity Financial Indicators and Demographic
Indices – Total Population
Financial Indicators

Demographic Indices

-0.00

0.01

-0.02

0.09

Nation
Wellness
0.21*
0.06

0.10*

0.16*

-0.08

0.19*

0.27*

0.20*

Gross Business Sales
Ratio

0.17*

0.12*

-0.16*

0.14*

0.07

0.08

Gross Business Sales
Capita

0.17*

0.18*

-0.16*

0.18*

0.04

0.14*

Business and Ec Dev
Expense Ratio

0.21*

0.19*

-0.24*

0.19*

0.04

0.09*

Business and Ec Dev
Expense Capita

0.17*

0.23*

-0.20*

0.18*

-0.01

0.13*

Education Workforce Language
Investment Asset
Ratio
Investment Asset
Capita

Housing

Income

69

Table 42: R Summary Between Government Business Entity (GBE) Activity Financial
Indicators and Demographic Indices – Total Population
Financial Indicators

Demographic Indices

-0.01
0.01
-0.01
0.01

0.04
0.17*
0.10
0.15*

-0.02
-0.03
-0.01
-0.02

0.09
0.16*
0.13*
0.16*

0.18*
0.19*
0.22*
0.18*

Nation
Wellness
0.05
0.17*
0.12*
0.17*

-0.00
0.02
-0.01
0.01
-0.06

0.07
0.18*
-0.02
0.11*
0.00

-0.00
-0.02
0.02
-0.01
0.02

0.11*
0.16*
0.04
0.12*
-0.05

0.20*
0.19*
0.30*
0.41*
-0.08

0.12*
0.18*
0.05
0.14*
-0.03

-0.02

-0.02

-0.00

0.08

-0.18*

0.04

Education Workforce Language
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue
Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

Housing

Income

Education Index
The hypothesis expected the education index to have a statistically significant
correlation with the business activity and GBE activity indicators. Based on the results of
Tables 41-42, the hypothesis holds true for the business financial indicators but not for the
GBE financial indicators. The business activity indicators show statistically significant
positive correlation with the education index, particularly with gross business sales
ratio/capita (0.17*, 0.17*), and business & economic development expense ratio/capita
(0.21*, 0.17*). Curiously, the education index maintains a non-statistically significant
correlation with all of the GBE activity indicators. This indicates that business activities that
are more closely associated with the Nation government have a stronger relation with the
education index, while more arms-length GBE activities have nearly no correlation with the
education index.
Note the following statistically significant correlations at the subgroup level. Subgroup
SC maintains statistically significant positive correlations for GBE asset, revenue, and
expense indicators (both ratio and capita). Subgroup LR also maintains statistically
significant positive correlations for GBE revenue and expense capita measures.

70

Workforce Index
The hypothesis expected the workforce index to have a statistically significant
correlation with the business activity and GBE activity indicators. Based on the results of
Tables 41-42, this hypothesis is supported for the population as a whole. The results indicate
statistically significant positive correlation. The business activity indicators show positive
correlations with the workforce index, particularly with gross business sales ratio/capita
(0.12*, 0.18*), and business & economic development expense ratio/capita (0.19*, 0.23*).
Positive correlations also exist for the GBE activity indicators, but only for the capita
indicators of GBE asset capita (0.17*), GBE revenue capita (0.15*), GBE expense capita
(0.18*), and GBE equity capita (0.11*). This indicates that per capita GBE activity plays a
more significant role in local workforce levels versus the GBE ratios.
Note the following statistically significant correlations at the subgroup level. Subgroup
SM maintains a statistically significant correlation for GBE asset capita, GBE revenue
ratio/capita, GBE expense ratio/capita, and GBE equity capita. Subgroup MM maintains a
statistically significant correlation for investment asset capita, gross business sales
ratio/capita, and business & economic development expense ratio/capita.
Language Index
No hypothesis was established regarding the correlation between the language index
and the business activity and GBE activity indicators. Based on the results of Tables 41-42,
the results indicate statistically significant negative correlations for the business activity
indicators and the language index. Business activity indicators show a negative correlation
with the language index, particularly with gross business sales ratio/capita (-0.16*, -0.16*),
and business & economic development expense ratio/capita (-0.24*, -0.20*). The GBE
activity indicators maintain a non-statistically significant correlation with the language index.
Note the following statistically significant correlations relating at the subgroup level.
Geographically remote communities with medium or large populations (MR, LR)
demonstrate a negative correlation between the business activity indicators and the language
index.
Housing Index
The hypothesis expected the housing index to have a statistically significant correlation
with the business activity and GBE activity indicators. Based on the results of Tables 41-42,
this hypothesis is supported for the population as a whole. Business activity indicators show
71

statistically significant positive correlations with the housing index, particularly with
investment asset capita (0.19*), gross business sales ratio/capita (0.14*, 0.18*), and business
& economic development expense ratio/capita (0.19*, 0.18*). The GBE activity indicators
show statistically significant positive correlations with the housing index, particularly with
GBE asset capita (0.16*), GBE revenue ratio/capita (0.13*, 0.16*), GBE expense ratio/capita
(0.11*, 0.16*), and GBE equity capita (0.12*). This indicates a positive correlation between
business and GBE activities with the housing index. For the GBE activity indicators, this
relationship is stronger with gross revenue and expenses compared to GBE net income or
GBE equity. This demonstrates that gross levels of GBE activity may be more significant
than net profit levels.
Note the following statistically significant correlations at the subgroup level. Business
activity indicators are statistically significant for subgroup SC. Business activity and GBE
activity indicators are statistically significant for subgroup MM, particularly the capita
indicators. Also, the GBE activity capita measures of GBE revenue and GBE expense are
statistically significant for subgroup MR.
Income Index
The hypothesis expected the income index to have a statistically significant correlation
with the business activity and GBE activity indicators. Based on the results of Tables 41-42,
this hypothesis is supported for the population as a whole. Two of the business activity
indicators show a statistically significant positive correlation with the income index, those
being investment asset ratio/capita (0.21*, 0.27*). GBE activity indicators show a
statistically significant positive correlation with the income index, particularly GBE asset
ratio/capita (0.18*, 0.19*), GBE revenue ratio/capita (0.22*, 0.18*), GBE expense
ratio/capita (0.20*, 0.19*), and GBE equity ratio/capita (0.30*, 0.41*). Note that the business
activity indicators of gross revenue and expenses shows a nearly 0.00 correlation, while the
investment asset indicators show a positive correlation. This indicates that cumulative
investment asset levels have a stronger relation with income levels when evaluating
businesses that have stronger Nation government control. Conversely, note that GBE gross
activity levels (revenues and expenses) have positive correlations with the income index.
GBE asset levels and equity levels also maintain positive correlations, while GBE net income

72

does not. This indicates that gross GBE activities may be more important than net GBE
income.
Note the following statistically significant correlations at the subgroup level. Medium
and large population communities generally show a statistically significant positive
correlation between GBE activities and income levels, most commonly for GBE revenue and
expense indicators. This correlation often exists even when GBE net income is not
correlated. This demonstrates that gross GBE activities hold a stronger correlation that just
net GBE income alone. Note also that investment asset ratio/capita maintain a positive
correlation for subgroups MC, MM, and LR.
Nation Wellness Index
The hypothesis expected the Nation wellness index to have a statistically significant
correlation with the business activity and GBE activity indicators. Based on the results of
Table 41-42, this hypothesis is supported for the population as a whole. Business activity
indicators have statistically significant positive correlations with the Nation wellness index,
particularly investment asset capita (0.20*), gross business sales capita (0.14*), and business
& economic development expense ratio/capita (0.09*, 0.13*). GBE activity indicators have
statistically significant positive correlations with the Nation wellness index, particularly GBE
asset capita (0.17*), GBE revenue ratio/capita (0.12*, 0.17*), GBE expense ratio/capita
(0.12*, 0.18*), and GBE equity capita (0.14*). The strongest correlations exist with capita
indicators, both for the business activity and GBE activity indicators. Also, the recurring
trend exists that GBE gross activity (revenues and expenses) has a stronger relation than
GBE net income. This demonstrates that gross GBE activity, particularly on a per capita
basis, has the strongest relationship with Nation wellness.
Note the following statistically significant correlations at the subgroup level. The
business activity indicators demonstrate a statistically significant positive correlation in
subgroups SC and MM. The GBE activity indicators demonstrate a statistically significant
positive correlation in subgroups SM and MM. The GBE correlation is notable particularly in
the GBE capita measures. The business activity indicators for subgroup LR are distinct, in
that there is a statistically significant negative correlation in the business & economic
development expense ratio/capita (-0.67*, -0.66*). This appears to relate largely to a negative
correlation present between the business activity indicators and the language index
73

(correspondingly -0.55* and -0.64*). It is important to recall that the number of First Nations
in subgroup LR is small, which could result in the outlier First Nations distorting the
statistical results.
R Results Between Trust Activity Financial Indicators and Demographic Indices
This subsection reviews the r results between the trust financial indicators and the
demographic indices. The r results for the total population are presented in Table 43, which is
followed by discussion. Supplementary information regarding the subgroup correlational
results is provided throughout the discussion section. Note that the r results for the subgroups
can be found in Appendix L. Finally, a stratified population analysis will be conducted to
determine if distinct trends exist between First Nations that hold a low, moderate, or high
levels of trust fund assets.
Table 43: R Summary Between Trust Activity Financial Indicators and Demographic Indices
– Total Population
Financial
Indicators

Demographic Indices
Education

Workforce

Language

Housing

Trust Fund
Assets Ratio
Trust Fund
Assets Capita

-0.07

-0.05

-0.01

-0.11*

Nation
Wellness
0.03
-0.11*

-0.01

0.05

0.00

-0.02

0.04

0.01

Trust Revenue
Ratio
Trust Revenue
Capita

-0.07

-0.03

0.03

-0.07

-0.02

-0.06

-0.01

0.12*

0.01

0.07

0.03

0.10*

Income

Education Index
The hypothesis expected the education index to have a non-statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
is supported for the population as a whole. The results indicate a non-statistically significant
correlation. Note the following statistically significant correlations at the subgroup level.
Subgroup MM maintains statistically significant negative correlations with trust fund assets
ratio and capita indicators, and subgroup LC maintains statistically significant negative
correlations with trust revenue ratio/capita.
74

Workforce Index
The hypothesis expected the workforce index to have a non-statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
is supported for the population as a whole. The results indicate a non-statistically significant
correlation, with the exception of trust revenue capita (0.12*). Note the following statistically
significant correlation at the subgroup level. Subgroup SR maintains statistically significant
negative correlations for all trust indicators.
Language Index
The hypothesis expected the language index to have a non-statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
is supported for the population as a whole. The results indicate a non-statistically significant
correlation. Note the following statistically significant correlations at the subgroup level.
Geographically remote communities that have small and large populations (SR, LR) maintain
statistically significant negative correlations with trust fund asset capita.
Housing Index
The hypothesis expected the housing index to have a non-statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
is supported for the population as a whole. The results indicate a non-statistically significant
correlation, except for the trust fund assets ratio (-0.11*). Note the following statistically
significant correlations at the subgroup level. Subgroup SR maintains a statistically
significant negative correlation for trust fund assets ratio/capita. Subgroup LC maintains a
statistically significant negative correlation for trust fund assets capita and trust revenue
ratio/capita.
Income Index
The hypothesis expected the income index to have a non-statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
is supported for the population as a whole. The results indicate a non-statistically significant
correlation. Note the following statistically significant correlation. Subgroup LM maintains a
statistically significant positive correlation for trust fund asset ratio/capita.
Nation Wellness Index
The hypothesis expected the Nation wellness index to have a statistically significant
correlation with the trust activity indicators. Based on the results of Table 43, this hypothesis
75

is not supported for the population as a whole. The correlations are not statistically
significant, except for trust fund assets ratio (-0.11*) and trust revenue capita (0.10*). Note
the following statistically significant correlations at the subgroup level. Geographically
remote communities with small populations (SR) maintain statistically significant negative
correlations with all trust indicators. Geographically remote communities with medium
populations (MR) maintain statistically significant positive correlations with trust revenue
ratio/capita.
Appendix U – Analysis of Trust Activity by Stratified Group
Appendix U conducts a Pearson correlational analysis between the trust activity
indicators and the demographic indices by a stratified grouping. Based on the trust fund
activity descriptive statistics (Table 12), there appears to be a large spread amoung First
Nations in trust fund asset holdings. To determine if distinct trends are present between
Nations with low, moderate, or high levels of trust assets, an analysis of the stratified
population will be conducted. The First Nations are stratified on the basis of trust fund assets
per capita, which are defined as low trust assets ($0 - $4,999), moderate trust assets ($5,000 $39,999), and high trust assets ($40,000 or higher). This section will provide a high-level
discussion of the analysis. Refer to Appendix U for the detailed analysis.
Very distinct Pearson correlation coefficients are present between the stratified groups.
First Nations with a low level of trust assets maintain the lowest correlation between the trust
activity financial indicators and the demographic indices. While some statistically significant
correlations exist, the r value is very low and range from -0.14 to 0.13. This makes intuitive
sense, as low levels of trust assets may not be sufficient to make a strong impact on First
Nation communities. A very different trend is present, however, for First Nations with
moderate or high levels of trust assets per capita.
Moderate and high trust assets Nations maintain negative and statistically significant
correlations between the workforce index and the trust fund assets ratio. Moderate trust assets
Nations maintain a correlation of -0.38*, while high trust assets Nations maintain a
correlation of -0.55*. These relationships are not intuitive as it indicates a negative
correlation between trust fund assets ratio and workforce levels. It is important to not make a
causal conclusion about this analysis, as external factors may be the underlying reason for the
observed correlation. Note that a higher trust fund assets ratio means that a higher percentage
76

of the Nation’s assets are invested in trust funds. One possible explanation could be that less
funds are available to invest in Nation owned business that could provide employment
opportunities. Better understanding this negative correlation would be an interesting area for
future research.
Moderate and high-level trust assets Nations also maintain negative and statistically
significant correlations between the housing index and the trust fund assets ratio. Moderate
trust assets Nations maintain a correlation of -0.60*, while high trust assets Nations maintain
a correlation of -0.56*. Note that low trust assets Nations maintain a non-statistically
significant correlation of -0.06. These relationships are also not intuitive, it indicates that a
negative correlation between trust fund assets ratio and the condition of residential housing.
Similar to the previous paragraph, it is important not to draw causal conclusions from this
analysis. External factors may contribute to this negative correlation, such as having less
assets available to invest in tangible capital assets such as community housing. This negative
correlation would be an interesting area for future research.
R Results Between Tangible Capital Asset (TCA) Activity Financial Indicators and
Demographic Indices
This subsection reviews the r results between the TCA financial indicators and the
demographic indices. The r results for the total population are presented in Table 44, which is
followed by discussion. Supplementary information regarding the subgroup correlational
results are provided throughout the discussion section. Note that the r results for the
subgroups can be found in Appendix M.

77

Table 44: R Summary Between TCA Financial Indicators and Demographic Indices – Total
Population
Financial
Indicators

TCA Assets
Ratio
TCA Assets
Capita
Gross Cash
Outflows from
Capital Ratio
Gross Cash
Outflows from
Capital Capita

Demographic Indices
Nation
Wellness
-0.43*
-0.22*

Education

Workforce

Language

Housing

Income

-0.19*

-0.23*

0.17*

-0.19*

-0.06

0.24*

-0.06

0.06

0.07

0.12*

-0.08

-0.04

0.12*

-0.05

-0.11

-0.00

0.04

-0.18*

0.03

-0.04

-0.06

-0.09

Education Index
The hypothesis expected the education index to have a statistically significant
correlation with the TCA activity indicators. Based on the results of Table 44, this hypothesis
is not supported for the population as a whole. The TCA assets ratio actually maintains a
statistically significant negative correlation of -0.19*. Note the following statistically
significant correlations at the subgroup level. Subgroup LC maintains a statistically
significant negative correlation with TCA assets ratio. Subgroup LR maintains a statistically
significant negative correlation with gross cash outflows from capital.
Workforce Index
The hypothesis expected the workforce index to have a statistically significant
correlation with the TCA activity indicators. Based on the results of Table 44, this hypothesis
is not supported due to mixed results from the various financial indicators. The workforce
index maintains correlations with TCA assets ratio/capita (-0.23*, 0.24*) and gross cash
outflows from capital capita (-0.18*). Note the following statistically significant correlations
at the subgroup level. Geographically medium communities with small or medium
populations (SM, MM) maintain a statistically significant negative correlation with TCA
assets ratio.

78

Language Index
No hypothesis was expected regarding the language index and its correlation with the
TCA activity indicators. Based on the results from Table 44, the results indicate a statistically
significant correlation for the population as a whole. The language index maintains
correlations with TCA ratio (0.17*) and gross cash outflows from capital ratio (0.12*). The
language index follows a different pattern from the other demographic indices. The
correlation with TCA asset ratio is positive instead of negative. Note the following
statistically significant correlations at the subgroup level. Subgroup SR maintains a
statistically significant negative correlation with TCA assets capita, and a statistically
significant positive correlation with gross cash outflows from capital capita.
Housing Index
The hypothesis expected the housing index to have a statistically significant correlation
with the TCA activity indicators. Based on the results of Table 44, this hypothesis is not
supported for the population as a whole. The results are not statistically significant, except
for TCA assets ratio (-0.19*). Note the following statistically significant correlations at the
subgroup level. Subgroup SC maintains a statistically significant positive correlation with
TCA assets capita, while subgroup SR maintains a statistically significant negative
correlation with TCA assets capita.
Income Index
The hypothesis expected the income index to have a statistically significant correlation
with the TCA activity indicators. Based on the results of Table 44, this hypothesis is not
supported for the population as a whole. The results indicate a non-statistically significant
correlation, except for one exception regarding the TCA assets ratio. TCA asset ratio
maintains a statistically significant negative correlation of -0.43*. The TCA assets ratio
follows a similar pattern for most subgroups. Note the following statistically significant
correlations at the subgroup level. No income data is available for small populations due to
data quality issues. Medium population communities (MC, MM, MR) maintain a statistically
significant negative correlation with the TCA asset ratio, while subgroups MC and MM
maintain statistically significant positive correlations with the TCA asset capita indicators.
The negative correlation with the TCA asset ratio is surprising to the author. This indicates
that First Nation governments with a higher percentage of tangible capital assets compared to
total assets correlates with lower income levels in those communities. It may be possible that
79

this negative correlation is more a function of lowered total assets, instead of higher tangible
capital assets. This would be an interesting area for further research.
Nation Wellness Index
The hypothesis expected the Nation wellness index to have a statistically significant
correlation with the TCA activity indicators. Based on the results of Table 44, this hypothesis
is not supported for the population as a whole. The results are mixed based on the specific
financial indicator. The Nation wellness index maintains statistically significant correlations
for the total population with TCA assets ratio/capita (-0.22*, 0.12*). The results are also
mixed amoung the subgroups, with no clearly distinct pattern emerging.
R Results Between Other Financial Indicators and Demographic Indices
This subsection reviews the r results between the other financial indicators and the
demographic indices. These financial indicators evaluate revenue by source. The three
sources of revenue evaluated are earned & other revenue, federal & provincial transfer
revenue, and First Nation sources of transfer revenue. The r results for the total population
are presented in Table 45, which is followed by discussion. Supplementary information
regarding the subgroup correlational results are provided throughout the discussion section.
Note that the r results for the subgroups can be found in Appendix N.

80

Table 45: R Summary Between Other Financial Indicators and Demographic Indices – Total
Population
Financial
Indicators

Earned and
Other Revenue
Ratio
Earned and
Other Revenue
Capita
Federal and
Provincial
Revenue Ratio
Federal and
Provincial
Revenue Capita
Tribal Gov't and
Other FN
Revenue Ratio
Tribal Gov't and
Other FN
Revenue Capita

Demographic Indices
Education

Workforce

Language

Housing

0.38*

0.17*

-0.33*

0.31*

Nation
Wellness
0.26*
0.19*

0.18*

0.19*

-0.17*

0.14*

0.03

0.14*

-0.35*

-0.19*

0.29*

-0.27*

-0.27*

-0.20*

-0.11*

0.16*

0.00

-0.05

-0.21*

0.03

0.00

0.05

0.05

-0.02

-0.03

0.06

0.08

0.14*

-0.01

0.00

0.01

0.12*

Income

Education Index
The hypothesis expected the education index to have a statistically significant
correlation with the other activity indicators. Based on the results of Table 45, the hypothesis
is supported for the population as a whole for earned & other revenue. Statistically
significant positive correlations exist for earned & other revenue ratio/capita (0.38*, 0.18*).
Statistically significant negative results are present for federal & provincial revenue
ratio/capita (-0.35*, -0.11*). This demonstrates that a higher level of earned & other revenue
is positively correlated with education levels, while a higher level of federal & provincial
transfers is negatively correlated with education levels.
Note the following statistically significant correlations at the subgroup level.
Geographically close (SC, MC, and LC) and medium (SM, MM, and LM) populations have
statistically significant positive correlations with earned & other revenue ratio. Several of
these subgroups also have positive correlations with earned & other revenue capita. Medium
81

population communities (MC, MM, and MR) have statistically significant negative
correlations with federal & provincial revenue ratio. This trend also exists for subgroups SC
and LM. This indicates that many of the subgroups show a statistically significant positive
correlation between education levels and the higher levels of earned & other revenue, while
many of the subgroups show a statistically significant negative correlation between the
education levels and the level of federal & provincial transfer revenue.
Workforce Index
The hypothesis expected the workforce index to have a statistically significant
correlation with the other activity indicators. Based on the results of Table 45, this hypothesis
is supported for the population as a whole for earned & other revenue and for the transfer
revenue capita measures. The workforce index maintains the following correlations with the
other financial indicators: earned & other revenue ratio/capita (0.17*, 0.19*), federal &
provincial revenue ratio/capita (-0.19*, 0.16*), and Tribal government and other First Nation
entity revenue capita (0.14*). This demonstrates that earned & other revenue is positively
correlated with workforce levels. Also, a higher ratio of federal & provincial transfer revenue
is negatively correlated with workforce levels. Converse to the other demographic indices, a
higher per capita amount of federal/provincial transfer revenue is positively correlated with
workforce levels. Finally, a higher per capita amount of Tribal government and other First
Nation entity revenue is positively correlated with workforce levels.
Note the following statistically significant correlations at the subgroup level.
Geographically medium communities with small or medium population (SM, MM)
demonstrate a statistically significant negative correlation with the federal & provincial
revenue ratio. A similar pattern emerges with large population communities that are
geographically close or remote (LC, LR). Geographically medium communities with medium
populations (MM) and geographically remote communities with large populations (LR)
demonstrate a statistically significant positive correlation with earned & other revenue ratio
and capita. These general trends with the other financial indicators are similar to correlations
found with the education index, although the correlations are not as consistent for the
workforce index.
Language Index
No hypothesis was predetermined between the language index and the other activity
indicators. Based on the results of Table 45, the correlations are mixed based on the type of
82

revenue. The language index maintains statistically significant correlations with earned &
other revenue ratio/capita (-0.33*, -0.17*) and federal & provincial revenue ratio (0.29*).
The language index follows a different pattern from many of the other demographic indices.
Higher levels of earned & other revenue are negatively correlated with knowledge of
Indigenous language. Also, the federal/provincial revenue ratio is positively correlated with
knowledge of Indigenous language. This trend is somewhat unsettling, as it indicates that
increased earning activities is correlated with a lower levels of Indigenous language
knowledge.
Note the following statistically significant correlations at the subgroup level. Medium
population communities that are geographically close and remote (MC, MR) maintain
statistically significant positive correlations between Indigenous language knowledge and
percentage of federal & provincial. This same pattern exists for large populations that are
geographically remote (LR). Medium and large population communities that are
geographically close and remote (MC, LC, MR, LR) maintain statistically significant
negative correlations between Indigenous language knowledge and percentage of earned &
other revenue. The general trends indicate that higher levels of federal & provincial transfer
revenue correlate with higher levels of Indigenous language knowledge, while higher levels
of earned & other revenue correlate with lower levels of Indigenous language knowledge.
Note that these trends only occur for medium and large population communities, and not for
small population communities.
Housing Index
The hypothesis expected the housing index to have a statistically significant correlation
with the other activity indicators. Based on the results of Table 45, the hypothesis is
supported for earned & other revenue only. A statistically significant positive correlation
exists for earned & other revenue ratio/capita (0.31*, 0.14*). Note that a statistically
significant negative correlation exists for federal & provincial revenue ratio of -0.27*.
Note the following statistically significant correlations at the subgroup level. Large
populations that are geographically close and medium (LC, LM) maintain statistically
significant negative correlations between the housing index and the federal & provincial
revenue ratio. This same pattern exists for medium populations that are geographically close
(MC). Medium populations that are geographically close (MC) and medium (MM) maintain
83

statistically significant positive correlations with earned & other revenue ratio. This same
pattern exists for large populations that are geographically close (LC). The general trends
indicate that a higher percentage of earned & other revenue is correlated with better housing
conditions, while a higher percentage of federal & provincial transfer revenue is correlated
with worse housing conditions. Note that these trends only occur for medium and large
population communities, and not for small population communities.
Income Index
The hypothesis expected the income index to have a statistically significant correlation
with the other activity indicators. Based on the results of Table 45, the hypothesis is not
supported. The results are mixed based on the specific financial indicator being evaluated.
The income index maintains the statistically significant correlations with earned & other
revenue ratio (0.26*) and federal & provincial revenue ratio/capita (-0.27*, -0.21*). This
demonstrates that earned & other revenue as a percentage of total revenue is positively
correlated with higher income levels. Also, federal & provincial revenue (both ratio and
capita) is negatively correlated with income levels.
Note the following statistically significant correlations at the subgroup level. Large
population communities that are geographically close and remote (LC, LR) maintain
statistically significant positive correlations with earned & other revenue ratio. This pattern is
also present with medium population communities that are geographically medium (MM).
Medium population communities that are geographically medium (MM) and large population
communities that are geographically close/remote (LC, LR) maintain a statistically
significant negative correlation with federal & provincial revenue ratio. The general trend
indicates that a higher percentage of earned & other revenue is correlated with higher income
levels, while a higher percentage of federal/provincial transfer revenue is correlated with
lower income levels. Note that no income data is available for small population communities,
so no analysis is conducted for small population communities.
Nation Wellness Index
The hypothesis expected the Nation wellness index to have a statistically significant
correlation with the other activity indicators. Based on the results of Table 45, this hypothesis
is not supported for the population as a whole. The results are mixed based on the type of
financial indicator. The Nation wellness index maintains statistically significant correlations
for earned & other revenue ratio/capita (0.19*, 0.14*), federal & provincial ratio (-0.20*),
84

and Tribal government and other First Nation entity revenue capita (0.12*). This
demonstrates that earned & other revenue is positively correlated with Nation wellness. Also,
a higher percentage of federal & provincial revenue is negatively correlated with Nation
wellness. Finally, a higher per capita amount of Tribal government and other First Nation
entity revenue is positively correlated with Nation wellness.
Note the following statistically significant correlations at the subgroup level. Medium
population communities that are geographically close and medium (MC, MM) maintain
statistically significant positive correlations between Nation wellness and percentage of
earned & other revenue. This same pattern exists for large populations that are
geographically close (LC). The general trend is that a higher percentage of earned & other
revenue is correlated with higher levels of Nation wellness.

Pearson Correlation Coefficient (r) Analysis and Hypotheses – Concluding
Statements
This chapter has reviewed the r analysis and relating hypotheses between the investing
financial indicators. Statistically significant correlations have been identified for the
population as a whole, as well as at the subgroup level. The next chapter will present the
findings of the multiple linear regression for each of the demographic indices discussed in
this manuscript.

85

Chapter 5: Multiple Linear Regression
The multiple linear regression analysis evaluates the marginal effects of several
variables on the demographic indices. As distinct regressions are expected from each
demographic index, a separate regression will be conducted for each of the demographic
indices of education, workforce, language, housing, income, and Nation wellness.
The independent variables used in each of the regressions will be the same, and consist
of several investing financial indicators, as well as community population and geographic
remoteness. Multiple linear regression provides further insight by holding each of the
independent variables constant within the regression model, which allows the reader to better
understand the variable impact of each independent variable more accurately. Refer to
Table 7 for the linear regression models and Table 8 for a description of the independent
variables. Table 46 presents the results of the multiple linear regression for each of the
demographic indices. A variance inflation factor (VIF) test has been conducted to measure
the degree of multicollinearity between the independent variables. The mean VIF amoung the
independent variables is 1.17, with the highest variable VIF amount being 1.39. This result
provides evidence that the degree of multicollinearity is low for the regression models. Note
that all r-squared values presented in Table 46 are statistically significant at the 5% level.
The subsequent section provides the regression results table, after which a general
discussion highlights the key findings of the regression models.

86

87

N
R-squared
Mean Variance Inflation Factor (VIF)

Earned & other revenue ratio
(per 0.1 change in ratio) (X1)
Federal & provincial revenue capita
(per $1,000) (X2)
Tribal Gov't and other FN entity
revenue capita (per $1,000) (X3)
GBE expense capita
(per $1,000) (X4)
Trust fund asset ratio
(per 0.1 change in ratio) (X5)
TCA assets ratio
(per 0.1 change in ratio) (X6)
Community Population
(per 100 people) (X7)
Geographically medium differential
(from geographically close) (X8)
Geographically remote differential
(from geographically close) (X9)

Variable

Notes:
1. Robust standard errors are reported in parentheses.
2. * indicates significance at the 5% level.

Geographic

Population
level

Financial

Variable
Category

446
0.34
1.17

1.72*
(0.30)
-0.01
(0.05)
0.40*
(0.16)
-0.01
(0.01)
-0.74*
(0.31)
-0.77*
(0.26)
-0.19*
(0.07)
-4.76*
(1.30)
-16.89*
(1.79)
446
0.20
1.17

0.83*
(0.29)
0.15*
(0.04)
0.37*
(0.18)
0.03*
(0.02)
-0.19
(0.24)
-0.92*
(0.26)
-0.36*
(0.06)
-3.09*
(1.22)
-0.15
(1.76)

Education Workforce
Index (E) Index (W)

446
0.37
1.17

-2.29*
(0.44)
-0.13
(0.09)
-0.17
(0.17)
0.01*
(0.00)
-0.08
(0.42)
1.07*
(0.38)
0.78*
(0.15)
9.26*
(1.93)
30.62*
(3.43)

Language
Index (L)

446
0.22
1.17

1.72*
(0.37)
0.05
(0.08)
0.18
(0.16)
0.04*
(0.01)
-1.25*
(0.46)
-0.87*
(0.36)
-0.09
(0.10)
-6.17*
(1.72)
-15.81*
(2.19)

Housing
Index (H)

Table 46: Multiple Linear Regression – Average Marginal Effects of Variables with Demographic Indices

Multiple Linear Regression Results Table

303
0.25
1.17

0.49
(0.26)
-0.19*
(0.09)
0.14
(0.27)
0.05
(0.06)
-0.17
(0.28)
-1.69*
(0.30)
-0.05
(0.05)
-2.59*
(1.24)
-1.90
(1.57)

Income
Index (I)

446
0.13
1.17

Nation
Wellness
Index (N)
0.77*
(0.26)
0.05
(0.05)
0.35*
(0.13)
0.03*
(0.00)
-0.68*
(0.25)
-0.84*
(0.24)
-0.07
(0.05)
-1.69
(1.12)
-1.16
(1.61)

Multiple Linear Regression Results Discussion
This section reviews each demographic index regression, and evaluates the most
significant variables affecting each community wellbeing demographic index.
Education Index
The first regression shown in Table 46 evaluates the education index as the dependent
variable. This regression maintains an r-squared of 0.34, meaning that this model explains
34% of the dependent variable variation in the regression. All independent variables are
statistically significant at the 5% level except for federal & provincial revenue capita and
GBE expense capita. The geographic variables have significant coefficient values, which
suggests that being located more remotely is associated with a lower education index. On
average, geographically remote communities have an education index 16.89 units lower than
communities located close to population centres. Also, geographically medium communities
have on average an education index 4.76 units lower than communities located close to
population centres. The population variable also maintains statistical significance (p < 0.05)
with a negative coefficient. This implies that a 100 person increase in the population is
associated with a decrease of 0.19 in the education index.
Regarding the financial variables, the earned & other revenue ratio has the largest
coefficient suggesting that a 0.1 increase in the ratio is associated with the education index
increasing by 1.72. When evaluating transfer revenue, the Tribal Government and other First
Nation entity capita’s coefficient suggests that an increase of $1,000 in this capita spending is
associated with a 0.40 increase in the education index. Note that the federal & provincial
government capita variable is not statistically significant. The trust fund asset ratio’s
coefficient suggests that a 0.1 increase in the ratio is associated with a 0.74 decrease in the
education index. Likewise, the tangible capital asset (TCA) ratio coefficient suggests that a
0.1 increase in the ratio is associated with a 0.77 decrease in the education index.
Workforce Index
The second regression from Table 46 evaluates the workforce index as the dependent
variable. The regression has an r-squared of 0.20, meaning that the model explains 20% of
the dependent variable variation in the regression. All of the independent variables are
statistically significant at the 5% level except for trust fund asset ratio and the geographically
remote differential variable. When evaluating the financial variables, earned & other revenue
88

ratio has the largest coefficient suggesting that a 0.1 increase in the ratio is associated with
the workforce index increasing by 0.83. The Tribal Government & other First Nation entity
revenue capita’s coefficient suggests than an increase of $1,000 in this capita spending is
associated with a 0.37 increase in the workforce index. The federal & provincial revenue
capita’s coefficient suggests an increase of $1,000 is associated with a 0.15 increase in the
workforce index. The TCA ratio coefficient suggests that a 0.1 increase in the ratio is
associated with a 0.92 decrease in the workforce index.
The population variable has a negative coefficient, implying that a 100 person increase
in the population is associated with a decrease of 0.36 in the workforce index. The
geographically remote differential variable does not maintain a statistically significant
relation, while the geographically medium differential does. This implies that on average
geographically medium communities have a workforce index 3.09 lower than communities
located close to population centres.
Language Index
The third regression as shown in Table 46 assesses the language index as the dependent
variable. The regression has an r-squared of 0.37, which means that the model explains 37%
of the dependent variable variation in the regression. All of the independent variables are
statistically significant (p < 0.05) except for federal & provincial revenue capita, Tribal
Government & other First Nation entity capita, and trust fund asset ratio. The geographic
variables have by far the largest coefficients, indicating that greater geographic remoteness is
associated with a higher language index. On average, geographically remote communities
have a language index 30.62 units higher than communities located close to population
centres. Geographically medium communities have, on average, a language index 9.26
higher than communities located close to population centres. The population variable also
maintains a positive coefficient, indicating that a 100 increase in population is associated
with a 0.78 increase in the language index.
Regarding the financial variables, the earned & other revenue ratio has the largest
coefficient, suggesting that a 0.1 increase in this ratio is associated with the language index
decreasing by 2.29 units. A decreased level of Indigenous language knowledge with the
presence of greater earned & other revenue is somewhat concerning, as Indigenous language

89

is an important part of Indigenous culture. The TCA ratio coefficient suggests that a 0.1
increase in the ratio is associated with a 1.07 increase in the knowledge index.
Housing Index
The fourth regression shown in Table 46 evaluates the housing index as the dependent
variable. The regression has an r-squared of 0.22, meaning that the model explains 22% of
the dependent variable variation in the regression. All of the independent variables are
statistically significant at the 5% level except for federal & provincial revenue capita, Tribal
Government & other First Nation entity capita, and community population. The geographic
variables have the largest coefficients, suggesting that being located more remotely is
associated with a lower housing index. On average, geographically remote communities have
a housing index 15.81 units lower than communities located close to population centres.
Geographically medium communities have, on average, a housing index 6.17 units lower
than communities located close to population centres. The geographic variable coefficients
for the housing index follow a very similar pattern to the education index – both demonstrate
that greater geographic remoteness is associated with lower housing and education indices.
When evaluating the financial indicators, the earned & other revenue ratio has the
largest coefficient, which suggests that a 0.1 increase in the ratio is associated with the
housing index increasing by 1.72. The GBE expense capita coefficient indicates that a $1,000
increase in GBE expense is associated with a 0.04 increase in the housing index. Note that
the following two ratios maintain negative coefficients with the housing index. The trust fund
asset ratio coefficient is -1.25, indicating that a 0.1 increase in this ratio is associated with a
1.25 decrease in the housing index. Likewise, the TCA ratio coefficient is -0.87, indicating
that a 0.1 increase in this ratio is associated with a 0.87 decrease in the housing index.
Income Index
The fifth regression from Table 46 evaluates the income index as the dependent
variable. The regression has an r-squared of 0.25, meaning that the model explains 25% of
the dependent variable variation in the regression. Note that the number of communities
evaluated in this regression is fewer than the other regression models in Table 46. The reason
is that no income data was available for small population communities and some medium
population communities due to data quality issues noted by Statistics Canada. The
independent variables that are statistically significant at the 5% level are federal & provincial
90

revenue capita, TCA ratio, and the geographic variable for communities that are
geographically medium. Geographically medium communities, on average, have an income
index 2.59 units lower than communities that are located close to population centres.
All of the statistically significant financial ratio coefficients maintain negative
correlations with the income index. The federal & provincial revenue capita coefficient
suggests than an increase of $1,000 in this capita spending is associated with a decrease of
0.19 in the income index. The TCA ratio coefficient suggests that a 0.1 increase in this ratio
is associated with a decrease in the income index of 1.69.
Nation Wellness Index
The sixth regression from Table 46 evaluates the Nation wellness index (NWI) as the
dependent variable. The regression has an r-squared of 0.13, meaning that the model explains
13% of the dependent variable variation in the regression. Note that the NWI is made up of
an average of the preceding demographic indices. A key reason why the r-squared is lower
for the NWI is the trend that the language index often runs converse to the other indices.
These marginal amounts effectively cancel each other out, resulting in a lower r-squared for
the NWI regression model. Largely for this reason the community population and geographic
variables are not statistically significant for the NWI regression. The independent variables
that are statistically significant are earned & other revenue ratio, Tribal Government & other
First Nation entity revenue capita, trust fund asset ratio, and TCA ratio.
In regard to the financial indicators, the earned & other revenue ratio has the largest
coefficient suggesting that a 0.1 increase in the ratio is associated with the NWI increasing by
0.77 units. The Tribal Government & other First Nation entity capita coefficient suggests
than an increase of $1,000 in this capita spending is associated with an increase of 0.35 in the
NWI. The following two coefficients demonstrate a negative association. The trust fund asset
ratio coefficient suggests that every 0.1 increase in this ratio is associated with a 0.68
decrease in the NWI. Likewise, the TCA ratio coefficient suggests that every 0.1 increase in
this ratio is associated with a 0.84 decrease in the NWI.

Relationship of the Language Index with the Nation Wellness Index
The regression results of the Nation wellness index demonstrate a low explanatory
power, as evidenced by a low r-squared value of 0.13. To better understand the reasons for
this, two additional multiple linear regressions are performed in Appendix S. For brevity, this
91

section presents the high-level findings of these regressions. For further details and analysis,
refer to Appendix S.
The first regression evaluates the Nation wellness index as the dependent variable, and
is calculated without the language index. The Nation wellness index without the language
index is termed NwoL, and the original Nation wellness index as per Table 46 is termed N.
The r-squared of NwoL is 0.35, compared to N at 0.13. This demonstrates that NwoL has
higher explanatory power over the dependent variable variation. Most of the financial
indicator variables in NwoL have higher beta coefficients compared to N. This supports the
argument that the language index often maintains a converse relationship with the financial
indicators compared to the other sub-indices in the Nation wellness index. The most
significant difference is found when comparing the beta coefficients of the community
population and geographic variables. The coefficient of community population for NwoL is
-0.36*, compared to -0.07 for N. The geographically medium differential for NwoL is -4.72*,
compared to -1.69 for N. Similarly, the geographically remote differential for NwoL is
-12.33*, compared to -1.16 for N. This indicates that the presence of the language index in
the Nation wellness index reduces the explanatory power of the regression model. It would
be beneficial to better understand the factors influencing the level of Indigenous language
knowledge. We observe that a statistically significant relationship exists between the
language index and the other subindices, as per Table 31. To better understand this
relationship, a second regression is conducted with the language index as the dependent
variable and includes additional independent variables.
The second regression considers the language index as presented in Table 46, but
includes several new independent variables. The additional independent variables are the
education index, workforce index, housing index, income index, and the % of population that
are registered Indians (term as used by Indigenous Services Canada). This new language
regression is termed L2, while the original language index is termed L. As additional
independent variables are used in this regression, adjusted r-squared values are reported. The
adjusted r-squared of L2 is higher at 0.46, compared to L at 0.35. This demonstrates that L2
explains a higher amount of the dependent variable variation. Of the additional variables, the
education index has the largest coefficient and suggests that a 1 unit increase in the education

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index is associated with the language index decreasing by 0.46. A 1 unit increase in the
income index is associated with a 0.42 increase in the language index. Note that no
statistically significant relationship exists between the workforce index and the language
index. The coefficient for % of population who are registered Indians is 0.33, which indicates
that a 1% increase in this variable is linked to a 0.33 increase in the language index.
The negative relationship between the education index and language index is troubling.
While this doesn’t necessarily imply a causal connection, this relationship may demonstrate
that additional efforts could be taken to incorporate Indigenous language within formal
educational institutions. Gomashie (2019) provides a successful example of this by the
Kanien’keha First Nation community, where their elementary/secondary school teaches
bilingual classes in English and Kanien’keha. The positive relationship between the income
index and language index is interesting. This may indicate that higher levels of income may
enable resources to be focused towards cultural activities, such as the passing on and
preservation of Indigenous language. This would be an interesting area for future research.
The positive beta coefficients for both geographic variables are lower in L2 compared to L,
indicating that the positive relationship between geographic remoteness and the language
index is lessened once the additional independent variables are considered. Also, a positive
association exists between the % of registered Indians and knowledge of Indigenous
language. This relationship is expected due to the fact that Indigenous people would more
likely speak Indigenous languages. The beta coefficients of L2 compared to L are mixed for
the financial indicator variables, with some increasing and others decreasing.
By including the additional independent variables, we have a more accurate
understanding of the financial, population, and geographic variables’ effects on the language
index. We observe that the geographic variables have less explanatory power when we
consider the additional independent variables of the demographic subindices and % of
population that are registered Indians. This increased accuracy is due to the regression model
holding each of the independent variables constant when considering the impact of any
specific variable. The increased adjusted r-squared value of L2 compared to L demonstrates
that the expanded regression of L2 provides greater explanatory power and a more accurate
understanding regarding the language index.

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Multiple Linear Regression – Concluding Statements
This chapter evaluates six multiple linear regression models, with each model
evaluating a demographic index as the dependent variable. Numerous trends and statistically
significant independent variable coefficients are identified. The relationship between the
language index and the other subindices of the Nation wellness index are also reviewed.
The r-squared values from Table 46 demonstrate the percentage of the dependent
variable variation explained in the regression, which range from 0.13 to 0.37. This leads to
the question of what accounts for the residual variation for the dependent variables. It is
possible that the demographic subindices have an effect on each other to some degree. The
literature review also brings up several other possible factors that could account for the
residual, such as the level of transportation or information technology infrastructure in the
community, proximity to economic development opportunities, development of property
rights on reserve lands, level of cultural attachment, or the degree of local input into
community decisions to name a few. Including these other variables in the regression models
would be ideal, but widespread and reliable data on these factors are often limited. Collecting
such data and making them publicly available would be very valuable to better understand
the factors affecting First Nation wellbeing.
The next and final chapter provides detailed discussion about the results from this and
the preceding chapters, and ties in all of this information in the conclusion. Areas of future
research are evaluated, and the closing statements summarize the key findings of this
manuscript.

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Chapter 6: Conclusion
This manuscript has so far evaluated the results from the descriptive
statistics/comparative analysis, correlational analysis, and multiple linear regression analysis.
Discussion has been provided about the results of each of these topics within their own
chapter. This concluding section brings the key findings of this study together as a whole,
and allows for the research methodologies to complement each other. The main topics in this
section include the strengths and limitations of the research methodologies, discussion of
results, areas for future research, and closing remarks.

Strengths and Limitations of the Research Methodologies
Three research methodologies were employed in this thesis. The first research
methodology was the use of descriptive statistics and comparative analysis. Key figures
evaluated include the demographic indices and financial investing indicators. These figures
were considered for the total population, population subgroupings, geographic remoteness
subgroupings, and subgroups as per Table 3. Statistically significant differences were
evaluated via t-test statistic comparisons between means, specifically comparing the mean of
a subgrouping/subgroup versus the mean of total population excluding the
subgrouping/subgroup being evaluated. The strengths and limitations of the descriptive
statistics and comparative analysis methodology are reviewed in Table 47.
Table 47: Strengths and Limitations of Descriptive Statistics and Comparative Analysis
Methodology
Strengths
Highlighting the demographic and financial
realities of First Nation communities across
Canada at the total population, population
subgrouping, geographic subgrouping, and
subgroup levels.
Isolating the effects due to population level
and geographic remoteness via comparative
analysis.
Determining when significant differences
exist between major subgroupings /
subgroups of First Nations in the
demographic indices or financial indicators.

Limitations
The large volume of comparative analysis
could result in the researcher and reader
getting lost in the data. The challenge is to
translate the comparative analysis findings
into meaningful conclusions about the
relationships and trends identified.
The high number of hypothesis tests
increases the risk of familywise error,
resulting in a higher potential for Type 1
error.
The descriptive statistics are static, and do
not convey information about relationships
between variables (aside from population/
geographic remoteness comparisons).
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The second research methodology was to conduct a Pearson correlation coefficient (r)
analysis amongst the demographic indices, and between the demographic indices and
financial indicators. Hypotheses were developed regarding these correlations, along with
further analysis of statistically significant (at the 5% level) correlations via scatterplot and
line of best fit graphs. The strengths and limitations of the Pearson correlation coefficient (r)
analysis are reviewed in Table 48.
Table 48: Strengths and Limitations of Pearson Correlation Coefficient (r) Analysis
Strengths

Limitations

The ability to evaluate the strength of
correlations between demographic indices
and investing financial indicators, thus
providing deeper insight into the relation
between the underlying community
wellbeing measures and investing policies.
The ability to identify if certain subgroups
have stronger/weaker correlations, which
could help identify if certain investing
policies are better suited for specific
subgroups of communities.
The ability to evaluate correlations from a
large variety of financial investing
indicators.

The large volume of correlations evaluated
could result in the research and reader
getting lost in the analysis. The challenge is
to translate the many r analysis results into
meaningful conclusions about the
correlations.
The high number of hypothesis tests
increases the risk of familywise error,
resulting in a higher potential for Type 1
error.
A component of the r analysis was the
development of hypotheses regarding the
statistical significance of the correlations.
While statistical relationships were often
found at the total population level (due to a
higher number of community observations),
many of the subgroups were statistically
insignificant. This resulted in less
meaningful findings at the subgroup level.

The third research methodology was multiple linear regression. The dependent
variables utilized were the demographic indices of education, workforce, language, housing,
income, and Nation wellness. The independent variables consisted of six investing financial
indicators used in the correlational analysis, the community population level, and
geographically remoteness categorical variables. The strengths and limitations of the multiple
linear regression are reviewed in Table 49.

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Table 49: Strengths and Limitations of Multiple Linear Regression
Strengths

Limitations

The ability to measure the marginal effects
of independent variables in relation to the
demographic indices.

Multicollinearity could significantly impact
the efficacy of the regression. This occurs
when independent variables maintain linear
relationships with each other. As many of
the investing financial indicators have some
linear relationship with each other, only a
select few of the investing financial
indicators could be used in the regression
model.
The potential for the reader to draw causal
conclusions based on the observational data
used in the study. As this study does not
employ an experimental design, it is best to
consider the marginal effects between the
demographic indices and other variables in
a correlational context instead of a causal
context.
The multiple regressions and number of
independent variables increases the risk of
familywise error, resulting in a higher
potential for Type 1 error.

The regression model’s ability to hold the
independent variables constant when
evaluating the marginal effect of each
specific independent variable. This allows
for a clearer understanding of the
relationship between each independent
variable and the demographic index being
evaluated.
The ability to present clear and concise
results that are intuitive for the reader to
understand.

We have now considered the strengths and limitations of each research methodology in
this study. It is important to recognize that a specific methodology’s limitations are often
supplemented by the strengths of another methodology. For example, both the descriptive
statistics and correlational methodologies have the limitation of large volumes of data
analysis. This is supplemented by the regression’s strength of providing clear and concise
results. Also, the regression’s use of a limited number of investing financial indicators can be
supplemented by the descriptive statistic and correlational methodologies’ more
comprehensive analysis. This supplemental use of the three research methodologies will be
employed in the following section as this study’s results are discussed.

Discussion of Results
As we discuss the research results, it is helpful to recall the research objectives of this
thesis, which is to determine the relationship between First Nation government investing
policies and First Nation community wellbeing and to evaluate how geographic remoteness

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and population levels influence this relationship. The investing policies are measured via the
investing financial indicators, and community wellbeing by the demographic indices.
Geographic remoteness is measured via subgroup comparative analysis and regression
categorial variables. Population level is measured via subgroup comparative analysis and a
regression continuous variable.
This discussion section first reviews the results by each of the community wellbeing
demographic indices. Second, this section reviews the key patterns identified relating to
geographic remoteness and population level. Third, this section reviews key patterns
identified for each category of investing financial indicators. The results from the multiple
regression analysis will be emphasised, while the correlational and descriptive
statistics/comparative analysis results will be used to supplement the analysis.
Discussion: Community Wellbeing
Community wellbeing has been measured via the demographic indices. The first
community wellbeing measure is the education index. The correlational analysis
demonstrates that the education index maintains a positive and statistically significant
correlation with businesses more closely controlled by the First Nation government (Table
41), while the more arms-length government business entity (GBE) businesses have a
correlation close to 0.00 (Table 42). This pattern is important to consider when educational
capacity development strategies are being created. Note that this correlational analysis has
the limitation of not considering other variables that may impact the education index levels,
and that causal conclusions cannot be made. The regression analysis provides a more robust
analysis as it considers all of the variables listed in Table 8. The regression analysis indicates
that earned & other revenue ratio has a statistically significant and positive marginal effect
with the education index (Table 46). This provides support that earned & other revenue
activities can play an important role in educational attainment within First Nation
communities.
The regression analysis indicates that community population level has a mildly
negative impact on education levels (Table 46). A possible explanation for this would be the
significantly lower per capita revenue available to First Nation governments of larger
population communities. Mean per capita revenue (from all sources) for large population
communities is often less than half of small population communities (Table 21). This could
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have significant consequences due to the fact that that First Nation governments are often
responsible for providing educational services. The regression analysis indicates that the
degree of geographic remoteness maintains a very high and statistically significant impact on
education levels (Table 46). Geographically medium communities’ education index is on
average lower than geographically close by 4.76, while geographically remote communities
are on average lower than geographically close by 16.89. This pattern of decreasing
education levels in more remote communities is corroborated by the descriptive statistics in
Table 29. The statistically significant drop in education levels for geographically remote
communities is distressing, as several studies demonstrate that strong education levels are
associated with positive social outcomes (Hossain & Lamb, 2012) (Simpson et al., 2007).
Possible reasons for this decline in education levels could be a lack of facilities available in
remote communities, the lack of partnering opportunities with other school districts or
educational institutions, and difficulties in attracting and maintaining education professionals
in remote locations.
When conducting the correlational analysis, it was found that the education index
maintained a positive and statistically significant correlation with all of the other
demographic indices (except the language index) (Table 31). This demonstrates that higher
levels of education have statistically significant correlations with workforce levels,
residential housing conditions, income levels, and overall Nation wellness. This positive
correlation aligns with the existing literature that links educational attainment with other
beneficial social outcomes (Hossain & Lamb, 2012) (Simpson et al., 2007). Even so, the
statistically significant and negative correlation with the language index is concerning. While
other variables may be impacting this correlation, further efforts may be warranted to
encourage the use of Indigenous languages within educational institutions.
The second community wellbeing measure is the workforce index. When evaluating
per capita business and GBE correlations with the workforce index, statistically significant
and positive correlations are observed (Table 41 and Table 42). These results are reinforced
by the regression analysis, which indicates a mild positive and statistically significant
marginal effect of earned & other revenue ratio on workforce levels (Table 46). Also, per
capita transfer payments are associated with a higher workforce index. Note that the variables
of Tribal government & other First Nation entities and federal & provincial government are
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both capita measures of transfer revenue received by the First Nation. Both variables show
the marginal effect per $1,000 of revenue transfer on the demographic indices. It is
interesting to note that the marginal effect per $1,000 transfer is 0.37 for funds from Tribal
governments & other First Nation entities, compared to 0.15 from the federal & provincial
governments (Table 46). This indicates that a stronger marginal benefit to workforce levels is
present when greater transfer revenue is controlled by First Nation entities.
Similar to the education index, community population maintains a mildly negative and
statistically significant marginal effect on the workforce index (Table 46). The lower mean
per capita revenue from business and other sources in higher population communities could
limit the economic activity and job availability within these First Nation communities (Table
21). Studying the relationship between per capita revenue and job creation would be an
interesting area of future research. The regression analysis demonstrates a unique marginal
effect between geographic remoteness and workforce levels (Table 46). Geographically
medium communities demonstrate an average 3.09 lower workforce level than close
communities, while remote communities show no statistically significant marginal effect.
The third community wellbeing measure is the language index. The language index
maintains very different, and often converse, relationships compared to the other indices. The
correlational analysis demonstrates a negative and statistically significant correlation
between the language index and gross business sales and business expenses (Table 41).
However, a nearly 0.00 correlation exists between the language index and all of the
government business entity financial indicators (Table 42). While other variables may be
impacting this correlation, the dynamics of this relationship would be an interesting area for
future research. The regression analysis demonstrates a statistically significant and negative
marginal effect of earned & other revenue ratio on the language index (Table 46). This
relationship is worrying, as it indicates a loss of an important part of Indigenous culture.
While concerning, this relationship does make intuitive sense. Activities involved with
earned income often require increased interactions with members outside of the local
community, which would require the use of non-Indigenous language.
Appendix S (Figure A739) explored the relationship between the language index and
an expanded number of independent variables. The variables with the most notable
relationships are as follows. The regression demonstrates that a 1 unit increase in the
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education index is associated with a 0.46 unit decrease in the language index. Conversely, a 1
unit increase in the income index is associated with a 0.42 unit increase in the language
index. The negative association between the education and language indices is concerning.
While this doesn’t necessarily imply a causal connection, this may indicate that greater
integration of Indigenous language in formal educational institutions could be beneficial. The
positive association between the income index and language index is an interesting
observation, and may demonstrate that increased income allows for greater resources to be
dedicated towards cultural activities such as the renewal and passing on of Indigenous
language.
The regression analysis indicates that higher population levels have a statistically
significant and positive marginal effect on Indigenous language knowledge levels (Table 46).
This result is expected, as a larger number of people could be actively using and passing on
the language to younger generations. The regression analysis also demonstrates that
geographic remoteness has a statistically significant marginal effect on language levels.
Geographically remote communities have on average a language index higher (than
geographically close) by 30.62, while geographically medium are higher by 9.26 (Table 46).
This is a very significant difference, which also makes intuitive sense. More remote
communities would have fewer external interactions, and would have less need for other
languages such as English or French.
The fourth community wellbeing measure is the housing index. The correlational
analysis demonstrates that both business activities and government business entity activities
maintain positive and statistically significant correlations with the housing index (both on a
ratio and per capita basis) (Table 41 and Table 42). Note that the GBE activity indicators of
gross revenue and gross expenses have stronger correlations than GBE net income. While
other variables may be influencing this relationship, this pattern could be insightful when
developing business and GBE policies. The regression analysis indicates that the earned &
other revenue ratio maintains a statistically significant and positive marginal effect on the
housing index (Table 46). The regression result is important, as it demonstrates that a higher
earned & other revenue ratio is associated with higher residential housing conditions even
when all of the variables from Table 8 are held constant.

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Population levels do not impact the housing index in a statistically significant manner
(Table 46). Geographic remoteness, however, has a very important and statistically
significant marginal effect on the housing index. Geographically medium communities have
a housing index lower by 6.17 (compared to close), while geographically remote have an
index lower by 15.81 (Table 46). This demonstrates a severe decline in the state of residential
housing for communities that are more geographically remote. Table 29 indicates that nearly
half (48%) of on-reserve residential houses in geographically remote communities are in
need of major repairs. This figure is astounding for a nation as developed as Canada. There
are numerous possible explanations for this poor state of residential housing, which are
explored below.
Note that cumulative mean TCA capita for remote communities is $58K, which is
higher than close communities at $37K (Table 26). Note also that capital gross cash outflows
per capita for remote communities is $4.6K, which is higher than close communities at $3.4K
(Table 26). These accounting figures, however, may be misleading when we consider what
those dollars can actually buy when comparing geographically remote and close
communities. Remote communities have the disadvantage of higher costs for goods and
services, especially for large and complex assets. In remote locations, it is unlikely that all of
the required construction contractors and needed tradespeople will be available locally. This
could result in significant travel expenses for the needed contractors/workers to complete a
housing project. This applies not just to new residential construction, but also to ongoing
maintenance and repairs.
Let us consider an example. A house may be in need of an electric upgrade. In most
non-Indigenous communities, a bid could be put out to several local electrical contractors to
find the contractor with the best value. In a remote Indigenous community, it is possible that
no local electrical contractors are present. Instead, an electrical contractor may be required to
fly in or drive several hours to reach the community. This could drastically increase the price
of an electrical upgrade, and decrease the pool of contractors that would be willing to make
the long journey to the remote community. Regardless, the total cost of conducting the
electrical upgrade would be recorded to the capital or housing account. Even though the
dollar amount would be larger, the “on-the-ground” benefit of the electrical upgrade would

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be the same. This example demonstrates the unique problems that remote communities face
when constructing and maintaining capital assets, including residential housing assets.
This problem is not isolated to electrical upgrades, but applies to items such as
requirements of skilled labour, the use of specialized building equipment, or the delivery of
building supplies. The costs of building and maintaining a large pool of Nation owned
residential housing can soon become prohibitively expensive and very difficult to attract the
required human capital to complete the work. All the while, the accounting figures indicate
that sufficient spending has already been provided to fulfill the housing needs. A possible
step in addressing this problem would be to develop a coordinated remote community
procurement system to meet the needs of remote community capital assets. Coordinating
numerous remote communities’ procurement needs could generate sufficient economies of
scale to drive down the price of capital asset purchases and maintenance. This would be an
interesting area of future research that could result in increased residential housing conditions
for remote First Nation communities, and reduce the expenditure requirements for these
critical capital assets.
The fifth community wellbeing measure is the income index. Curiously, there is no
statistically significant marginal effect of the earned & other revenue ratio on the income
index (Table 46). While a statistically significant correlation appears in the correlational
analysis (Table 45), this relationship does not appear in the regression once the other
independent variables are held constant. This appears to relate to the geographic remoteness
variables being held constant, which results in the marginal effect of earned & other revenue
ratio on the income index to be statistically insignificant. This lack of a statistically
significant marginal effect is even more curious due to the fact that a statistically significant
relationship exists between earned & other revenue and the workforce index (Table 46). This
would be an interesting area for future research.
Community population level does not maintain a statistically significant relationship
with income levels (Table 46). The degree of geographic remoteness maintains a minor
impact on income levels (Table 46). When evaluating income levels, it is important to recall
that the income amount is denoted in dollars. Note that the purchasing power of these dollars
between geographically close and remote communities may not be the same, as costs are
often higher in remote locations.
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The sixth community wellbeing measure is the Nation wellness index (NWI). Note that
this index is a combined average of the previous five demographic indices. Also note that the
language index runs converse to the other indices, thus reducing the level of marginal effect
or correlation present between the NWI and a given variable. Table 41 and Table 42
demonstrate that positive and statistically significant correlations exist for both business and
GBE financial indicators and the NWI. This correlation is reinforced by the more robust
regression analysis, which demonstrates that the earned & other revenue ratio maintains a
moderately positive and statistically significant marginal effect on the NWI (Table 46). This
is due to the fact that a positive and statistically significant marginal effect exists between
earned & other revenue ratio and the education index, workforce index, and housing index.
Note that the language index maintains a negative and statistically significant marginal
effect.
Of particular interest is the observation that Tribal government & other First Nation
entity transfer revenue capita maintains a positive and statistically significant marginal effect
with the NWI. For every $1,000 increase in this capita measure, the NWI increases by 0.35
(Table 46). Note that the federal & provincial transfer revenue capita measure has no
statistically significant effect (Table 46). This is important as it demonstrates that transfer
revenues with greater First Nations control may result in stronger community wellbeing
outcomes.
Note that there is no statistically significant marginal effect of community population
or geographic remoteness with the NWI (Table 46). It is important to remember, however,
that this is due to a cancelling out effect amoung the demographic indices that make up the
NWI. The language index maintains a positive and statistically significant marginal effect
with the community population and geographic remoteness variables, while most of the other
indices maintain a negative and statistically significant marginal effect. Even though this
results in a statistically insignificant marginal effect at the NWI level, statistically significant
relationships do exist for the sub-indices previously discussed.
Appendix S (Figure A736) presents the regression of a recalculated NWI that excludes
the language index. This regression was conducted in part due to the low r-squared value in
the original NWI regression, and to determine if the explanatory value of the regression was
stronger without the language index included. After removing the language index from the
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NWI, the r-squared value increased to 0.35 (compared to 0.13 with the language index). The
explanatory power of most of the financial variables slightly increased, while the explanatory
power of the population and geographic variables increased significantly. This result supports
the argument that the language index has a cancelling out effect with the other subindices.
This section has reviewed this study’s results relating to community wellbeing and the
demographic indices. The next section considers the research results in relation to
community population levels and degrees of geographic remoteness.
Discussion: Population Level and Geographic Remoteness
Throughout this study, the results have indicated that community population level and
geographic remoteness of First Nations has a statistically significant impact on community
wellbeing. The key findings relating to population level and geographic remoteness will be
reviewed.
Table 46 demonstrates that higher community population levels have a mild negative
and statistically significant marginal effect on the education and workforce indices.
Population level, however, has a strong positive and statistically significant marginal effect
on the language index. The other demographic indices maintain no statistically significant
relation with population levels.
An important trend exists when evaluating revenue per capita (from all sources) by
population subgrouping. The following mean amounts are taken from Table 21. Revenue per
capita by the population subgroupings (small, medium, and large) for earned & other revenue
capita is $20.7K, $11.5K, and $8.4K. Revenue per capita by the population subgroupings for
federal & provincial transfer revenue capita is $22.7K, $14.8K, $12.6K. This demonstrates
that the revenue per capita available to large population First Nation governments is
approximately half compared to small population communities. This may put strains on large
population First Nation governments in delivering the required services for their community
members. Another significant contrast exists when evaluating the mean cumulative tangible
capital asset (TCA) capita by the same population subgroupings, which are $65.4K, $42.1K
and $26.7K (Table 19). While some economies of scale could be gained by sharing common
TCAs amoung a larger population, this sharp of a contrast between TCA per capita is
surprising. This may indicate that large population communities are not receiving sufficient
funds to build and maintain community infrastructure. Considering the sharp contrast in per
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capita revenue and TCAs, it would be beneficial to conduct a review and determine if this
lower level of funding has resulted in a lack of government services or infrastructure in large
population First Nation communities. Note that one possible explanation is the fact that large
population communities are on average more geographically close. Due to this, third-party
funders may provide less funds due to differences in geographic remoteness costs.
Another trend noted by population subgrouping is the degree of per capita business and
GBE activities. The following mean figures are taken from Table 16 and Table 17. The
financial indicator balances by population subgroupings of small, medium, and large
communities are presented as follows: gross business sales capita ($6.4K, $4.0K, $3.1K),
business and economic development expense capita ($7.9K, $4.9K, $2.8K), GBE revenue
capita ($21.7K, $7.3K, $4.5K), GBE expense capita ($18.4K, $6.8K, $4.7K). This
demonstrates that small population communities benefit from greater business activities per
person. While there are significant differences noted between the subgroup means, the
differences between the median values are significantly less. The regression analysis has
demonstrated that earned & other revenue (business activities being a large component) has
positive and statistically significant marginal effects on several community wellbeing
measures. It follows that increased business and GBE activities in large population
communities has the potential to increase the wellbeing of the First Nation communities. A
policy directive, then, could be to promote economic development grants and entrepreneurial
loans for prospective business activities in large population First Nation communities across
Canada.
The mean values in Table 23 and Table 24 demonstrate that there is a greater level of
business activity per capita for geographically close communities compared to more remote.
However, the reverse trend is true for GBE activities. While these trends appear when
evaluating the means, it is important to note that significant variability is present as indicated
by a higher standard deviation. Also, the median values are significantly lower than the
means for most financial indicators in Table 23 and Table 24. The amount of federal &
provincial transfer revenue per capita is higher for remote communities. This is expected, as
Indigenous Services Canada provides a higher level of funding due to the higher costs for
remote communities.

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The regression analysis results from Table 46 demonstrate that the degree of
geographic remoteness maintains a statistically significant marginal effect on several of the
community wellbeing measures. The differential effect for geographically medium and
remote communities (compared to geographically close) for the education index are -4.76
and -16.89. The corresponding differential effects for the housing index are -6.17 and -15.81.
Finally, the corresponding differential effects for the language index are 9.26 and 30.62.
These regression results indicate that geographic remoteness maintains a statistically
significant effect on the education, housing, and language indices even when the other
variables from Table 8 are held constant.
A very prominent finding when evaluating population and geographic remoteness is the
impact on the community wellbeing measures of education, housing, and language.
Appendix D evaluates these indices by subgroup (based on a matrix between population and
geographic zone). Table 50 reviews key subgroup figures taken from Appendix D, Figures
A1, A5, and A7.
Table 50: Education, Housing, and Language Indices by Affected Subgroup
Community
MR (medium population
LR (large population & Total
Wellbeing Measure
& geographically remote) geographically remote) Population
Education Index
28.6
25.8
45.1
Housing Index
51.2
43.0
63.1
Language Index
52.4
64.5
28.7
Table 50 demonstrates that education levels and residential housing conditions for
subgroups MR and LR are far lower compared to other First Nation communities.
Considering that these communities have large and medium populations, there are a greater
number of First Nations people that are impacted by these very low education levels and
residential housing conditions. Contrasting to this, however, the level of Indigenous language
knowledge is much higher for subgroups MR and LR. This latter observation is positive, as
over half of the community members have knowledge of the Indigenous language.
Knowledge of Indigenous language is a very critical component of Indigenous culture.
The regression analysis (Table 46) and comparative analysis (Table 16 to Table 29)
demonstrate very distinctive demographic indices and financial indicator trends depending on
a local community’s population level and degree of geographic remoteness. Varying degrees
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of community population and geographic remoteness would result in different public service
requirements for the communities involved. It makes intuitive sense that distinct policies and
financial requirements would be present for these differing population levels and geographic
remoteness realities. It would be beneficial to better understand the distinct requirements for
the geographically remote communities with large populations (LR) and medium populations
(MR). This would be an interesting area for future research.
This section has evaluated the impact that population level and geographic remoteness
has on First Nation community wellbeing. Several statistically significant relations have been
identified, along with discussion as to the practical implications. The next section considers
the impact that investing financial indicators have on First Nation community wellbeing.
Discussion: Financial Investing Indicators
This section reviews the key investing policies of First Nation governments. The first
investing policies evaluated relate to business activities, government business entities
(GBEs), and earned & other revenue. The regression analysis demonstrates that the earned &
other revenue ratio maintains positive and statistically significant marginal effect on the
education index, workforce index, housing index, and Nation wellness index. This ratio also
maintains a negative and statistically significant marginal effect on the language index (Table
46). The correlational analysis provides greater insight into the relationships associated with
the specific types of earned and other income.
The correlational results (Table 41) demonstrate that gross business sales and
business/economic development expenses maintain statistically significant correlations with
all of the demographic indices mentioned in the above paragraph. The GBE financial
indicators, however, show very different patterns (Table 42). All of the GBE indicators
maintain a near 0.00 correlation with the education index and language index. Also, only the
GBE capita measures maintain statistically significant correlations with the workforce index.
A positive and statistically significant correlation exists between most GBE indicators and
the Nation wellness index. Recall that GBEs are Nation owned businesses that maintain a
more arms-length relationship with the Nation government. Of particular note is that the
education index maintains a positive and statistically significant correlation with business
activities, versus GBE activities (businesses that operate independently from the First Nation
government) with a nearly 0.00 correlation. Note that this correlational analysis does not
108

consider other possible variables that could be impacting these relationships. However, the
very differing correlational patterns highlight that distinct relationships exist between
businesses with greater or lesser First Nation government control.
The second investing policy evaluated is trust fund activity. There has been limited
mention of trust activity in the discussion section so far – largely due to the fact that almost
no statistically significant correlations for the total population were found throughout the
study (Table 43). The regression analysis found a negative and statistically significant
marginal effect of the trust fund asset ratio on the education index, housing index, and Nation
wellness index (Table 46). This negative effect is only minor, but may indicate that allocating
resources to trust funds may not provide a major benefit for First Nation communities.
It is important to recall from the literature review chapter that trust funds are often set
up to provide a longitudinal benefit for communities (Rodon et al., 2018). This may be the
result of large one-time land claim settlements or natural resource royalty payments. The
very purpose of a trust fund is to delay the usage of trust fund resources so that the
community can benefit over time. As such, the cross-sectional nature of this study may not
be the best method to evaluate the efficacy of trust funds for First Nation communities. This
would be an interesting area for future research.
A large spread of trust asset levels was noted between First Nations as per Table 12.
Due to this, a stratified population analysis was conducted on First Nations that maintain a
low, moderate, and high level of trust assets per capita (refer to Appendix U for further
details). Weak correlations were found for low trust asset First Nations between trust
activities and the demographic subindices. However, much stronger correlations were found
for First Nations that maintain moderate and high levels of trust assets. Two notable trends
for these stratified groups include statistically significant and negative correlations between
the trust fund assets ratio and the workforce/housing indices.
The third investing policy evaluated is tangible capital asset activity. Most of the TCA
activity indicators do not maintain statistically significant correlations with the demographic
indices (Table 44). The regression analysis demonstrates that the tangible capital asset ratio
maintains a negative and statistically significant marginal effect on all of the demographic
indices except for the language index (Table 46). This means that First Nations with a higher
percentage of TCAs as a percentage of total assets have slightly lower levels of community
109

wellbeing (except for knowledge of Indigenous language). This result is quite unexpected.
This result may be more a function of what other assets the First Nation government is
holding, instead of the tangible capital assets themselves. It is important to recall that TCAs
consist of a large variety of different assets, such as community buildings, residential
housing, equipment, vehicles, water/sewer infrastructure, or assets of Nation owned
businesses (excluding GBEs) to name a few. An interesting area for future research would be
to evaluate the correlations of the specific asset categories with the community wellbeing
measures.

Areas for Future Research
Throughout the course of this study, several areas of future research have been revealed
to better understand the relationship between First Nation community wellbeing and First
Nation government investing policy. This section reviews several meaningful areas for future
research.
First, a positive and statistically significant correlation was found between per capita
business/government business entity activities and the workforce index (Table 41 and Table
42). An interesting area of future research would be to study the long-term impact of this
type of per capita revenue available to First Nation governments and job creation figures.
Questions to consider include whether or not job creation is sustained over the long-term, and
whether specific industries are more disposed to new job creation.
Second, the language index demonstrates very distinct relationships with sources of
earned revenue. A negative and statistically significant marginal effect was found between
earned & other revenue ratio and the language index (Table 46). When evaluating the
correlational analysis, corresponding negative and statistically significant correlations are
found for the business activity indicators (Table 41). Note, however, that a nearly 0.00
correlation is present between the language index and the GBE indicators (Table 42). Even
though the correlational analysis does not factor in other possible variables, this distinct
correlation would be an interesting area of future research. This research could study how
external business activities impact the knowledge of and day-to-day use of traditional
Indigenous languages within communities. Maintaining Indigenous language is an important
aspect of Indigenous culture, so deeper insight in this area could assist in preserving
Indigenous languages.
110

Third, remote communities often struggle with higher costs associated with purchasing
and maintaining large and complex capital assets. An interesting area for future research
would be to develop a workable business model that combines the procurement needs of
numerous remote First Nation governments. The goal would be to combine the purchasing
power of multiple First Nation communities’ capital procurements. This concentrated
purchasing power could boost economies of scale and bargaining power to reduce capital
procurement costs.
Fourth, the earned & other revenue ratio maintains a statistically significant marginal
effect on all of the demographic indices, except the income index (Table 46). This is
surprising, especially due to the fact that the workforce index maintains a statistically
significant marginal effect. An interesting area of future research would be to evaluate the
relationship between the various types of personal income (such as earned income or transfer
payments) and the various types of First Nation government earned & other income. Perhaps
statistically significant marginal effects exist for specific types of income.
Fifth, very distinctive community wellbeing measures were found when evaluating
geographically remote communities with large and medium populations. The demographic
indices showing these distinctive differences are the education, housing, and language
indices (refer to Table 50). An interesting area for future research would be to conduct an
investigative study of a large sample of these communities to better understand the unique
needs of these communities and potential causes for the significantly lower education levels
and lower residential housing conditions compared to other First Nation communities. These
same communities also maintain much higher levels of Indigenous language knowledge. As
such, this investigative study could also determine the causes of why Indigenous language
knowledge is so much higher in these communities compared to other First Nations.
Sixth, this study found a lack of statistically significant correlations between most of
the trust fund activity indicators and the demographic indices (Table 43) at the total
population level. This may be due to the cross-section nature of this study (one year of data),
and the fact that trust funds are designed to benefit First Nation communities over several
years or decades. An interesting area of future research would be to conduct a longitudinal
study analyzing the effects of trust funds on First Nation communities over several years, if
not several decades.
111

Seventh, the correlational analysis from Appendix U provided evidence that distinct
patterns emerge between stratified samples when evaluating trust fund activity indicators.
The stratified groups are based on the level of trust fund assets per capita (levels of low,
moderate, or high). When First Nations maintain a moderate and high level of trust fund
assets per capita, a statistically significant negative correlation exists with the workforce and
housing indices. Better understanding this relationship could provide deeper insight into the
effects of trust fund resources on local communities. It is also possible that other contributing
factors are impacting these observed correlations, such as geographic remoteness of the First
Nation or the underlying reason that First Nations use trust funds. As trust funds are often
designed to provide benefits to First Nations over longer time frames, analyzing these
correlations over multiple decades could provide evidence of the long-term impact of trust
funds on First Nation communities (similar to the previous area of future research).
Eighth, this study found that the tangible capital asset ratio maintains a negative and
statistically significant marginal effect on most of the demographic indices except the
language index (Table 46). Most of the other TCA activity indicators do not maintain
statistically significant correlations with the demographic indices (Table 44). More distinct
and meaningful relations may be found by analyzing the correlations between the major TCA
categories and the demographic indices. The First Nation government financial statements
disclose the major TCA values by category, such as buildings, equipment, automotive or
water/sewer infrastructure to name a few. An interesting area of future research would be to
prepare a comparable database of these TCA values by category, and conduct a correlational
analysis of these TCA categories with the demographic indices.
Ninth, the regression from Appendix S (Figure A739) demonstrated that a higher
income index was positively associated with higher levels of Indigenous language
knowledge. This may indicate that the presence of higher income allows for greater resources
to be allocated to cultural activities such as Indigenous language renewal. An interesting area
of future research would be to evaluate the relationship between specific types of income
(earned income, passive income, transfer income to name a few) and the level of Indigenous
language knowledge.
Tenth, several First Nations present negative values for investment assets in their
consolidated financial statements. Upon further review, most of these negative values
112

represent negative investment values of First Nation owned businesses. These businesses are
government business entities or government business partnerships, which are recorded using
the modified equity method of accounting. While it is theoretically possible to have a
negative value investment using modified equity, its occurrence is very rare. Reporting a
negative investment asset, or an investment liability, also brings into question whether such
reporting practices provide meaningful information for users of the financial statements. An
interesting area of future research would be to evaluate the Public Sector Accounting
Standards (accounting standard used for most governments in Canada, including First Nation
governments) and to determine if further clarification would be beneficial regarding negative
value investments using the modified equity accounting method.
Several areas for future research have been reviewed, along with recommendations for
how this research could be conducted. The following section brings this study to its
conclusion, and reviews the key findings discussed throughout this manuscript.

Concluding Statements
The objectives of this thesis were to provide greater insight into the relationship
between First Nation community wellbeing and First Nation government investing policies,
and to better understand the impact of population level and geographic remoteness on this
relationship. Through a comprehensive analysis of demographic and financial data, this study
has revealed new insights in these areas and also raised new topics for future research. The
key areas of insight covered in this study include the analysis of community wellbeing at the
subindex level, the relationship between earned & other income and community wellbeing,
the relationship between First Nation controlled transfer revenue per capita and community
wellbeing, and the relationship between geographic remoteness and the demographic indices
of education, housing, and language.
The community wellbeing subindices (education, workforce, language, housing, and
income) have distinct relationships with the variables of investing financial indicators,
population level, and geographic remoteness. The distinct relationships uncovered in this
study will be more applicable to policy makers that focus in specific areas. For example,
education professionals could more readily apply the insights of this study by evaluating the
relationships of the education index instead of the Nation wellness index as a whole. The

113

same applies for professionals/policy makers in the areas of economic development,
community housing, or Indigenous language renewal.
This study has found that earned & other income has a largely positive and statistically
significant correlation with most measures of community wellbeing, with the exception of
Indigenous language knowledge. The benefit of earned income to community wellbeing has
been discussed in prior scholarly work (Vining & Richards, 2016) (Dylan et al., 2013)
(Simpson et al., 2007), albeit these studies focused on a smaller subset of First Nation
communities. This study confirms the benefit of earned & other revenue ratio on community
wellbeing, as a positive marginal effect is present between this ratio and the Nation wellness
index.
The regression analysis found a stronger and statistically significant marginal increase
to the education and workforce indices when transfer revenue is received from a First Nation
Tribal governments or First Nation entities, instead of transfers directly from the
provincial/federal government. Note that the income index maintains a statistically
significant marginal decrease from federal/provincial transfer revenue, while First Nation
controlled transfers do not. This demonstrates that transfer revenues with greater First
Nations control may have stronger community wellbeing outcomes than direct transfers from
the federal or provincial governments.
The degree of geographic remoteness of First Nation communities has a statistically
significant impact on education levels, the state of residential housing, and knowledge of
Indigenous language. Education levels and residential housing conditions fall drastically for
geographically remote communities with large and medium populations. Conversely, the
knowledge of Indigenous language in these communities is much higher. Now that this
pattern has been identified, it would be beneficial to investigate and determine the unique
needs of these communities. This could facilitate the development of new and more
impactful policy to address the educational and housing needs of these communities. At the
same time, the investigation could determine how and why these communities maintain a
stronger knowledge of Indigenous language. These insights could be used to facilitate
Indigenous language renewal in other First Nation communities.
This study also sought to better understand the relationship between trust fund
activities and tangible capital asset activities on community wellbeing. After reviewing the
114

results, it has been found that few statistically significant relationships exist for either of
these investing activities at the total population level. The regression analysis demonstrates
that both the trust fund asset ratio and tangible capital asset ratio maintain minor negative and
statistically significant marginal effects on most of the community wellbeing measures.
While more significant findings would have been desired in these areas, several areas of
future research have been discussed in the previous section to gain more insight into these
areas of First Nation government investing policy. Note that several statistically significant
trends were identified for trust activities once the population was stratified based on the level
of trust assets held by First Nations, as discussed in Appendix U.
As this study comes to its conclusion, several important observations can be made.
First, these results and discussions provide new insight for First Nation community leaders
and policy makers to make more informed decisions for their local communities. By
analyzing the findings in this study, local leaders may develop new ideas for what policies
may be effective for their own Nations. Let us consider an example. By observing the
positive marginal effect of earned & other revenue on the Nation wellness index, local
leaders may seek to start Nation owned business ventures to benefit their First Nation
communities. Note, however, that this study does not predetermine that this would be the
best choice for every Nation. Local Indigenous leaders must always determine what is best
for their community, while taking into consideration the community’s Indigenous culture,
importance of the land, and local resources. This study simply provides additional insights
for local leaders to make the most informed decision possible.
The second observation is that this study maintained a focus on First Nation
governments and communities. Making comparisons between First Nations and non-First
Nations was specifically avoided. The reason is that many First Nation communities are
making great progress in advancing their communities’ wellbeing, and are doing so in a
distinctly Indigenous manner. First Nation goals and wellbeing cannot be defined as “better
than” or “worse than” non-First Nation people. First Nations seek to forge a vision and future
that are shaped by Indigenous culture and an Indigenous worldview. By keeping comparisons
between First Nations, the goal is to reinforce this Indigenous worldview.
Finally, this study evaluated demographic and financial data from the year 2016. The
relationships analyzed from 2016 provide a framework for understanding the existing
115

realities of First Nation communities, but does not decide the realities for First Nations going
forward. The new insights from this study will enable First Nation leaders to better
understand the relationships between investing policies and community wellbeing. This new
insight can inform visionary Indigenous leaders as they shape a path for First Nation people
into the future.

116

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Appendix A: Summary of Financial Indicators
Financial Indicators To Be Used in This Study (Note 1)
Financial item used in
Financial item used in
Used in Used in r Used in
financial indicator
financial indicator
descripitve analysis regression
(numerator)
(denominator)
statistics
analysis
Business Activity Ratios
Total investment assets
(includes GBEs, exclude
trust funds)
Gross business sales
(excluding GBE income)
Business and Ec Dev
expenses

Total financial assets

Y

Y

N

Total revenue

Y

Y

N

Total expenses

Y

Y

N

GBE Ratios (Note 2)
GBE assets
GBE liabilities
GBE equity
GBE revenue
GBE expenses
GBE net income

/ Total financial assets
/ Total liabilities
/ Accumulated surplus
/ Total revenue
/ Total expenses
/ Surplus in year

Y
Y
Y
Y
Y
Y

Y
N
Y
Y
Y
Y

N
N
N
N
Y (capita)
N

Trust Ratios
Trust funds assets
Trust revenue

/ Total financial assets
/ Total revenue

Y
Y

Y
Y

Y (ratio)
N

/ Total assets
Total gross cash inflows
/

Y
Y

Y
N

Y (ratio)
N

Total gross cash outflows Y

N

N

/ Total net cash flows

Y

N

Capital Ratios
Tangible capital assets
Gross cash inflows from
capital
Gross cash outflows from
capital
Net cash flows from capital

/
/
/

/

Y

A1

Appendix A: Summary of Financial Indicators (continued)
Other Ratios
Long-term debt
/ Total liability
Net cash flow from operating Total net cash flows
/
Gross cash inflows from
investing
Gross cash outflows from
investing
Net cash flows from
investing
Earned revenue (Note 3)
Earned revenue + other
revenue (Note 4)
Federal and provincial
revenue
Tribal gov't revenue + Other
FN revenue (Note 5)

Y
Y

N
N

N
N

Y

N

N

Total gross cash outflows Y

N

N

Total net cash flows

Y

N

N

/ Total revenue
Total revenue
/

Y
Y

Y
Y

N
Y (ratio)

Total revenue

Y

Y

Y (capita)

Total revenue

Y

Y

Y (capita)

/
/
/

/
/

Total gross cash inflows

Note 1: This financial information is taken from the audited 2016 First Nation
Financial Statements, which are publicly available via the Indigenous Services
Canada (n.d.a) website. Below is a link where each First Nation can be looked up, and its
audited financial statements can be downloaded as a PDF document. This is the financial
data source for this study. See the link below.
https://fnp-ppn.aadnc-aandc.gc.ca/FNP/Main/Search/SearchFN.aspx?lang=eng
Note 2: GBE refers to government business entities as defined by the Public Sector
Accounting Standards of Canada. As per the Chartered Professional Accountants of
British Columbia, a GBE must have all of the following characteristics:
- "It is a separate entity with the power to contract in its own name, and can sue and be sued.
- It has been delegated the financial and operational authority to carry on a business.
- It sells goods and services to individuals and organizations outside of the government
reporting entity as its principal activity.
- It can, in the normal course of its operations, maintain its operations and meet its liabilities
from revenues received from sources outside of the government reporting entity."
(Chartered Professional Accountants of British Columbia, 2016, para. 1)

A2

Appendix A: Summary of Financial Indicators (continued)
The previously listed characteristics must be present for a GBE to be classified as such on
the financial statements. Businesses not meeting the above characteristics will be recorded
via another method, such as consolidated, equity-method, or at cost. Note that the financial
indicator numerator listed on the previous page as "Gross business sales" is most likely
business revenue from First Nation owned businesses that don't meet the above
characteristics and are reported on a consolidated basis with the First Nation government
financial statements.
Detailed GBE financial information is presented in the First Nation financial statement
note disclosures. The information is used throghout this study. Note also that this
information is audited.
Note 3: Earned revenue includes revenue such as business income, tax income, roytalities,
user fees, investment income, etc.
Note 4: Earned revenue + other revenue includes all items listed above in earned income,
as well as all non-categorized income, and income labelled as Other Revenue.
Note 5: Tribal gov't revenue + Other FN revenue includes all transfer revenue received
from Tribal governments, Tribal associations, and non-government First Nation entities
(e.g. NPOs).
Note 6: each of the previously listed financial indicator numerators will also evaluated
against the specific First Nation community's population level (as per 2016 Census per
Statistics Canada) to establish a per capita measure. These additional financial indicators
can be expressed as follows:
Additional Financial Indicators To Be Used in This Study
Each financial indicator
Total population of relating First
numerator previously listed / Nation community (as per 2016
Census per Statistics Canada)

A3

Appendix B: Summary of Demographic Indices
Note 1) The data for calculating the following indices has been taken from the 2016 Census
prepared by Statistics Canada. Statistics Canada prepares and provides demographic data
to Indigenous Services Canada for each First Nation community. The data for each
community is made up of Census subdivisions of all reserve land and crown land designated
to each First Nation community.
Note 2) An index is calculated for each community based on the following demographic
categories: education, housing, income, language, and workforce. These indices are then
combined into a general Nation wellness index. The method for calculating each index is
reviewed below. Also below is a link to the Indigenous Services Canada (n.d.a) website,
where each First Nation can be looked up and the detailed demographic data can be
reviewed. See the link below.
https://fnp-ppn.aadnc-aandc.gc.ca/FNP/Main/Search/SearchFN.aspx?lang=eng
Education Index
Step
1: Input education data calculation

2: Divide balance by population 15
years and over

3: Adjust index to a scale of 0-100

Calculation
[# of people how have a high school diploma (or
equivalent) only] * 1
+
[(# of people with trade or apprenticeship or other nonuniversity certification) + (# of people university
certificate below bachelor level) + (# of people with a
university degree bachelor or higher)] * 1.25
=
Sum of amounts
Sum of amounts
/
Population 15 years and over * 100
=
Unadjusted education index
Unadjusted education index
*
(adjustment factor)
=
Education Index

A4

Appendix B: Summary of Demographic Indices (continued)
Housing Index
Step
1: Input housing data calculation

2: Adjust index to a scale of 0-100

Calculation
1 - (# of dwellings requiring major repair / Total
number of dwellings)
* 100
=
Unadjusted housing index
Unadjusted housing index
*
(adjustment factor)
=
Housing Index

Income Index
Step
Calculation
1: Determine the maximum
Use MAX() function in Excel to calculate this
"Average total income (all persons
with income $)" of all First Nation
communities
2: Divide each community "Average Community "average total income (all persons with
total income (all persons with
income $)"
income $)" by the maximum
/
determined in step 1
Maximum "average total income (all person with
income $)" * 100
=
Income Index

A5

Appendix B: Summary of Demographic Indices (continued)
Workforce Index
Step
1: Input workforce data calculation

2: Adjust index to a scale of 0-100

Calculation
Participation rate
+
Employment rate
/2
=
Unadjusted workforce index
Unadjusted workforce index
*
(adjustment factor)
=
Workforce Index

Language Index
Step
1: Evaluate % of population with
knowledge of Indigenous language
(direct from Census)

Nation Wellness Index
Step
1: Average the preceding 5 indices

2: Adjust index to a scale of 0-100

Calculation
% of population with knowledge of Indigenous
language
=
Language Index

Calculation
(Education Index + housing Index + Income Index +
Workforce Index + Language Index)/5
=
Unadjusted Nation wellness index
Unadjusted Nation wellness index
*
(adjustment factor)
=
Nation Wellness Index

A6

Appendix C: Subgroups of First Nation Communities
General Discussion
The factors of population level and geographic remoteness are hypothesized to impact the
effectiveness of the investing policies utilized by First Nation governments. A key
part of this study will evaluate how population level and geographic remoteness impacts the
effectiveness of investing policy. To accomplish this, sub-categories of First Nation
communities will be evaluated to compare the strength of the correlations present between
the financial indicators and demographic indices.
Geographic Zones
Indigenous Services Canada prescribes a "Geographic Zone" for each First Nation
community from a scale of 1-4. Due to the smaller number of First Nation communities in
zones 3 and 4, First Nations in zones 3 and 4 will be evaluated as one subgroup in this
study. Each geographic zone is defined by Indigenous Services Canada below.
A reference to these definitions can be found on the Indigenous Services Canada
(n.d.b, para. 6-9) website. The geogrpahic zones are defined as follows:
"Zone 1: First Nation is located within 50 km of the nearest service centre to which it has
year-round road access.
Zone 2: First Nation is located between 50 and 350 km from the nearest service centre to
which it has year-round road access.
Zone 3: First Nation is located over 350 km from the nearest service centre to which it has
year-round road access.
Zone 4: First Nation has no year-round road access to a service centre, as a result,
experiences a higher cost of transportation."
Population Level
The population level is based on the number of people living within the reserve land and
First Nation associated Crown Land. The population numbers are based on the 2016
Census as provided by Statistics Canada. The population categories are as follows:
Population less than or equal to 200
Population greater than 200 but less than 1,000
Population greater than or equal to 1,000
Matrix of Subgroups
For ease of reference, a matrix has been developed to summarize the subgroup. Each
subgroup is provided a 2 letter mnemonic code as follows:
Geography Geography Zone Geography Zones
Zone 1 (close)
2 (medium)
3&4 (remote)
Population (small) <= 200
SC
SM
SR
Population (medium) 201-999
MC
MM
MR
Population (large) >=1000
LC
LM
LR
A7

A8

Min
29.1
12.9
12.8
24.3
8.9
3.7
23.7
20.1
13.5
3.7

Min
33.2
32.8
30.4
13.5
23.2
37.4
28.7
20.6
26.5
13.5

Figure A1: Education Index DS Data
Education Index
Subgroup Mean Median SD
CV
SC
53.8
53.7 12.2 0.23
SM
49.5
49.8 14.4 0.29
SR
46.3
48.9 16.4 0.35
MC
50.8
53.1 10.8 0.21
MM
44.6
44.8 12.1 0.27
MR
28.6
28.2 11.1 0.39
LC
51.9
55.8 13.6 0.26
LM
38.9
36.0 11.0 0.28
LR
25.8
24.1 10.0 0.39
Total Pop 45.1
46.2 14.5 0.32

Figure A3: Workforce Index DS Data
Workforce Index
Subgroup Mean Median SD
CV
SC
59.6
60.9 12.1 0.20
SM
63.1
63.9 13.4 0.21
SR
64.1
60.9 17.6 0.27
MC
58.2
59.3 11.3 0.19
MM
53.1
53.1 12.3 0.23
MR
57.4
57.6 11.1 0.19
LC
54.1
53.6 12.6 0.23
LM
42.7
44.6
8.1 0.19
LR
47.8
48.9
9.4 0.20
Total Pop 55.9
55.8 13.2 0.24
Max
90.2
100.0
100.0
78.4
91.9
79.1
82.7
55.0
63.5
100.0

Mean

MR

Median

Subgroup

MM

LR

Total
Pop

0

20
SM

SR

Mean

MC

MR

Median

Subgroup

MM

LC

SD

LM

LR

Total
Pop

7
0

14

21

28
60
40

35

80

SC

SD

LM

Workforce Index Descriptive Stats

LC

7
0

20
0
MC

14

40

SR

21

60

SM

28

80

SC

35

100

Education Index Descriptive Stats

Figure A4: Workforce Index DS Graph

Mean & Median Scale

Max
81.3
100.0
75.1
70.6
68.8
53.1
75.5
60.2
46.9
100.0
Mean & Median Scale

Figure A2: Education Index DS Graph

Appendix D: Descriptive Statistics of Demographic Indices with Breakdown Between Subgroups

SD Scale
SD Scale

A9

Min
5.2
4.5
7.8
-

Min
33.3
25.0
30.8
28.6
5.7
14.3
30.4
32.0
17.5
5.7

Figure A5: Language Index DS Data
Language Index
Subgroup Mean Median SD
CV
SC
10.7
7.4 13.6 1.27
SM
19.9
18.0 14.5 0.73
SR
36.2
36.1 23.8 0.66
MC
16.2
13.2 14.1 0.87
MM
28.4
26.0 18.6 0.65
MR
52.4
50.9 30.6 0.58
LC
26.5
17.1 24.5 0.92
LM
42.8
40.6 24.8 0.58
LR
64.5
69.2 30.4 0.47
Total Pop 28.7
22.8 24.3 0.85

Figure A7: Housing Index DS Data
Housing Index
Subgroup Mean Median SD
CV
SC
70.4
66.7 18.7 0.27
SM
68.7
66.7 19.6 0.29
SR
60.8
64.3 17.9 0.30
MC
69.1
70.3 14.7 0.21
MM
60.3
61.3 17.2 0.29
MR
51.2
51.5 14.2 0.28
LC
72.2
78.0 18.7 0.26
LM
57.0
59.7 11.7 0.21
LR
43.0
42.5 12.7 0.30
Total Pop 63.1
63.1 18.1 0.29
Max
100.0
100.0
100.0
100.0
93.1
86.4
98.7
74.2
72.0
100.0

Mean

Median

Subgroup

LR

Total
Pop

Mean

Median

Subgroup

MR

LC

SD

LM

LR

Total
Pop

7
0

20
0
MM

14

40

MC

21

60

SR

28

80

SM

35

100

SC

SD

LM

Housing Index Descriptive Stats

LC

0
MR

0
MM

7

20
MC

14

40

SR

21

60

SM

28

80

SC

35

100

Language Index Descriptive Stats

Figure A8: Housing Index DS Graph

Mean & Median Scale

Max
56.2
59.8
79.2
56.3
99.3
99.3
98.5
99.0
100.0
100.0
Mean & Median Scale

Figure A6: Language Index DS Graph

Appendix D: Descriptive Statistics of Demographic Indices with Breakdown Between Subgroups (continued)

SD Scale
SD Scale

A10

Max
46.4
100.0
56.3
92.8
40.0
38.7
100.0

Max
94.3
100.0
97.5
82.0
93.6
84.5
98.9
78.4
77.8
67.7

Min
17.3
17.3
17.6
19.5
17.9
18.9
17.3

Figure A11: Nation Wellness Index DS Data
Nation Wellness Index
Subgroup Mean Median SD
CV
Min
SC
68.7
69.1 10.0 0.15
45.5
SM
71.0
70.4 12.5 0.18
40.5
SR
73.2
75.9 14.4 0.20
45.3
MC
64.6
65.5
8.1 0.13
45.1
MM
61.7
62.1 11.3 0.18
32.3
MR
62.6
61.1
9.7 0.16
42.5
LC
68.2
69.0 12.0 0.18
43.3
LM
58.7
60.0 10.1 0.17
38.5
LR
58.5
59.7
9.3 0.16
45.8
Total Pop 64.9
65.5
0.2 32.3 100.0

Median

LC

SD

LM

LR

Total
Pop

Mean

MR

Median

Subgroup

MM

LC

SD

LM

LR

Total
Pop

7
0

20
0
MC

14

40

SR

21

60

SM

28

80

SC

35

100

Nation Wellness Index Descriptive Stats

Figure A12: Nation Wellness Index DS Graph

Mean

MR

Subgroup

MM

7
0

20
0
MC

14

40

SR

21

60

SM

28

80

SC

35

100

Income Index Descriptive Stats

Figure A10: Income Index DS Graph

Mean & Median Scale
Mean & Median Scale

Figure A9: Income Index DS Data
Income Index
Subgroup Mean Median SD
CV
SC
SM
SR
MC
32.6
33.5
6.6 0.20
MM
30.2
27.1 10.7 0.35
MR
29.9
27.4 10.1 0.34
LC
36.8
34.0 15.3 0.41
LM
26.7
26.6
4.3 0.16
LR
26.1
24.9
5.4 0.21
Total Pop 31.0
28.5 10.3 0.33

Appendix D: Descriptive Statistics of Demographic Indices with Breakdown Between Subgroups (continued)

SD Scale
SD Scale

A11

Range
6.40
1.07
0.83
0.93
1.57
1.03
0.84
0.89
0.96
6.73

Range
430,856
718,271
333,095
94,386
253,959
83,894
29,915
75,412
95,693
718,271

CV
2.48
1.14
1.22
1.05
1.29
1.11
0.82
0.81
1.04
1.44

Figure A15: Investment Asset Capita DS Data
Investment Asset Capita
Subgroup
Mean
Median
SD
CV
SC
30,015
2,148
77,735
2.59
SM
25,820
2,640
92,335
3.58
SR
25,912
2,022
75,352
2.91
MC
10,549
2,236
19,260
1.83
MM
12,497
1,459
35,651
2.85
MR
7,256
1,291
14,499
2.00
LC
5,312
2,846
7,442
1.40
LM
7,356
2,565
14,186
1.93
LR
11,346
1,397
25,408
2.24
Total Pop
14,306
2,098
48,980
3.42

SC

SM

Median

Subgroup

MC MM MR

Mean

SR

LC

CV

LM

30,000
25,000
20,000
15,000
10,000
5,000
-

LR Total
Pop

SC

SM

Mean

Median

Subgroup
CV

SR MC MM MR LC LM LR Total
Pop

Investment Asset Capita DS

Figure A16: Investment Asset Capita DS Graph

0.00

0.10

0.20

0.30

0.40

0.50

Investment Asset Ratio DS

Figure A14: Investment Asset Ratio DS Graph

Mean & Median Scale
Mean & Median Scale

Figure A13: Investment Asset Ratio DS Data
Investment Asset Ratio
Subgroup
Mean
Median
SD
SC
0.44
0.11
1.08
SM
0.25
0.11
0.29
SR
0.20
0.15
0.25
MC
0.28
0.18
0.29
MM
0.24
0.16
0.30
MR
0.28
0.15
0.31
LC
0.31
0.31
0.26
LM
0.32
0.29
0.26
LR
0.34
0.31
0.36
Total Pop
0.28
0.18
0.40

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups

6
5
4
3
2
1
0

6
5
4
3
2
1
0

CV Scale
CV Scale

A12

Range
0.75
0.55
0.24
0.77
0.61
0.48
0.68
0.68
0.32
0.77

Range
108,670
51,131
9,737
77,464
23,391
37,240
37,531
15,344
6,176
108,670

Figure A17: Gross Business Sales Ratio DS Data
Gross Business Sales Ratio
Subgroup
Mean
Median
SD
CV
SC
0.16
0.02
0.23
1.49
SM
0.08
0.14
1.71
SR
0.03
0.07
2.73
MC
0.13
0.01
0.20
1.48
MM
0.09
0.15
1.56
MR
0.06
0.13
2.07
LC
0.11
0.02
0.18
1.72
LM
0.12
0.06
0.15
1.25
LR
0.05
0.09
1.72
Total Pop
0.10
0.16
1.65

Figure A19: Gross Business Sales Capita DS Data
Gross Business Sales Capita
Subgroup
Mean
Median
SD
CV
SC
11,674
267
24,189
2.07
SM
5,214
11,096
2.13
SR
1,361
3,196
2.35
MC
6,201
109
13,633
2.20
MM
2,901
5,319
1.83
MR
3,247
7,907
2.44
LC
4,235
120
9,107
2.15
LM
2,558
985
3,431
1.34
LR
961
1,715
1.78
Total Pop
4,436
10,893
2.46
Mean & Median Scale

0.00

0.04

0.08

0.12

0.16

SC

SM

Median

Subgroup

MC MM MR

Mean

SR

LC

CV

LM

LR Total
Pop

Gross Business Sales Ratio DS

-

3,000

6,000

9,000

12,000

SC

SM

Mean

Median

Subgroup
CV

SR MC MM MR LC LM LR Total
Pop

Gross Business Sales Capita DS

Figure A20: Gross Business Sales Capita DS Graph

Mean & Median Scale

Figure A18: Gross Business Sales Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
0

6
5
4
3
2
1
0

CV Scale
CV Scale

A13

Range
0.70
0.65
0.27
0.74
0.61
0.51
0.70
0.43
0.31
0.74

Range
77,479
48,470
45,262
56,122
48,929
29,279
41,669
13,586
5,864
77,480

Figure A21: Bus and Ec Dev Expense Ratio DS Data
Business and Ec Dev Expense Ratio
Subgroup
Mean
Median
SD
CV
SC
0.20
0.06
0.23
1.15
SM
0.14
0.08
0.15
1.08
SR
0.07
0.01
0.10
1.41
MC
0.16
0.07
0.19
1.15
MM
0.14
0.07
0.16
1.10
MR
0.08
0.03
0.13
1.51
LC
0.11
0.04
0.15
1.34
LM
0.12
0.08
0.11
0.93
LR
0.08
0.06
0.09
1.08
Total Pop
0.13
0.06
0.16
1.19

Figure A23: Bus and Ec Dev Expense Capita DS Data
Business and Ec Dev Expense Capita
Subgroup
Mean
Median
SD
CV
SC
11,736
1,085
20,248
1.73
SM
7,086
3,090
10,026
1.41
SR
4,292
298
10,340
2.41
MC
6,163
1,605
10,826
1.76
MM
4,462
1,631
6,992
1.57
MR
3,777
558
7,129
1.89
LC
3,409
604
7,326
2.15
LM
2,573
1,551
2,801
1.09
LR
1,697
1,297
1,796
1.06
Total Pop
5,251
1,572
9,800
1.87
Mean & Median Scale

0.00

0.05

0.10

0.15

0.20

SC

SM

Median

Subgroup

MC MM MR

Mean

SR

LC

CV

LM

LR Total
Pop

Business and Ec Dev Expense Ratio DS

-

3,000

6,000

9,000

12,000

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Business and Ec Dev Expense Capita DS

Figure A24: Bus and Ec Dev Expense Capita DS Graph

Mean & Median Scale

Figure A22: Bus and Ec Dev Expense Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
0

6
5
4
3
2
1
0

CV Scale
CV Scale

A14

CV
1.75
2.70
2.21
1.39
2.27
1.70
1.17
1.04
1.26
2.11

CV
2.12
3.33
3.57
2.45
3.02
1.83
1.69
1.50
1.20
4.11

Figure A25: GBE Asset Ratio DS Data
GBE Asset Ratio
Subgroup
Mean
Median
SD
SC
0.14
0.24
SM
0.47
0.02
1.26
SR
0.21
0.47
MC
0.31
0.14
0.43
MM
0.45
0.03
1.01
MR
0.39
0.05
0.66
LC
0.41
0.25
0.48
LM
0.35
0.23
0.36
LR
0.47
0.14
0.59
Total Pop
0.38
0.06
0.80

Figure A27: GBE Asset Capita DS Data
GBE Asset Capita
Subgroup
Mean
Median
SD
SC
8,250
17,454
SM
31,387
386
104,674
SR
50,022
178,501
MC
8,743
1,244
21,449
MM
13,029
406
39,320
MR
7,075
467
12,931
LC
6,765
1,961
11,461
LM
6,890
2,350
10,360
LR
7,629
6,471
9,172
Total Pop
14,481
854
59,570
Range
62,718
751,189
717,494
160,266
284,081
52,817
53,305
38,247
24,822
751,699

0.00

0.10

0.20

0.30

0.40

0.50

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

GBE Asset Ratio DS

-

10,000

20,000

30,000

40,000

50,000

SC SM

CV

LM

LR Total
Pop

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

GBE Asset Capita DS

Figure A28: GBE Asset Capita DS Graph

Mean & Median Scale

Range
0.71
7.86
1.56
2.06
7.73
3.09
1.67
1.06
1.61
7.89
Mean & Median Scale

Figure A26: GBE Asset Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
0

CV Scale
CV Scale

A15

CV
2.85
4.47
2.11
2.34
4.32
1.72
1.93
2.08
1.16
5.07

CV
2.26
2.53
2.78
2.46
3.52
2.47
1.58
1.96
1.27
3.44

Figure A29: GBE Liability Ratio DS Data
GBE Liability Ratio
Subgroup
Mean
Median
SD
SC
0.18
0.52
SM
1.41
0.02
6.30
SR
0.19
0.40
MC
0.38
0.04
0.89
MM
1.09
0.01
4.73
MR
0.29
0.03
0.50
LC
0.40
0.10
0.78
LM
0.31
0.09
0.65
LR
0.23
0.14
0.27
Total Pop
0.69
0.02
3.51

Figure A31: GBE Liability Capita DS Data
GBE Liability Capita
Subgroup
Mean
Median
SD
SC
3,302
7,450
SM
21,001
484
53,163
SR
12,592
34,970
MC
5,211
386
12,819
MM
10,300
105
36,214
MR
4,402
246
10,866
LC
3,485
854
5,515
LM
3,837
725
7,528
LR
3,005
1,702
3,803
Total Pop
8,714
280
30,013
Range
27,058
328,243
139,096
88,534
245,667
48,250
22,329
35,312
10,621
328,243

0.00

0.30

0.60

0.90

1.20

1.50

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

-

5,000

10,000

15,000

20,000

SC

SM

LR Total
Pop

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

GBE Liability Capita DS

CV

LM

GBE Liability Ratio DS

Figure A32: GBE Liability Capita DS Graph

Mean & Median Scale

Range
2.58
45.76
1.36
5.42
33.99
1.88
2.96
3.27
0.69
45.76
Mean & Median Scale

Figure A30: GBE Liability Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
0

6
5
4
3
2
1
0

CV Scale
CV Scale

A16

CV
2.17
4.76
3.78
2.56
3.09
2.35
5.97
1.43
1.87
3.86

CV
2.28
5.98
4.06
2.41
3.54
2.59
2.41
1.73
1.90
5.48

Figure A33: GBE Equity Ratio DS Data
GBE Equity Ratio
Subgroup
Mean
Median
SD
SC
0.15
0.00
0.33
SM
0.16
0.78
SR
0.08
0.31
MC
0.10
0.01
0.27
MM
0.05
0.16
MR
0.10
0.01
0.24
LC
0.07
0.03
0.42
LM
0.09
0.04
0.12
LR
0.14
0.00
0.26
Total Pop
0.10
0.00
0.38

Figure A35: GBE Equity Capita DS Data
GBE Equity Capita
Subgroup
Mean
Median
SD
SC
13,271
0
30,276
SM
10,233
61,240
SR
33,531
136,073
MC
4,064
479
9,809
MM
4,804
17,021
MR
5,747
404
14,896
LC
3,612
946
8,716
LM
2,739
664
4,749
LR
4,243
24
8,081
Total Pop
7,113
24
39,001
Range
141,829
555,266
583,201
73,932
121,284
83,732
50,090
22,083
23,801
710,717

-0.04

0.01

0.06

0.11

0.16

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

GBE Equity Ratio DS

-

10,000

20,000

30,000

SC SM

CV

LM

LR Total
Pop

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

GBE Equity Capita DS

Figure A36: GBE Equity Capita DS Graph

Mean & Median Scale

Range
1.46
6.14
1.45
2.01
1.16
1.34
2.91
0.45
0.74
7.83
Mean & Median Scale

Figure A34: GBE Equity Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

0

1

2

3

4

5

6

CV Scale
CV Scale

A17

CV
1.76
2.88
3.30
1.96
2.40
1.87
1.80
1.17
1.15
2.47

CV
1.86
4.70
3.86
2.41
2.31
2.50
2.42
1.09
1.11
5.36

Figure A37: GBE Revenue Ratio DS Data
GBE Revenue Ratio
Subgroup
Mean
Median
SD
SC
0.11
0.20
SM
0.31
0.00
0.88
SR
0.25
0.84
MC
0.24
0.03
0.47
MM
0.35
0.00
0.83
MR
0.12
0.03
0.22
LC
0.20
0.04
0.36
LM
0.25
0.15
0.29
LR
0.21
0.17
0.24
Total Pop
0.26
0.01
0.64

Figure A39: GBE Revenue Capita DS Data
GBE Revenue Capita
Subgroup
Mean
Median
SD
SC
4,621
8,588
SM
23,342
34
109,780
SR
42,744
165,155
MC
5,914
314
14,277
MM
9,114
32
21,086
MR
3,940
355
9,846
LC
4,217
581
10,189
LM
5,121
3,762
5,587
LR
3,879
2,140
4,306
Total Pop
10,398
253
55,710
Range
37,682
827,843
661,988
97,670
113,136
50,342
49,031
18,647
11,319
827,843

0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

GBE Revenue Ratio DS

-

10,000

20,000

30,000

40,000

CV

LR Total
Pop

Mean

Median

Subgroups
CV

SC SM SR MC MM MR LC LM LR Total
Pop

GBE Revenue Capita DS

Figure A40: GBE Revenue Capita DS Graph

Mean & Median Scale

Range
0.74
6.27
3.38
2.75
6.46
1.11
1.86
1.04
0.71
7.09
Mean & Median Scale

Figure A38: GBE Revenue Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A18

CV
2.88
2.50
3.58
2.10
2.95
1.90
1.79
1.08
1.19
2.87

CV
1.47
4.69
3.80
2.45
2.27
2.56
2.28
1.14
1.17
5.19

Figure A41: GBE Expense Ratio DS Data
GBE Expense Ratio
Subgroup
Mean
Median
SD
SC
0.16
0.46
SM
0.33
0.00
0.84
SR
0.40
1.44
MC
0.24
0.02
0.50
MM
0.41
0.00
1.22
MR
0.10
0.01
0.19
LC
0.21
0.04
0.37
LM
0.25
0.19
0.27
LR
0.20
0.07
0.23
Total Pop
0.29
0.02
0.83

Figure A43: GBE Expense Capita DS Data
GBE Expense Capita
Subgroup
Mean
Median
SD
SC
2,396
3,532
SM
23,758
126
111,430
SR
25,172
95,600
MC
5,554
339
13,618
MM
8,598
60
19,533
MR
3,823
181
9,778
LC
4,506
518
10,251
LM
5,227
2,808
5,984
LR
3,710
851
4,350
Total Pop
9,362
303
48,619
Range
11,901
819,095
383,506
92,054
104,879
50,327
48,386
19,166
11,908
819,142

0.00

0.10

0.20

0.30

0.40

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

GBE Expense Ratio DS

-

5,000

10,000

15,000

20,000

25,000

CV

LR Total
Pop

Mean

Median

Subgroups
CV

SC SM SR MC MM MR LC LM LR Total
Pop

GBE Expense Capita DS

Figure A44: GBE Expense Capita DS Graph

Mean & Median Scale

Range
2.26
5.21
5.78
3.16
10.86
0.96
1.90
0.82
0.67
10.86
Mean & Median Scale

Figure A42: GBE Expense Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A19

CV
5.60
7.16
2.52
91.69
18.36
5.87
8.17
4.23
12.94
17.50

CV
2.34
7.55
4.24
4.30
10.40
4.28
11.85
10.62
3.33
15.02

Figure A45: GBE Net Income Ratio DS Data
GBE Net Income Ratio
Subgroup
Mean
Median
SD
SC
0.86
4.81
SM
2.45
17.53
SR
0.51
1.28
MC
0.13
0.00
12.03
MM
- 0.24
4.40 MR
1.13
6.61
LC
- 0.35
2.87 LM
0.83
0.09
3.50
LR
- 0.25
3.17 Total Pop
0.51
9.01

Figure A47: GBE Net Income Capita DS Data
GBE Net Income Capita
Subgroup
Mean
Median
SD
SC
2,514
5,876
SM
585
4,418 SR
15,469
65,650
MC
394
1,694
MM
294
3,061
MR
398
1,706
LC
270
3,198 LM
117
1,243 LR
159
531
Total Pop
941
14,135
Range
27,645
31,683
281,224
12,065
31,269
11,125
22,059
7,757
1,878
300,448

0.00

0.50

1.00

1.50

2.00

2.50

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

GBE Net Income Ratio DS

Mean

Median

CV

(20)

-

Subgroups

(10)

5,000

SC SM SR MC MM MR LC LM LR Total
Pop

10
10,000

-

20

100
80
60
40
20
(20)
(40)

15,000

GBE Net Income Capita DS

Figure A48: GBE Net Income Capita DS Graph

Mean & Median Scale

Range
31.68
133.53
4.71
142.59
50.11
42.00
18.93
21.02
12.57
202.15
Mean & Median Scale

Figure A46: GBE Net Income Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A20

Range
0.60
0.78
0.62
0.77
0.88
0.86
0.95
0.83
0.14
0.99

Range
188,636
134,055
15,912
100,644
79,104
652,801
119,369
49,227
2,913
652,801

CV
2.31
1.72
2.04
2.07
1.64
2.68
1.69
2.15
2.01
1.95

Figure A51: Trust Fund Asset Capita DS Data
Trust Fund Asset Capita
Subgroup
Mean
Median
SD
CV
SC
8,064
75
33,552
4.16
SM
4,837
508
17,431
3.60
SR
2,110
254
4,242
2.01
MC
2,730
176
12,227
4.48
MM
4,676
85
13,341
2.85
MR
20,669
34
98,841
4.78
LC
8,203
113
22,416
2.73
LM
3,917
14
11,110
2.84
LR
254
15
769
3.02
Total Pop
6,279
84
35,566
5.66

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

-

5,000

10,000

15,000

20,000

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Trust Fund Asset Capita DS

SC SM

LR Total
Pop

CV

Figure A52: Trust Fund Asset Capita DS Graph

0.00

0.05

0.10

0.15

Trust Fund Asset Ratio DS

Figure A50: Trust Fund Asset Ratio DS Graph

Mean & Median Scale
Mean & Median Scale

Figure A49: Trust Fund Asset Ratio DS Data
Trust Fund Asset Ratio
Subgroup
Mean
Median
SD
SC
0.06
0.00
0.14
SM
0.10
0.02
0.17
SR
0.08
0.01
0.17
MC
0.07
0.01
0.15
MM
0.13
0.01
0.22
MR
0.08
0.00
0.21
LC
0.16
0.01
0.27
LM
0.11
0.00
0.23
LR
0.02
0.00
0.04
Total Pop
0.10
0.01
0.20

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A21

Range
0.08
0.35
0.02
0.35
0.56
0.31
0.52
0.07
0.04
0.60

Range
2,014
49,057
306
11,718
21,251
8,411
16,873
926
449
49,922

Figure A53: Trust Fund Revenue Ratio DS Data
Trust Fund Revenue Ratio
Subgroup
Mean
Median
SD
CV
SC
0.00
0.00
0.01
3.88
SM
0.04
0.09
2.13
SR
0.00
0.00
2.50
MC
0.02
0.06
2.66
MM
0.04
0.00
0.09
2.10
MR
0.01
0.05
3.77
LC
0.04
0.11
2.71
LM
0.01
0.02
1.76
LR
0.00
0.01
3.38
Total Pop
0.03
0.07
2.65

Figure A55: Trust Fund Revenue Capita DS Data
Trust Fund Revenue Capita
Subgroup
Mean
Median
SD
CV
SC
89
4
359
4.02
SM
2,140
6,912
3.23
SR
46
89
1.96
MC
473
1,521
3.21
MM
1,214
12
3,122
2.57
MR
382
1,354
3.54
LC
949
3,007
3.17
LM
203
343
1.69
LR
38
120
3.18
Total Pop
868
3,363
3.87
Mean & Median Scale

0.00

0.01

0.02

0.03

0.04

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

LR Total
Pop

CV

Trust Fund Revenue Ratio DS

-

500

1,000

1,500

2,000

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Trust Fund Revenue Capita DS

Figure A56: Trust Fund Revenue Capita DS Graph

Mean & Median Scale

Figure A54: Trust Fund Revenue Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A22

Range
1.19
0.87
0.65
0.77
0.96
0.91
0.76
0.84
0.70
1.24

Range
185,798
205,980
366,385
158,992
144,135
185,385
107,794
53,035
26,340
392,368

Figure A57: TCA Ratio DS Data
Tangible Capital Asset Ratio
Subgroup
Mean
Median
SD
CV
SC
0.57
0.60
0.29
0.51
SM
0.64
0.70
0.22
0.35
SR
0.66
0.70
0.20
0.30
MC
0.62
0.67
0.22
0.35
MM
0.69
0.75
0.22
0.31
MR
0.68
0.76
0.24
0.35
LC
0.58
0.64
0.22
0.38
LM
0.69
0.73
0.21
0.31
LR
0.63
0.71
0.25
0.40
Total Pop
0.65
0.71
0.23
0.35

Figure A59: TCA Capita DS Data
Tangible Capital Assets Capita
Subgroup
Mean
Median
SD
CV
SC
50,660
38,496
39,627
0.78
SM
65,209
53,765
44,404
0.68
SR
93,628
51,587
100,037
1.07
MC
37,319
28,903
28,552
0.77
MM
41,127
35,344
24,130
0.59
MR
54,172
42,571
40,376
0.75
LC
27,962
22,499
19,691
0.70
LM
25,543
22,491
11,187
0.44
LR
25,672
21,755
9,051
0.35
Total Pop
44,600
34,008
38,167
0.86
Mean & Median Scale

0.00

0.20

0.40

0.60

0.80

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

-

20,000

40,000

60,000

80,000

100,000

LM

CV

LR Total
Pop

Mean

Median

Subgroups
CV

SC SM SR MC MM MR LC LM LR Total
Pop

Tangible Capital Asset Capita DS

LC

Tangible Capital Asset Ratio DS

Figure A60: TCA Capita DS Graph

Mean & Median Scale

Figure A58: TCA Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A23

Range
1.00
1.00
0.89
1.00
1.00
0.71
0.91
0.33
1.00

Range
9,624
2,127
254
1,028
3,008
379
2,529
411
9,624

Figure A61: Gross Cash In From Cap Ratio DS Data
Gross Cash Inflows From Capital Ratio
Subgroup
Mean
Median
SD
CV
SC
0.17
0.34
1.95
SM
0.12
0.31
2.58
SR
0.26
0.38
1.47
MC
0.08
0.25
3.08
MM
0.08
0.23
2.95
MR
0.02
0.13
5.42
LC
0.07
0.22
3.16
LM
0.02
0.06
2.75
LR
Total Pop
0.08
0.24
2.95

Figure A63: Gross Cash In From Cap Capita DS Data
Gross Cash Inflows From Capital Capita
Subgroup
Mean
Median
SD
CV
SC
458
1,855
4.05
SM
98
360
3.69
SR
27
69
2.57
MC
57
193
3.39
MM
73
314
4.32
MR
13
62
4.70
LC
101
422
4.18
LM
40
96
2.39
LR
Total Pop
91
556
6.13
Mean & Median Scale

0.30
0.25
0.20
0.15
0.10
0.05
0.00
SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LR Total
Pop

CV

LM

Gross Cash Inflows From Capital Ratio DS
6
5
4
3
2
1
-

-

100

200

300

400

500

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LR Total
Pop

CV

LM

Gross Cash Inflows From Capital Capita DS
6
5
4
3
2
1
-

Figure A64: Gross Cash Inflows From Capital Capita DS Graph

Mean & Median Scale

Figure A62: Gross Cash Inflows From Capita Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A24

Range
1.00
1.00
0.71
1.00
1.00
0.98
0.92
0.82
0.91
1.00

Range
29,467
36,203
49,071
30,651
44,725
17,233
32,231
14,993
16,923
49,267

Figure A65: Gross Cash Out From Cap Ratio DS Data
Gross Cash Outflow From Capital Ratio
Subgroup
Mean
Median
SD
CV
SC
0.44
0.38
0.36
0.83
SM
0.48
0.44
0.32
0.66
SR
0.75
0.79
0.22
0.30
MC
0.55
0.65
0.32
0.57
MM
0.52
0.48
0.30
0.59
MR
0.55
0.66
0.33
0.60
LC
0.55
0.65
0.30
0.54
LM
0.56
0.58
0.23
0.40
LR
0.53
0.57
0.28
0.53
Total Pop
0.53
0.57
0.31
0.58

Figure A67: Gross Cash Out From Cap Capita DS Data
Gross Cash Outflow From Capital Capita
Subgroup
Mean
Median
SD
CV
SC
4,113
2,051
6,280
1.53
SM
5,948
1,567
8,589
1.44
SR
7,927
3,181
12,777
1.61
MC
3,229
1,840
4,792
1.48
MM
4,687
1,984
7,440
1.59
MR
3,854
2,498
4,397
1.14
LC
3,251
1,743
5,224
1.61
LM
2,423
1,564
2,773
1.14
LR
2,911
1,063
4,835
1.66
Total Pop
4,232
1,937
6,694
1.58
Mean & Median Scale

0.00

0.20

0.40

0.60

0.80

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LR Total
Pop

CV

LM

Gross Cash Outflow From Capital Ratio DS
6
5
4
3
2
1
-

-

2,000

4,000

6,000

8,000

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Gross Cash Outflow From Capital Capita DS
6
5
4
3
2
1
-

Figure A68: Gross Cash Outflows From Capital Capita DS Graph

Mean & Median Scale

Figure A66: Gross Cash Outflows From Capital Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A25

Range
20.44
164.11
67.36
172.50
292.94
408.13
265.43
6,542.18
37.96
6,542.18

SR MC MM MR LC LM LR Total
Pop

-6.00

-4.00

Mean

Median

Subgroups
CV

(60)

(40)

(20)

SM

0.00
-2.00

-

2.00
SC

20

6.00
4.00

40

8.00

Net Cash Flow From Capital Ratio DS

Figure A70: Net Cash Flow From Capital Ratio DS Graph

Figure A71: Net Cash Flow From Cap Capita DS Data
Figure A72: Net Cash Flow From Capital Capita DS Graph
Net Cash Flow From Capital Capita
Net Cash Flow From Capital Capita DS (positive
Subgroup
Mean
Median
SD
CV
Range
amounts indicate net cash outflows)
SC
3,654
1,714
6,652
1.82
37,016
8,000
6
SM
5,851
1,493
8,594
1.47 - 37,537
5
6,000
4
SR
7,900
3,181
12,781
1.62 - 49,071
4,000
3
MC
3,172
1,750
4,798
1.51 - 30,896
2
2,000
1
MM
4,615
1,944
7,445
1.61 - 44,725
MR
3,841
2,498
4,395
1.14 - 17,233
SC SM SR MC MM MR LC LM LR Total
Pop
LC
3,150
1,740
5,235
1.66 - 32,930
Subgroups
LM
2,383
1,409
2,766
1.16 - 15,072
LR
2,911
1,063
4,835
1.66 - 16,923
Mean
Median
CV
Total Pop
4,141
1,796
6,721
1.62 - 56,816

Figure A69: Net Cash Flow From Cap Ratio DS Data
Net Cash Flow From Capital Ratio
Subgroup
Mean
Median
SD
CV
SC
0.25
3.59
14.07
SM
2.05 0.06
20.23
9.86
SR
4.60
0.53
15.77
3.43
MC
2.93
0.10
19.02
6.48
MM
- 1.63 0.51
26.09 - 16.04
MR
6.81
60.28
8.85
LC
1.26 0.35
34.44
27.38
LM
- 81.18
0.62
882.15 - 10.87
LR
6.27
1.33
11.73
1.87
Total Pop - 5.26 0.01
252.71 - 48.00

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

Mean & Median Scale
Mean & Median Scale

CV Scale
CV Scale

A26

CV
0.69
0.65
0.99
0.47
0.48
0.59
0.37
0.26
0.31
0.52

CV
1.76
1.31
2.09
0.95
1.21
1.69
1.07
1.07
1.57
1.42

Figure A73: Long Term Debt Ratio DS Data
Long Term Debt Ratio
Subgroup
Mean
Median
SD
SC
0.46
0.44
0.31
SM
0.44
0.45
0.29
SR
0.35
0.30
0.35
MC
0.56
0.64
0.26
MM
0.54
0.58
0.26
MR
0.43
0.45
0.26
LC
0.59
0.67
0.22
LM
0.66
0.69
0.17
LR
0.63
0.63
0.19
Total Pop
0.52
0.57
0.27

Figure A75: Long Term Debt Capita DS Data
Long Term Debt Capita
Subgroup
Mean
Median
SD
SC
15,290
7,572
26,962
SM
14,848
8,914
19,427
SR
15,907
6,662
33,194
MC
10,745
7,645
10,209
MM
10,481
7,019
12,645
MR
9,773
6,196
16,489
LC
9,357
9,396
9,996
LM
10,195
7,466
10,910
LR
11,214
6,215
17,657
Total Pop
11,563
7,394
16,389
Range
134,586
88,407
141,752
48,598
62,302
109,917
60,737
58,801
68,164
141,752

0.00

0.20

0.40

0.60

0.80

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

-

4,000

8,000

12,000

16,000

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Long Term Debt Capita DS

LR Total
Pop

CV

LM

Long Term Debt Ratio DS

Figure A76: Long Term Debt Capita DS Graph

Mean & Median Scale

Range
0.94
0.94
0.98
0.92
0.97
0.90
0.95
0.67
0.64
0.98
Mean & Median Scale

Figure A74: Long Term Debt Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A27

CV
0.85
0.89
2.71
0.83
1.02
1.29
0.86
0.78
1.19
1.02

CV
1.37
1.25
3.43
1.52
1.26
2.04
1.46
0.97
1.62
1.83

Figure A77: Earned Revenue Ratio DS Data
Earned Revenue Ratio
Subgroup
Mean
Median
SD
SC
0.32
0.30
0.27
SM
0.17
0.15
0.16
SR
0.08
0.04
0.21
MC
0.28
0.23
0.23
MM
0.17
0.14
0.18
MR
0.13
0.05
0.16
LC
0.25
0.20
0.21
LM
0.18
0.13
0.14
LR
0.11
0.09
0.14
Total Pop
0.20
0.15
0.20

Figure A79: Earned Revenue Capita DS Data
Earned Revenue Capita
Subgroup
Mean
Median
SD
SC
20,438
10,554
27,931
SM
9,314
4,464
11,675
SR
9,564
1,020
32,777
MC
9,706
4,137
14,755
MM
5,221
3,173
6,567
MR
7,207
896
14,686
LC
6,506
2,697
9,522
LM
3,744
3,455
3,614
LR
2,455
1,251
3,985
Total Pop
7,982
3,262
14,615
Range
128,733
50,056
156,532
79,829
35,362
72,981
40,097
17,128
14,698
156,532

0.00

0.10

0.20

0.30

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

Earned Revenue Ratio DS

-

5,000

10,000

15,000

20,000

SC SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Earned Revenue Capita DS

LR Total
Pop

CV

Figure A80: Earned Revenue Capita DS Graph

Mean & Median Scale

Range
1.08
0.64
1.17
1.00
1.03
0.59
0.73
0.52
0.43
1.31
Mean & Median Scale

Figure A78: Earned Revenue Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A28

Range
0.86
1.05
1.03
1.27
1.38
1.06
0.80
0.77
0.60
1.59

Range
131,335
116,510
175,491
109,089
77,721
259,641
45,914
98,832
18,683
277,248

Figure A81: Earned & Other Revenue Ratio DS Data
Earned and Other Revenue Ratio
Subgroup
Mean
Median
SD
CV
SC
0.43
0.44
0.25
0.60
SM
0.36
0.36
0.21
0.58
SR
0.28
0.32
0.25
0.91
MC
0.42
0.41
0.23
0.56
MM
0.29
0.29
0.21
0.72
MR
0.26
0.19
0.21
0.80
LC
0.38
0.31
0.23
0.59
LM
0.32
0.28
0.17
0.53
LR
0.21
0.19
0.15
0.71
Total Pop
0.34
0.30
0.22
0.66

Figure A83: Earned & Other Revenue Capita DS Data
Earned and Other Revenue Capita
Subgroup
Mean
Median
SD
CV
SC
23,976
11,439
28,454
1.19
SM
18,895
11,590
21,607
1.14
SR
21,482
8,942
40,918
1.90
MC
13,570
7,668
16,769
1.24
MM
8,900
6,092
9,695
1.09
MR
14,850
5,559
39,006
2.63
LC
9,018
5,129
10,315
1.14
LM
9,096
5,814
16,613
1.83
LR
4,973
3,222
4,937
0.99
Total Pop
13,286
6,991
21,782
1.64
Mean & Median Scale

0.00

0.10

0.20

0.30

0.40

0.50

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LR Total
Pop

CV

LM

Earned and Other Revenue Ratio DS

-

6,000

12,000

18,000

24,000

SC SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Earned and Other Revenue Capita DS

Figure A84: Earned & Other Revenue Capita DS Graph

Mean & Median Scale

Figure A82: Earned & Other Revenue Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

6
5
4
3
2
1
-

6
5
4
3
2
1
-

CV Scale
CV Scale

A29

Range
0.85
1.09
1.07
1.18
1.56
1.06
0.76
0.76
0.64
1.56
0.00

0.20

0.40

0.60

0.80

SC

SM

LC

Median

Subgroups

MC MM MR

Mean

SR

LM

CV

LR Total
Pop

Federal & Provincial Gov't Revenue Ratio DS

Figure A86: Fed & Prov Gov't Revenue Ratio DS Graph
6
5
4
3
2
1
-

Figure A87: Fed & Prov Gov't Rev Capita DS Data
Figure A88: Fed & Prov Gov't Revenue Capita DS Graph
Federal and Provincial Gov't Revenue Capita
Federal & Provincial Gov't Revenue Capita DS
Subgroup
Mean
Median
SD
CV
Range
30,000
6
SC
19,335
15,165
12,677
0.66
43,301
5
24,000
SM
22,630
18,119
16,989
0.75
92,983
4
18,000
3
SR
28,378
21,548
26,638
0.94
124,041
12,000
2
MC
12,382
12,465
5,829
0.47
25,745
6,000
1
MM
14,963
14,169
7,959
0.53
53,463
MR
18,266
18,148
10,148
0.56
44,019
SC SM SR MC MM MR LC LM LR Total
Pop
LC
11,818
10,207
11,666
0.99
70,908
Subgroups
LM
12,756
12,160
3,949
0.31
17,290
LR
14,408
14,777
3,596
0.25
11,981
Mean
Median
CV
Total Pop
16,392
14,244
12,135
0.74
127,652

Figure A85: Fed & Prov Gov't Rev Ratio DS Data
Federal & Provincial Gov't Revenue Ratio
Subgroup
Mean
Median
SD
CV
SC
0.50
0.46
0.24
0.49
SM
0.51
0.53
0.20
0.39
SR
0.61
0.63
0.28
0.46
MC
0.51
0.53
0.21
0.42
MM
0.58
0.60
0.23
0.40
MR
0.67
0.74
0.23
0.34
LC
0.52
0.55
0.22
0.43
LM
0.63
0.64
0.16
0.25
LR
0.76
0.74
0.16
0.22
Total Pop
0.57
0.59
0.23
0.40

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

Mean & Median Scale
Mean & Median Scale

CV Scale
CV Scale

A30

Figure A89: Tribal Gov't & Other FN Rev Ratio DS Data
Figure A90: Tribal Gov't & Other FN Ent Rev Ratio DS Graph
Tribal Gov't & Other FN Entity Revenue Ratio
Tribal Gov't & Other FN Entity Revenue Ratio DS
Subgroup
Mean
Median
SD
CV
Range
6
SC
0.07
0.02
0.10
1.46
0.40
0.10
5
SM
0.08
0.04
0.10
1.22
0.47
4
3
SR
0.11
0.04
0.20
1.78
0.87
0.05
2
MC
0.05
0.02
0.06
1.32
0.28
1
MM
0.08
0.03
0.13
1.57
0.68
0.00
MR
0.06
0.03
0.11
1.86
0.69
SC SM SR MC MM MR LC LM LR Total
Pop
LC
0.06
0.02
0.11
1.93
0.57
Subgroups
LM
0.04
0.02
0.08
1.75
0.34
LR
0.02
0.01
0.03
1.40
0.11
Mean
Median
CV
Total Pop
0.07
0.03
0.11
1.63
0.87

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale

Mean & Median Scale

Figure A91: Tribal Gov't & Other FN Rev Capita DS Data
Figure A92: Tribal Gov't & Other FN Revenue Capita DS Graph
Tribal Gov't & Other FN Revenue Capita
Tribal Gov't & Other FN Revenue Capita DS
Subgroup
Mean
Median
SD
CV
Range
6
6,000
SC
2,126
1,016
2,663
1.25
11,651
5
SM
3,378
2,047
4,509
1.33
23,166
4
4,000
3
SR
6,178
1,547
16,344
2.65
72,722
2
2,000
MC
1,087
306
1,624
1.49
8,091
1
MM
1,818
873
2,461
1.35
13,773
MR
1,771
596
4,565
2.58
30,430
SC SM SR MC MM MR LC LM LR Total
Pop
LC
1,425
292
3,408
2.39
20,022
Subgroups
LM
794
458
1,262
1.59
5,189
LR
441
96
573
1.30
1,396
Mean
Median
CV
Total Pop
1,966
659
4,577
2.33
72,722
CV Scale

Mean & Median Scale

A31

Range
129.96
141.27
64.43
309.22
217.27
339.39
186.64
9,903.44
93.63
9,903.44

Range
51,567
98,430
56,220
29,651
48,301
31,501
13,626
23,846
19,237
107,376

Figure A93: Net Cash Flow From Op Ratio DS Data
Net Cash Flow From Operating Ratio
Subgroup
Mean
Median
SD
CV
SC
2.60
0.73
20.53
7.88
SM
- 1.66
1.22
18.98 - 11.41
SR
- 3.75
0.20
14.28 - 3.81
MC
- 5.02
0.83
36.53 - 7.28
MM
2.72
1.35
19.51
7.18
MR
- 14.54 0.33
63.14 - 4.34
LC
- 0.23
1.10
23.65 - 100.84
LM
54.94
0.79 1,303.42
23.73
LR
- 10.92 1.11
25.80 - 2.36
Total Pop
2.09
0.97
359.78 172.32

Figure A95: Net Cash Flow From Op Capita DS Data
Net Cash Flow From Operating Capita
Subgroup
Mean
Median
SD
CV
SC
9,059
3,646
12,475
1.38
SM
9,560
4,565
15,792
1.65
SR
6,496
2,187
13,434
2.07
MC
2,592
1,910
4,059
1.57
MM
3,625
2,493
5,580
1.54
MR
3,944
1,821
6,463
1.64
LC
2,177
1,898
2,922
1.34
LM
359
1,066
3,939
10.96
LR
2,621
835
4,960
1.89
Total Pop
4,445
2,214
8,949
2.01
Mean & Median Scale

SC SM SR MC MM MR LC LM LR Total
Pop

Mean

Median

CV

(150)

-15.00

Subgroups

(100)

(50)

-

-10.00

-5.00

50

100

5.00
0.00

150

200

10.00

15.00

Net Cash Flow From Operating Ratio DS

10,000
8,000
6,000
4,000
2,000
SC SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Net Cash Flow From Operating Capita DS (positive amounts
indicate net cash outflows)
6
5
4
3
2
1
-

Figure A96: Net Cash Flow From Operating Capita DS Data

Mean & Median Scale

Figure A94: Net Cash Flow From Operating Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A32

Range
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.96
1.00
1.00

Range
103,514
32,893
7,282
141,805
121,728
12,667
16,479
22,980
1,650
141,805

Figure A97: Gross Cash In From Inv Ratio DS Data
Gross Cash Inflows From Investing Ratio
Subgroup
Mean
Median
SD
CV
SC
0.45
0.24
0.47
1.04
SM
0.29
0.00
0.41
1.41
SR
0.36
0.23
0.40
1.10
MC
0.26
0.00
0.38
1.47
MM
0.29
0.03
0.39
1.36
MR
0.30
0.02
0.38
1.29
LC
0.39
0.16
0.42
1.10
LM
0.26
0.18
0.29
1.13
LR
0.24
0.00
0.40
1.64
Total Pop
0.30
0.03
0.39
1.30

Figure A99: Gross Cash In From Inv Capita DS Data
Gross Cash Inflows From Investing Capita
Subgroup
Mean
Median
SD
CV
SC
5,476
18,954
3.46
SM
1,699
4,953
2.92
SR
429
1,663
3.87
MC
2,649
16,354
6.17
MM
3,252
6
15,392
4.73
MR
1,080
2,641
2.45
LC
1,093
103
2,869
2.62
LM
1,599
121
5,125
3.20
LR
176
442
2.50
Total Pop
2,317
0
11,901
5.14
Mean & Median Scale

0.00

0.10

0.20

0.30

0.40

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LM

CV

LR Total
Pop

Gross Cash Inflows From Investing Ratio DS
6
5
4
3
2
1
-

-

1,500

3,000

4,500

6,000

SC

SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Gross Cash Inflows From Investing Capita DS
6
5
4
3
2
1
-

Figure A100: Gross Cash Inflows from Investing Ratio DS Graph

Mean & Median Scale

Figure A98: Gross Cash Inflows From Investing Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A33

Range
0.99
0.93
0.44
1.00
0.90
0.90
0.93
0.72
0.22
1.00

Range
126,494
59,882
2,995
142,249
110,458
43,078
14,611
12,656
1,531
142,249

Figure A101: Gross Cash Out From Inv Ratio DS Data
Gross Cash Outflows From Investing Ratio
Subgroup
Mean
Median
SD
CV
SC
0.23
0.01
0.35
1.55
SM
0.20
0.01
0.31
1.51
SR
0.04
0.11
2.51
MC
0.16
0.00
0.28
1.80
MM
0.13
0.00
0.22
1.70
MR
0.06
0.15
2.55
LC
0.17
0.03
0.26
1.52
LM
0.15
0.04
0.20
1.35
LR
0.04
0.00
0.07
1.76
Total Pop
0.14
0.00
0.25
1.75

Figure A103: Gross Cash Out From Inv Capita DS Data
Gross Cash Outflows From Investing Capita
Subgroup
Mean
Median
SD
CV
SC
8,805
37
23,875
2.71
SM
3,937
36
10,121
2.57
SR
375
887
2.37
MC
3,478
6
16,878
4.85
MM
3,151
17
14,130
4.48
MR
1,133
6,349
5.60
LC
1,215
96
2,954
2.43
LM
1,079
116
2,496
2.31
LR
192
1
417
2.18
Total Pop
2,972
16
12,838
4.32
Mean & Median Scale

0.00

0.05

0.10

0.15

0.20

0.25

SC

SM

Median

Subgroups

MC MM MR

Mean

SR

LC

LR Total
Pop

CV

LM

Gross Cash Outflows From Investing Ratio DS
6
5
4
3
2
1
-

-

2,000

4,000

6,000

8,000

10,000

SC SM

Mean

Median

Subgroups
CV

SR MC MM MR LC LM LR Total
Pop

Gross Cash Outflows From Investing Capita DS
6
5
4
3
2
1
-

Figure A104: Gross Cash Outflows From Inv Capita DS Graph

Mean & Median Scale

Figure A102: Gross Cash Outflows From Inv Ratio DS Graph

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

CV Scale
CV Scale

A34

Figure A105: Net Cash Flows From Inv Ratio DS Data
Figure A106: Net Cash Flows From Inv Ratio DS Graph
Net Cash Flows From Investing Ratio
Net Cash Flows From Investing Ratio DS
Subgroup
Mean
Median
SD
CV
Range
15.00
20
SC
- 3.22
19.09 - 5.93
113.16
15
12.00
SM
3.08
27.11
8.80
233.22
10
9.00
5
SR
- 0.11
0.91 - 8.46
4.84
6.00
MC
6.12
26.79
4.38
158.31
3.00
(5)
MM
0.64
11.71
18.29
151.88
0.00
(10)
MR
12.83
77.92
6.07
532.35
SC SM SR MC MM MR LC LM LR Total
Pop
LC
0.76
0.00
3.74
4.95
20.22
Subgroups
LM
152.69
658.92
4.32
3,157.81
LR
0.84
2.08
2.48
8.18
Mean
Median
CV
Total Pop
14.67
187.91
12.81
3,157.81

Appendix E: Descriptive Statistics of Financial Indicators with Breakdown Between Subgroups (continued)

Figure A107: Net Cash Flows from Inv Capita DS Data
Figure A108: Net Cash Flows from Inv Capita DS Graph
Net Cash Flows From Investing Capita
Net Cash Flows From Investing Capita DS
Subgroup
Mean
Median
SD
CV
Range
3,000
SC
- 3,329 37
8,530 - 2.56
39,703
2,000
SM
2,238
6 - 11,516
5.14 - 92,776
1,000
SR
55
1,956 - 35.88 - 10,273
MC
828
4,218
5.09 - 35,486
SC SM SR MC MM MR LC LM LR Total
-1,000
Pop
MM
101
4,492 - 44.60 - 45,738
-2,000
MR
53
6,993 130.98 - 55,252
-3,000
LC
122
1,550
12.74 - 10,318
-4,000
Subgroups
LM
520
20 4,459 - 8.58 - 30,253
LR
15
604
39.26 2,980
Mean
Median
CV
Total Pop
655
6,367
9.73 - 92,776

Mean & Median Scale

Mean & Median Scale

(50)

-

50

100

150

CV Scale

Appendix F: T-test Statistic Details
Note: a t-test is performed for the index/financial indicator noted. The mean of a given
subgroup is tested against the rest of the population (total population less the subgroup being
evaluated). The test is peroformed assuming unequal variances, and uses Welch’s
approximation.
Figure A109: Education Index: Means comparison between subgroup SC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

32
414

53.77
44.43

2.151372
.7131276

12.17
14.51

49.38225
43.02819

58.15775
45.83181

combined

446

45.10013

.6886994

14.54444

43.74663

46.45364

9.34

2.266485

4.754125

13.92587

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9999

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

4.1209
38.6112

Ha: diff > 0
Pr(T > t) = 0.0001

A35

Appendix F: T-test Statistic Details (continued)
Figure A110: Education Index: Means comparison between subgroup MC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

76
370

50.8
43.93

1.23311
.7772135

10.75
14.95

48.34352
42.40168

53.25648
45.45832

combined

446

45.10067

.688625

14.54287

43.74731

46.45403

6.87

1.457608

3.988855

9.751145

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.7132
143.562

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A111: Education Index: Means comparison between subgroup LC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

41
405

51.89
44.41

2.122401
.719517

13.59
14.48

47.60047
42.99554

56.17953
45.82446

combined

446

45.09762

.6888522

14.54767

43.74382

46.45143

7.48

2.241047

2.97903

11.98097

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9992

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0016

3.3377
50.1375

Ha: diff > 0
Pr(T > t) = 0.0008

A36

Appendix F: T-test Statistic Details (continued)
Figure A112: Education Index: Means comparison between subgroup SR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

19
427

46.28
45.05

3.877126
.7007363

16.9
14.48

38.13446
43.67267

54.42554
46.42733

combined

446

45.1024

.6899873

14.57164

43.74636

46.45844

1.23

3.939941

-7.006961

9.466961

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.6209

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.7582

0.3122
19.3269

Ha: diff > 0
Pr(T > t) = 0.3791

Figure A113: Education Index: Means comparison between subgroup MR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

46
400

28.61
47

1.635131
.684

11.09
13.68

25.31668
45.65531

31.90332
48.34469

combined

446

45.10327

.6887759

14.54606

43.74962

46.45693

-18.39

1.772431

-21.9323

-14.8477

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

[95% Conf. Interval]

t = -10.3756
Welch's degrees of freedom = 62.6559
Ha: diff != 0
Pr(|T| > |t|) = 0.0000

Ha: diff > 0
Pr(T > t) = 1.0000

A37

Appendix F: T-test Statistic Details (continued)
Figure A114: Education Index: Means comparison between subgroup LR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

14
432

25.77
45.73

2.677958
.6851223

10.02
14.24

19.98462
44.3834

31.55538
47.0766

combined

446

45.10345

.6885868

14.54207

43.75017

46.45674

-19.96

2.764209

-25.85091

-14.06909

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.2209
15.0253

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A115: Workforce Index: Means comparison between subgroup SC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

32
414

59.6
55.66

2.13723
.6516934

12.09
13.26

55.24109
54.37895

63.95891
56.94105

combined

446

55.94269

.6253296

13.20615

54.71372

57.17166

3.94

2.234381

-.5856726

8.465673

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9570

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0860

1.7634
37.3948

Ha: diff > 0
Pr(T > t) = 0.0430

A38

Appendix F: T-test Statistic Details (continued)
Figure A116: Workforce Index: Means comparison between subgroup SM and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

65
381

63.12
54.72

1.660825
.6552515

13.39
12.79

59.80212
53.43163

66.43788
56.00837

combined

446

55.94422

.62511

13.20152

54.71568

57.17275

8.4

1.785412

4.850588

11.94941

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.7048
85.7784

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A117: Workforce Index: Means comparison between subgroup SR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

19
427

64.11
55.58

4.030834
.6233069

17.57
12.88

55.64153
54.35486

72.57847
56.80514

combined

446

55.94339

.6250964

13.20123

54.71488

57.17189

8.53

4.078742

-.0079002

17.0679

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9749

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0502

2.0913
18.9674

Ha: diff > 0
Pr(T > t) = 0.0251

A39

Appendix F: T-test Statistic Details (continued)
Figure A118: Workforce Index: Means comparison between subgroup LM and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

34
412

42.66
57.04

1.385709
.6380007

8.08
12.95

39.84075
55.78585

45.47925
58.29415

combined

446

55.94377

.6251916

13.20324

54.71507

57.17246

-14.38

1.525527

-17.44532

-11.31468

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-9.4262
49.2165

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A119: Workforce Index: Means comparison between subgroup LR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

14
432

47.82
56.2

2.517601
.6365287

9.42
13.23

42.38105
54.94891

53.25895
57.45109

combined

446

55.93695

.6250713

13.2007

54.70849

57.16541

-8.38

2.596822

-13.91575

-2.844252

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0028

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0057

-3.2270
14.9766

Ha: diff > 0
Pr(T > t) = 0.9972

A40

Appendix F: T-test Statistic Details (continued)
Figure A120: Housing Index: Means comparison between subgroup SC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

32
414

70.4
62.54

3.307492
.8841603

18.71
17.99

63.65433
60.80198

77.14567
64.27802

combined

446

63.10395

.8587161

18.13498

61.4163

64.79159

7.86

3.42363

.9156793

14.80432

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9862

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0276

2.2958
35.8695

Ha: diff > 0
Pr(T > t) = 0.0138

Figure A121: Housing Index: Means comparison between subgroup MC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

76
370

69.06
61.88

1.685059
.9643686

14.69
18.55

65.70319
59.98365

72.41681
63.77635

combined

446

63.1035

.8588875

18.1386

61.41552

64.79148

7.18

1.941502

3.339177

11.02082

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9998

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

3.6982
130.745

Ha: diff > 0
Pr(T > t) = 0.0002

A41

Appendix F: T-test Statistic Details (continued)
Figure A122: Housing Index: Means comparison between subgroup LC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

41
405

72.24
62.18

2.920449
.8869736

18.7
17.85

66.33755
60.43634

78.14245
63.92366

combined

446

63.1048

.8590931

18.14294

61.41641

64.79318

10.06

3.052171

3.923402

16.1966

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9991

[95% Conf. Interval]

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0018

3.2960
48.0615

Ha: diff > 0
Pr(T > t) = 0.0009

Figure A123: Housing Index: Means comparison between subgroup SR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

x
y

19
427

60.75
63.21

4.118012
.878824

17.95
18.16

52.09838
61.48263

69.40162
64.93737

combined

446

63.1052

.8588567

18.13795

61.41728

64.79312

-2.46

4.210743

-11.2474

6.327396

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.2828

[95% Conf. Interval]

t =
Welch's degrees of freedom =
Ha: diff != 0
Pr(|T| > |t|) = 0.5656

-0.5842
19.8611

Ha: diff > 0
Pr(T > t) = 0.7172

A42

Appendix F: T-test Statistic Details (continued)
Figure A124: Housing Index: Means comparison between subgroup MR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

46
400

51.2087
64.4737

2.08794
.902955

14.1611
18.0591

47.00337
62.69856

55.41403
66.24884

combined

446

63.10556

.8588902

18.13865

61.41758

64.79355

-13.265

2.274824

-17.80955

-8.720454

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.8312
63.9538

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A125: Housing Index: Means comparison between subgroup LR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

14
432

42.9643
63.7583

3.39224
.8623207

12.6926
17.923

35.63581
62.06342

50.29279
65.45318

combined

446

63.10557

.8588896

18.13864

61.41759

64.79356

-20.794

3.500127

-28.2544

-13.3336

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =
Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.9409
14.9988

Ha: diff > 0
Pr(T > t) = 1.0000

A43

Appendix F: T-test Statistic Details (continued)
Figure A126: Nation Wellness Index: Means comparison between subgroup SC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

32
414

68.6525
64.6331

1.773565
.5700057

10.0328
11.5979

65.03529
63.51263

72.26971
65.75357

combined

446

64.92149

.5459369

11.52948

63.84855

65.99442

4.0194

1.862912

.2485716

7.790228

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9813

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0373

2.1576
38.1353

Ha: diff > 0
Pr(T > t) = 0.0187

Figure A127: Nation Wellness Index: Means comparison between subgroup SM and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

65
381

71.0437
63.877

1.544828
.565955

12.4548
11.047

67.95755
62.7642

74.12985
64.9898

combined

446

64.92147

.5459374

11.5295

63.84854

65.99441

7.1667

1.645235

3.894184

10.43922

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.3560
82.642

Ha: diff > 0
Pr(T > t) = 0.0000

A44

Appendix F: T-test Statistic Details (continued)
Figure A128: Nation Wellness Index: Means comparison between subgroup SR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

19
427

73.1916
64.5535

3.296796
.5452532

14.3704
11.2671

66.26529
63.48178

80.11791
65.62522

combined

446

64.92149

.5459402

11.52955

63.84855

65.99443

8.6381

3.341581

1.646774

15.62943

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9909

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0181

2.5850
19.1084

Ha: diff > 0
Pr(T > t) = 0.0091

Figure A129: Nation Wellness Index: Means comparison between subgroup LC and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

41
405

68.2146
64.5881

1.878536
.568478

12.0285
11.4404

64.41794
63.47056

72.01126
65.70564

combined

446

64.92148

.5459381

11.52951

63.84854

65.99441

3.6265

1.962668

-.3197054

7.572705

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9646

t =
Welch's degrees of freedom =
Ha: diff != 0
Pr(|T| > |t|) = 0.0708

1.8477
48.0014

Ha: diff > 0
Pr(T > t) = 0.0354

A45

Appendix F: T-test Statistic Details (continued)
Figure A130: Nation Wellness Index: Means comparison between subgroup LM and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

34
412

58.7224
65.4331

1.731278
.5666776

10.095
11.5023

55.20009
64.31915

62.24471
66.54705

combined

446

64.92152

.5459392

11.52953

63.84858

65.99446

-6.7107

1.821661

-10.39

-3.031398

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0003

t =
Welch's degrees of freedom =
Ha: diff != 0
Pr(|T| > |t|) = 0.0007

-3.6838
40.8596

Ha: diff > 0
Pr(T > t) = 0.9997

Figure A131: Nation Wellness Index: Means comparison between subgroup LR and rest of
population
Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

x
y

14
432

58.4871
65.13

2.49777
.5553292

9.3458
11.5423

53.091
64.03851

63.8832
66.22149

combined

446

64.92148

.5459383

11.52951

63.84854

65.99442

-6.6429

2.558759

-12.11257

-1.173228

diff

diff = mean(x) - mean(y)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0103

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0207

-2.5961
14.5182

Ha: diff > 0
Pr(T > t) = 0.9897

A46

Appendix F: T-test Statistic Details (continued)
Figure A132: Language Index: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

10.735
30.0857

2.404284
1.198232

13.60069
24.38041

5.83143
27.73031

15.63857
32.44109

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

-19.3507

2.686325

-24.74858

-13.95282

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.2034
49.1776

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A133: Language Index: Means comparison between subgroup MC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

76
370

16.19855
31.26462

1.612808
1.306946

14.06013
25.13962

12.98567
28.69462

19.41143
33.83462

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

-15.06607

2.075875

-19.16052

-10.97162

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.2577
191.972

Ha: diff > 0
Pr(T > t) = 1.0000

A47

Appendix F: T-test Statistic Details (continued)
Figure A134: Language Index: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

26.54561
28.91514

3.824076
1.206455

24.48603
24.27943

18.81686
26.54342

34.27436
31.28685

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

-2.369526

4.009874

-10.42882

5.689768

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.2787

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.5573

-0.5909
48.7249

Ha: diff > 0
Pr(T > t) = 0.7213

Figure A135: Language Index: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

36.20737
28.36314

5.460357
1.174746

23.80114
24.27492

24.73558
26.05412

47.67915
30.67216

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

7.84423

5.585295

-3.810545

19.49901

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9122

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1756

1.4044
19.8921

Ha: diff > 0
Pr(T > t) = 0.0878

A48

Appendix F: T-test Statistic Details (continued)
Figure A136: Language Index: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

52.42087
25.9691

4.507738
1.095153

30.57297
21.90306

43.34182
23.81611

61.49992
28.12209

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

26.45177

4.638865

17.13748

35.76606

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

5.7022
50.6905

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A137: Language Index: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

64.48
27.53769

8.118582
1.115879

30.37695
23.19311

46.94087
25.34444

82.01913
29.73093

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

36.94232

8.194911

19.31383

54.5708

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9997

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0005

4.5080
13.5719

Ha: diff > 0
Pr(T > t) = 0.0003

A49

Appendix F: T-test Statistic Details (continued)
Figure A138: Income Index: Means comparison between subgroup MC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

66
237

32.62061
30.56392

.8110643
.7208535

6.589118
11.0974

31.0008
29.14379

34.24041
31.98405

combined

303

31.01191

.5923212

10.31047

29.84631

32.17751

2.056682

1.085106

-.0844359

4.1978

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9702

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0596

1.8954
180.584

Ha: diff > 0
Pr(T > t) = 0.0298

Figure A139: Income Index: Means comparison between subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
262

36.8378
30.10023

2.386803
.5561694

15.283
9.002388

32.0139
29.00508

41.66171
31.19538

combined

303

31.01191

.5923212

10.31047

29.84631

32.17751

6.737576

2.450745

1.800493

11.67466

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9957

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0086

2.7492
44.6629

Ha: diff > 0
Pr(T > t) = 0.0043

A50

Appendix F: T-test Statistic Details (continued)
Figure A140: Investment Asset Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.4356992
.2676756

.1907559
.0143097

1.079078
.2911584

.04665
.2395467

.8247484
.2958044

combined

446

.2797311

.0190396

.4020919

.2423124

.3171498

.1680237

.1912919

-.2219311

.5579784

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8068

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3864

0.8784
31.3724

Ha: diff > 0
Pr(T > t) = 0.1932

Figure A141: Investment Asset Capita: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

30014.86
13091.85

13741.75
2257.985

77735.07
45943.21

1988.383
8653.272

58041.35
17530.43

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

16923.02

13926.02

-11416.13

45262.16

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8835

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2330

1.2152
32.804

Ha: diff > 0
Pr(T > t) = 0.1165

A51

Appendix F: T-test Statistic Details (continued)
Figure A142: Investment Asset Capita: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

65
381

25819.62
12341.8

11452.72
1880.258

92334.8
36701.18

2940.179
8644.787

48699.06
16038.81

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

13477.82

11606.04

-9684.175

36639.82

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8752

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2496

1.1613
67.5971

Ha: diff > 0
Pr(T > t) = 0.1248

Figure A143: Investment Asset Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

25911.61
13789.65

17287.01
2300.532

75352.32
47538.14

-10407.05
9267.844

62230.27
18311.46

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

12121.96

17439.41

-24416.89

48660.81

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7522

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4955

0.6951
18.7144

Ha: diff > 0
Pr(T > t) = 0.2478

A52

Appendix F: T-test Statistic Details (continued)
Figure A144: Investment Asset Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

5311.607
15216.61

1162.179
2547.334

7441.574
51264.11

2962.757
10208.92

7660.458
20224.29

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

-9904.999

2799.923

-15408.77

-4401.226

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0002

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0004

-3.5376
415.677

Ha: diff > 0
Pr(T > t) = 0.9998

Figure A145: Investment Asset Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

7355.74
14879.63

2432.881
2500.991

14186.01
50764.58

2406.006
9963.297

12305.47
19795.96

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

-7523.887

3489.107

-14425.08

-622.6923

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0164

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0328

-2.1564
133.26

Ha: diff > 0
Pr(T > t) = 0.9836

A53

Appendix F: T-test Statistic Details (continued)
Figure A146: Investment Asset Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

11345.74
14401.99

6790.623
2384.957

25408.18
49570.41

-3324.512
9714.399

26015.98
19089.59

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

-3056.257

7197.262

-18246.71

12134.19

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.3382

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.6764

-0.4246
16.9188

Ha: diff > 0
Pr(T > t) = 0.6618

Figure A147: Investment Asset Capita: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

7256.246
15116.79

2137.806
2571.745

14499.3
51434.9

2950.484
10060.92

11562.01
20172.65

combined

446

14306.06

2319.281

48980.24

9747.952

18864.16

-7860.539

3344.261

-14450.78

-1270.3

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0098

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0196

-2.3505
223.992

Ha: diff > 0
Pr(T > t) = 0.9902

A54

Appendix F: T-test Statistic Details (continued)
Figure A148: Gross Business Sales Ratio: Means comparison between subgroup SR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.0264094
.1023521

.016541
.0080127

.0721004
.1655739

-.0083419
.0866028

.0611607
.1181014

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

-.0759427

.0183795

-.1135671

-.0383184

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

-4.1319
28.4093

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A149: Gross Business Sales Ratio: Means comparison between subgroup MR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.06063
.1035429

.0185001
.0083369

.1254737
.1667372

.0233689
.0871532

.0978911
.1199326

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

-.0429129

.0202918

-.0834303

-.0023956

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0191

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0382

-2.1148
65.7001

Ha: diff > 0
Pr(T > t) = 0.9809

A55

Appendix F: T-test Statistic Details (continued)
Figure A150: Gross Business Sales Ratio: Means comparison between subgroup LR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.0533109
.1006014

.0244718
.0079399

.0915652
.1650271

.0004428
.0849957

.106179
.116207

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

-.0472905

.0257276

-.1017446

.0071637

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0422

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0843

-1.8381
16.3172

Ha: diff > 0
Pr(T > t) = 0.9578

Figure A151: Gross Business Sales Ratio: Means comparison between subgroup SC and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.1563646
.094692

.0412105
.0076779

.2331218
.1562225

.0723152
.0795993

.240414
.1097846

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

.0616727

.0419196

-.0235817

.146927

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9247

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1506

1.4712
33.3273

Ha: diff > 0
Pr(T > t) = 0.0753

A56

Appendix F: T-test Statistic Details (continued)
Figure A152: Gross Business Sales Capita: Means comparison between subgroup SR and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

1360.871
4572.533

733.139
536.8954

3195.679
11094.39

-179.3969
3517.24

2901.139
5627.827

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

-3211.662

908.7076

-5042.372

-1380.953

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0005

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0010

-3.5343
44.5783

Ha: diff > 0
Pr(T > t) = 0.9995

Figure A153: Gross Business Sales Capita: Means comparison between subgroup MR and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

3246.714
4572.449

1165.887
559.2673

7907.432
11185.35

898.4961
3472.97

5594.931
5671.928

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

-1325.735

1293.087

-3905.587

1254.117

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1544

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3088

-1.0252
68.6798

Ha: diff > 0
Pr(T > t) = 0.8456

A57

Appendix F: T-test Statistic Details (continued)
Figure A154: Gross Business Sales Capita: Means comparison between subgroup LR and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

961.321
4548.31

458.3978
531.4767

1715.168
11046.54

-28.98733
3503.701

1951.629
5592.918

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

-3586.989

701.8519

-4984.975

-2189.003

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.1107
75.5771

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A155: Gross Business Sales Capita: Means comparison between subgroup SC and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

11674.24
3876.214

4276.091
438.3943

24189.23
8920.005

2953.09
3014.452

20395.38
4737.977

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

7798.022

4298.505

-961.0301

16557.07

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9604

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0791

1.8141
31.6971

Ha: diff > 0
Pr(T > t) = 0.0396

A58

Appendix F: T-test Statistic Details (continued)
Figure A156: Business and Economic Development Expense Ratio: Means comparison
between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.0718825
.136386

.0232751
.0077994

.1014537
.1611665

.0229833
.1210559

.1207816
.151716

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

-.0645035

.0245471

-.1153165

-.0136905

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0076

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0151

-2.6277
22.7292

Ha: diff > 0
Pr(T > t) = 0.9924

Figure A157: Business and Economic Development Expense Ratio: Means comparison
between subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.0841174
.1393329

.0187409
.0081008

.1271069
.1620154

.0463713
.1234074

.1218635
.1552585

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

-.0552156

.0204167

-.0960035

-.0144276

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0044

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0088

-2.7044
63.934

Ha: diff > 0
Pr(T > t) = 0.9956

A59

Appendix F: T-test Statistic Details (continued)
Figure A158: Business and Economic Development Expense Ratio: Means comparison
between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.0837305
.1352554

.0241537
.0077503

.0903747
.1610866

.0315497
.1200224

.1359113
.1504885

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

-.0515249

.0253666

-.1052349

.0021851

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0295

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0589

-2.0312
16.2411

Ha: diff > 0
Pr(T > t) = 0.9705

Figure A159: Business and Economic Development Expense Ratio: Means comparison
between subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.1964823
.1287805

.0399297
.0074963

.2258767
.1525281

.1150451
.1140448

.2779195
.1435163

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

.0677018

.0406273

-.0149209

.1503244

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9475

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1050

1.6664
33.3637

Ha: diff > 0
Pr(T > t) = 0.0525

A60

Appendix F: T-test Statistic Details (continued)
Figure A160: Business and Economic Development Expense Capita: Means comparison
between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

4292.062
5293.269

2372.179
473.5806

10340.09
9786.059

-691.6998
4362.424

9275.824
6224.115

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

-1001.207

2418.989

-6053.328

4050.915

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.3417

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.6834

-0.4139
19.6244

Ha: diff > 0
Pr(T > t) = 0.6583

Figure A161: Business and Economic Development Expense Capita: Means comparison
between subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

3776.776
5420.109

1051.137
502.7552

7129.161
10055.1

1659.676
4431.728

5893.875
6408.489

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

-1643.333

1165.184

-3968.094

681.4283

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0815

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1630

-1.4104
68.5312

Ha: diff > 0
Pr(T > t) = 0.9185

A61

Appendix F: T-test Statistic Details (continued)
Figure A162: Business and Economic Development Expense Capita: Means comparison
between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

1697.316
5365.77

480.0865
477.8491

1796.319
9931.906

660.1522
4426.566

2734.48
6304.974

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

-3668.454

677.3646

-5025.654

-2311.254

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.4158
55.4887

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A163: Business and Economic Development Expense Capita: Means comparison
between subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

11735.74
4749.351

3579.405
408.8423

20248.17
8318.71

4435.497
3945.68

19035.99
5553.022

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

6986.39

3602.678

-353.2336

14326.01

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9693

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0614

1.9392
31.8662

Ha: diff > 0
Pr(T > t) = 0.0307

A62

Appendix F: T-test Statistic Details (continued)
Figure A164: GBE Asset Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

25
346

.1355627
.3966674

.0473499
.0443226

.2367495
.8244487

.0378373
.3094908

.2332881
.483844

combined

371

.3790727

.0415897

.8010747

.2972909

.4608546

-.2611047

.0648576

-.390069

-.1321404

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

-4.0258
84.5465

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A165: GBE Asset Ratio: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

16
355

.2137594
.3865235

.1181187
.0431171

.4724748
.8123885

-.0380046
.3017256

.4655235
.4713214

combined

371

.3790727

.0415897

.8010747

.2972909

.4608546

-.172764

.1257422

-.4352159

.0896878

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0924

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1848

-1.3740
19.8138

Ha: diff > 0
Pr(T > t) = 0.9076

A63

Appendix F: T-test Statistic Details (continued)
Figure A166: GBE Asset Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

36
335

6764.761
15310.16

1910.094
3416.466

11460.56
62531.6

2887.064
8589.657

10642.46
22030.66

combined

371

14480.96

3092.722

59570.03

8399.44

20562.47

-8545.399

3914.167

-16247.62

-843.1834

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0149

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0298

-2.1832
304.731

Ha: diff > 0
Pr(T > t) = 0.9851

Figure A167: GBE Asset Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

27
344

6890.434
15076.72

1993.826
3330.137

10360.23
61764.85

2792.065
8526.663

10988.8
21626.79

combined

371

14480.96

3092.722

59570.03

8399.44

20562.47

-8186.29

3881.386

-15831.52

-541.0637

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0180

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0360

-2.1091
244.459

Ha: diff > 0
Pr(T > t) = 0.9820

A64

Appendix F: T-test Statistic Details (continued)
Figure A168: GBE Asset Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
360

7629.11
14690.32

2765.562
3185.686

9172.332
60444.14

1467.053
8425.368

13791.17
20955.27

combined

371

14480.96

3092.722

59570.03

8399.44

20562.47

-7061.209

4218.641

-15501.56

1379.137

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0497

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0994

-1.6738
59.3813

Ha: diff > 0
Pr(T > t) = 0.9503

Figure A169: GBE Asset Capita: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

54
317

31387.18
11601.03

14244.26
2670.189

104673.5
47541.37

2816.81
6347.436

59957.56
16854.63

combined

371

14480.96

3092.722

59570.03

8399.44

20562.47

19786.15

14492.38

-9235.205

48807.51

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9112

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1775

1.3653
56.9208

Ha: diff > 0
Pr(T > t) = 0.0888

A65

Appendix F: T-test Statistic Details (continued)
Figure A170: GBE Asset Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

16
355

50022.31
12879.09

44625.26
2544.92

178501
47949.97

-45094.17
7874.029

145138.8
17884.16

combined

371

14480.96

3092.722

59570.03

8399.44

20562.47

37143.22

44697.77

-58067.03

132353.5

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7905

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4189

0.8310
15.1107

Ha: diff > 0
Pr(T > t) = 0.2095

Figure A171: GBE Equity Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

30
378

.1518326
.0929782

.0600267
.0194761

.3287798
.3786592

.0290642
.0546827

.274601
.1312736

combined

408

.0973057

.0185737

.3751703

.0607933

.133818

.0588544

.0631073

-.0691533

.1868622

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8214

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3573

0.9326
35.8362

Ha: diff > 0
Pr(T > t) = 0.1786

A66

Appendix F: T-test Statistic Details (continued)
Figure A172: GBE Equity Ratio: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

57
351

.1639204
.0864879

.1032685
.0136685

.7796599
.2560784

-.0429512
.0596053

.370792
.1133706

combined

408

.0973057

.0185737

.3751703

.0607933

.133818

.0774325

.1041691

-.1310811

.285946

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7699

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4603

0.7433
58.0469

Ha: diff > 0
Pr(T > t) = 0.2301

Figure A173: GBE Equity Ratio: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

18
390

.0819841
.0980128

.073139
.0191516

.3103023
.3782148

-.0723256
.0603591

.2362938
.1356665

combined

408

.0973057

.0185737

.3751703

.0607933

.133818

-.0160287

.0756048

-.173897

.1418396

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.4171

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.8343

-0.2120
19.6899

Ha: diff > 0
Pr(T > t) = 0.5829

A67

Appendix F: T-test Statistic Details (continued)
Figure A174: GBE Equity Capita: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

30
378

13271.46
6623.906

5527.627
2036.95

30276.06
39602.83

1966.198
2618.699

24576.73
10629.11

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

6647.558

5890.995

-5278.853

18573.97

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8669

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2662

1.1284
37.9307

Ha: diff > 0
Pr(T > t) = 0.1331

Figure A175: GBE Equity Capita: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

57
351

10232.54
6606.055

8111.387
1823.356

61239.63
34160.56

-6016.516
3019.943

26481.61
10192.17

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

3626.49

8313.798

-12992.65

20245.63

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.6679

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.6642

0.4362
61.9827

Ha: diff > 0
Pr(T > t) = 0.3321

A68

Appendix F: T-test Statistic Details (continued)
Figure A176: GBE Equity Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

18
390

33530.92
5893.394

32072.8
1385.39

136073.4
27359.26

-34136.77
3169.605

101198.6
8617.183

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

27637.53

32102.71

-40071.82

95346.88

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7994

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4012

0.8609
17.071

Ha: diff > 0
Pr(T > t) = 0.2006

Figure A177: GBE Equity Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

38
370

3612.439
7472.183

1413.953
2123.705

8716.194
40850.29

747.497
3296.1

6477.38
11648.27

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

-3859.744

2551.35

-8883.039

1163.551

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0658

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1315

-1.5128
267.343

Ha: diff > 0
Pr(T > t) = 0.9342

A69

Appendix F: T-test Statistic Details (continued)
Figure A178: GBE Equity Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

33
375

2739.419
7497.545

826.7614
2098.608

4749.383
40639.38

1055.361
3370.994

4423.477
11624.1

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

-4758.126

2255.591

-9192.618

-323.6344

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0178

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0355

-2.1095
394.223

Ha: diff > 0
Pr(T > t) = 0.9822

Figure A179: GBE Equity Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

12
396

4242.973
7199.658

2332.909
1988.124

8081.434
39563.16

-891.7249
3291.031

9377.671
11108.29

combined

408

7112.697

1930.857

39001.4

3316.999

10908.39

-2956.685

3065.143

-9172.593

3259.223

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1706

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3412

-0.9646
36.0819

Ha: diff > 0
Pr(T > t) = 0.8294

A70

Appendix F: T-test Statistic Details (continued)
Figure A180: GBE Revenue Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

25
346

.1124287
.2675616

.0396851
.0352198

.1984254
.6551263

.0305227
.198289

.1943347
.3368341

combined

371

.2571079

.0330099

.6358156

.1921973

.3220184

-.1551329

.0530598

-.2607798

-.049486

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0023

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0045

-2.9237
77.3952

Ha: diff > 0
Pr(T > t) = 0.9977

Figure A181: GBE Revenue Ratio: Means comparison between subgroup MM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

103
268

.3471978
.2224837

.0822325
.0328837

.8345683
.5383289

.1840901
.1577395

.5103055
.287228

combined

371

.2571079

.0330099

.6358156

.1921973

.3220184

.124714

.0885636

-.0504195

.2998476

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9193

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1613

1.4082
136.551

Ha: diff > 0
Pr(T > t) = 0.0807

A71

Appendix F: T-test Statistic Details (continued)
Figure A182: GBE Revenue Ratio: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

30
341

.115631
.2695545

.0394201
.0356767

.2159127
.6588125

.0350078
.1993797

.1962541
.3397294

combined

371

.2571079

.0330099

.6358156

.1921973

.3220184

-.1539236

.0531674

-.2594784

-.0483687

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0024

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0047

-2.8951
94.7015

Ha: diff > 0
Pr(T > t) = 0.9976

Figure A183: GBE Revenue Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

36
335

4217.01
11062.1

1698.196
3196.39

10189.17
58503.55

769.4889
4774.505

7664.53
17349.69

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

-6845.089

3619.5

-13966.24

276.0572

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0298

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0595

-1.8912
318.537

Ha: diff > 0
Pr(T > t) = 0.9702

A72

Appendix F: T-test Statistic Details (continued)
Figure A184: GBE Revenue Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

27
344

5120.918
10812.07

1075.229
3117.45

5587.055
57820.08

2910.753
4680.34

7331.083
16943.79

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

-5691.148

3297.667

-12175.91

793.6159

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0426

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0852

-1.7258
365.828

Ha: diff > 0
Pr(T > t) = 0.9574

Figure A185: GBE Revenue Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
360

3878.963
10597.07

1298.328
2979.944

4306.066
56540.46

986.1084
4736.735

6771.817
16457.41

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

-6718.112

3250.495

-13120.82

-315.3996

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0199

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0398

-2.0668
243.231

Ha: diff > 0
Pr(T > t) = 0.9801

A73

Appendix F: T-test Statistic Details (continued)
Figure A186: GBE Revenue Capita: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

25
346

4620.752
10815.31

1717.683
3097.995

8588.414
57626.03

1075.629
4721.974

8165.875
16908.64

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

-6194.556

3542.316

-13169.8

780.6873

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0408

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0815

-1.7487
260.304

Ha: diff > 0
Pr(T > t) = 0.9592

Figure A187: GBE Revenue Capita: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

54
317

23341.9
8192.91

14939.15
2231.916

109779.9
39738.13

-6622.245
3801.617

53306.05
12584.2

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

15148.99

15104.96

-15116.16

45414.15

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8399

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3203

1.0029
55.4777

Ha: diff > 0
Pr(T > t) = 0.1601

A74

Appendix F: T-test Statistic Details (continued)
Figure A188: GBE Revenue Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

16
355

42744.05
8940.03

41288.72
2396.401

165154.9
45151.66

-45260.78
4227.057

130748.9
13653

combined

371

10397.89

2892.311

55709.84

4710.456

16085.31

33804.02

41358.21

-54290.68

121898.7

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7868

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4264

0.8173
15.1147

Ha: diff > 0
Pr(T > t) = 0.2132

Figure A189: GBE Expense Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

25
346

.1582051
.2974694

.0911869
.0455918

.4559345
.848057

-.0299955
.2077964

.3464056
.3871423

combined

371

.288085

.0429791

.8278358

.203571

.3725989

-.1392643

.1019493

-.3455733

.0670447

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0899

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1799

-1.3660
38.4345

Ha: diff > 0
Pr(T > t) = 0.9101

A75

Appendix F: T-test Statistic Details (continued)
Figure A190: GBE Expense Ratio: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

30
341

.1010901
.3045361

.0350572
.0465615

.1920161
.8598135

.0293901
.2129512

.1727901
.396121

combined

371

.288085

.0429791

.8278358

.203571

.3725989

-.203446

.0582836

-.3184415

-.0884506

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0003

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0006

-3.4906
182.728

Ha: diff > 0
Pr(T > t) = 0.9997

Figure A191: GBE Expense Ratio: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

16
355

.4021925
.2829421

.3596211
.0420594

1.438484
.7924595

-.3643217
.2002244

1.168707
.3656598

combined

371

.288085

.0429791

.8278358

.203571

.3725989

.1192504

.3620723

-.6504593

.8889601

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.6268

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.7463

0.3294
15.4681

Ha: diff > 0
Pr(T > t) = 0.3732

A76

Appendix F: T-test Statistic Details (continued)
Figure A192: GBE Expense Ratio: Means comparison between subgroup MM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

103
268

.4129561
.2400935

.1199519
.0374163

1.217379
.6125318

.1750321
.1664249

.6508801
.3137621

combined

371

.288085

.0429791

.8278358

.203571

.3725989

.1728626

.125652

-.0758626

.4215878

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9143

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1714

1.3757
122.766

Ha: diff > 0
Pr(T > t) = 0.0857

Figure A193: GBE Expense Capita: Means comparison between subgroup SM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

54
317

23758.26
6909.584

15163.75
1425.092

111430.4
25373.04

-6656.373
4105.716

54172.89
9713.451

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

16848.68

15230.57

-13687.1

47384.45

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8632

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2735

1.1062
53.9751

Ha: diff > 0
Pr(T > t) = 0.1368

A77

Appendix F: T-test Statistic Details (continued)
Figure A194: GBE Expense Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

16
355

25172.07
8649.383

23900.05
2415.686

95600.21
45515

-25769.68
3898.483

76113.83
13400.28

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

16522.69

24021.82

-34577.4

67622.78

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7491

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.5018

0.6878
15.349

Ha: diff > 0
Pr(T > t) = 0.2509

Figure A195: GBE Expense Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

36
335

4505.512
9883.838

1708.515
2788.464

10251.09
51037.27

1037.042
4398.673

7973.982
15369

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

-5378.326

3270.253

-11816.05

1059.4

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0506

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1012

-1.6446
276.806

Ha: diff > 0
Pr(T > t) = 0.9494

A78

Appendix F: T-test Statistic Details (continued)
Figure A196: GBE Expense Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

27
344

5226.947
9686.502

1151.685
2720.376

5984.332
50455.46

2859.624
4335.782

7594.27
15037.22

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

-4459.555

2954.12

-10270.1

1350.994

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0660

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1321

-1.5096
341.709

Ha: diff > 0
Pr(T > t) = 0.9340

Figure A197: GBE Expense Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
360

3709.527
9534.665

1311.723
2600.608

4350.493
49343.07

786.8259
4420.325

6632.227
14649

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

-5825.138

2912.693

-11570.36

-79.91365

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0235

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0469

-1.9999
190.747

Ha: diff > 0
Pr(T > t) = 0.9765

A79

Appendix F: T-test Statistic Details (continued)
Figure A198: GBE Expense Capita: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

30
341

3823.091
9849.242

1785.194
2740.657

9777.91
50609.48

171.9594
4458.463

7474.223
15240.02

combined

371

9361.952

2524.193

48619.39

4398.389

14325.51

-6026.151

3270.798

-12470.66

418.3557

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0334

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0667

-1.8424
230.342

Ha: diff > 0
Pr(T > t) = 0.9666

Figure A199: Trust Fund Asset Ratio: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

.1597136
.09615

.0420499
.0094065

.2692509
.1893015

.0747275
.0776583

.2446997
.1146417

combined

446

.1019933

.0093975

.198464

.0835242

.1204624

.0635636

.0430892

-.0232605

.1503878

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9264

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1472

1.4752
44.2966

Ha: diff > 0
Pr(T > t) = 0.0736

A80

Appendix F: T-test Statistic Details (continued)
Figure A200: Trust Fund Asset Ratio: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.0186583
.104694

.0100136
.0096696

.0374674
.2009779

-.0029748
.0856886

.0402913
.1236993

combined

446

.1019933

.0093975

.198464

.0835242

.1204624

-.0860357

.0139202

-.1139638

-.0581075

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-6.1806
52.3785

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A201: Trust Fund Asset Capita: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

2109.798
6464.294

973.0852
1758.075

4241.58
36328.83

65.42184
3008.712

4154.174
9919.877

combined

446

6278.789

1684.096

35565.95

2969.019

9588.559

-4354.496

2009.409

-8312.761

-396.232

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0156

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0312

-2.1671
240.784

Ha: diff > 0
Pr(T > t) = 0.9844

A81

Appendix F: T-test Statistic Details (continued)
Figure A202: Trust Fund Asset Capita: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

20669.29
4623.882

14573.33
840.1155

98841.13
16802.31

-8682.904
2972.276

50021.48
6275.488

combined

446

6278.789

1684.096

35565.95

2969.019

9588.559

16045.41

14597.52

-13349.92

45440.73

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8613

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2775

1.0992
45.3128

Ha: diff > 0
Pr(T > t) = 0.1387

Figure A203: Trust Fund Asset Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

254.1911
6474.031

205.4264
1737.915

768.6353
36121.88

-189.6057
3058.188

697.9879
9889.873

combined

446

6278.789

1684.096

35565.95

2969.019

9588.559

-6219.84

1750.013

-9659.249

-2780.43

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0002

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0004

-3.5542
440.69

Ha: diff > 0
Pr(T > t) = 0.9998

A82

Appendix F: T-test Statistic Details (continued)
Figure A204: Trust Fund Revenue Ratio: Means comparison between subgroup SR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.001651
.0284883

.0009486
.00358

.0041348
.0739776

-.0003418
.0214516

.0036439
.035525

combined

446

.027345

.0034372

.072589

.0205899

.0341002

-.0268373

.0037036

-.0341161

-.0195585

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.2463
441.433

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A205: Trust Fund Revenue Ratio: Means comparison between subgroup MR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.013187
.0289732

.0073295
.0037323

.0497113
.0746469

-.0015755
.0216357

.0279494
.0363107

combined

446

.027345

.0034372

.072589

.0205899

.0341002

-.0157863

.0082251

-.0321829

.0006104

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0295

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0589

-1.9193
71.9521

Ha: diff > 0
Pr(T > t) = 0.9705

A83

Appendix F: T-test Statistic Details (continued)
Figure A206: Trust Fund Revenue Ratio: Means comparison between subgroup LR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.0028405
.0281392

.0025672
.0035412

.0096056
.0736029

-.0027056
.0211789

.0083866
.0350994

combined

446

.027345

.0034372

.072589

.0205899

.0341002

-.0252987

.0043739

-.0339664

-.016631

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.7841
110.306

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A207: Trust Fund Revenue Ratio: Means comparison between subgroup SC and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.003839
.0291619

.002634
.0036827

.0149002
.0749309

-.0015331
.0219228

.0092111
.036401

combined

446

.027345

.0034372

.072589

.0205899

.0341002

-.0253229

.0045277

-.0342463

-.0163995

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.5929
218.966

Ha: diff > 0
Pr(T > t) = 1.0000

A84

Appendix F: T-test Statistic Details (continued)
Figure A208: Trust Fund Revenue Capita: Means comparison between subgroup SR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

45.56408
904.6196

20.43993
166.1169

89.09558
3432.637

2.621385
578.1087

88.50677
1231.13

combined

446

868.023

159.247

3363.092

555.0534

1180.993

-859.0555

167.3697

-1188.005

-530.1056

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.1327
436.905

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A209: Trust Fund Revenue Capita: Means comparison between subgroup MR and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

382.3685
923.8733

199.6736
175.9061

1354.252
3518.122

-19.79472
578.0547

784.5316
1269.692

combined

446

868.023

159.247

3363.092

555.0534

1180.993

-541.5048

266.1061

-1067.729

-15.28063

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0219

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0438

-2.0349
136.487

Ha: diff > 0
Pr(T > t) = 0.9781

A85

Appendix F: T-test Statistic Details (continued)
Figure A210: Trust Fund Revenue Capita: Means comparison between subgroup LR and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

37.59149
894.9352

31.96765
164.2479

119.612
3413.828

-31.47042
572.1087

106.6534
1217.762

combined

446

868.023

159.247

3363.092

555.0534

1180.993

-857.3437

167.3299

-1186.197

-528.4905

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.1237
445.874

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A211: Trust Fund Revenue Capita: Means comparison between subgroup SC and rest
of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

89.28381
928.2154

63.43475
171.146

358.8411
3482.306

-40.09221
591.7896

218.6598
1264.641

combined

446

868.023

159.247

3363.092

555.0534

1180.993

-838.9316

182.5237

-1197.677

-480.1863

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.5963
431.879

Ha: diff > 0
Pr(T > t) = 1.0000

A86

Appendix F: T-test Statistic Details (continued)
Figure A212: Tangible Capital Asset (TCA) Capita: Means comparison between subgroup
SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

28
379

50660.07
44152.64

7488.865
1955.662

39627.35
38072.68

35294.18
40307.3

66025.95
47997.98

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

6507.424

7740.007

-9276.81

22291.66

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7965

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4069

0.8408
31.0785

Ha: diff > 0
Pr(T > t) = 0.2035

Figure A213: TCA Capita: Means comparison between subgroup SM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

56
351

65208.58
41312.4

5933.779
1925.349

44404.34
36071.4

53317.02
37525.69

77100.14
45099.11

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

23896.18

6238.326

11446.15

36346.2

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9999

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

3.8305
67.5093

Ha: diff > 0
Pr(T > t) = 0.0001

A87

Appendix F: T-test Statistic Details (continued)
Figure A214: TCA Capita: Means comparison between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

15
392

93627.86
42724.27

25829.42
1643.271

100036.9
32535.1

38229.26
39493.52

149026.5
45955.03

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

50903.59

25881.64

-4559.226

106366.4

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9654

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0692

1.9668
14.1298

Ha: diff > 0
Pr(T > t) = 0.0346

Figure A215: TCA Capita: Means comparison between subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

40
367

27962.46
46413.72

3113.416
2049.156

19690.97
39256.19

21664.98
42384.12

34259.94
50443.32

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

-18451.26

3727.251

-25868.03

-11034.48

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.9504
80.4905

Ha: diff > 0
Pr(T > t) = 1.0000

A88

Appendix F: T-test Statistic Details (continued)
Figure A216: TCA Capita: Means comparison between subgroup LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

33
374

25542.56
46281.89

1947.39
2029.123

11186.9
39241.37

21575.86
42291.94

29509.26
50271.85

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

-20739.33

2812.413

-26302.71

-15175.96

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.3742
131.624

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A217: TCA Capita: Means comparison between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
396

25671.91
45126.12

2728.969
1936.459

9050.965
38535.04

19591.39
41319.06

31752.44
48933.17

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

-19454.2

3346.213

-26346.97

-12561.43

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.8138
24.9207

Ha: diff > 0
Pr(T > t) = 1.0000

A89

Appendix F: T-test Statistic Details (continued)
Figure A218: Gross Cash Outflow From Capital Ratio: Means comparison between subgroup
SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

15
391

.7452518
.5250584

.0573468
.015574

.2221032
.3079562

.6222551
.4944389

.8682484
.5556779

combined

406

.5331936

.0152773

.3078298

.5031608

.5632264

.2201934

.0594239

.0944955

.3458912

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9991

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0018

3.7055
16.4431

Ha: diff > 0
Pr(T > t) = 0.0009

Figure A219: Gross Cash Outflow From Capital Capita: Means comparison between
subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

40
367

-3251.128
-4338.933

826.0412
356.6267

5224.343
6831.984

-4921.954
-5040.228

-1580.302
-3637.639

combined

407

-4232.024

331.7896

6693.603

-4884.264

-3579.784

1087.805

899.737

-714.953

2890.564

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8841

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2318

1.2090
55.4859

Ha: diff > 0
Pr(T > t) = 0.1159

A90

Appendix F: T-test Statistic Details (continued)
Figure A220: Gross Cash Outflow From Capital Capita: Means comparison between
subgroup LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

33
374

-2422.758
-4391.665

482.8035
357.4761

2773.495
6913.26

-3406.197
-5094.586

-1439.32
-3688.743

combined

407

-4232.024

331.7896

6693.603

-4884.264

-3579.784

1968.906

600.7399

772.7631

3165.049

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9992

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0016

3.2775
77.3355

Ha: diff > 0
Pr(T > t) = 0.0008

Figure A221: Gross Cash Outflow From Capital Capita: Means comparison between
subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
396

-2910.931
-4268.721

1457.894
338.6328

4835.289
6738.708

-6159.323
-4934.469

337.4601
-3602.972

combined

407

-4232.024

331.7896

6693.603

-4884.264

-3579.784

1357.789

1496.706

-1924.818

4640.396

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8084

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3832

0.9072
11.3286

Ha: diff > 0
Pr(T > t) = 0.1916

A91

Appendix F: T-test Statistic Details (continued)
Figure A222: Gross Cash Outflow From Capital Capita: Means comparison between
subgroup SM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

56
351

-5948.245
-3958.21

1147.819
336.873

8589.488
6311.313

-8248.525
-4620.76

-3647.965
-3295.66

combined

407

-4232.024

331.7896

6693.603

-4884.264

-3579.784

-1990.035

1196.232

-4378.963

398.893

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0505

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1010

-1.6636
65.1617

Ha: diff > 0
Pr(T > t) = 0.9495

Figure A223: Gross Cash Outflow From Capital Capita: Means comparison between
subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

15
392

-7927.362
-4090.62

3298.896
319.9741

12776.57
6335.164

-15002.79
-4719.705

-851.9327
-3461.535

combined

407

-4232.024

331.7896

6693.603

-4884.264

-3579.784

-3836.741

3314.378

-10931.3

3257.817

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1330

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2660

-1.1576
14.3024

Ha: diff > 0
Pr(T > t) = 0.8670

A92

Appendix F: T-test Statistic Details (continued)
Figure A224: Net Cash Flow From Capital Capita: Means comparison between subgroup LM
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

33
374

-2382.55
-4296.435

481.4553
359.0613

2765.75
6943.915

-3363.243
-5002.473

-1401.858
-3590.397

combined

407

-4141.255

333.1602

6721.254

-4796.19

-3486.321

1913.885

600.6032

718.198

3109.571

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9990

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0021

3.1866
78.0926

Ha: diff > 0
Pr(T > t) = 0.0010

Figure A225: Net Cash Flow From Capital Capita: Means comparison between subgroup LR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

11
396

-2910.931
-4175.431

1457.894
340.076

4835.289
6767.427

-6159.323
-4844.016

337.4601
-3506.846

combined

407

-4141.255

333.1602

6721.254

-4796.19

-3486.321

1264.5

1497.033

-2018.427

4547.426

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7921

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4158

0.8447
11.3402

Ha: diff > 0
Pr(T > t) = 0.2079

A93

Appendix F: T-test Statistic Details (continued)
Figure A226: Net Cash Flow From Capital Capita: Means comparison between subgroup SM
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

56
351

-5850.709
-3868.522

1148.442
338.6527

8594.152
6344.656

-8152.238
-4534.572

-3549.18
-3202.472

combined

407

-4141.255

333.1602

6721.254

-4796.19

-3486.321

-1982.187

1197.332

-4373.243

408.8686

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0513

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1026

-1.6555
65.2614

Ha: diff > 0
Pr(T > t) = 0.9487

Figure A227: Net Cash Flow From Capital Capita: Means comparison between subgroup SR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

15
392

-7900.438
-3997.409

3299.957
321.4157

12780.68
6363.706

-14978.14
-4629.328

-822.7342
-3365.49

combined

407

-4141.255

333.1602

6721.254

-4796.19

-3486.321

-3903.028

3315.573

-11000.03

3193.972

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1292

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2583

-1.1772
14.305

Ha: diff > 0
Pr(T > t) = 0.8708

A94

Appendix F: T-test Statistic Details (continued)
Figure A228: Net Cash Flow From Operating Capita: Means comparison between subgroup
SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

9058.596
4088.692

2205.335
419.4167

12475.26
8533.867

4560.785
3264.234

13556.41
4913.15

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

4969.904

2244.864

404.9073

9534.901

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9831

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0338

2.2139
33.4267

Ha: diff > 0
Pr(T > t) = 0.0169

Figure A229: Net Cash Flow From Operating Capita: Means comparison between subgroup
SM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

65
381

9559.747
3572.73

1958.717
349.504

15791.68
6822.046

5646.76
2885.526

13472.73
4259.934

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

5987.018

1989.655

2016.995

9957.041

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9982

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0037

3.0091
68.2574

Ha: diff > 0
Pr(T > t) = 0.0018

A95

Appendix F: T-test Statistic Details (continued)
Figure A230: Net Cash Flow From Operating Capita: Means comparison between subgroup
SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

6495.937
4354.03

3081.999
421.413

13434.12
8708.068

20.89847
3525.722

12970.98
5182.337

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

2141.908

3110.676

-4374.585

8658.4

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.7502

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.4995

0.6886
18.7545

Ha: diff > 0
Pr(T > t) = 0.2498

Figure A231: Net Cash Flow From Operating Capita: Means comparison between subgroup
LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

2176.913
4674.914

456.3303
462.9135

2921.94
9315.955

1254.635
3764.894

3099.191
5584.934

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

-2498.001

650.0202

-3782.118

-1213.884

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.8430
153.845

Ha: diff > 0
Pr(T > t) = 0.9999

A96

Appendix F: T-test Statistic Details (continued)
Figure A232: Net Cash Flow From Operating Capita: Means comparison between subgroup
LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

359.3008
4782.469

675.5992
451.4377

3939.386
9163.185

-1015.216
3895.054

1733.818
5669.884

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

-4423.168

812.5456

-6043.733

-2802.604

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.4436
70.0156

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A233: Net Cash Flow From Operating Capita: Means comparison between subgroup
LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

2621.103
4504.394

1325.708
435.22

4960.347
9045.878

-242.9164
3648.976

5485.122
5359.811

combined

446

4445.277

423.7364

8948.767

3612.504

5278.05

-1883.291

1395.321

-4835.384

1068.802

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0977

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1954

-1.3497
16.4001

Ha: diff > 0
Pr(T > t) = 0.9023

A97

Appendix F: T-test Statistic Details (continued)
Figure A234: Gross Cash Inflows From Investing Ratio: Means comparison between
subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

25
353

.4549919
.2925757

.0946097
.0205214

.4730484
.3855614

.2597271
.2522157

.6502567
.3329356

combined

378

.3033175

.0202288

.3932924

.2635421

.3430928

.1624162

.0968097

-.0363966

.3612291

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9474

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1052

1.6777
26.4994

Ha: diff > 0
Pr(T > t) = 0.0526

Figure A235: Gross Cash Inflows From Investing Ratio: Means comparison between
subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

39
339

.3856417
.2938465

.0677159
.0211435

.4228856
.3892931

.2485581
.2522571

.5227254
.3354359

combined

378

.3033175

.0202288

.3932924

.2635421

.3430928

.0917952

.07094

-.0509892

.2345796

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8989

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2021

1.2940
46.1258

Ha: diff > 0
Pr(T > t) = 0.1011

A98

Appendix F: T-test Statistic Details (continued)
Figure A236: Gross Cash Inflows From Investing Capita: Means comparison between
subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

429.4663
2401.282

381.4575
588.0565

1662.735
12151.59

-371.9462
1245.428

1230.879
3557.135

combined

446

2317.281

563.5155

11900.72

1209.798

3424.763

-1971.815

700.9424

-3355.02

-588.6106

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0027

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0055

-2.8131
178.407

Ha: diff > 0
Pr(T > t) = 0.9973

Figure A237: Gross Cash Inflows From Investing Capita: Means comparison between
subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

1079.993
2459.569

389.4632
626.4412

2641.468
12528.82

295.5737
1228.031

1864.412
3691.106

combined

446

2317.281

563.5155

11900.72

1209.798

3424.763

-1379.576

737.6382

-2830.533

71.38085

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0312

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0623

-1.8703
336.908

Ha: diff > 0
Pr(T > t) = 0.9688

A99

Appendix F: T-test Statistic Details (continued)
Figure A238: Gross Cash Inflows From Investing Capita: Means comparison between
subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

176.2821
2386.665

117.9978
581.4812

441.5073
12085.86

-78.63663
1243.773

431.2008
3529.556

combined

446

2317.281

563.5155

11900.72

1209.798

3424.763

-2210.383

593.3328

-3376.462

-1044.304

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.7254
445.491

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A239: Gross Cash Inflows From Investing Capita: Means comparison between
subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

5476.19
2073.114

3350.684
549.0463

18954.33
11171.44

-1357.574
993.8398

12309.95
3152.387

combined

446

2317.281

563.5155

11900.72

1209.798

3424.763

3403.077

3395.369

-3506.503

10312.66

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8382

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3236

1.0023
32.7939

Ha: diff > 0
Pr(T > t) = 0.1618

A100

Appendix F: T-test Statistic Details (continued)
Figure A240: Gross Cash Outflows From Investing Ratio: Means comparison between
subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
426

.0445929
.1471079

.0257092
.0122825

.1120636
.2535083

-.00942
.1229658

.0986059
.1712499

combined

445

.1427308

.011847

.2499119

.1194477

.1660139

-.1025149

.0284925

-.1608699

-.0441599

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0006

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0012

-3.5980
28.0982

Ha: diff > 0
Pr(T > t) = 0.9994

Figure A241: Gross Cash Outflows From Investing Ratio: Means comparison between
subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
399

.0578944
.1525115

.0217372
.0128895

.1474291
.257467

.0141134
.1271715

.1016754
.1778514

combined

445

.1427308

.011847

.2499119

.1194477

.1660139

-.0946171

.0252714

-.1448843

-.0443499

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0002

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

-3.7440
82.6326

Ha: diff > 0
Pr(T > t) = 0.9998

A101

Appendix F: T-test Statistic Details (continued)
Figure A242: Gross Cash Outflows From Investing Ratio: Means comparison between
subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
431

.0386012
.1461132

.0181872
.0121843

.0680502
.2529524

-.0006898
.1221651

.0778922
.1700614

combined

445

.1427308

.011847

.2499119

.1194477

.1660139

-.107512

.0218913

-.1522671

-.062757

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.9112
29.2674

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A243: Gross Cash Outflows From Investing Ratio: Means comparison between
subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
413

.2255234
.1363159

.0617041
.0118061

.3490512
.2399291

.0996771
.1131081

.3513698
.1595237

combined

445

.1427308

.011847

.2499119

.1194477

.1660139

.0892075

.0628234

-.0385414

.2169565

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9176

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1649

1.4200
33.4566

Ha: diff > 0
Pr(T > t) = 0.0824

A102

Appendix F: T-test Statistic Details (continued)
Figure A244: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

-374.96
-3087.432

203.458
634.3613

886.853
13108.43

-802.4095
-4334.3

52.48946
-1840.565

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

2712.472

666.1903

1403.012

4021.933

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

4.0716
422.464

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A245: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

-1133.383
-3183.306

936.0401
668.673

6348.533
13373.46

-3018.665
-4497.868

751.8984
-1868.743

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

2049.923

1150.345

-231.7731

4331.618

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9611

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0777

1.7820
102.034

Ha: diff > 0
Pr(T > t) = 0.0389

A103

Appendix F: T-test Statistic Details (continued)
Figure A246: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

-191.6574
-3061.978

111.4237
627.1563

416.9095
13035.2

-432.3737
-4294.644

49.059
-1829.313

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

2870.321

636.9775

1618.47

4122.172

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.5062
445.885

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A247: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

-1214.673
-3149.769

461.3753
667.3056

2954.243
13429.27

-2147.147
-4461.593

-282.199
-1837.944

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

1935.095

811.273

337.9852

3532.206

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9911

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0177

2.3853
274.392

Ha: diff > 0
Pr(T > t) = 0.0089

A104

Appendix F: T-test Statistic Details (continued)
Figure A248: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

-1079.248
-3128.067

428.1236
656.6335

2496.368
13328.21

-1950.272
-4418.846

-208.2242
-1837.288

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

2048.818

783.8733

505.4267

3592.21

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9953

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0095

2.6137
265.772

Ha: diff > 0
Pr(T > t) = 0.0047

Figure A249: Gross Cash Outflows From Investing Capita: Means comparison between
subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

-8805.247
-2520.99

4220.5
564.6016

23874.75
11487.94

-17413.01
-3630.841

-197.4816
-1411.139

combined

446

-2971.879

607.9202

12838.49

-4166.63

-1777.127

-6284.257

4258.097

-14955.7

2387.187

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0749

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1497

-1.4758
32.1908

Ha: diff > 0
Pr(T > t) = 0.9251

A105

Appendix F: T-test Statistic Details (continued)
Figure A250: Earned Revenue Ratio: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.3191751
.1895742

.048195
.009479

.2726318
.1928685

.2208809
.1709411

.4174694
.2082072

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

.129601

.0491183

.0297366

.2294653

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9937

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0125

2.6385
33.5982

Ha: diff > 0
Pr(T > t) = 0.0063

Figure A251: Earned Revenue Ratio: Means comparison between subgroup MC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

76
370

.2801405
.1821801

.0266453
.009949

.2322881
.1913729

.2270604
.1626162

.3332206
.2017439

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

.0979604

.0284421

.0415148

.154406

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9996

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0008

3.4442
97.5654

Ha: diff > 0
Pr(T > t) = 0.0004

A106

Appendix F: T-test Statistic Details (continued)
Figure A252: Earned Revenue Ratio: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

.2489387
.1938045

.0334826
.0099547

.2143931
.2003353

.1812679
.1742349

.3166095
.2133741

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

.0551342

.0349311

-.0151103

.1253788

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9395

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1211

1.5784
47.7131

Ha: diff > 0
Pr(T > t) = 0.0605

Figure A253: Earned Revenue Ratio: Means comparison between subgroup SR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.0789281
.20421

.0489879
.0096843

.2135331
.2001157

-.0239915
.1851751

.1818478
.2232449

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

-.1252819

.0499359

-.2295855

-.0209782

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0105

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0210

-2.5089
19.5922

Ha: diff > 0
Pr(T > t) = 0.9895

A107

Appendix F: T-test Statistic Details (continued)
Figure A254: Earned Revenue Ratio: Means comparison between subgroup MR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.1270616
.2071312

.0241997
.0102259

.1641306
.2045181

.0783208
.1870278

.1758024
.2272346

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

-.0800696

.0262716

-.1325685

-.0275707

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0017

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0034

-3.0478
63.04

Ha: diff > 0
Pr(T > t) = 0.9983

Figure A255: Earned Revenue Ratio: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.1144611
.2016085

.0363167
.0097838

.1358846
.2033532

.0360037
.1823785

.1929185
.2208384

combined

446

.1988729

.0095671

.2020456

.1800705

.2176753

-.0871474

.0376115

-.1671986

-.0070961

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0174

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0348

-2.3170
15.2532

Ha: diff > 0
Pr(T > t) = 0.9826

A108

Appendix F: T-test Statistic Details (continued)
Figure A256: Earned Revenue Capita: Means comparison between subgroup LC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

6506.204
8131.306

1487.059
747.0836

9521.822
15034.77

3500.746
6662.649

9511.662
9599.962

combined

446

7981.913

692.0243

14614.66

6621.871

9341.955

-1625.102

1664.175

-4950.233

1700.029

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1663

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3325

-0.9765
63.4455

Ha: diff > 0
Pr(T > t) = 0.8337

Figure A257: Earned Revenue Capita: Means comparison between subgroup LM and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

3744.118
8331.634

619.7482
744.8865

3613.722
15119.55

2483.231
6867.371

5005.005
9795.896

combined

446

7981.913

692.0243

14614.66

6621.871

9341.955

-4587.516

968.9911

-6499.873

-2675.158

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.7343
175.731

Ha: diff > 0
Pr(T > t) = 1.0000

A109

Appendix F: T-test Statistic Details (continued)
Figure A258: Earned Revenue Capita: Means comparison between subgroup LR and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

2455.218
8161.019

1064.904
712.0378

3984.505
14799.43

154.633
6761.52

4755.803
9560.517

combined

446

7981.913

692.0243

14614.66

6621.871

9341.955

-5705.801

1281.022

-8325.027

-3086.575

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

-4.4541
29.1946

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A259: Earned Revenue Capita: Means comparison between subgroup SC and rest of
population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

20437.85
7019.135

4937.55
619.0011

27931
12594.81

10367.65
5802.349

30508.05
8235.921

combined

446

7981.913

692.0243

14614.66

6621.871

9341.955

13418.71

4976.2

3283.081

23554.34

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9945

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0111

2.6966
32.0448

Ha: diff > 0
Pr(T > t) = 0.0055

A110

Appendix F: T-test Statistic Details (continued)
Figure A260: Earned and Other Revenue Ratio: Means comparison between subgroup SC
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

.4275272
.3298052

.0449843
.010759

.2544698
.2189138

.3357811
.3086559

.5192734
.3509545

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

.097722

.0462531

.0038111

.1916329

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9791

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0419

2.1128
34.8738

Ha: diff > 0
Pr(T > t) = 0.0209

Figure A261: Earned and Other Revenue Ratio: Means comparison between subgroup MC
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

76
370

.4199893
.3197326

.0267897
.0112758

.2335469
.2168937

.3666215
.2975597

.473357
.3419054

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

.1002567

.0290659

.0426179

.1578955

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9996

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0008

3.4493
104.008

Ha: diff > 0
Pr(T > t) = 0.0004

A111

Appendix F: T-test Statistic Details (continued)
Figure A262: Earned and Other Revenue Ratio: Means comparison between subgroup LC
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

.3833561
.3321053

.0351527
.0110446

.2250872
.222269

.3123098
.3103931

.4544024
.3538174

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

.0512508

.036847

-.0228094

.125311

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9147

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1706

1.3909
48.6503

Ha: diff > 0
Pr(T > t) = 0.0853

Figure A263: Earned and Other Revenue Ratio: Means comparison between subgroup SR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.2767485
.3394895

.0575025
.0107141

.2506474
.2213962

.1559403
.3184304

.3975567
.3605486

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

-.062741

.0584921

-.1849909

.0595089

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.1483

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2966

-1.0726
19.4116

Ha: diff > 0
Pr(T > t) = 0.8517

A112

Appendix F: T-test Statistic Details (continued)
Figure A264: Earned and Other Revenue Ratio: Means comparison between subgroup MR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.2586841
.3458019

.0306043
.0111471

.2075686
.2229414

.1970439
.3238876

.3203244
.3677162

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

-.0871177

.0325712

-.1523119

-.0219236

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0048

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0097

-2.6747
58.1736

Ha: diff > 0
Pr(T > t) = 0.9952

Figure A265: Earned and Other Revenue Ratio: Means comparison between subgroup LR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.2143025
.340787

.0408651
.0107614

.1529034
.2236716

.1260187
.3196357

.3025862
.3619384

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

-.1264846

.0422583

-.2164786

-.0364905

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0045

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0090

-2.9931
15.1497

Ha: diff > 0
Pr(T > t) = 0.9955

A113

Appendix F: T-test Statistic Details (continued)
Figure A266: Earned and Other Revenue Capita: Means comparison between subgroup SC
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

23975.76
12460.09

5030.026
1032.011

28454.12
20998.32

13716.96
10431.44

34234.56
14488.74

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

11515.67

5134.803

1078.584

21952.76

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9842

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0316

2.2427
33.8317

Ha: diff > 0
Pr(T > t) = 0.0158

Figure A267: Earned and Other Revenue Capita: Means comparison between subgroup SM
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

65
381

18895.22
12329.43

2680.072
1111.505

21607.43
21695.71

13541.16
10143.96

24249.28
14514.9

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

6565.794

2901.419

800.0128

12331.58

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9870

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0261

2.2630
88.1956

Ha: diff > 0
Pr(T > t) = 0.0130

A114

Appendix F: T-test Statistic Details (continued)
Figure A268: Earned and Other Revenue Capita: Means comparison between subgroup SR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

21481.57
12921.67

9387.32
993.849

40918.38
20536.87

1759.544
10968.21

41203.6
14875.12

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

8559.905

9439.783

-11237.67

28357.48

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8119

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3762

0.9068
18.4507

Ha: diff > 0
Pr(T > t) = 0.1881

Figure A269: Earned and Other Revenue Capita: Means comparison between subgroup LC
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

9017.795
13718.45

1610.894
1122.23

10314.75
22584.45

5762.057
11512.31

12273.53
15924.59

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

-4700.653

1963.258

-8601.934

-799.3707

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0094

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0188

-2.3943
88.4556

Ha: diff > 0
Pr(T > t) = 0.9906

A115

Appendix F: T-test Statistic Details (continued)
Figure A270: Earned and Other Revenue Capita: Means comparison between subgroup LM
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

9096.181
13632.11

2849.102
1090.553

16612.98
22135.82

3299.639
11488.36

14892.72
15775.87

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

-4535.932

3050.687

-10684.49

1612.625

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0721

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1442

-1.4869
43.9237

Ha: diff > 0
Pr(T > t) = 0.9279

Figure A271: Earned and Other Revenue Capita: Means comparison between subgroup LR
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

4972.859
13555.74

1319.568
1061.571

4937.371
22064.33

2122.106
11469.24

7823.612
15642.24

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

-8582.884

1693.574

-12011

-5154.768

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.0679
38.1166

Ha: diff > 0
Pr(T > t) = 1.0000

A116

Appendix F: T-test Statistic Details (continued)
Figure A272: Federal & Provincial Government Revenue Ratio: Means comparison between
subgroup MR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

46
400

.6694749
.5537656

.0340236
.0112453

.2307591
.2249069

.6009479
.531658

.7380019
.5758731

combined

446

.5656997

.0107957

.227992

.5444828

.5869167

.1157093

.0358338

.0439184

.1875002

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9990

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0021

3.2291
55.7488

Ha: diff > 0
Pr(T > t) = 0.0010

Figure A273: Federal & Provincial Government Revenue Ratio: Means comparison between
subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.7590109
.559435

.0438628
.0109294

.1641195
.2271634

.6642512
.5379534

.8537707
.5809166

combined

446

.5656997

.0107957

.227992

.5444828

.5869167

.1995759

.0452039

.10318

.2959719

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9997

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0005

4.4150
14.9182

Ha: diff > 0
Pr(T > t) = 0.0003

A117

Appendix F: T-test Statistic Details (continued)
Figure A274: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup SC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

32
414

19334.75
16164.13

2240.945
593.6364

12676.7
12078.71

14764.31
14997.2

23905.18
17331.06

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

3170.616

2318.241

-1532.001

7873.234

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9100

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.1799

1.3677
35.7792

Ha: diff > 0
Pr(T > t) = 0.0900

Figure A275: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup SM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

65
381

22629.55
15327.4

2107.241
551.918

16989.12
10773.01

18419.85
14242.21

26839.25
16412.6

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

7302.147

2178.32

2961.065

11643.23

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9994

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0013

3.3522
73.3045

Ha: diff > 0
Pr(T > t) = 0.0006

A118

Appendix F: T-test Statistic Details (continued)
Figure A276: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

28378.34
15858.25

6111.195
523.817

26638.08
10824.14

15539.2
14828.66

41217.49
16887.84

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

12520.09

6133.603

-351.2595

25391.44

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9720

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0559

2.0412
18.2949

Ha: diff > 0
Pr(T > t) = 0.0280

Figure A277: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup LC and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

41
405

11818.42
16854.58

1821.97
601.2387

11666.3
12099.69

8136.082
15672.64

15500.76
18036.53

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

-5036.165

1918.609

-8890.61

-1181.72

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0057

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0115

-2.6249
49.582

Ha: diff > 0
Pr(T > t) = 0.9943

A119

Appendix F: T-test Statistic Details (continued)
Figure A278: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

12755.61
16691.68

677.3071
617.3393

3949.345
12530.62

11377.61
15478.14

14133.6
17905.21

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

-3936.072

916.4348

-5752.449

-2119.696

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.2950
108.827

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A279: Federal & Provincial Government Revenue Capita: Means comparison
between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

14408.32
16455.89

961.14
592.2561

3596.257
12309.81

12331.91
15291.82

16484.74
17619.96

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

-2047.569

1128.963

-4366.426

271.2873

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0406

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0811

-1.8137
26.4119

Ha: diff > 0
Pr(T > t) = 0.9594

A120

Appendix F: T-test Statistic Details (continued)
Figure A280: Tribal Government & Other First Nation Entity Revenue Ratio: Means
comparison between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

.1128173
.0652678

.0459803
.0050355

.2004234
.1040541

.0162163
.0553702

.2094183
.0751653

combined

446

.0672934

.0052048

.1099192

.0570643

.0775225

.0475495

.0462552

-.0494475

.1445466

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8414

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.3172

1.0280
18.4825

Ha: diff > 0
Pr(T > t) = 0.1586

Figure A281: Tribal Government & Other First Nation Entity Revenue Ratio: Means
comparison between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

.0238461
.0687014

.0089041
.0053528

.0333162
.111256

.0046099
.0581806

.0430823
.0792223

combined

446

.0672934

.0052048

.1099192

.0570643

.0775225

-.0448553

.0103892

-.0662238

-.0234868

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-4.3175
25.6757

Ha: diff > 0
Pr(T > t) = 0.9999

A121

Appendix F: T-test Statistic Details (continued)
Figure A282: Tribal Government & Other First Nation Entity Revenue Capita: Means
comparison between subgroup SR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

19
427

6178.18
1778.781

3749.455
151.2696

16343.5
3125.832

-1699.133
1481.454

14055.49
2076.109

combined

446

1966.2

216.729

4577.037

1540.26

2392.139

4399.398

3752.505

-3482.285

12281.08

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.8719

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.2563

1.1724
18.0652

Ha: diff > 0
Pr(T > t) = 0.1281

Figure A283: Tribal Government & Other First Nation Entity Revenue Capita: Means
comparison between subgroup LM and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

34
412

793.7466
2062.955

216.366
233.3348

1261.62
4736.179

353.5466
1604.277

1233.947
2521.634

combined

446

1966.2

216.729

4577.037

1540.26

2392.139

-1269.209

318.2128

-1898.147

-640.2709

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

-3.9886
144.911

Ha: diff > 0
Pr(T > t) = 0.9999

A122

Appendix F: T-test Statistic Details (continued)
Figure A284: Tribal Government & Other First Nation Entity Revenue Capita: Means
comparison between subgroup LR and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

yes
no

14
432

441.3934
2015.615

153.0446
223.3058

572.6404
4641.324

110.7606
1576.711

772.0261
2454.519

combined

446

1966.2

216.729

4577.037

1540.26

2392.139

-1574.221

270.7178

-2110.009

-1038.434

diff

diff = mean(yes) - mean(no)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.8150
124.926

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A285: Business and Economic Development Expenses Capita: Means comparison
between small population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

7911.201
4315.381

1279.19
427.061

13777.29
7757.948

5377.373
3475.266

10445.03
5155.496

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

3595.82

1348.594

929.8883

6261.752

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9957

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0086

2.6663
141.903

Ha: diff > 0
Pr(T > t) = 0.0043

A123

Appendix F: T-test Statistic Details (continued)
Figure A286: Business and Economic Development Expenses Capita: Means comparison
between large population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

89
357

2820.369
5856.477

562.884
558.2075

5310.237
10547.02

1701.756
4758.678

3938.983
6954.276

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

-3036.108

792.7383

-4596.524

-1475.692

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.8299
282.816

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A287: Tangible Capital Asset Capita: Means comparison between small population
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

99
308

65399.8
37914.78

5643.372
1545.464

56150.84
27122.79

54200.71
34873.74

76598.89
40955.83

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

27485.02

5851.163

15893.2

39076.84

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.6974
113.352

Ha: diff > 0
Pr(T > t) = 0.0000

A124

Appendix F: T-test Statistic Details (continued)
Figure A288: Tangible Capital Asset Capita: Means comparison between large population
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

84
323

26711.83
49252.44

1696.454
2273.295

15548.26
40856.11

23337.66
44780.06

30086.01
53724.83

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

-22540.61

2836.516

-28118.94

-16962.27

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.9466
357.898

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A289: Earned and Other Revenue Capita: Means comparison between small
population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

20720.38
10673.14

2534.373
1037.183

27296.03
18841.36

15700.27
8632.797

25740.48
12713.49

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

10047.23

2738.393

4638.094

15456.37

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9998

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

3.6690
155.907

Ha: diff > 0
Pr(T > t) = 0.0002

A125

Appendix F: T-test Statistic Details (continued)
Figure A290: Earned and Other Revenue Capita: Means comparison between large
population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

89
357

8411.458
14501.63

1331.099
1237.477

12557.56
23381.45

5766.179
12067.94

11056.74
16935.31

combined

446

13286.33

1031.429

21782.46

11259.25

15313.4

-6090.169

1817.464

-9668.906

-2511.433

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0005

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0009

-3.3509
261.345

Ha: diff > 0
Pr(T > t) = 0.9995

Figure A291: Federal and Provincial Revenue Capita: Means comparison between small
population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

22662.25
14187.4

1669.951
451.8722

17985.92
8208.665

19354.4
13298.47

25970.1
15076.32

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

8474.856

1730.007

5052.851

11896.86

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.8987
132.506

Ha: diff > 0
Pr(T > t) = 0.0000

A126

Appendix F: T-test Statistic Details (continued)
Figure A292: Federal and Provincial Revenue Capita: Means comparison between large
population communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

89
357

12583.85
17340.9

889.6298
673.9387

8392.751
12733.7

10815.89
16015.49

14351.8
18666.3

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

-4757.049

1116.08

-6957.587

-2556.511

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-4.2623
203.892

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A293: Education Index: Means comparison between small population communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

50.17422
43.31509

1.324639
.7837214

14.2668
14.23701

47.55037
41.77335

52.79808
44.85683

combined

446

45.09908

.6886828

14.54409

43.74561

46.45256

6.859133

1.539119

3.824368

9.893898

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.4565
202.395

Ha: diff > 0
Pr(T > t) = 0.0000

A127

Appendix F: T-test Statistic Details (continued)
Figure A294: Workforce Index: Means comparison between small population communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

62.30776
53.70403

1.28144
.6740948

13.80154
12.24554

59.76947
52.37795

64.84605
55.03011

combined

446

55.94177

.6252669

13.20483

54.71293

57.17061

8.603729

1.447927

5.747022

11.46044

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

5.9421
183.686

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A295: Workforce Index: Means comparison between large population communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

89
357

48.72213
57.74162

1.244446
.6851974

11.74008
12.94642

46.24906
56.39408

51.19521
59.08917

combined

446

55.94177

.6252669

13.20483

54.71293

57.17061

-9.01949

1.420613

-11.82689

-6.212089

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-6.3490
147.39

Ha: diff > 0
Pr(T > t) = 1.0000

A128

Appendix F: T-test Statistic Details (continued)
Figure A296: Language Index: Means comparison between small population communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

20.07
31.72994

1.668806
1.402396

17.9736
25.4758

16.76442
28.97114

23.37558
34.48873

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

-11.65994

2.179824

-15.95037

-7.369506

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-5.3490
287.557

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A297: Language Index: Means comparison between large population communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

89
357

38.70483
26.20244

3.035053
1.18699

28.63264
22.42751

32.6733
23.86804

44.73636
28.53683

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

12.50239

3.25891

6.048258

18.95653

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9999

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

3.8364
116.938

Ha: diff > 0
Pr(T > t) = 0.0001

A129

Appendix F: T-test Statistic Details (continued)
Figure A298: Housing Index: Means comparison between small population communities and
rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

67.84302
61.4403

1.785914
.9613682

19.23488
17.46412

64.30546
59.5491

71.38057
63.33151

combined

446

63.10558

.8588904

18.13866

61.4176

64.79357

6.402714

2.02823

2.401564

10.40386

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9991

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0019

3.1568
187.021

Ha: diff > 0
Pr(T > t) = 0.0009

Figure A299: Nation Wellness Index: Means comparison between small population
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

116
330

70.73586
62.87767

1.129702
.5824229

12.16727
10.58024

68.49814
61.73192

72.97359
64.02341

combined

446

64.9215

.5459382

11.52951

63.84856

65.99444

7.858196

1.271001

5.350301

10.36609

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

6.1827
180.895

Ha: diff > 0
Pr(T > t) = 0.0000

A130

Appendix F: T-test Statistic Details (continued)
Figure A300: Gross Business Sales Ratio: Means comparison between geographically close
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

.1305004
.0833723

.0164508
.0080443

.2008075
.1386333

.0979917
.067541

.1630092
.0992036

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

.0471282

.0183123

.0110399

.0832164

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9946

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0107

2.5736
221.868

Ha: diff > 0
Pr(T > t) = 0.0054

Figure A301: Gross Business Sales Ratio: Means comparison between geographically remote
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

.0511026
.1094524

.0122644
.0089373

.1090084
.1712137

.0266861
.0918775

.0755192
.1270273

combined

446

.0991169

.0077359

.1633715

.0839135

.1143203

-.0583497

.0151753

-.0883003

-.0283992

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.8450
174.692

Ha: diff > 0
Pr(T > t) = 0.9999

A131

Appendix F: T-test Statistic Details (continued)
Figure A302: Gross Business Sales Capita: Means comparison between geographically close
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

6835.78
3231.64

1285.714
413.9452

15694.13
7133.802

4295.053
2416.991

9376.508
4046.289

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

3604.14

1350.707

938.8558

6269.425

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9958

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0083

2.6683
179.726

Ha: diff > 0
Pr(T > t) = 0.0042

Figure A303: Gross Business Sales Capita: Means comparison between geographically
remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

2388.15
4876.47

711.37
605.7375

6322.795
11604.26

971.9214
3685.307

3804.379
6067.633

combined

446

4435.714

515.8149

10893.35

3421.978

5449.449

-2488.32

934.326

-4330.097

-646.5429

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0042

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0083

-2.6632
211.651

Ha: diff > 0
Pr(T > t) = 0.9958

A132

Appendix F: T-test Statistic Details (continued)
Figure A304: Business and Economic Development Expense Ratio: Means comparison
between geographically close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

.1574323
.1217009

.0155218
.0081829

.1894682
.1410211

.1267592
.1055969

.1881053
.1378049

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

.0357314

.0175467

.0011615

.0703012

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9786

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0428

2.0364
233.796

Ha: diff > 0
Pr(T > t) = 0.0214

Figure A305: Business and Economic Development Expense Ratio: Means comparison
between geographically remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

.0811063
.144946

.0128697
.0086458

.1143884
.1656302

.0554846
.1279443

.1067279
.1619477

combined

446

.1336381

.0075543

.1595369

.1187915

.1484846

-.0638397

.0155042

-.0944599

-.0332196

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

-4.1176
159.359

Ha: diff > 0
Pr(T > t) = 1.0000

A133

Appendix F: T-test Statistic Details (continued)
Figure A306: Business and Economic Development Expense Capita: Means comparison
between geographically close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

6601.698
4572.801

1063.089
445.0002

12976.65
7668.995

4500.905
3697.036

8702.492
5448.567

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

2028.897

1152.468

-243.5126

4301.306

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9601

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0798

1.7605
202.018

Ha: diff > 0
Pr(T > t) = 0.0399

Figure A307: Business and Economic Development Expense Capita: Means comparison
between geographically remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

3532.193
5620.523

836.7609
532.8751

7437.294
10208.42

1866.33
4572.641

5198.056
6668.404

combined

446

5250.617

464.0525

9800.191

4338.61

6162.623

-2088.329

992.0306

-4048.425

-128.2331

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0185

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0369

-2.1051
150.591

Ha: diff > 0
Pr(T > t) = 0.9815

A134

Appendix F: T-test Statistic Details (continued)
Figure A308: Tangible Capital Asset Capita: Means comparison between geographically
close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

140
267

37313.76
48421

2523.125
2534.459

29854.02
41413.4

32325.09
43430.85

42302.42
53411.15

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

-11107.24

3576.261

-18139.68

-4074.809

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0010

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0020

-3.1058
368.589

Ha: diff > 0
Pr(T > t) = 0.9990

Figure A309: Tangible Capital Asset Capita: Means comparison between geographically
remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

64
343

58521.24
42002.84

7590.655
1713.43

60725.24
31733.17

43352.53
38632.65

73689.95
45373.03

combined

407

44600.33

1891.862

38166.89

40881.26

48319.4

16518.4

7781.638

997.4677

32039.34

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9813

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0373

2.1227
69.7575

Ha: diff > 0
Pr(T > t) = 0.0187

A135

Appendix F: T-test Statistic Details (continued)
Figure A310: Earned and Other Revenue Ratio: Means comparison between geographically
close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

.4115279
.2993353

.0192492
.012002

.2349663
.2068383

.3734891
.2757153

.4495666
.3229553

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

.1121926

.0226843

.0675296

.1568556

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.9458
266.846

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A311: Earned and Other Revenue Ratio: Means comparison between geographically
remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

.2551636
.3543932

.0235118
.011588

.2089773
.2219936

.2083553
.3316058

.301972
.3771806

combined

446

.3368167

.0105484

.2227679

.3160859

.3575475

-.0992296

.0262123

-.151128

-.0473311

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.7856
120.021

Ha: diff > 0
Pr(T > t) = 0.9999

A136

Appendix F: T-test Statistic Details (continued)
Figure A312: Federal and Provincial Revenue Ratio: Means comparison between
geographically close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

.5091485
.5940705

.0181068
.013143

.2210222
.2265023

.4733672
.5682049

.5449299
.6199361

combined

446

.5656997

.0107957

.227992

.5444828

.5869167

-.084922

.022374

-.128949

-.0408949

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0001

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0002

-3.7956
304.827

Ha: diff > 0
Pr(T > t) = 0.9999

Figure A313: Federal and Provincial Revenue Ratio: Means comparison between
geographically remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

.6707453
.5430877

.0266111
.0114819

.2365244
.2199619

.6177667
.5205089

.7237239
.5656665

combined

446

.5656997

.0107957

.227992

.5444828

.5869167

.1276576

.0289825

.0702195

.1850957

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

4.4046
109.718

Ha: diff > 0
Pr(T > t) = 0.0000

A137

Appendix F: T-test Statistic Details (continued)
Figure A314: Federal and Provincial Revenue Capita: Means comparison between
geographically close communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

13720.03
17731.91

804.3512
751.6689

9818.358
12954.03

12130.53
16252.62

15309.52
19211.2

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

-4011.884

1100.903

-6176.538

-1847.23

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0002

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0003

-3.6442
378.369

Ha: diff > 0
Pr(T > t) = 0.9998

Figure A315: Federal and Provincial Revenue Capita: Means comparison between
geographically remote communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

20014.3
15611.8

1778.226
577.4553

15805.22
11062.45

16474.12
14476.26

23554.48
16747.35

combined

446

16391.62

574.6314

12135.48

15262.29

17520.95

4402.496

1869.637

691.0613

8113.931

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9897

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0206

2.3547
95.5265

Ha: diff > 0
Pr(T > t) = 0.0103

A138

Appendix F: T-test Statistic Details (continued)
Figure A316: Education Index: Means comparison between geographically close
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

51.73537
41.76976

.9725718
.8493425

11.87175
14.6373

49.81345
40.09825

53.65729
43.44128

combined

446

45.09908

.6886828

14.54409

43.74561

46.45256

9.965605

1.291231

7.426265

12.50494

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

7.7179
358.497

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A317: Education Index: Means comparison between geographically remote
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

32.35456
47.84245

1.642157
.6789604

14.59581
13.00701

29.08527
46.5073

35.62384
49.17761

combined

446

45.09908

.6886828

14.54409

43.74561

46.45256

-15.4879

1.776982

-19.01056

-11.96523

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-8.7158
106.997

Ha: diff > 0
Pr(T > t) = 1.0000

A139

Appendix F: T-test Statistic Details (continued)
Figure A318: Language Index: Means comparison between geographically close
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

17.87235
34.12801

1.497789
1.457126

18.28284
25.11165

14.91253
31.26037

20.83216
36.99565

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

-16.25566

2.089638

-20.36404

-12.14729

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-7.7792
389.689

Ha: diff > 0
Pr(T > t) = 1.0000

Figure A319: Language Index: Means comparison between geographically remote
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

50.65848
23.96997

3.395392
1.039

30.17891
19.90438

43.89877
21.92681

57.41819
26.01313

combined

446

28.69731

1.149714

24.28048

26.43777

30.95685

26.68851

3.550804

19.63781

33.7392

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

7.5162
93.5015

Ha: diff > 0
Pr(T > t) = 0.0000

A140

Appendix F: T-test Statistic Details (continued)
Figure A320: Housing Index: Means comparison between geographically close communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

70.22369
59.53455

1.368177
1.032911

16.70073
17.80086

67.52001
57.50177

72.92738
61.56732

combined

446

63.10558

.8588904

18.13866

61.4176

64.79357

10.68915

1.714296

7.316258

14.06203

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 1.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

6.2353
315.756

Ha: diff > 0
Pr(T > t) = 0.0000

Figure A321: Housing Index: Means comparison between geographically remote
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

79
367

52.04253
65.487

1.780893
.9257528

15.82892
17.73487

48.49705
63.66654

55.58802
67.30746

combined

446

63.10558

.8588904

18.13866

61.4176

64.79357

-13.44447

2.007136

-17.41682

-9.472118

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.0000

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0000

-6.6983
125.059

Ha: diff > 0
Pr(T > t) = 1.0000

A141

Appendix F: T-test Statistic Details (continued)
Figure A322: Income Index: Means comparison between geographically close communities
and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

107
196

34.23654
29.25153

1.054612
.6818596

10.90899
9.546034

32.14567
27.90676

36.32741
30.5963

combined

303

31.01191

.5923212

10.31047

29.84631

32.17751

4.985011

1.255842

2.508328

7.461694

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9999

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0001

3.9695
196.181

Ha: diff > 0
Pr(T > t) = 0.0001

Figure A323: Nation Wellness Index: Means comparison between geographically close
communities and rest of population
Group

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf. Interval]

Yes
No

149
297

66.47174
64.14377

.8073121
.7094155

9.8545
12.22585

64.8764
62.74763

68.06709
65.53991

combined

446

64.9215

.5459382

11.52951

63.84856

65.99444

2.327974

1.07472

.2144625

4.441485

diff

diff = mean(Yes) - mean(No)
Ho: diff = 0
Ha: diff < 0
Pr(T < t) = 0.9845

t =
Welch's degrees of freedom =

Ha: diff != 0
Pr(|T| > |t|) = 0.0310

2.1661
360.343

Ha: diff > 0
Pr(T > t) = 0.0155

A142

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography
This appendix provides detailed analysis of the mean trends present within Tables 16 –
29 by: population subcategory and geography subcategory respectively. For general
discussions about this analysis and the median value trends, refer Chapter 3, subheadings
Descriptive Statistics by Population and Descriptive Statistics by Geographic Remoteness.
The general trends in the descriptive statistics by population include:


Business and economic development expenses capita are higher for small
populations, and lower for large populations:
o T-test for small population (M = $7,911, SD = $13,777) and rest of population
(M = $4,315, SD = $7,758); t(142) = 2.67, p = 0.01. The difference is
statistically significant (Appendix F, Figure A285).
o T-test for large populations (M = $2,820, SD = $5,310) and rest of population
(M = $5,856, SD = $10,547); t(283) = -3.83, p = 0.00. The difference is
statistically significant (Appendix F, Figure A286).



Tangible capital assets capita is higher for small populations, and lower for large
populations:
o T-test for small populations (M = $65,400, SD = $56,151) and rest of
population (M = $37,915, SD = $27,123); t(113) = 4.70, p = 0.00. The
difference is statistically significant (Appendix F, Figure A287).
o T-test for large populations (M = $26,712, SD = $15,548) and rest of
population (M = $49,252, SD = $40,856); t(358) = -7.95, p = 0.00. The
difference is statistically significant (Appendix F, Figure A288).



Earned and other revenue capita is higher for small populations, and lower for large
populations:
o T-test for small populations (M = $20,720, SD = $27,296) and rest of
population (M = $10,673, SD = $18,841); t(156) = 3.67, p = 0.00. The
difference is statistically significant (Appendix F, Figure A289).

A143

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography (continued)
o T-test for large populations (M = $8,411, SD = $12,558) and rest of
population (M = $14,502, SD = $23,381); t(261) = -3.35, p = 0.00. The
difference is statistically significant (Appendix F, Figure A290).


Federal and provincial revenue capita is higher for small populations, and lower for
large populations:
o T-test for small populations (M = $22,662, SD = $17,986) and rest of
population (M = $14,187, SD = $8,209); t(133) = 4.90, p = 0.00. The
difference is statistically significant (Appendix F, Figure A291).
o T-test for large populations (M = $12,584, SD = $8,393) and rest of
population (M = $17,341, SD = $12,734); t(204) = -4.26, p = 0.00. The
difference is statistically significant (Appendix F, Figure A292).



Education index is higher for small populations:
o T-test for small populations (M = 50.17, SD = 14.27) and rest of population
(M = 43.32, SD = 14.24); t(202) = 4.46, p = 0.00. The difference is
statistically significant (Appendix F, Figure A293).



Workforce index is higher for small populations, and lower for large populations:
o T-test for small populations (M = 62.31, SD = 13.80) and rest of population
(M = 53.70, SD = 12.25); t(184) = 5.94, p = 0.00. The difference is
statistically significant (Appendix F, Figure A294).
o T-test for large populations (M = 48.72, SD = 11.74) and rest of population (M
= 57.74, SD = 12.95); t(147) = -6.35, p = 0.00. The difference is statistically
significant (Appendix F, Figure A295).



Language index is lower for small populations, and higher for large populations:
o T-test for small populations (M = 20.07, SD = 17.97) and rest of population
(M = 31.73, SD = 25.48); t(288) = -5.35, p = 0.00. The difference is
statistically significant (Appendix F, Figure A296).

A144

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography (continued)
o T-test for large populations (M = 38.70, SD = 28.63) and rest of population (M
= 26.20, SD = 22.43); t(117) = 3.84, p = 0.00. The difference is statistically
significant (Appendix F, Figure A297).


Housing index is higher for small populations
o T-test for small populations (M = 67.84, SD = 19.23) and rest of population
(M = 61.44, SD = 17.46); t(187) = 3.16, p = 0.00. The difference is
statistically significant (Appendix F, Figure A298).



The Nation wellness index is higher for small populations
o T-test for small populations (M = 70.74, SD = 12.17) and rest of population
(M = 62.88, SD = 10.58); t(181) = 6.18, p = 0.00. The difference is
statistically significant (Appendix F, Figure A299).

The general trends in the descriptive statistics by geographic zone include:


Gross business sales ratio is higher for geographically close communities, and lower
for geographically remote communities:
o T-test for geographically close communities (M = 0.131, SD = 0.201) and rest
of population (M = 0.083, SD = 0.139); t(222) = 2.57, p = 0.01. The difference
is statistically significant (Appendix F, Figure A300).
o T-test for geographically remote communities (M = 0.051, SD = 0.109) and
rest of population (M = 0.109, SD = 0.171); t(175) = -3.85, p = 0.00. The
difference is statistically significant (Appendix F, Figure A301).



Gross business sales capita is higher for geographically close communities, and lower
for geographically remote communities:
o T-test for geographically close communities (M = $6,836, SD = $15,694) and
rest of population (M = $3,232, SD = $7,134); t(180) = 2.67, p = 0.01. The
difference is statistically significant (Appendix F, Figure A302).
o T-test for geographically remote communities (M = $2,388, SD = $6,323) and
rest of population (M = $4,876, SD = $11,604); t(212) = -2.66, p = 0.01. The
difference is statistically significant (Appendix F, Figure A303).
A145

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography (continued)


Business and economic development expense ratio is higher geographically close
communities, and lower for geographically remote communities:
o T-test for geographically close communities (M = 0.157, SD = 0.189) and rest
of population (M = 0.122, SD = 0.141); t(234) = 2.04, p = 0.04. The difference
is statistically significant (Appendix F, Figure A304).
o T-test for geographically remote communities (M = 0.081, SD = 0.114) and
rest of population (M = 0.145, SD = 0.166); t(159) = -4.12, p = 0.00. The
difference is statistically significant (Appendix F, Figure A305).



Business and economic development expense capita is higher geographically close
communities, and lower for geographically remote communities:
o T-test for geographically close communities (M = $6,602, SD = $12,977) and
rest of population (M = $4,573, SD = $7,669); t(202) = 1.76, p = 0.08. The
difference is not statistically significant (Appendix F, Figure A306).
o T-test for geographically remote communities (M = $3,532, SD = $7,437) and
rest of population (M = $5,621, SD = $10,208); t(151) = -2.11, p = 0.04. The
difference is statistically significant (Appendix F, Figure A307).



Tangible capital asset (TCA) capita is lower for geographically close communities,
and higher for geographically remote communities:
o T-test for geographically close communities (M = $37,314, SD = $29,854)
and rest of population (M = $48,421, SD = $41,413); t(369) = -3.11, p = 0.00.
The difference is statistically significant (Appendix F, Figure A308).
o T-test for geographically remote communities (M = $58,521, SD = $60,725)
and rest of population (M = $42,003, SD = $31,733); t(70) = 2.12, p = 0.04.
The difference is statistically significant (Appendix F, Figure A309).



Earned and other revenue ratio is higher for geographically close communities, and
lower for geographically remote communities:

A146

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography (continued)
o T-test for geographically close communities (M = 0.412, SD = 0.235) and rest
of population (M = 0.299, SD = 0.207); t(267) = 4.95, p = 0.00. The difference
is statistically significant (Appendix F, Figure A310).
o T-test for geographically remote communities (M = 0.255, SD = 0.209) and
rest of population (M = 0.354, SD = 0.222); t(120) = -3.79, p = 0.00. The
difference is statistically significant (Appendix F, Figure A311).


Federal and provincial revenue ratio is lower for geographically close communities,
and higher for geographically remote communities:
o T-test for geographically close communities (M = 0.509, SD = 0.221) and rest
of population (M = 0.594, SD = 0.227); t(305) = -3.80, p = 0.00. The
difference is statistically significant (Appendix F, Figure A312).
o T-test for geographically remote communities (M = 0.671, SD = 0.237) and
rest of population (M = 0.543, SD = 0.220); t(110) = 4.40, p = 0.00. The
difference is statistically significant (Appendix F, Figure A313).



Federal and provincial revenue capita is lower for geographically close communities,
and higher for geographically remote communities:
o T-test for geographically close communities (M = $13,720, SD = $9,818) and
rest of population (M = $17,732, SD = $12,954); t(378) = -3.64, p = 0.00. The
difference is statistically significant (Appendix F, Figure A314).
o T-test for geographically remote communities (M = $20,014, SD = $15,805)
and rest of population (M = $15,612, SD = $11,062); t(96) = 2.35, p = 0.02.
The difference is statistically significant (Appendix F, Figure A315).



Education index is higher for geographically close communities, and lower for
geographically remote communities:
o T-test for geographically close communities (M = 51.7, SD = 11.9) and rest of
population (M = 41.8, SD = 14.6); t(358) = 7.72, p = 0.00. The difference is
statistically significant (Appendix F, Figure A316).

A147

Appendix G: Descriptive Statistics Analysis and T-Test Results by Population and
Geography (continued)
o T-test for geographically remote communities (M = 32.4, SD = 14.6) and rest
of population (M = 47.8, SD = 13.0); t(107) = -8.72, p = 0.00. The difference
is statistically significant (Appendix F, Figure A317).


Language index is lower for geographically close communities, and higher for
geographically remote communities:
o T-test for geographically close communities (M = 17.9, SD = 18.3) and rest of
population (M = 34.1, SD = 25.1); t(390) = -7.78, p = 0.00. The difference is
statistically significant (Appendix F, Figure A318).
o T-test for geographically remote communities (M = 50.7, SD = 30.2) and rest
of population (M = 24.0, SD = 19.9); t(94) = 7.52, p = 0.00. The difference is
statistically significant (Appendix F, Figure A319).



Housing index is higher for geographically close communities, and lower for
geographically remote communities:
o T-test for geographically close communities (M = 70.2, SD = 16.7) and rest of
population (M = 59.5, SD = 17.8); t(316) = 6.24, p = 0.00. The difference is
statistically significant (Appendix F, Figure A320).
o T-test for geographically remote communities (M = 52.0, SD = 15.8) and rest
of population (M = 65.5, SD = 17.7); t(125) = -6.70, p = 0.00. The difference
is statistically significant (Appendix F, Figure A321).



Income index is higher for geographically close communities:
o T-test for geographically close communities (M = 34.2, SD = 10.9) and rest of
population (M = 29.3, SD = 9.5); t(196) = 3.97, p = 0.00. The difference is
statistically significant (Appendix F, Figure A322).



Nation wellness index is higher for geographically close communities:
o T-test for geographically close communities (M = 66.5, SD = 9.9) and rest of
population (M = 64.1, SD = 12.2); t(360) = 2.17, p = 0.03. The difference is
statistically significant (Appendix F, Figure A323).

A148

Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup
This appendix reviews the demographic indices of the First Nation communities. The
indices reviewed are: education, workforce, language, housing, income, and the overall
Nation wellness index (NWI). As the mean and median values are very similar, only the
mean values will be discussed in this appendix. High level discussion of the results presented
in this appendix are provided throughout Chapter 3 of this manuscript.
The education index measures the level of education of the community, and is
measured by high school graduation rates, trades and apprenticeship training, and postsecondary education. This index, along with all the other indices, are measured on a scale of
0-100. Refer to Appendix D, Figure A1. The total population mean is 45.1. Two key patterns
exist for the education index:


Education levels are higher for geographically close communities. The means for
these subgroups are: SC 53.8, MC 50.8, and LC 51.9.
o T-test between SC (M = 53.77, SD = 12.17) and rest of population (M =
44.43, SD = 14.51); t(39) = 4.12, p = 0.00. The difference is statistically
significant (Appendix F, Figure A109).
o T-test for MC (M = 50.80, SD = 10.75) and rest of population (M = 43.93, SD
= 14.95); t(144) = 4.71, p = 0.00. The difference is statistically significant.
(Appendix F, Figure A110).
o T-test for LC (M = 51.89, SD = 13.59) and rest of population (M = 44.41, SD
= 14.48); t(50) = 3.34, p = 0.00. The difference is statistically significant
(Appendix F, Figure A111).



Education levels are much lower for geographically remote communities that have a
medium and high population. The means for geographically remote subgroups are:
SR 46.3, MR 28.6, and LR 25.8.
o T-test for SR (M = 46.28, SD = 16.90) and rest of population (M = 45.05, SD
= 14.48); t(19) = 0.31, p = 0.76. The difference is not statistically significant
(Appendix F, Figure A112).

A149

Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup (continued)
o T-test for MR (M = 28.61, SD = 11.09) and rest of population (M = 47.00, SD
= 13.68); t(63) = -10.38, p = 0.00. The difference is statistically significant
(Appendix F, Figure A113).
o T-test for LR (M = 25.77, SD = 10.02) and rest of population (M = 45.73, SD
= 14.24); t(15) = -7.22, p = 0.00. The difference is statistically significant
(Appendix F, Figure A114).
The workforce index measures the employment rate and participation rate of the
community. Refer to Appendix D, Figure A3. The total population mean is 55.9. There are
not drastic differences between the subgroups, but the following patterns exist:


Workforce levels are slightly higher for small populations. The means for these
subgroups are: SC: 59.6, SM 63.1, and SR 64.1. The mean income decreases with
large populations.
o T-test for SC (M = 59.60, SD = 12.09) and rest of population (M = 55.66, SD
= 13.26); t(37) = 1.76, p = 0.09. The difference is not statistically significant
(Appendix F, Figure A115).
o T-test for SM (M = 63.12, SD = 13.39) and rest of population (M = 54.72, SD
= 12.79); t(86) = 4.70, p = 0.00. The difference is statistically significant
(Appendix F, Figure A116).
o T-test for SR (M = 64.11, SD = 17.57) and rest of population (M = 55.58, SD
= 12.88); t(19) = 2.09, p = 0.05. The difference is statistically significant
(Appendix F, Figure A117).



Workforce levels are lower for large populations that are geographically medium and
remote: LM 42.7 and LR 47.8.
o T-test for LM (M = 42.66, SD = 8.08) and rest of population (M = 57.04, SD =
12.95); t(49) = -9.43, p = 0.00. The difference is statistically significant
(Appendix F, Figure A118).

A150

Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup (continued)
o T-test for LR (M = 47.82, SD = 9.42) and rest of population (M = 56.20, SD =
13.23); t(15) = -3.23, p = 0.01. The difference is statistically significant
(Appendix F, Figure A119).
The language index measures the percentage of the population with knowledge of
Indigenous language. This is also an effective measure for the degree of cultural knowledge
that is passed on within a community. Refer to Appendix D, Figure A5. This index has a
significant amount of variation between the subgroups. The total population mean is 28.7.
The key patterns are:


Language knowledge is much lower for geographically close communities. The
means for these subgroups are: SC 10.7, MC 16.2, and LC 26.6.
o T-test for SC (M = 10.74, SD = 13.60) and rest of population (M = 30.09, SD
= 24.38); t(49) = -7.20, p = 0.00. The difference is statistically significant
(Appendix F, Figure A132).
o T-test for MC (M = 16.20, SD = 14.06) and rest of population (M = 31.26, SD
= 25.14); t(192) = -7.26, p = 0.00. The difference is statistically significant
(Appendix F, Figure A133).
o T-test for LC (M = 26.55, SD = 24.49) and rest of population (M = 28.92, SD
= 24.28); t(49) = -0.59, p = 0.56. The difference is not statistically significant
(Appendix F, Figure A134).



Language knowledge is much higher for geographically remote communities. The
means for these subgroups are: SR 36.2, MR 52.4, and LR 64.5.
o T-test for SR (M = 36.21, SD = 23.80) and rest of population (M = 28.36, SD
= 24.27); t(20) = 1.40, p = 0.18. The difference is not statistically significant
(Appendix F, Figure A135).
o T-test for MR (M = 52.42, SD = 30.57) and rest of population (M = 25.97, SD
= 21.90); t(51) = 5.70, p = 0.00. The difference is statistically significant
(Appendix F, Figure A136).

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Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup (continued)
o T-test for LR (M = 64.48, SD = 30.38) and rest of population (M = 27.54, SD
= 23.19); t(14) = 4.51, p = 0.00. The difference is statistically significant
(Appendix F, Figure A137).


Language knowledge is also progressively higher with larger populations.
The housing index measures the degree of residential housing in need of major repair.

Refer to Appendix D, Figure A7. The total population mean is 63.1. Significant variation
exists between the subgroups, with the following major patterns:


The state of housing is higher for geographically close communities. The means for
these subgroups are: SC 70.4, MC 69.1, and LC 72.2.
o T-test for SC (M = 70.40, SD = 18.71) and rest of population (M = 62.54, SD
= 17.99); t(36) = 2.30, p = 0.03. The difference is statistically significant
(Appendix F, Figure A120).
o T-test for MC (M = 69.06, SD = 14.69) and rest of population (M = 61.88, SD
= 18.55); t(131) = 3.70, p = 0.00. The difference is statistically significant
(Appendix F, Figure A121).
o T-test for LC (M = 72.24, SD = 18.70) and rest of population (M = 62.18, SD
= 17.85); t(48) = 3.30, p = 0.00. The difference is statistically significant
(Appendix F, Figure A122).



The state of housing is much lower for geographically remote communities with
medium and high populations. The means for geographically remote subgroups are:
SR 60.8, MR 51.2, and LR 43.0.
o T-test for SR (M = 60.75, SD = 17.95) and rest of population (M = 63.21, SD
= 18.16); t(20) = -0.58, p = 0.57. The difference is not statistically significant
(Appendix F, Figure A123).
o T-test for MR (M = 51.21, SD = 14.16) and rest of population (M = 64.47, SD
= 18.06); t(64) = -5.83, p = 0.00. The difference is statistically significant
(Appendix F, Figure A124).

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Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup (continued)
o T-test for LR (M = 42.96, SD = 12.69) and rest of population (M = 63.76, SD
= 17.92); t(15) = -5.94, p = 0.00. The difference is statistically significant
(Appendix F, Figure A125).
The income index measures the level of personal income of the communities. Note that
no Census data is available for communities with small populations. Statistics Canada
deemed that the quality of this data was too poor to post publicly. As such, no analysis can be
completed for communities with small populations. Refer to Appendix D, Figure A9. The
total population mean is 31.0. While patterns exist between the subgroups, the difference are
more subtle compared to the other indices. The pattern that exists include:


Income levels are progressively higher for communities that are more geographically
close. The means for the geographically close subgroups are: MC 32.6 and LC 36.8.
o T-test for MC (M = 32.62, SD = 6.59) and rest of population (M = 30.56, SD =
11.10); t(181) = 1.90, p = 0.06. The difference is not statistically significant
(Appendix F, Figure A138).
o T-test for LC (M = 36.84, SD = 15.28) and rest of population (M = 30.10, SD
= 9.00); t(45) = 2.75, p = 0.01. The difference is statistically significant
(Appendix F, Figure A139).
The Nation wellness index (NWI) is an overall measure for the wellness of the

communities. This index is comprised of the previously listed five sub-indices. Note that if
no income index information was available (for small populations), the NWI was based on
the other available sub-indices. Refer to Appendix D, Figure A11. The total population mean
is 64.9. Variations between the subgroups exist, with the following patterns:


Nation wellness is higher for communities with small populations. The means for
these subgroups are: SC 68.7, SM 71.0, and SR 73.2.
o T-test for SC (M = 68.65, SD = 10.03) and rest of population (M = 64.63, SD
= 11.60); t(38) = 2.16, p = 0.04. The difference is statistically significant
(Appendix F, Figure A126).

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Appendix H: Descriptive Statistics Analysis and T-test Results of Demographic Indices
by Subgroup (continued)
o T-test for SM (M = 71.04, SD = 12.45) and rest of population (M = 63.88, SD
= 11.05); t(83) = 4.36, p = 0.00. The difference is statistically significant
(Appendix F, Figure A127).
o T-test for SR (M = 73.19, SD = 14.37) and rest of population (M = 64.55, SD
= 11.27); t(19) = 2.59, p = 0.02. The difference is statistically significant
(Appendix F, Figure A128).


Nation wellness is lower for communities with larger populations, with the exception
of large populations that are also geographically close. The means for the large
population subgroups are: LC 68.2, LM 58.7, and LR 58.5.
o T-test for LC (M = 68.21, SD = 12.03) and rest of population (M = 64.59, SD
= 11.44); t(48) = 1.85, p = 0.07. The difference is not statistically significant
(Appendix F, Figure A129).
o T-test for LM (M = 58.72, SD = 10.10) and rest of population (M = 65.43, SD
= 11.50); t(41) = -3.68, p = 0.00. The difference is statistically significant
(Appendix F, Figure A130).
o T-test for LR (M = 58.49, SD = 9.35) and rest of population (M = 65.13, SD =
11.54); t(15) = -2.60, p = 0.02. The difference is statistically significant
(Appendix F, Figure A131).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup
This appendix reviews the investing financial indicators, which are based off of the
2016 audited financial statements of the First Nation governments. Accounting ratios
(referred to as ratio) are reviewed, as well as per capita measures (referred to as capita). Note
that the financial indicators are summarized in Appendix A. The categories of indicators that
will be reviewed include: business activity, government business entity activity, trust
activity, capital activity, and other activity. The financial indicators are reviewed by the
subgroups as defined in Table 1. Refer to Appendix E for the detailed data tables and graphs.
Both the mean and median values are evaluated in this appendix. A high-level discussion of
the analysis presented in this appendix are provided throughout Chapter 3 of this manuscript.

Business Activity Indicators
Business activity indicators measure the general level of business activities carried on
by the First Nation governments. Note that this includes businesses that are controlled by the
First Nation government. Business entities that are owned, but maintain independence from
the government, will be reviewed in the next section.
The investment asset ratio measures total investment assets (excluding government
business entities and trust funds) divided by total financial assets. Refer to Appendix E,
Figure A13. The total population mean is 0.28. The patterns that exist include:


The mean ratio increases slightly with larger populations. The means for these
subgroups are: LC 0.31, LM 0.32, and LR 0.34. As the difference is not significant,
no further analysis will be conducted.



The mean ratio is much larger for communities with small populations that are
geographically close. The mean for this subgroup, SC, is 0.44.
o T-test for SC (M = 0.436, SD = 1.079) and rest of population (M = 0.268, SD
= 0.291); t(31) = 0.88, p = 0.39. The difference is not statistically significant
(Appendix F, Figure A140).



The median and mean values are very similar for the subgroups LC, LM, and LR,
while the median values are relatively much lower for the other subgroups. Also, the

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

coefficients of variation for these subgroups are very high.
The investment asset capita measures total investment assets (excluding government
business entities and trust funds) divided by community population. Refer to Appendix E,
Figure A15. The total population mean is $14,306. The patterns that exist are:


The mean capita measure is higher for communities with small populations. The
means for these subgroups are: SC $30,015, SM $25,820, and SR $25,912.
o T-test for SC (M = $30,015, SD = $77,735) and rest of population (M =
$13,092, SD = $45,943); t(33) = 1.22, p = 0.23. The difference is not
statistically significant (Appendix F, Figure A141).
o T-test for SM (M = $25,820, SD = $92,335) and rest of population (M =
$12,342, SD = $36,701); t(68) = 1.16, p = 0.25. The difference is not
statistically significant (Appendix F, Figure A142).
o T-test for SR (M = $25,912, SD = $75,352) and rest of population (M =
$13,790, SD = $47,538); t(19) = 0.70, p = 0.50. The difference is not
statistically significant (Appendix F, Figure A143).



The mean capita measure is much lower for larger populations. The means for these
subgroups are: LC $5,312, LM $7,356, and LR $11,346.
o T-test for LC (M = $5,312, SD = $7,442) and rest of population (M = $15,217,
SD = $51,264); t(416) = -3.54, p = 0.00. The difference is statistically
significant (Appendix F, Figure A144).
o T-test for LM (M = $7,356, SD = $14,186) and rest of population (M =
$14,880, SD = $50,765); t(133) = -2.16, p = 0.03. The difference is
statistically significant (Appendix F, Figure A145).
o T-test for LR (M = $11,346, SD = $25,408) and rest of population (M =
$14,402, SD = $49,570); t(17) = -0.42, p = 0.68. The difference is not
statistically significant (Appendix F, Figure A146).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


The mean capita measure is also much lower for medium populations that are
geographically remote. The means for MR is $7,256.
o T-test for MR (M = $7,256, SD = $14,499) and rest of population (M =
$15,117, SD = 51,435); t(224) = -2.35, p = 0.02. The difference is statistically
significant (Appendix F, Figure A147).



The median values are significantly lower than the mean values for all subgroups,
with a greatest difference for the subgroups SC, SM, and SR that have median values
less than a tenth of the mean.
Gross business sales ratio measures gross business sales divided by total revenue. Refer

to Appendix E, Figure A17. The total population mean is 0.10. The patterns that exist are:


The mean ratio is much lower for geographically remote communities. The means for
these subgroups are: SR 0.03, MR 0.06, and LR 0.05. Communities that are
geographically closer have progressively higher mean ratios. Subgroup SC’s mean is
much higher at 0.16.
o T-test for SR (M = 0.026, SD = 0.072) and rest of population (M = 0.102, SD
= 0.166); t(28) = -4.13, p = 0.00. The difference is statistically significant
(Appendix F, Figure A148).
o T-test for MR (M = 0.061, SD = 0.125) and rest of population (M = 0.104, SD
= 0.167); t(66) = -2.11, p = 0.04. The difference is statistically significant
(Appendix F, Figure A149).
o T-test for LR (M = 0.053, SD = 0.092) and rest of population (M = 0.101, SD
= 0.165); t(16) = -1.84, p = 0.08. The difference is not statistically significant
(Appendix F, Figure A150).
o T-test for SC (M = 0.156, SD = 0.233) and rest of population (M = 0.095, SD
= 0.156); t(33) = 1.47, p = 0.15. The difference is not statistically significant
(Appendix F, Figure A151).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


The median values for all subgroups, except LM, are zero or nearly zero and are
substantially lower than the mean values.
Gross business sales capita measures gross business sales divided by community

population. Refer to Appendix E, Figure A19. The total population mean is $4,436. The
patterns that exist are:


The mean capita measure is much lower for geographically remote communities. The
means for these subgroups are: SR $1,361, MR $3,247, and LR $961. The trends
show that this measure is progressively higher when communities are more
geographically close, and have smaller populations. Note that subgroup SC’s mean is
much higher at $11,674.
o T-test for SR (M = $1,361, SD = $3,196) and rest of population (M = $4,573,
SD = $11,094); t(45) = -3.53, p = 0.00. The difference is statistically
significant (Appendix F, Figure A152).
o T-test for MR (M = $3,247, SD = $7,907) and rest of population (M = $4,572,
SD = $11,185); t(69) = -1.03, p = 0.31. The difference is not statistically
significant (Appendix F, Figure A153).
o T-test for LR (M = $961, SD = $1,715) and rest of population (M = $4,548,
SD = $11,047); t(76) = -5.11, p = 0.00. The difference is statistically
significant (Appendix F, Figure A154).
o T-test for SC (M = $11,674, SD = $24,189) and rest of population (M =
$3,876, SD = $8,920); t(32) = 1.81, p = 0.08. The difference is not statistically
significant (Appendix F, Figure A155).



The median values for all subgroups, except LM, are zero or nearly zero and are
substantially lower than the mean values.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

Business and economic development expense ratio measures business and economic
expenses divided by total expenses. Refer to Appendix E, Figure A21. The total population
mean is 0.13. The patterns that exist are:


The mean ratio is much lower for geographically remote communities. The means for
these subgroups are: SR 0.07, MR 0.08, and LR 0.08. The trends show that this ratio
is progressively higher when communities are more geographically close, and have
smaller populations. Note that subgroup SC’s mean is much higher at 0.20.
o T-test for SR (M = 0.072, SD = 0.101) and rest of population (M = 0.136, SD
= 0.161); t(23) = -2.63, p = 0.02. The difference is statistically significant
(Appendix F, Figure A156).
o T-test for MR (M = 0.084, SD = 0.127) and rest of population (M = 0.139, SD
= 0.162); t(64) = -2.70, p = 0.01. The difference is statistically significant
(Appendix F, Figure A157).
o T-test for LR (M = 0.084, SD = 0.090) and rest of population (M = 0.135, SD
= 0.161); t(16) = -2.03, p = 0.06. The difference is not statically significant
(Appendix F, Figure A158).
o T-test for SC (M = 0.196, SD = 0.226) and rest of population (M = 0.129, SD
= 0.153); t(33) = 1.67, p = 0.11. The difference is not statistically significant
(Appendix F, Figure A159).



The median values are substantially lower than the mean values, except for the
subgroups LM and LR.
Business and economic development expense capita measures business and economic

development expenses divided by community population. Refer to Appendix E, Figure A23.
The total population mean is $5,251. The patterns that exist are:


The mean capita measure is much lower for geographically remote communities. The
means for these subgroups are: SR $4,292, MR $3,777, and LR $1,697. The trends
show that this capita measure is progressively higher when communities are more

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

geographically close, and have smaller populations. Note that subgroup SC’s mean is
much higher at $11,736.
o T-test for SR (M = $4,292, SD = $10,340) and rest of population (M = $5,293,
SD = $9,786); t(20) = -0.41, p = 0.68. The difference is not statically
significant (Appendix F, Figure A160).
o T-test for MR (M = $3,777, SD = $7,129) and rest of population (M = $5,420,
SD = $10,055); t(69) = -1.41, p = 0.16. The difference is not statically
significant (Appendix F, Figure A161).
o T-test for LR (M = $1,697, SD = $1,796) and rest of population (M = $5,366,
SD = $9,932); t(55) = -5.42, p = 0.00. The difference is statistically significant
(Appendix F, Figure A162).
o T-test for SC (M = $11,736, SD = $20,248) and rest of population (M =
$4,749, SD = $8,319); t(32) = 1.94, p = 0.06. The difference is not statistically
significant (Appendix F, Figure A163).


The median values for all subgroups are substantially lower than the mean values.

Government Business Entity (GBE) Activity Indicators
The GBE asset ratio measures GBE assets divided by total financial assets. Refer to
Appendix E, Figure A25. The total population mean is 0.38. The patterns that emerge are:


The mean ratio is much lower for small population communities that are
geographically close and remote. The subgroup means for small populations are: SC
0.14, SM, 0.47, and SR 0.21. No other major trends appear.
o T-test for SC (M = 0.136, SD = 0.237) and rest of population (M = 0.397, SD
= 0.824); t(85) = -4.03, p = 0.00. The difference is statistically significant
(Appendix F, Figure A164).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SR (M = 0.214, SD = 0.472) and rest of population (M = 0.387, SD
= 0.812); t(20) = -1.37, p = 0.18. The difference is not statically significant
(Appendix F, Figure A165).


The median values for all subgroups, except LM and LR, are substantially lower than
the mean values. Subgroups LM and LR’s medians are less than the means, but are
relatively closer in value (approximately two-thirds the value).
The GBE asset capita measures GBE assets divided by community population. Refer to

Appendix E, Figure A27. The total population mean is $14,481. The patterns are:


The mean capita measure is lower for large populations. The subgroup means are: LC
$6,765, LM $6,890, and LR $7,629.
o T-test for LC (M = $6,765, SD = $11,461) and rest of population (M =
$15,310, SD = $62,532); t(305) = -2.18, p = 0.03. The difference is
statistically significant (Appendix F, Figure A166).
o T-test for LM (M = $6,890, SD = $10,360) and rest of population (M =
$15,077, SD = $61,765); t(244) = -2.11, p = 0.04. The difference is
statistically significant (Appendix F, Figure A167).
o T-test for LR (M = $7,629, SD = $9,172) and rest of population (M = $14,690,
SD = $60,444); t(59) = -1.67, p = 0.10. The difference is not statistically
significant (Appendix F, Figure A168).



The mean capita measure is much higher for small populations if the communities are
geographically medium or remote. The subgroup means are: SM $31,387 and SR
$50,022.
o T-test for SM (M = $31,387, SD = $104,674) and rest of population (M =
$11,601, SD = $47,541); t(57) = 1.37, p = 0.18. The difference is not
statistically significant (Appendix F, Figure A169).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SR (M = $50,022, SD = $178,501) and rest of population (M =
$12,879, SD = $47,950); t(15) = 0.83, p = 0.42. The difference is not
statistically significant (Appendix F, Figure A170).


The median values for all subgroups, except LR, are substantially lower than the
mean values. This is most notable in the subgroups SM and SR.
GBE equity ratio measures GBE equity divided by accumulated surplus. Refer to

Appendix E, Figure A33. The total population mean is 0.10. The patterns are:


The mean ratio is higher for small populations that are geographically close and
medium. The subgroup means for small populations are: SC 0.15, SM 0.16, and SR
0.08.
o T-test for SC (M = 0.152, SD = 0.329) and rest of population (M = 0.093, SD
= 0.379); t(36) = 0.93, p = 0.36. The difference is not statistically significant
(Appendix F, Figure A171).
o T-test for SM (M = 0.164, SD = 0.800) and rest of population (M = 0.086, SD
= 0.256); t(58) = 0.74, p = 0.46. The difference is not statistically significant
(Appendix F, Figure A172).
o T-test for SR (M = 0.082, SD = 0.310) and rest of population (M = 0.098, SD
= 0.378); t(20) = -0.21, p = 0.83. The difference is not statistically significant
(Appendix F, Figure A173).



The median values are zero or near zero for all subgroups except LC and LM.
GBE equity capita measures GBE equity divided by community population. Refer to

Appendix E, Figure A35. The total population mean is $7,113. The patterns are:


The mean capita measure is much higher for small populations. The subgroup means
are: SC $13,271, SM $10,233, and SR $33,531.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SC (M = $13,271, SD = $30,276) and rest of population (M =
$6,624, SD = $39,603); t(38) = 1.13, p = 0.27. The difference is not
statistically significant (Appendix F, Figure A174).
o T-test for SM (M = $10,233, SD = $61,240) and rest of population (M =
$6,606, SD = $34,161); t(62) = 0.44, p = 0.66. The difference is not
statistically significant (Appendix F, Figure A175).
o T-test for SR (M = $33,531, SD = $136,073) and rest of population (M =
$5,893, SD = $27,359); t(17) = 0.86, p = 0.40. The difference is not
statistically significant (Appendix F, Figure A176).


The mean capita measure is lower for large population. The subgroup means are: LC
$3,612, LM $2,739 and LR $4,243.
o T-test for LC (M = $3,612, SD = $8,716) and rest of population (M = $7,472,
SD = $40,850); t(267) = -1.51, p = 0.13. The difference is not statistically
significant (Appendix F, Figure A177).
o T-test for LM (M = $2,739, SD = $4,749) and rest of populations (M =
$7,498, SD = $40,639); t(394) = -2.11, p = 0.04. The difference is statistically
significant (Appendix F, Figure A178).
o T-test for LR (M = $4,243, SD = $8,081) and rest of population (M = $7,120,
SD = $39,563); t(36) = -0.96, p = 0.34. The difference is not statistically
significant (Appendix F, Figure A179).



The median values are substantially lower compared to the mean values for all
subgroups.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

GBE revenue ratio measures GBE revenue divided by total revenue. Refer to Appendix
E, Figure A37. The total population mean is 0.26. The patterns are:


Most subgroups are closely aligned with the total population mean. Three subgroups’
means are exceptions, which are: small population and geographically close (SC
0.11), medium populations that are geographically medium (MM 0.35), and medium
populations that are geographically remote (MR 0.12).
o T-test for SC (M = 0.112, SD = 0.198) and rest of population (M = 0.268, SD
= 0.655); t(77) = -2.92, p = 0.00. The difference is statistically significant
(Appendix F, Figure A180).
o T-test for MM (M = 0.347, SD = 0.835) and rest of population (M = 0.222, SD
= 0.538); t(137) = 1.41, p = 0.16. The difference is not statistically significant
(Appendix F, Figure A181).
o T-test for MR (M = 0.116, SD = 0.216) and rest of population (M = 0.270, SD
= 0.659); t(95) = -2.90, p = 0.00. The difference is statistically significant
(Appendix F, Figure A182).



The median values are zero or near zero for all subgroups except LM and LR.
GBE revenue capita measures GBE revenue divided by community population. Refer

to Appendix E, Figure A39. The total population mean is $10,398. The patterns are:


The mean capita measure is lower for large populations. The subgroup means are: LC
$4,217, LM $5,121, and LR $3,879.
o T-test for LC (M = $4,217, SD = $10,189) and rest of population (M =
$11,062, SD = $58,504); t(319) = -1.89, p = 0.06. The difference is not
statistically significant (Appendix F, Figure A183).
o T-test for LM (M = $5,121, SD = $5,587) and rest of population (M =
$10,812, SD = $57,820); t(366) = -1.73, p = 0.09. The difference is not
statistically significant (Appendix F, Figure A184).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for LR (M = $3,879, SD = $4,306) and rest of population (M = $10,597,
SD = $56,540); t(243) = -2.07, p = 0.04. The difference is statistically
significant (Appendix F, Figure A185).


The mean capita measure is much higher small populations that are geographically
medium and remote, but is lower for small populations that are geographically close.
The subgroup means for small population communities are: SC $4,621, SM $23,342,
and SR $42,744.
o T-test for SC (M = $4,621, SD = $8,588) and rest of population (M = $10,815,
SD = $57,626); t(260) = -1.75, p = 0.08. The difference is not statistically
significant (Appendix F, Figure A186).
o T-test for SM (M = $23,342, SD = $109,780) and rest of population (M =
$8,193, SD = $39,738); t(55) = 1.00, p = 0.32. The difference is not
statistically significant (Appendix F, Figure A187).
o T-test for SR (M = $42,744, SD = $165,155) and rest of population (M =
$8,940, SD = $45,152); t(15) = 0.82, p = 0.43. The difference is not
statistically significant (Appendix F, Figure A188).



The median values are substantially lower compared to the mean values for all
subgroups except LM and LR.
GBE expense ratio measures GBE expenses divided by total expenses. Refer to

Appendix E, Figure A41. The total population mean is 0.29. The patterns are:


No distinct patterns emerge based on geographic location or population. Two specific
subgroups’ means differ significantly from the total population. The ratio is much
lower for small populations that are geographically close (SC 0.16), is much lower
for medium populations that are geographically remote (MR 0.10), is much higher for
small populations that are geographically remote (SR 0.40), and higher for medium
populations that are geographically medium (MM 0.41).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SC (M = 0.158, SD = 0.456) and rest of population (M = 0.297, SD
= 0.848); t(38) = -1.37, p = 0.18. The difference is not statistically significant
(Appendix F, Figure A189).
o T-test for MR (M = 0.101, SD = 0.192) and rest of population (M = 0.305, SD
= 0.860); t(183) = -3.49, p = 0.00. The difference is statistically significant
(Appendix F, Figure A190).
o T-test for SR (M = 0.402, SD = 1.438) and rest of population (M = 0.283, SD
= 0.792); t(15) = 0.33, p = 0.75. The difference is not statistically significant
(Appendix F, Figure A191).
o T-test for MM (M = 0.413, SD = 1.217) and rest of population (M = 0.240, SD
= 0.613); t(123) = 1.38, p = 0.17. The difference is not statistically significant
(Appendix F, Figure A192).


The median values are substantially lower compared to the mean values for all
subgroups except LM and LR.
GBE expense capita measures GBE expenses divided by community population. Refer

to Appendix E, Figure A43. The total population mean is $9,362. The patterns are:


The mean is much higher for small populations that are geographically medium and
remote: SM $23,758 and SR $25,172
o T-test for SM (M = $23,758, SD = $111,430) and rest of population (M =
$6,910, SD = $25,373); t(54) = 1.11, p = 0.27. The difference is not
statistically significant (Appendix F, Figure A193).
o T-test for SR (M = $25,172, SD = $95,600) and rest of population (M =
$8,649, SD = $45,515); t(15) = 0.69, p = 0.50. The difference is not
statistically significant (Appendix F, Figure A194).



The mean is much lower for large populations: LC $4,506, LM $5,227, and LR
$3,710. The mean is also much lower for the subgroup MR $3,823.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)
o T-test for LC (M = $4,506, SD = $10,251) and rest of population (M = $9,884,
SD = $51,037); t(277) = -1.64, p = 0.10. The difference is not statistically
significant (Appendix F, Figure A195).
o T-test for LM (M = $5,227, SD = $5,984) and rest of population (M = $9,687,
SD = $50,455), t(342) = -1.51, p = 0.13. The difference is not statistically
significant (Appendix F, Figure A196).
o T-test for LR (M = $3,710, SD = $4,350) and rest of population (M = $9,535,
SD = $49,343); t(191) = -2.00, p = 0.05. The difference is statistically
significant (Appendix F, Figure A197).
o T-test for MR (M = $3,823, SD = $9,778) and rest of population (M = $9,849,
SD = $50,609); t(230) = -1.84, p = 0.07. The difference is not statistically
significant (Appendix F, Figure A198).


The median values are substantially lower compared to the mean values for all
subgroups except LM.
GBE net income ratio and capita measure were originally going to be evaluated in this

study. Upon reviewing the results, the results have a significantly large coefficient of
variation. As a result, this information will not be included in this study. The raw data is
included in Appendix E, figures A45-A48 for reference purposes.

Trust Fund Activity Indicators
Trust fund asset ratio measures trust fund assets divided by total financial assets. Refer
to Appendix E, Figure A49. The total population mean is 0.10. The patters are:


No clear patterns emerge regarding population or geographic remoteness. Most
subgroup means are similar to the total population mean, with two exceptions:
geographically close communities with small populations (LC 0.16) and
geographically remote communities with large populations (LR 0.02).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for LC (M = 0.160, SD = 0.269) and rest of population (M = 0.096, SD
= 0.189); t(44) = 1.48, p = 0.15. The difference is not statistically significant
(Appendix F, Figure A199).
o T-test for LR (M = 0.019, SD = 0.037) and rest of population (M = 0.105, SD
= 0.201); t(52) = -6.18, p = 0.00. The difference is statistically significant
(Appendix F, Figure A200).


The median values are zero or near zero for all subgroups.
Trust fund asset capita measures trust fund assets divided by community population.

Refer to Appendix E, Figure A51. The total population mean is $6,279. The patterns are:


Geographically remote communities have either much higher or lower mean capita
measures. The subgroup means are: SR $2,110, MR $20,669, and LR $254. The
medium population subgroup is unusually high. Once the outlier is adjusted for, it is
likely that geographically remote communities have a lower capita measure.
o T-test for SR (M = $2,110, SD = $4,242) and rest of population (M = $6,464,
SD = $36,329); t(241) = -2.17, p = 0.03. The difference is statistically
significant (Appendix F, Figure A201).
o T-test for MR (M = $20,669, SD = $98,841) and rest of population (M =
$4,624, SD = $16,802); t(45) = 1.10, p = 0.28. The difference is not
statistically significant (Appendix F, Figure A202).
o T-test for LR (M = $254, SD = 769) and rest of population (M = $6,474, SD =
$36,122); t(441) = -3.55, p = 0.00. The difference is statistically significant
(Appendix F, Figure A203).



The median values are substantially lower than the mean values for all subgroups.

A168

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

Trust fund revenue ratios measures trust fund revenue divided by total revenue. Refer
to Appendix E, Figure A53. The total population mean is 0.03. The patterns are:


Geographically remote communities have a very low, or zero, mean ratio. The
subgroup means are: SR 0.00, MR 0.01, and LR 0.00.
o T-test for SR (M = 0.002, SD = 0.004) and rest of population (M = 0.028, SD
= 0.074); t(442) = -7.25, p = 0.00. The difference is statistically significant
(Appendix F, Figure A204).
o T-test for MR (M = 0.013, SD = 0.050) and rest of population (M = 0.029, SD
= 0.075); t(72) = -1.92, p = 0.06. The difference is not statistically significant
(Appendix F, Figure A205).
o T-test for LR (M = 0.003, SD = 0.001) and rest of population (M = 0.028, SD
= 0.074); t(110) = -5.78, p = 0.00. The difference is statistically significant
(Appendix F, Figure A206).



Geographically close with small populations also have a zero mean ratio: SC 0.00.
o Test for SC (M = 0.004, SD = 0.015) and rest of population (M = 0.029, SD =
0.075); t(219) = -5.59, p = 0.00. The difference is statistically significant
(Appendix F, Figure A207).



The median values are zero for all subgroups.
Trust fund revenue capita measures trust fund revenue divided by community

population. Refer to Appendix E, Figure A55. The total population mean is $868. The
patterns are:


Geographically remote communities have a very low mean capita measure, at: SR
$46, MR $382, and LR $38.
o T-test for SR (M = $46, SD = $89) and rest of population (M = $905, SD =
$3,433); t(437) = -5.13, p = 0.00. The difference is statistically significant
(Appendix F, Figure A208).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for MR (M = $382, SD = $1,354) and rest of population (M = $924, SD
= $3,518); t(136) = -2.03, p = 0.04. The difference is statistically significant
(Appendix F, Figure A209).
o T-test for LR (M = $38, SD = $120) and rest of population (M = $895, SD =
$3,414); t(446) = -5.12, p = 0.00. The difference is statistically significant
(Appendix F, Figure A210).


Geographically close with small populations also have a low mean capita measure:
SC $89.
o T-test for SC (M = $89, SD = $359) and rest of population (M = $928, SD =
$3,482); t(432) = -4.60, p = 0.00. The difference is statistically significant
(Appendix F, Figure A211).



The median values are zero or near zero for all subgroups.

Capital Activity Indicators
Tangible capital asset (TCA) ratio measures TCA divided by total assets. Refer to
Appendix E, Figure A57. The total population mean is 0.65. The patterns are:


Geographically close communities have a marginally lower mean ratio. Aside from
this, all the subgroup means are similar to the total population.



The median values are very similar to the mean values for all subgroups.
TCA capita measures TCA divided by community population. Refer to Appendix E,

Figure A59. The total population mean is $44,600. The patterns are:


Small population communities have a much higher mean capita measure: SC
$50,660, SM $65,209, and SR $93,628.
o T-test SC (M = $50,660, SD = $39,627) and rest of population (M = $44,153,
SD = $38,073); t(31) = 0.84, p = 0.41. The difference is not statistically
significant (Appendix F, Figure A212).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test SM (M = $65,209, SD = $44,404) and rest of population (M = $41,312,
SD = $36,071); t(68) = 3.83, p = 0.00. The difference is statistically
significant (Appendix F, Figure A213).
o T-test SR (M = $93,628, SD = $100,037) and rest of population (M = $42,724,
SD = $32,535); t(14) = 1.97; p = 0.07. The difference is not statistically
significant (Appendix F, Figure A214).


Large population communities have a lower mean capita measure: LC $27,962, LM
$25,543, and LR $25,672.
o T-test LC (M = $27,962, SD = $19,691) and rest of population (M = $46,414,
SD = $39,256); t(80) = -4.95, p = 0.00. The difference is statistically
significant (Appendix F, Figure A215).
o T-test LM (M = $25,543, SD = $11,187) and rest of population (M = $46,282,
SD = $39,241); t(132) = -7.37, p = 0.00. The difference is statistically
significant (Appendix F, Figure A216).
o T-test LR (M = $25,672, SD = $9,051) and rest of population (M = $45,126,
SD = $38,535); t(25) = -5.81, p = 0.00. The difference is statistically
significant (Appendix F, Figure A217).



The median values are slightly lower than the mean values for all of the subgroups,
except for SR which has a substantially lower median value (median is half of mean).
Note that the variability between the median values is less than between the mean
values.
Gross cash inflows from capital represents only a minor amount of cash inflows. Due

to the insignificant amount, this ratio and capita measure will not be reviewed. The raw data
is available for reference in Appendix E, Figures A61 – A64.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

Gross cash outflow from capital ratio measures gross cash outflows from capital
divided by total gross cash outflows (excluding operating cash flows). Refer to Appendix E,
Figure A65. The total population mean is 0.53. The patterns are:


Most of the subgroup means are very similar to the population mean. Only one
exception exists, which is small populations that are geographically remote: SR 0.75.
o T-test for SR (M = 0.745, SD = 0.222) and rest of population (M = 0.525, SD
= 0.308); t(16) = 3.71, p = 0.00. The difference is statistically significant
(Appendix F, Figure A218).



The median values are very similar to the mean values for all subgroups.
Gross cash outflow from capital capita measures gross cash outflows from capital

divided by community population. Refer to Appendix E, Figure A67. The total population
mean is $4,232. The patterns are:


The mean capita measure is lower for communities with large populations. The
subgroup means are: LC $3,251, LM $2,423, and LR $2,911.
o T-test for LC (M = $3,251, SD = $5,224) and rest of population (M = $4,339,
SD = $6,832); t(55) = 1.21, p = 0.23. The difference is not statistically
significant (Appendix F, Figure A219).
o T-test for LM (M = $2,423, SD = $2,773) and rest of population (M = $4,392,
SD = $6,913); t(77) = 3.28, p = 0.00. The difference is statistically significant
(Appendix F, Figure A220).
o T-test for LR (M = $2,911, SD = $4,835) and rest of population (M = $4,269,
SD = $6,739); t(11) = 0.91, p = 0.38. The difference is not statistically
significant (Appendix F, Figure A221).



The mean capita measure is higher for communities with small populations that are
geographically medium and remote. The subgroup means are: SM: $5,948 and SR
$7,927.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SM (M = $5,948, SD = $8,589) and rest of population (M = $3,958,
SD = $6,311); t(65) = -1.66, p = 0.10. The difference is not statistically
significant (Appendix F, Figure A222).
o T-test for SR (M = $7,927, SD = $12,777) and rest of population (M = $4,091,
SD = $6,335); t(14) = -1.16, p = 0.27. The difference is not statistically
significant (Appendix F, Figure A223).


The median values are lower than the median values for all subgroups, with the most
significant difference present for the subgroups SC, SM, and SR.
Net cash flow from capital ratio has significant variation, and does not provide

valuable insight. This ratio will not be analyzed. The raw data can be viewed in Appendix E,
Figures A69-A70.
Net cash flow from capital capita measures net cash flows from capital divided by
community population. Refer to Appendix E, Figure A71. The total population mean is
$4,141. The patterns are:


The mean capita measure is lower for large populations. The subgroup means are: LC
$3,150, LM $2,383, and LR $2,911.
o T-test for LM (M = $2,383, SD = $2,766) and rest of population (M = $4,296,
SD = $6,944); t(78) = 3.19, p = 0.00. The difference is statistically significant
(Appendix F, Figure A224).
o T-test for LR (M = $2,911, SD = $4,835) and rest of population (M = $4,175,
SD = $6,767); t(11) = 0.84, p = 0.42. The difference is not statistically
significant (Appendix F, Figure A225).



The mean capita measure is higher for small populations that are geographically
medium and remote. The subgroup means are: SM: $5,851 and SR $7,900.



The median values are lower than the median values for all subgroups, with the most
significant difference present for the subgroups SC, SM, and SR.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)
o T-test for SM (M = $5,851, SD = $8,594) and rest of population (M = $3,869,
SD = $6,345); t(65) = -1.66, p = 0.10. The difference is not statistically
significant (Appendix F, Figure A226).
o T-test for SR (M = $7,900, SD = $12,781) and rest of population (M = $3,997,
SD = $6,364); t(14) = -1.18, p = 0.26. The difference is not statistically
significant (Appendix F, Figure A227).

Other Ratios
Long term debt ratio measures long term debt divided by total liabilities. Refer to
Appendix E, Figure A73. The total population ratio is 0.52. The patterns are:


The mean ratios for large populations are slightly higher. The subgroup means are:
LC 0.59, LM 0.66, LR 0.63. As the differences are only slight, further analysis will
not be conducted.



The median and mean values are very similar for all subgroups.
Long term debt capita measures long term debt divided by community population.

Refer to Appendix E, Figure A75. The total population mean is $11,563. The patterns are:


Small populations have a higher mean capita measure: SC $15,290, SM $14,848, and
SR $15,907. The difference is not significant, and will not be evaluated further.



The median values are approximately half of the mean values for the subgroups SC,
SM, and SR. The median values are slightly less than the mean values for the other
subgroups.
Net cash flow from operating ratio has significant variances, and does not provide

valuable insight. No further analysis of this ratio will be conducted. The raw data is available
in Appendix E, Figures A93-A94.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

Net cash flow from operating capita measures net cash flows from operating divided by
community population. Refer to Appendix E, Figure A95. The total population mean is
$4,445. The patterns are:


Small populations have a higher mean capita measure: SC $9,059, SM $9,560, and
SR $6,496.
o T-test for SC (M = $9,059, SD = $12,475) and rest of population (M = $4,089,
SD = $8,534); t(33) = 2.21, p = 0.03. The difference is statistically significant
(Appendix F, Figure A228).
o T-test for SM (M = $9,560, SD = $15,792) and rest of population (M =
$3,573, SD = $6,822); t(68) = 3.01, p = 0.00. The difference is statistically
significant (Appendix F, Figure A229).
o T-test for SR (M = $6,496, SD = $13,434) and rest of population (M = $4,354,
SD = $8,708); t(19) = 0.69, p = 0.50. The difference is not statistically
significant (Appendix F, Figure A230).



Large populations have a lower mean capita measure: LC: $2,177, LM $359, and LR
$2,621.
o T-test for LC (M = $2,177, SD = $2,922) and rest of population (M = $4,675,
SD = $9,316); t(154) = -3.84, p = 0.00. The difference is statistically
significant (Appendix F, Figure A231).
o T-test for LM (M = $359, SD = $3,940) and rest of population (M = $4,782,
SD = $9,163); t(70) = -5.44, p = 0.00. The difference is statistically significant
(Appendix F, Figure A232).
o T-test for LR (M = $2,621, SD = $4,960) and rest of population (M = $4,504,
SD = $9,046); t(16) = -1.35, p = 0.20. The difference is not statistically
significant (Appendix F, Figure A233).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


The median values are less than half of the mean values for the subgroups SC, SM,
SR, MR, and SR. The median values show mixed results for the other subgroups.
Gross cash inflows from investing ratio measures gross cash inflows from investing

divided by total gross cash inflows (excluding operating). Refer to Appendix E, Figure A97.
The total population mean is 0.30. The patterns are:


Geographically close communities with small or large populations have higher mean
ratios: SC 0.45 and LC 0.39.
o T-test for SC (M = 0.455, SD = 0.473) and rest of population (M = 0.293, SD
= 0.386); t(26) = 1.68, p = 0.11. The difference is not statistically significant
(Appendix F, Figure A234).
o T-test for LC (M = 0.386, SD = 0.423) and rest of population (M = 0.294, SD
= 0.389); t(46) = 1.29, p = 0.20. The difference is not statistically significant
(Appendix F, Figure A235).



The median values show mixed results amoung the subgroups with no distinct
patterns to note.
Gross cash inflows from investing capita measures gross cash inflows from investing

divided by community population. Refer to Appendix E, Figure A99. The total population
mean is $2,317. The patterns are:


Geographically remote communities have a much lower mean capita measure: SR
$429, MR $1,080, and LR $176.
o T-test for SR (M = $429, SD = $1,663) and rest of population (M = $2,401,
SD = $12,152); t(178) = -2.81, p = 0.01. The difference is statistically
significant (Appendix F, Figure A236).
o T-test for MR (M = $1,080, SD = $2,641) and rest of population (M = $2,460,
SD = $12,529); t(337) = -1.87, p = 0.06. The difference is not statistically
significant (Appendix F, Figure A237).

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for LR (M = $176, SD = $442) and rest of population (M = $2,387, SD
= $12,086); t(445) = -3.73, p = 0.00. The difference is statistically significant
(Appendix F, Figure A238).


Small populations that are geographically close have a much higher mean capita
measure: SC $5,476.
o T-test for SC (M = $5,476, SD = $18,954) and rest of population (M = $2,073,
SD = $11,171); t(33) = 1.00, p = 0.32. The difference is not statistically
significant (Appendix F, Figure A239).



The median values are zero or near zero for all subgroups, which are substantially
lower than the mean values.
Gross cash outflows from investing ratio measures gross cash outflows from investing

divided by total gross cash outflows (excluding operating). Refer to Appendix E, Figure
A101. The total population mean is 0.14. The patterns are:


Geographically remote communities have lower mean ratios: SR 0.04, MR 0.06, LR
0.04.
o T-test for SR (M = 0.045, SD = 0.112) and rest of population (M = 0.147, SD
= 0.254); t(28) = -3.60, p = 0.00. The difference is statistically significant
(Appendix F, Figure A240).
o T-test for MR (M = 0.058, SD = 0.147) and rest of population (M = 0.153, SD
= 0.257); t(83) = -3.74, p = 0.00. The difference is statistically significant
(Appendix F, Figure A241).
o T-test for LR (M = 0.039, SD = 0.068) and rest of population (M = 0.146, SD
= 0.253); t(29) = -4.91, p = 0.00. The difference is statistically significant
(Appendix F, Figure A242).



Small populations that are geographically close have a high mean ratio: SC 0.23

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SC (M = 0.226, SD = 0.349) and rest of population (M = 0.136, SD
= 0.240); t(33) = 1.42, p = 0.16. The difference is not statically significant
(Appendix F, Figure A243).


The median values are zero or near zero for all subgroups, which are substantially
lower than the mean values.
Gross cash outflows from investing capita measures gross cash outflows from investing

divided by community population. Refer to Appendix E, Figure A103. The total population
mean is $2,972. The patterns are:


Geographically remote communities have lower mean ratios: SR $375, MR $1,133,
and LR $192.
o T-test for SR (M = $375, SD = $887) and rest of population (M = $3,087, SD
= $13,108); t(422) = 4.07, p = 0.00. The difference is statistically significant
(Appendix F, Figure A244).
o T-test for MR (M = $1,133, SD = $6,349) and rest of population (M = $3,183,
SD = $13,373); t(102) = 1.78, p = 0.08. The difference is not statistically
significant (Appendix F, Figure A245).
o T-test for LR (M = $192, SD = $417) and rest of population (M = $3,062, SD
= $13,035); t(446) = 4.51, p = 0.00. The difference is statistically significant
(Appendix F, Figure A246).



Large populations have lower mean ratios: LC $1,215, LM $1,079, and LR $192
o T-test for LC (M = $1,215, SD = $2,954) and rest of population (M = $3,150,
SD = $13,429); t(274) = 2.39; p = 0.02. The difference is statistically
significant (Appendix F, Figure A247).
o T-test for LM (M = $1,079, SD = $2,496) and rest of population (M = $3,128,
SD = $13,328); t(266) = 2.61, p = 0.01. The difference is statistically
significant (Appendix F, Figure A248).
o T-test for LR: see above. The difference is statistically significant.

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Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


Small populations that are geographically close have a much higher mean capita
measure: SC $8,805
o T-test for SC (M = $8,805, SD = $23,875) and rest of population (M = $2,521,
SD = $11,488); t(32) = -1.48; p = 0.15. The difference is not statistically
significant (Appendix F, Figure A249).



The median values are zero or near zero for all subgroups, which are substantially
lower than the mean values.
The financial indicators for net cash flows from investing (both ratio and capita) have

significant variation and do not provide valuable analysis. These indicators will not be
reviewed further. The raw data is available for reference in Appendix E, Figures A105 –
A108.
Earned revenue ratio measures earned revenue divided by total revenue. Refer to
Appendix E, Figure A77. The total population mean is 0.20. The patterns are:


Geographically close have higher mean ratios: SC 0.32, MC 0.28, and LC 0.25.
o T-test for SC (M = 0.319, SD = 0.273) and rest of population (M = 0.190, SD
= 0.193); t(34) = 2.64, p = 0.01. The difference is statistically significant
(Appendix F, Figure A250).
o T-test for MC (M = 0.280, SD = 0.232) and rest of population (M = 0.182, SD
= 0.191); t(98) = 3.44, p = 0.00. The difference is statistically significant
(Appendix F, Figure A251).
o T-test for LC (M = 0.249, SD = 0.214) and rest of population (M = 0.194, SD
= 0.200); t(48) = 1.58, p = 0.12. The difference is not statistically significant
(Appendix F, Figure A252).



Geographically remote have lower mean ratios: SR: 0.08, MR 0.13, and LR 0.11.
o T-test for SR (M = 0.079, SD = 0.214) and rest of population (M = 0.204, SD
= 0.200); t(20) = -2.51, p = 0.02. The difference is statistically significant
(Appendix F, Figure A253).

A179

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for MR (M = 0.127, SD = 0.164) and rest of population (M = 0.207, SD
= 0.205); t(63) = -3.05, p = 0.00. The difference is statistically significant
(Appendix F, Figure A254).
o T-test for LR (M = 0.114, SD = 0.136) and rest of population (M = 0.202, SD
= 0.203); t(15) = -2.32, p = 0.03. The difference is statistically significant
(Appendix F, Figure A255).


The median values are very similar, but slightly lower, than the mean values for all of
the subgroups except SR and MR. The median values for the SR and MR subgroups
are significantly lower at approximately half of the mean values.
Earned revenue capita measures earned revenue divided by community population.

Refer to Appendix E, Figure A79. The total population mean is $7,982. The patterns are:


Large populations have a much lower mean capita measure: LC: $6,506, LM $3,744,
and LR $2,455
o T-test for LC (M = $6,506, SD = $9,522) and rest of population (M = $8,131,
SD = $15,035); t(63) = -0.98, p = 0.33. The difference is not statistically
significant (Appendix F, Figure A256).
o T-test for LM (M = $3,744, SD = $3,614) and rest of population (M = $8,332,
SD = $15,120); t(176) = -4.73, p = 0.00. The difference is statistically
significant (Appendix F, Figure A257).
o T-test for LR (M = $2,455, SD = $3,985) and rest of population (M = $8,161,
SD = $14,799); t(29) = -4.45, p = 0.00. The difference is statistically
significant (Appendix F, Figure A258).



Small populations that are geographically close have a much higher mean capita
measure: SC $20,438
o T-test for SC (M = $20,438, SD = $27,931) and rest of population (M =
$7,019, SD = $12,595); t(32) = 2.70, p = 0.01. The difference is statistically
significant (Appendix F, Figure A259).

A180

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


The median values are significantly lower than the median values for all subgroups
except LM, many of which have median values less than half of the mean values.
Earned and other revenue ratio measures earned and other revenue divided by total

revenue. Refer to Appendix E, Figure A81. The total population mean is 0.34. The patterns
are:


Geographically close communities have slightly higher mean ratios: SC: 0.43, MC
0.42, and LC 0.38
o T-test for SC (M = 0.428, SD = 0.255) and rest of population (M = 0.330, SD
= 0.219); t(35) = 2.11, p = 0.04. The difference is statistically significant
(Appendix F, Figure A260).
o T-test for MC (M = 0.420, SD = 0.234) and rest of population (M = 0.320, SD
= 0.217); t(104) = 3.45, p = 0.00. The difference is statistically significant
(Appendix F, Figure A261).
o T-test for LC (M = 0.383, SD = 0.225) and rest of population (M = 0.332, SD
= 0.222); t(49) = 1.39, p = 0.17. The difference is not statistically significant
(Appendix F, Figure A262).



Geographically remote communities have slightly lower mean ratios: SR 0.28, MR
0.26, and LR 0.21
o T-test for SR (M = 0.277, SD = 0.251) and rest of population (M = 0.339, SD
= 0.221); t(19) = -1.07, p = 0.30. The difference is not statistically significant
(Appendix F, Figure A263).
o T-test for MR (M = 0.259, SD = 0.208) and rest of population (M = 0.346, SD
= 0.223); t(58) = -2.67, p = 0.01. The difference is statistically significant
(Appendix F, Figure A264).
o T-test for LR (M = 0.214, SD = 0.153) and rest of population (M = 0.341, SD
= 0.224); t(15) = -2.99, p = 0.01. The difference is statistically significant
(Appendix F, Figure A265).



The median values are very similar to the mean values for all subgroups.
A181

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)
Earned and other revenue capita measures earned and other revenue divided by
community population. Refer to Appendix E, Figure A83. The total population mean is
$13,286. The patterns are:


Small populations have a much higher mean capita measure: SC $23,976, SM
$18,895, and SR $21,482
o T-test for SC (M = $23,976, SD = $28,454) and rest of population (M =
$12,460, SD = $20,998); t(34) = 2.24, p = 0.03. The difference is statistically
significant (Appendix F, Figure A266).
o T-test for SM (M = $18,895, SD = $21,607) and rest of population (M =
$12,329, SD = $21,696); t(88) = 2.26, p = 0.03. The difference is statistically
significant (Appendix F, Figure A267).
o T-test for SR (M = $21,482, SD = $40,918) and rest of population (M =
$12,922, SD = $20,537); t(18) = 0.91, p = 0.38. The difference is not
statistically significant (Appendix F, Figure A268).



Large populations have a lower mean capita measure: LC $9,018, LM $9,096, and
LR $4,973
o T-test for LC (M = $9,018, SD = $10,315) and rest of population (M =
$13,718, SD = $22,584); t(88) = -2.39, p = 0.02. The difference is statistically
significant (Appendix F, Figure A269).
o T-test for LM (M = $9,096, SD = $16,613) and rest of population (M =
$13,632, SD = $22,136); t(44) = -1.49, p = 0.14. The difference is not
statistically significant (Appendix F, Figure A270).
o T-test for LR (M = $4,973, SD = $4,937) and rest of population (M = $13,556,
SD = $22,064); t(38) = -5.07, p = 0.00. The difference is statistically
significant (Appendix F, Figure A271).

A182

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)


The medians are lower than the means for all of the subgroups, with the median
values often at half the mean value. The median values are smaller for large
population (similar to the pattern of the means), however the variation between the
subgroups is less pronounced for the median values compared to the mean values.
Federal & provincial gov’t revenue ratio measures federal & provincial transfers

divided by total revenue. Refer to Appendix E, Figure A85. The total population mean is
0.57. The patterns are:


Geographically remote mean ratios are higher with medium and large populations:
SR 0.61, MR 0.67, and LR 0.76. The other subgroups are largely aligned with the
total population mean.
o T-test for MR (M = 0.669, SD = 0.231) and rest of population (M = 0.554, SD
= 0.225); t(56) = 3.23, p = 0.00. The difference is statistically significant
(Appendix F, Figure A272).
o T-test for LR (M = 0.759, SD = 0.164) and rest of population (M = 0.559, SD
= 0.227); t(15) = 4.42, p = 0.00. The difference is statistically significant
(Appendix F, Figure A273).



The median values are very similar to the mean values for all subgroups.
Federal & Provincial gov’t revenue capita measures federal & provincial transfers

divided by community population. Refer to Appendix E, Figure A87. The total population
mean is $16,392. The patterns are:


Small population mean capita measures are higher: SC $19,335, SM $22,630, and SR
$28,378. The capita measures progressively decline with larger populations. The
capita measure also progressively declines with more geographically close
communities.
o T-test for SC (M = $19,335, SD = $12,677) and rest of population (M =
$16,164, SD = $12,079); t(36) = 1.37, p = 0.18. The difference is not
statistically significant (Appendix F, Figure A274).

A183

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SM (M = $22,630, SD = $16,989) and rest of population (M =
$15,327, SD = $10,773); t(73) = 3.35, p = 0.00. The difference is statistically
significant (Appendix F, Figure A275).
o T-test for SR (M = $28,378, SD = $26,638) and rest of population (M =
$15,858, SD = $10,824); t(18) = 2.04, p = 0.06. The difference is not
statistically significant (Appendix F, Figure A276).


Large population mean capita measures are lower: LC $11,818, LM $12,756, LR
$14,408.
o T-test for LC (M = $11,818, SD = $11,666) and rest of population (M =
$16,854, SD = $12,100); t(50) = -2.62, p = 0.01. The difference is statistically
significant (Appendix F, Figure A277).
o T-test for LM (M = $12,756, SD = $3,949) and rest of population (M =
$16,692, SD = $12,531); t(109) = -4.30, p = 0.00. The difference is
statistically significant (Appendix F, Figure A278).
o T-test for LR (M = $14,408, SD = $3,596) and rest of population (M =
$16,456, SD = $12,310); t(26) = -1.81, p = 0.08. The difference is not
statistically significant (Appendix F, Figure A279).



The median values are very similar the mean values for all of the subgroups except
SC, SM, and SR. The subgroups SC, SM, and SR maintain median values lower than
the means, with median values approximately three quarters of the mean values.
Tribal gov’t and other First Nation entity revenue ratio measures Tribal gov’t transfers

& other First Nation entity (e.g. First Nation NPOs) transfers divided by total revenue. Refer
to Appendix E, Figure A89. The total population mean is 0.07. The patterns are:


Most subgroup means are similar to the total population with the following
exceptions: small populations that are geographically remote (SR 0.11) and large
populations that are geographically remote (LR 0.02).

A184

Appendix I: Descriptive Statistics Analysis and T-test Results of Financial Indicator by
Subgroup (continued)

o T-test for SR (M = 0.113, SD = 0.200) and rest of population (M = 0.065, SD
= 0.104); t(18) = 1.03, p = 0.32. The difference is not statistically significant
(Appendix F, Figure A280).
o T-test for LR (M = 0.024, SD = 0.033) and rest of population (M = 0.069, SD
= 0.111); t(26) = -4.32, p = 0.00. The difference is statistically significant
(Appendix F, Figure A281).


The median values are significantly lower than the mean values, with the median
values often half (or less than half) of the mean values.
Tribal gov’t and other First Nation entity revenue capita measures Tribal gov’t

transfers & other First Nation entity (e.g. NPOs) transfers divided by community population.
Refer to Appendix E, Figure A91. The total mean population is $1,966. The patterns are:


Most subgroup means are similar to the total population. The most distinct
differences include the following subgroups: small populations that are
geographically remote (SR $6,178), and large populations that are geographically
medium or remote (LM $794 and LR $441).
o T-test for SR (M = $6,178, SD = $16,344) and rest of population (M = $1,779,
SD = $3,126); t(18) = 1.17, p = 0.26. The difference is not statistically
significant (Appendix F, Figure A282).
o T-test for LM (M = $794, SD = $1,262) and rest of population (M = $2,063,
SD = $4,736); t(145) = -3.99, p = 0.00. The difference is statistically
significant (Appendix F, Figure A283).
o T-test for LR (M = $441, SD = $573) and rest of population (M = $2,016, SD
= $4,641); t(125) = -5.82, p = 0.00. The difference is statistically significant
(Appendix F, Figure A284).



The median values are significantly lower than the mean values, with the median
values often half (or less than half) of the mean values.

A185

Appendix J: R Results Between Business Activity Indicators and Demographic
Indices
Notes:
1) * indicates statistical significance at the 5% level
2) Highlighted cells indicate an r value between -0.40 and 0.40.
Figure A324: R Summary of Business Activity Financial Indicators - Total Population
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.00
0.01
-0.02
0.09
0.21*
0.06
Investment asset capita
0.10*
0.16*
-0.08
0.19* 0.27*
0.20*
Gross business sales
ratio
0.17*
0.12*
-0.16*
0.14*
0.07
0.08
Gross business sales
capita
0.17*
0.18*
-0.16*
0.18*
0.04
0.14*
Business and Ec Dev
expense ratio
0.21*
0.19*
-0.24*
0.19*
0.04
0.09*
Business and Ec Dev
expense capita
0.17*
0.23*
-0.20*
0.18* -0.01
0.13*
Figure A325: R Summary of Business Activity Financial Indicators - Subgroup SC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
0.12
-0.03
-0.06
-0.04
n/a
-0.01
0.23
-0.07
-0.17
0.24
n/a
0.15
Investment asset capita
Gross business sales
ratio
0.18
0.20
-0.21
0.49*
n/a
0.38*
Gross business sales
capita
0.20
0.13
-0.13
0.55*
n/a
0.44*
Business and Ec Dev
expense ratio
0.03
0.15
-0.33
0.50*
n/a
0.24
Business and Ec Dev
expense capita
0.04
0.19
-0.21
0.58*
n/a
0.38*

A186

Appendix J: R Results Between Business Activity Indicators and Demographic
Indices (continued)
Figure A326: R Summary of Business Activity Financial Indicators - Subgroup SM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.07
0.12
0.01
0.21
n/a
0.14
0.17
0.24
0.03
0.20
n/a
0.28*
Investment asset capita
Gross business sales
ratio
0.12
0.11
-0.08
-0.03
n/a
0.04
Gross business sales
capita
0.10
0.22
0.00
-0.05
n/a
0.10
Business and Ec Dev
expense ratio
0.26*
0.22
-0.01
-0.03
n/a
0.17
Business and Ec Dev
expense capita
0.21
0.21
-0.01
-0.09
n/a
0.11
Figure A327: R Summary of Business Activity Financial Indicators - Subgroup SR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.23
-0.12
-0.34
0.39
n/a
-0.17
-0.20
-0.13
-0.14
0.52*
n/a
0.01
Investment asset capita
Gross business sales
ratio
0.14
-0.15
0.25
-0.30
n/a
0.00
Gross business sales
capita
0.11
-0.05
-0.02
-0.46*
n/a
-0.19
Business and Ec Dev
expense ratio
0.31
0.30
0.16
-0.28
n/a
0.23
Business and Ec Dev
expense capita
0.12
0.22
-0.25
-0.39
n/a
-0.17

A187

Appendix J: R Results Between Business Activity Indicators and Demographic
Indices (continued)
Figure A328: R Summary of Business Activity Financial Indicators - Subgroup MC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.17
-0.09
-0.02
0.04
0.27*
-0.07
-0.09
0.04
-0.01
0.07
0.28*
0.05
Investment asset capita
Gross business sales
ratio
0.19
0.23*
-0.15
0.09
0.03
0.11
Gross business sales
capita
0.13
0.20
-0.12
0.05
-0.04
0.07
Business and Ec Dev
expense ratio
0.22
0.19
-0.29*
0.18
0.10
0.11
Business and Ec Dev
expense capita
0.14
0.21
-0.17
0.08
-0.01
0.07
Figure A329: R Summary of Business Activity Financial Indicators - Subgroup MM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.05
0.10
0.03
0.20* 0.24*
0.19*
0.02
0.27*
-0.10
0.17
0.37*
0.21*
Investment asset capita
Gross business sales
ratio
0.17
0.19*
-0.01
0.17
0.24*
0.23*
Gross business sales
capita
0.17
0.23*
0.01
0.20* 0.25*
0.27*
Business and Ec Dev
expense ratio
0.13
0.23*
-0.04
0.24*
0.10
0.22*
Business and Ec Dev
expense capita
0.08
0.23*
-0.03
0.25*
0.07
0.20*

A188

Appendix J: R Results Between Business Activity Indicators and Demographic
Indices (continued)
Figure A330: R Summary of Business Activity Financial Indicators - Subgroup MR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
0.13
-0.05
0.10
0.04
0.22
0.19
0.10
0.06
0.00
0.14
0.17
0.23
Investment asset capita
Gross business sales
ratio
0.19
0.28
-0.30*
0.06
0.00
-0.06
Gross business sales
capita
0.18
0.28
-0.33*
0.07
-0.03
-0.08
Business and Ec Dev
expense ratio
0.26
0.37*
-0.43*
0.14
-0.00
-0.10
Business and Ec Dev
expense capita
0.25
0.32*
-0.41*
0.11
-0.09
-0.12
Figure A331: R Summary of Business Activity Financial Indicators - Subgroup LC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
0.02
0.09
-0.11
0.11
0.19
0.09
0.31*
0.31*
-0.21
0.26
0.38*
0.32*
Investment asset capita
Gross business sales
ratio
0.18
0.15
-0.12
0.06
-0.14
0.01
Gross business sales
capita
0.15
0.12
-0.07
0.10
-0.17
0.03
Business and Ec Dev
expense ratio
0.15
0.10
-0.26
0.04
-0.16
-0.11
Business and Ec Dev
expense capita
0.10
0.07
-0.12
0.08
-0.19
-0.05

A189

Appendix J: R Results Between Business Activity Indicators and Demographic
Indices (continued)
Figure A332: R Summary of Business Activity Financial Indicators - Subgroup LM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
-0.19
-0.13
-0.00
-0.01
-0.09
-0.10
-0.03
0.15
0.04
0.03
0.12
0.08
Investment asset capita
Gross business sales
ratio
-0.19
-0.04
-0.19
-0.09
-0.00
-0.23
Gross business sales
capita
-0.18
0.00
-0.15
-0.09
-0.02
-0.19
Business and Ec Dev
expense ratio
-0.12
0.01
-0.19
-0.15
-0.07
-0.22
Business and Ec Dev
expense capita
-0.10
0.08
-0.15
-0.11
0.01
-0.15
Figure A333: R Summary of Business Activity Financial Indicators - Subgroup LR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Investment asset ratio
0.38
0.45
-0.04
0.15
0.62*
0.37
0.57*
0.40
-0.29
0.20
0.74*
0.21
Investment asset capita
Gross business sales
ratio
-0.12
-0.20
-0.13
-0.05
-0.33
-0.29
Gross business sales
capita
-0.13
-0.13
-0.16
-0.00
-0.30
-0.28
Business and Ec Dev
expense ratio
-0.07
-0.12
-0.55*
-0.20
-0.18
-0.67*
Business and Ec Dev
expense capita
-0.03
0.02
-0.64*
-0.14
-0.09
-0.66*

A190

Appendix K: R Results Between Between Government Business Entity
(GBE) Activity Indicators and Demographic Indices
Notes:
1) * indicates statistical significance at the 5% level
2) Highlighted cells indicate an r value between -0.40 and 0.40.
Figure A334: R Summary of GBE Activity Financial Indicators - Total Population
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
GBE Asset Ratio
-0.01
0.04
-0.02
0.09
0.18*
0.05
GBE Asset Capita
0.01
0.17*
-0.03
0.16* 0.19*
0.17*
GBE Revenue Ratio
-0.01
0.10
-0.01
0.13* 0.22*
0.12*
GBE Revenue Capita
0.01
0.15*
-0.02
0.16* 0.18*
0.17*
GBE Expense Ratio
-0.00
0.07
-0.00
0.11* 0.20*
0.12*
GBE Expense Capita
0.02
0.18*
-0.02
0.16* 0.19*
0.18*
GBE Equity Ratio
-0.01
-0.02
0.02
0.04
0.30*
0.05
GBE Equity Capita
0.01
0.11*
-0.01
0.12* 0.41*
0.14*
GBE Net Income
Ratio
-0.06
0.00
0.02
-0.05
-0.08
-0.03
GBE Net Income
Capita
-0.02
-0.02
-0.00
0.08 -0.18*
0.04
Figure A335: R Summary of GBE Activity Financial Indicators - Subgroup SC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.47*
0.40*
0.48*
0.47*
0.51*
0.55*
0.21
0.12

-0.26
-0.22
-0.07
-0.12
-0.09
-0.06
-0.12
-0.28

-0.08
-0.23
-0.16
-0.22
-0.14
-0.10
-0.28
-0.27

0.03
-0.16
-0.06
-0.14
-0.30
0.04
-0.16
-0.13

Nation
Wellness
n/a
0.08
n/a
-0.14
n/a
0.06
n/a
-0.04
n/a
-0.08
n/a
0.20
n/a
-0.20
n/a
-0.28

-0.28

0.06

-0.16

0.28

n/a

0.02

0.31

-0.21

-0.35

-0.25

n/a

-0.29

A191

Appendix K: R Results Between Between Government Business Entity
(GBE) Activity Indicators and Demographic Indices (continued)
Figure A336: R Summary of GBE Activity Financial Indicators - Subgroup SM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

-0.04
0.11
0.07
0.12
0.10
0.12
-0.20
0.11

-0.04
0.43*
0.33*
0.41*
0.35*
0.40*
-0.12
0.44*

-0.08
0.01
-0.03
0.02
-0.05
0.02
0.20
0.01

0.05
0.19
0.17
0.21
0.21
0.23
-0.13
0.09

Nation
Wellness
n/a
-0.03
n/a
0.30*
n/a
0.22
n/a
0.31*
n/a
0.25
n/a
0.32*
n/a
-0.10
n/a
0.26

-0.12

-0.03

0.06

-0.13

n/a

-0.10

0.03

-0.08

-0.01

-0.28*

n/a

-0.17

Figure A337: R Summary of GBE Activity Financial Indicators - Subgroup SR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

-0.50*
-0.23
-0.25
-0.20
-0.23
-0.21
-0.30
-0.21

-0.21
-0.13
-0.12
-0.11
-0.12
-0.12
-0.14
-0.12

0.06
-0.02
0.00
-0.02
-0.02
-0.02
-0.07
-0.05

0.59*
0.58*
0.58*
0.57*
0.58*
0.57*
0.54*
0.54*

Nation
Wellness
n/a
-0.01
n/a
0.09
n/a
0.10
n/a
0.10
n/a
0.10
n/a
0.10
n/a
0.01
n/a
0.08

-0.59*

0.00

0.27

0.26

n/a

0.04

-0.19

-0.10

-0.04

0.53*

n/a

0.09

A192

Appendix K: R Results Between Between Government Business Entity
(GBE) Activity Indicators and Demographic Indices (continued)
Figure A338: R Summary of GBE Activity Financial Indicators - Subgroup MC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

-0.16
-0.12
-0.13
-0.14
-0.15
-0.14
0.16
-0.12

-0.04
0.08
0.08
0.08
0.08
0.09
-0.18
-0.02

0.01
0.06
0.04
0.08
0.06
0.09
-0.06
0.08

-0.10
-0.10
-0.13
-0.15
-0.13
-0.14
0.17
-0.06

Nation
Wellness
0.25
-0.09
0.27*
0.00
0.25
-0.04
0.22
-0.03
0.26*
-0.03
0.24
-0.02
0.30*
0.07
0.32*
0.00

-0.03

0.07

0.01

-0.12

-0.17

-0.07

-0.11

-0.05

-0.04

-0.08

-0.04

-0.13

Figure A339: R Summary of GBE Activity Financial Indicators - Subgroup MM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.08
-0.03
-0.06
-0.01
-0.06
-0.03
-0.04
-0.03

0.19*
0.17
0.09
0.16
0.07
0.16
-0.03
0.13

-0.06
-0.03
0.08
-0.01
0.12
-0.00
0.11
0.02

0.17
0.16
0.15
0.21*
0.12
0.21*
0.07
0.12

Nation
Wellness
0.27*
0.18
0.23*
0.14
0.38*
0.19*
0.40*
0.23*
0.34*
0.18
0.40*
0.23*
0.32*
0.14
0.56*
0.24*

-0.11

-0.06

0.12

-0.02

0.01

0.00

0.07

-0.04

0.01

-0.02

-0.30*

-0.04

A193

Appendix K: R Results Between Between Government Business Entity
(GBE) Activity Indicators and Demographic Indices (continued)
Figure A340: R Summary of GBE Activity Financial Indicators - Subgroup MR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.07
-0.07
0.04
0.05
0.04
0.04
0.14
0.10

0.06
0.33
0.39*
0.30
0.37*
0.30
0.08
-0.02

0.02
-0.14
-0.24
-0.21
-0.27
-0.23
0.07
0.12

0.07
0.04
0.42*
0.21
0.43*
0.22
0.17
0.24

Nation
Wellness
0.07
0.10
0.20
0.07
0.40*
0.23
-0.04
0.08
0.20
0.18
-0.10
0.06
0.52*
0.33*
0.21
0.32

0.06

-0.19

-0.25

-0.07

-0.19

-0.35*

0.19

0.01

0.07

0.14

0.35*

0.29

Figure A341: R Summary of GBE Activity Financial Indicators - Subgroup LC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.03
0.24
-0.04
-0.12
-0.05
-0.13
0.28
0.24

-0.00
0.29
-0.04
-0.03
-0.02
0.04
0.24
0.29

-0.23
-0.23
-0.25
-0.16
-0.27
-0.19
-0.11
-0.12

0.28
0.29
0.25
0.17
0.26
0.19
0.26
0.24

Nation
Wellness
0.26
0.11
0.43*
0.33*
0.09
-0.02
-0.14
-0.12
0.08
-0.03
-0.10
-0.09
0.35*
0.34*
0.43*
0.37*

0.03

-0.19

0.08

-0.08

-0.07

-0.06

0.00

-0.22

0.09

-0.07

-0.12

-0.08

A194

Appendix K: R Results Between Between Government Business Entity
(GBE) Activity Indicators and Demographic Indices (continued)
Figure A342: R Summary of GBE Activity Financial Indicators - Subgroup LM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.03
-0.00
0.03
0.14
0.19
0.12
-0.24
-0.12

-0.00
0.12
0.12
0.20
0.16
0.21
-0.32
-0.09

-0.08
-0.14
-0.00
-0.07
-0.14
-0.08
-0.03
-0.03

0.23
0.27
0.34
0.34
0.36
0.32
-0.05
0.12

Nation
Wellness
-0.06
0.03
0.27
0.06
0.36
0.19
0.50*
0.22
0.43*
0.18
0.53*
0.21
-0.22
-0.21
0.14
-0.02

0.21

-0.03

0.35*

0.26

-0.05

0.37*

0.06

-0.12

0.06

-0.01

-0.29

-0.01

Figure A343: R Summary of GBE Activity Financial Indicators - Subgroup LR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
GBE Asset Ratio
GBE Asset Capita
GBE Revenue Ratio
GBE Revenue Capita
GBE Expense Ratio
GBE Expense Capita
GBE Equity Ratio
GBE Equity Capita
GBE Net Income
Ratio
GBE Net Income
Capita

0.04
0.27
0.28
0.63*
0.36
0.68*
-0.19
-0.13

0.14
0.38
0.22
0.44
0.26
0.44
0.08
0.12

0.02
0.19
-0.10
-0.42
-0.19
-0.49
0.46
0.45

0.13
0.11
0.17
0.47
0.24
0.51
-0.26
-0.24

Nation
Wellness
0.03
0.15
0.47
0.65*
0.26
0.22
0.61*
0.28
0.34
0.20
0.64*
0.23
0.07
0.38
0.15
0.43

-0.61*

-0.39

0.56

-0.30

-0.43

0.05

-0.47

-0.09

0.59*

-0.34

-0.26

0.25

A195

Appendix L: R Results Between Trust Activity Indicators and Demographic Indices
Notes:
1) * indicates statistical significance at the 5% level
2) Highlighted cells indicate an r value between -0.40 and 0.40.
Figure A344: R Summary of Trust Activity Financial Indicators - Total Population
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.07
-0.05
-0.01
-0.11* 0.03
-0.11*
Trust fund assets capita
-0.01
0.05
0.00
-0.02
0.04
0.01
Trust revenue ratio
-0.07
-0.03
0.03
-0.07 -0.02
-0.06
Trust revenue capita
-0.01
0.12*
0.01
0.07
0.03
0.10*
Figure A345: R Summary of Trust Activity Financial Indicators - Subgroup SC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.29
-0.08
0.29
0.00
n/a
-0.02
Trust fund assets capita
0.15
0.06
-0.02
0.32
n/a
0.29
Trust revenue ratio
-0.33
0.00
-0.11
-0.07
n/a
-0.24
Trust revenue capita
-0.31
0.07
-0.14
-0.03
n/a
-0.19
Figure A346: R Summary of Trust Activity Financial Indicators - Subgroup SM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.11
-0.02
-0.03
-0.25*
n/a
-0.21
Trust fund assets capita
-0.18
0.22
-0.07
-0.05
n/a
-0.05
Trust revenue ratio
-0.01
0.12
-0.02
0.07
n/a
0.08
Trust revenue capita
0.02
0.30*
0.04
0.24
n/a
0.28*
Figure A347: R Summary of Trust Activity Financial Indicators - Subgroup SR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
0.10
-0.46*
-0.17
-0.46*
n/a
-0.46*
Trust fund assets capita
0.05
-0.56*
-0.47*
-0.47*
n/a
-0.70*
Trust revenue ratio
0.06
-0.59*
-0.27
-0.32
n/a
-0.53*
Trust revenue capita
-0.11
-0.65*
-0.38
-0.33
n/a
-0.70*

A196

Appendix L: R Results Between Trust Activity Indicators and Demographic Indices
(continued)
Figure A348: R Summary of Trust Activity Financial Indicators - Subgroup MC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.06
-0.03
-0.00
0.01
0.13
0.01
Trust fund assets capita
0.02
-0.05
-0.11
0.09
0.14
0.01
Trust revenue ratio
-0.21
-0.28*
0.30*
-0.29* -0.19
-0.23*
Trust revenue capita
-0.03
-0.04
0.08
-0.06
0.14
0.01
Figure A349: R Summary of Trust Activity Financial Indicators - Subgroup MM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.25*
-0.08
0.11
-0.32* 0.00
-0.19*
Trust fund assets capita
-0.21*
0.12
0.16
-0.04 0.38*
0.12
Trust revenue ratio
-0.14
-0.08
0.02
-0.05 -0.03
-0.11
Trust revenue capita
-0.12
0.00
0.06
0.02
0.01
-0.02
Figure A350: R Summary of Trust Activity Financial Indicators - Subgroup MR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
0.09
0.18
-0.25
0.36* -0.08
0.05
Trust fund assets capita
0.28
0.08
-0.13
0.01 -0.05
0.02
Trust revenue ratio
0.07
0.23
0.17
0.05
0.31
0.34*
Trust revenue capita
0.13
0.26
0.11
0.05
0.28
0.31*
Figure A351: R Summary of Trust Activity Financial Indicators - Subgroup LC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.06
0.00
0.06
-0.20 -0.08
-0.10
Trust fund assets capita
-0.12
-0.06
0.10
-0.34* -0.12
-0.19
Trust revenue ratio
-0.33*
-0.08
0.25
-0.45* -0.10
-0.22
Trust revenue capita
-0.31*
-0.08
0.25
-0.42* -0.09
-0.20

A197

Appendix L: R Results Between Trust Activity Indicators and Demographic Indices
(continued)
Figure A352: R Summary of Trust Activity Financial Indicators - Subgroup LM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
-0.17
0.11
0.03
0.07 0.38*
0.06
Trust fund assets capita
-0.13
0.18
0.03
0.10 0.52*
0.12
Trust revenue ratio
-0.10
-0.02
-0.16
-0.09 -0.14
-0.19
Trust revenue capita
-0.12
-0.02
-0.17
-0.02 -0.10
-0.18
Figure A353: R Summary of Trust Activity Financial Indicators - Subgroup LR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income Nation
Wellness
Trust fund assets ratio
0.52
0.36
-0.52
0.14
0.22
-0.13
Trust fund assets capita
0.60*
0.46
-0.55*
0.16
0.44
-0.06
Trust revenue ratio
-0.18
-0.00
0.27
-0.27 -0.02
0.09
Trust revenue capita
-0.13
0.03
0.23
-0.26
0.01
0.09

A198

Appendix M: R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices
Notes:
1) * indicates statistical significance at the 5% level
2) Highlighted cells indicate an r value between -0.40 and 0.40.
Figure A354: R Summary of TCA Financial Indicators - Total Population
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
-0.19*
-0.06

-0.23*
0.24*

0.17*
-0.06

-0.19*
0.06

Nation
Wellness
-0.43*
-0.22*
0.07
0.12*

-0.08

-0.04

0.12*

-0.05

-0.11

-0.00

0.04

-0.18*

0.03

-0.04

-0.06

-0.09

Figure A355: R Summary of TCA Financial Indicators - Subgroup SC
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

-0.33
-0.29

0.10
0.10

0.10
-0.00

0.03
0.46*

Nation
Wellness
n/a
-0.03
n/a
0.22

0.02

-0.07

-0.18

0.12

n/a

-0.03

0.08

-0.16

0.02

-0.25

n/a

-0.18

Figure A356: R Summary of TCA Financial Indicators - Subgroup SM
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

-0.14
-0.28*

-0.31*
0.20

0.20
0.16

0.04
0.14

Nation
Wellness
n/a
-0.07
n/a
0.11

-0.01

0.12

0.08

0.12

n/a

0.14

0.19

-0.33*

-0.13

-0.10

n/a

-0.16

A199

Appendix M: R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices (continued)
Figure A357: R Summary of TCA Financial Indicators - Subgroup SR
Financial Indicators
Demographic Indices
Education Workforce Language Housing
0.06
0.06

0.05
-0.08

-0.23
-0.62*

-0.22
-0.61*

Nation
Wellness
n/a
-0.18
n/a
-0.62*

0.09

0.12

-0.10

-0.05

n/a

0.02

-0.11

0.10

0.58*

0.59*

n/a

0.57*

Figure A358: R Summary of TCA Financial Indicators - Subgroup MC
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

Income

-0.06
0.10

-0.03
0.27*

0.34*
0.10

-0.23
0.13

Nation
Wellness
-0.30*
-0.08
0.25*
0.34*

0.17

0.03

-0.06

0.14

0.08

0.11

-0.14

-0.16

0.09

-0.12

-0.17

-0.19

Figure A359: R Summary of TCA Financial Indicators - Subgroup MM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

-0.10
0.03

-0.40*
0.16

0.05
-0.05

-0.23*
0.16

Nation
Wellness
-0.46*
-0.35*
0.28*
0.18

-0.09

-0.10

0.20*

-0.07

-0.04

0.04

0.09

-0.16

-0.03

-0.11

-0.16

-0.16

A200

Appendix M: R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices (continued)
Figure A360: R Summary of TCA Financial Indicators - Subgroup MR
Financial Indicators
Demographic Indices
Education Workforce Language Housing
-0.27
-0.16

-0.17
0.17

0.21
-0.11

-0.34*
-0.12

Nation
Wellness
-0.43*
-0.23
-0.24
-0.11

-0.36*

-0.21

-0.01

-0.32*

-0.47*

-0.39*

0.24

0.19

-0.05

0.27

0.24

0.22

Figure A361: R Summary of TCA Financial Indicators - Subgroup LC
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

Income

-0.45*
-0.14

-0.37*
0.08

0.27
0.36*

-0.16
0.03

Nation
Wellness
-0.48*
-0.34*
-0.17
0.14

-0.23

-0.15

0.20

-0.26

-0.19

-0.18

-0.02

-0.14

-0.13

0.00

0.09

-0.09

Figure A362: R Summary of TCA Financial Indicators - Subgroup LM
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

-0.05
-0.18

-0.16
-0.02

0.04
-0.07

-0.14
0.12

Nation
Wellness
-0.33
-0.11
0.25
-0.04

-0.16

0.02

0.27

-0.18

0.18

0.12

0.13

-0.14

-0.02

0.03

-0.35*

-0.03

A201

Appendix M: R Results Between Tangible Capital Asset (TCA) Activity Indicators and
Demographic Indices (continued)
Figure A363: R Summary of TCA Financial Indicators - Subgroup LR
Financial Indicators
Demographic Indices
Education Workforce Language Housing
TCA ratio
TCA capita
Gross cash outflows
from capital ratio
Gross cash outflows
from capital capita

Income

-0.17
-0.08

-0.39
-0.29

0.26
0.07

0.16
0.19

Nation
Wellness
-0.59
0.07
-0.05
0.03

-0.61*

-0.50

0.53

0.09

-0.57

0.16

0.37

0.13

0.03

0.06

0.10

0.23

A202

Appendix N: R Results Between Other Activity Indicators and Demographic
Indices
Notes:
1) * indicates statistical significance at the 5% level
2) Highlighted cells indicate an r value between -0.40 and 0.40.
Figure A364: R Summary of Other Financial Indicators - Total Population
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

Nation
Wellness

0.38*

0.17*

-0.33*

0.31*

0.26*

0.19*

0.18*

0.19*

-0.17*

0.14*

0.03

0.14*

-0.35*

-0.19*

0.29*

-0.27*

-0.27*

-0.20*

-0.11*

0.16*

0.00

-0.05

-0.21*

0.03

0.00

0.05

0.05

-0.02

-0.03

0.06

0.08

0.14*

-0.01

0.00

0.01

0.12*

Figure A365: R Summary of Other Financial Indicators - Subgroup SC
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

Nation
Wellness

Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

0.44*

-0.04

-0.24

0.24

n/a

0.21

0.35*

0.04

-0.21

0.43*

n/a

0.35*

-0.42*

-0.07

0.17

-0.23

n/a

-0.28

-0.18

0.07

-0.15

0.20

n/a

0.02

-0.04

0.21

0.17

-0.02

n/a

0.14

0.12

0.26

0.18

0.06

n/a

0.28

A203

Appendix N: R Results Between Other Activity Indicators and Demographic
Indices (continued)
Figure A366: R Summary of Other Financial Indicators - Subgroup SM
Financial Indicators
Demographic Indices
Education Workforce Language Housing
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

Income

Nation
Wellness

0.28*

0.10

-0.06

-0.09

n/a

0.08

0.17

0.23

0.01

-0.14

n/a

0.08

-0.21

-0.26*

0.11

0.03

n/a

-0.12

-0.22

0.10

0.05

0.04

n/a

-0.01

-0.11

0.20

-0.05

0.09

n/a

0.06

0.00

0.29*

-0.07

0.08

n/a

0.12

Figure A367: R Summary of Other Financial Indicators - Subgroup SR
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

Nation
Wellness

Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

-0.35

-0.30

-0.06

0.09

n/a

-0.27

-0.21

-0.09

-0.23

0.30

n/a

-0.13

-0.02

0.36

0.04

-0.02

n/a

0.16

-0.03

0.20

-0.49*

-0.27

n/a

-0.33

0.47*

-0.11

0.02

-0.07

n/a

0.13

0.46

-0.05

-0.04

-0.09

n/a

0.09

A204

Appendix N: R Results Between Other Activity Indicators and Demographic
Indices (continued)
Figure A368: R Summary of Other Financial Indicators - Subgroup MC
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

0.36*

0.09

-0.31*

0.40*

0.18

0.25*

0.18

0.22

-0.16

0.18

0.04

0.17

-0.28*

-0.01

0.23*

-0.33*

-0.13

-0.18

-0.13

0.29*

0.10

-0.16

0.09

0.04

-0.17

-0.03

0.08

-0.11

-0.05

-0.12

-0.19

0.03

0.04

-0.06

-0.08

-0.10

Figure A369: R Summary of Other Financial Indicators - Subgroup MM
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

Nation
Wellness

Nation
Wellness

0.35*

0.28*

-0.18

0.28*

0.27*

0.31*

0.22*

0.29*

-0.09

0.30*

0.21*

0.31*

-0.19*

-0.19*

0.00

-0.22*

-0.25*

-0.27*

-0.08

0.06

-0.07

-0.05

-0.09

-0.06

-0.12

-0.09

0.25*

-0.05

-0.12

0.01

-0.13

0.01

0.30*

0.05

-0.06

0.12

A205

Appendix N: R Results Between Other Activity Indicators and Demographic
Indices (continued)
Figure A370: R Summary of Other Financial Indicators - Subgroup MR
Financial Indicators
Demographic Indices
Education Workforce Language Housing Income
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

Nation
Wellness

0.28

0.17

-0.43*

0.09

-0.07

-0.20

0.29*

0.09

-0.21

-0.04

-0.09

-0.09

-0.30*

-0.26

0.38*

0.00

-0.08

0.11

-0.38*

-0.15

0.19

-0.20

-0.48*

-0.11

0.08

0.12

-0.05

-0.19

0.32*

-0.00

0.03

0.12

-0.11

-0.27

0.10

-0.12

Figure A371: R Summary of Other Financial Indicators - Subgroup LC
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

Nation
Wellness

Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

0.52*

0.28

-0.40*

0.53*

0.37*

0.38*

0.13

0.16

-0.03

0.15

-0.16

0.08

-0.29

-0.31*

0.30

-0.31*

-0.35*

-0.28

-0.10

-0.15

0.34*

-0.10

-0.31

-0.03

-0.15

0.11

0.00

-0.03

0.02

-0.02

-0.07

0.18

-0.03

0.05

0.05

0.05

A206

Appendix N: R Results Between Other Activity Indicators and Demographic
Indices (continued)
Figure A372: R Summary of Other Financial Indicators - Subgroup LM
Financial Indicators
Demographic Indices
Education Workforce Language Housing
Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

Income

Nation
Wellness

0.36*

0.23

-0.24

0.30

0.22

0.12

0.36*

0.17

-0.26

0.19

0.23

0.06

-0.46*

-0.21

0.24

-0.40*

-0.18

-0.18

-0.10

0.11

0.07

-0.21

0.15

-0.00

0.20

-0.07

0.10

0.17

-0.07

0.16

0.21

-0.06

0.08

0.16

-0.07

0.15

Figure A373: R Summary of Other Financial Indicators - Subgroup LR
Financial Indicators
Demographic Indices
Education Workforce Language Housing

Income

Nation
Wellness

Earned & other revenue
ratio
Earned & other revenue
capita
Federal & provincial
revenue ratio
Federal & provincial
revenue capita
Tribal gov't & other FN
entity revenue ratio
Tribal gov't & other FN
entity revenue capita

0.53

0.79*

-0.65*

0.39

0.66*

0.05

0.49

0.63*

-0.68*

0.31

0.69*

-0.06

-0.46

-0.80*

0.56*

-0.30

-0.66*

-0.08

-0.13

-0.01

-0.24

0.26

0.06

-0.16

-0.12

0.29

0.17

-0.25

0.22

0.14

0.05

0.42

-0.15

-0.14

0.41

0.01

A207

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups
Note that r results with an asterisk indicate that the correlation is statistically significant at
the 5% level. The r value is presented, along with an * indicator showing statistical
significance.

Education Index and Workforce Index
The results are reviewed below for the education index and workforce index correlations:


Total population: 0.41*. Refer to Table 31 and Appendix R, Figure A570.



Subgroup SC: 0.04. Refer to Table 32.



Subgroup SM: 0.23. Refer to Table 33.



Subgroup SR: 0.21. Refer to Table 34.



Subgroup MC: 0.43*. Refer to Table 35 and Appendix R, Figure A589.



Subgroup MM: 0.57*. Refer to Table 36 and Appendix R, Figure A599.



Subgroup MR: 0.44*. Refer to Table 37 and Appendix R, Figure A607.



Subgroup LC: 0.57*. Refer to Table 38 and Appendix R, Figure A613.



Subgroup LM: 0.69*. Refer to Table 39 and Appendix R, Figure A625.



Subgroup LR: 0.64*. Refer to Table 40 and Appendix R, Figure A636.

Education Index and Income Index
The results are reviewed below for the education index and income index correlations:


Total population: 0.45*. Refer to Table 31 and Appendix R, Figure A573. Note that
the correlation increases substantially at first, and then levels off as the income index
is higher.



Subgroups SC, SM, and SR: no income data is available for these small population
subgroups due to data quality issues with the data from Statistics Canada. Therefore,
no correlation is available.



Subgroup MC: 0.43*. Refer to Table 35 and Appendix R, Figure A592.



Subgroup MM: 0.34*. Refer to Table 36.



Subgroup MR: 0.41*. Refer to Table 37 and Appendix R, Figure A609.

A208

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)


Subgroup LC: 0.59*. Refer to Table 38 and Appendix R, Figure A616.



Subgroup LM: 0.44*. Refer to Table 39 and Appendix R, Figure A627.



Subgroup LR: 0.75*. Refer to Table 40 and Appendix R, Figure A639.

Education Index and Language Index
The results are reviewed below for the education index and language index correlations:


Total population: -0.54*. Refer to Table 31 and Appendix R, Figure A571.



Subgroup SC: -0.01. Refer to Table 32.



Subgroup SM: -0.26*. Refer to Table 33.



Subgroup SR: -0.17. Refer to Table 34.



Subgroup MC: -0.42*. Refer to Table 35 and Appendix R, Figure A590.



Subgroup MM: -0.39*. Refer to Table 36.



Subgroup MR: -0.47*. Refer to Table 37 and Appendix R, Figure A608.



Subgroup LC: -0.69*. Refer to Table 38 and Appendix R, Figure A614.



Subgroup LM: -0.20. Refer to Table 39.



Subgroup LR: -0.54*. Refer to Table 40 and Appendix R, Figure A637.

Education Index and Housing Index
The results are reviewed below for the education index and housing index correlations:


Total population: 0.44*. Refer to Table 31 and Appendix R, Figure A572.



Subgroup SC: -0.07. Refer to Table 32.



Subgroup SM: 0.08. Refer to Table 33.



Subgroup SR: -0.11. Refer to Table 34.



Subgroup MC: 0.50*. Refer to Table 35 and Appendix R, Figure A591.



Subgroup MM: 0.39*. Refer to Table 36.



Subgroup MR: 0.22. Refer to Table 37.



Subgroup LC: 0.67*. Refer to Table 38 and Appendix R, Figure A615.



Subgroup LM: 0.59*. Refer to Table 39 and Appendix R, Figure A626.



Subgroup LR: 0.53. Refer to Table 40 and Appendix R, Figure A638.
A209

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Education Index and Nation Wellness Index
The results are reviewed below for the education index and Nation wellness index
correlations:


Total population: 0.51*. Refer to Table 31 and Appendix R, Figure A574.



Subgroup SC: 0.39*. Refer to Table 32.



Subgroup SM: 0.43*. Refer to Table 33 and Appendix R, Figure A583.



Subgroup SR: 0.34. Refer to Table 34.



Subgroup MC: 0.71*. Refer to Table 35 and Appendix R, Figure A593.



Subgroup MM: 0.57*. Refer to Table 36 and Appendix R, Figure A600.



Subgroup MR: 0.24. Refer to Table 37.



Subgroup LC: 0.60*. Refer to Table 38 and Appendix R, Figure A617.



Subgroup LM: 0.57*. Refer to Table 39 and Appendix R, Figure A628.



Subgroup LR: 0.31. Refer to Table 40.

Workforce Index and Language Index
The results are reviewed below for the workforce index and language index correlations:


Total population: -0.23*. Refer to Table 31.



Subgroup SC: 0.38*. Refer to Table 32.



Subgroup SM: 0.04. Refer to Table 33.



Subgroup SR: 0.08. Refer to Table 34.



Subgroup MC: -0.11. Refer to Table 35.



Subgroup MM: -0.28*. Refer to Table 36.



Subgroup MR: -0.38*. Refer to Table 37.



Subgroup LC: -0.31*. Refer to Table 38.



Subgroup LM: -0.03. Refer to Table 39.



Subgroup LR: -0.48. Refer to Table 40 and Appendix R, Figure A640.

A210

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Workforce Index and Housing Index
The results are reviewed below for the workforce index and housing index correlations:


Total population: 0.36*. Refer to Table 31.



Subgroup SC: 0.06. Refer to Table 32.



Subgroup SM: 0.35*. Refer to Table 33.



Subgroup SR: 0.24. Refer to Table 34.



Subgroup MC: 0.05. Refer to Table 35.



Subgroup MM: 0.52*. Refer to Table 36 and Appendix R, Figure A601.



Subgroup MR: 0.18. Refer to Table 37.



Subgroup LC: 0.48*. Refer to Table 38 and Appendix R, Figure A618.



Subgroup LM: 0.54*. Refer to Table 39 and Appendix R, Figure A629.



Subgroup LR: 0.55*. Refer to Table 40 and Appendix R, Figure A641.

Workforce Index and Income Index
The results are reviewed below for the workforce index and income index correlations:


Total population: 0.56*. Refer to Table 31 and Appendix R, Figure A575.



Subgroups SC, SM, and SR: no income data is available for these small population
subgroups due to data quality issues with the data from Statistics Canada. Therefore,
no correlation is available.



Subgroup MC: 0.34*. Refer to Table 35.



Subgroup MM: 0.54*. Refer to Table 36 and Appendix R, Figure A602.



Subgroup MR: 0.54*. Refer to Table 37 and Appendix R, Figure A610.



Subgroup LC: 0.74*. Refer to Table 38 and Appendix R, Figure A619.



Subgroup LM: 0.78*. Refer to Table 39 and Appendix R, Figure A630.



Subgroup LR: 0.74*. Refer to Table 40 and Appendix R, Figure A642.

A211

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Workforce Index and Nation Wellness Index
The results are reviewed below for the workforce index and Nation wellness index
correlations:


Total population: 0.69*. Refer to Table 31 and Appendix R, Figure A576.



Subgroup SC: 0.67*. Refer to Table 32 and Appendix R, Figure A580.



Subgroup SM: 0.69*. Refer to Table 33 and Appendix R, Figure A584.



Subgroup SR: 0.67*. Refer to Table 34 and Appendix R, Figure A586.



Subgroup MC: 0.64*. Refer to Table 35 and Appendix R, Figure A594.



Subgroup MM: 0.74*. Refer to Table 36 and Appendix R, Figure A603.



Subgroup MR: 0.38*. Refer to Table 37.



Subgroup LC: 0.77*. Refer to Table 38 and Appendix R, Figure A620.



Subgroup LM: 0.69*. Refer to Table 39 and Appendix R, Figure A631.



Subgroup LR: 0.37. Refer to Table 40.

Language Index and Housing Index
The results are reviewed below for the language index and housing index correlations:


Total population: -0.37*. Refer to Table 31.



Subgroup SC: -0.29. Refer to Table 32.



Subgroup SM: 0.06. Refer to Table 33.



Subgroup SR: 0.06. Refer to Table 34.



Subgroup MC: -0.46*. Refer to Table 35 and Appendix R, Figure A595.



Subgroup MM: -0.23*. Refer to Table 36.



Subgroup MR: -0.31*. Refer to Table 37.



Subgroup LC: -0.48*. Refer to Table 38 and Appendix R, Figure A621.



Subgroup LM: -0.16. Refer to Table 39.



Subgroup LR: -0.09. Refer to Table 40.

A212

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Language Index and Income Index
The results are reviewed below for the language index and income index correlations:


Total population: -0.23*. Refer to Table 31.



Subgroups SC, SM, and SR: no income data is available due to data quality issues. As
such, no correlation analysis is possible.



Subgroup MC: -0.26*. Refer to Table 35.



Subgroup MM: -0.19*. Refer to Table 36.



Subgroup MR: -0.01. Refer to Table 37.



Subgroup LC: -0.31. Refer to Table 38.



Subgroup LM: 0.06. Refer to Table 39.



Subgroup LR: -0.46. Refer to Table 40 and Appendix R, Figure A643.

Language Index and Nation Wellness Index
The results are reviewed below for the language index and Nation wellness index
correlations:


Total population: 0.09. Refer to Table 31.



Subgroup SC: 0.44*. Refer to Table 32 and Appendix R, Figure A581.



Subgroup SM: 0.36*. Refer to Table 33.



Subgroup SR: 0.58*. Refer to Table 34 and Appendix R, Figure A587.



Subgroup MC: -0.04. Refer to Table 35.



Subgroup MM: 0.12. Refer to Table 36.



Subgroup MR: 0.49*. Refer to Table 37 and Appendix R, Figure A611.



Subgroup LC: -0.06. Refer to Table 38.



Subgroup LM: 0.58*. Refer to Table 39 and Appendix R, Figure A632.



Subgroup LR: 0.51. Refer to Table 40 and Appendix R, Figure A644.

A213

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Housing Index and Income Index
The results are reviewed below for the housing index and income index correlations:


Total population: 0.50*. Refer to Table 31 and Appendix R, Figure A577.



Subgroups SC, SM, and SR: the income data is not available for these subgroups due
to data quality issues. As such, no correlational analysis was conducted for these
subgroups.



Subgroup MC: 0.50*. Refer to Table 35 and Appendix R, Figure A596.



Subgroup MM: 0.44*. Refer to Table 36 and Appendix R, Figure A604.



Subgroup MR: 0.34*. Refer to Table 37.



Subgroup LC: 0.56*. Refer to Table 38 and Appendix R, Figure A622.



Subgroup LM: 0.52*. Refer to Table 39 and Appendix R, Figure A633.



Subgroup LR: 0.49. Refer to Table 40 and Appendix R, Figure A645.

Housing Index and Nation Wellness Index
The results are reviewed below for the housing index and Nation wellness index correlations:


Total population: 0.66*. Refer to Table 31 and Appendix R, Figure A578.



Subgroup SC: 0.51*. Refer to Table 32 and Appendix R, Figure A582.



Subgroup SM 0.75*. Refer to Table 33 and Appendix R, Figure A585.



Subgroup SR: 0.54*. Refer to Table 34 and Appendix R, Figure A588.



Subgroup MC: 0.63*. Refer to Table 35 and Appendix R, Figure A597.



Subgroup MM: 0.75*. Refer to Table 36 and Appendix R, Figure A605.



Subgroup MR: 0.34*. Refer to Table 37.



Subgroup LC: 0.72*. Refer to Table 38 and Appendix R, Figure A623.



Subgroup LM: 0.58*. Refer to Table 39 and Appendix R, Figure A634.



Subgroup LR: 0.70*. Refer to Table 40 and Appendix R, Figure A646.

A214

Appendix O: Correlational Analysis, Results, and Referencing – Amongst Demographic
Indices for Total Population and Subgroups (continued)

Income Index and Nation Wellness Index
The results are reviewed below for the income index and Nation wellness index correlations:


Total population: 0.71*. Refer to Table 31 and Appendix R, Figure A579.



Subgroups SC, SM, and SR: the income data is not available for these subgroups due
to data quality issues. As such, no correlational analysis has been conducted.



Subgroup MC: 0.68*. Refer to Table 35 and Appendix R, Figure A598.



Subgroup MM: 0.66*. Refer to Table 36 and Appendix R, Figure A606.



Subgroup MR: 0.73*. Refer to Table 37 and Appendix R, Figure A612.



Subgroup LC: 0.84*. Refer to Table 38 and Appendix R, Figure A624.



Subgroup LM: 0.65*. Refer to Table 39 and Appendix R, Figure A635.



Subgroup LR: 0.37. Refer to Table 40.

A215

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population
Note that r results with an asterisk indicate that the correlation is statistically significant at
the 5% level. The r value is presented along with an * when statistical significance is present.

Business Activity Indicators/GBE Activity Indicators and Demographic Indices
Education
 Investment asset capita (0.10*). Refer to Table 41 and Appendix R, Figure A649.


Gross business sales ratio (0.17*). Refer to Table 41 and Appendix R, Figure A654.



Gross business sales capita (0.17*). Refer to Table 41 and Appendix R, Figure A659.



Business and economic development expense ratio (0.21*). Refer to Table 41 and
Appendix R, Figure A664.



Business and economic development expense capita (0.17*). Refer to Table 41 and
Appendix R, Figure A669.

Workforce
 Investment asset capita (0.16*). Refer to Table 41 and Appendix R, Figure A650.


Gross business sales ratio (0.12*). Refer to Table 41 and Appendix R, Figure A655.



Gross business sales capita (0.18*). Refer to Table 41 and Appendix R, Figure A660.



Business and economic development expense ratio (0.19*). Refer to Table 41 and
Appendix R, Figure A665.



Business and economic development expense capita (0.23*). Refer to Table 41 and
Appendix R, Figure A670.



GBE asset capita (0.17*). Refer to Table 42 and Appendix R, Figure A675.



GBE revenue capita (0.15*). Refer to Table 42 and Appendix R, Figure A682.



GBE expense capita (0.18*). Refer to Table 42 and Appendix R, Figure A689.



GBE equity capita (0.11*). Refer to Table 42 and Appendix R, Figure A694.

Language
 Gross business sales ratio (-0.16*). Refer to Table 41 and Appendix R, Fig. A656.


Gross business sales capita (-0.16*). Refer to Table 41 and Appendix R, Fig. A661.



Business and economic development expense ratio (-0.24*). Refer to Table 41 and
Appendix R, Fig. A666.
A216

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population (continued)


Business and economic development expense capita (-0.20*). Refer to Table 41 and
Appendix R, Figure A671.

Housing
 Investment asset capita (0.19*). Refer to Table 41 and Appendix R, Figure A651.


Gross business sales ratio (0.14*). Refer to Table 41 and Appendix R, Figure A657.



Gross business sales capita (0.18*). Refer to Table 41 and Appendix R, Figure A662.



Business and economic development expense ratio (0.19*). Refer to Table 41 and
Appendix R, Figure A667.



Business and economic development expense capita (0.18*). Refer to Table 41 and
Appendix R, Figure A672.



GBE asset capita (0.16*). Refer to Table 42 and Appendix R, Figure A676.



GBE revenue ratio (0.13*). Refer to Table 42 and Appendix R, Figure A679.



GBE revenue capita (0.16*). Refer to Table 42 and Appendix R, Figure A683.



GBE expense ratio (0.11*). Refer to Table 42 and Appendix R, Figure A686.



GBE expense capita (0.16*). Refer to Table 42 and Appendix R, Figure A690.



GBE equity capita (0.12*). Refer to Table 42 and Appendix R, Figure A695.

Income
 Investment asset ratio (0.21*). Refer to Table 41 and Appendix R, Figure A648.


Investment asset capita (0.27*). Refer to Table 41 and Appendix R, Figure A652.



GBE asset ratio (0.18*). Refer to Table 42 and Appendix R, Figure A674.



GBE asset capita (0.19*). Refer to Table 42 and Appendix R, Figure A677.



GBE revenue ratio (0.22*). Refer to Table 42 and Appendix R, Figure A680.



GBE revenue capita (0.18*). Refer to Table 42 and Appendix R, Figure A684.



GBE expense ratio (0.20*). Refer to Table 42 and Appendix R, Figure A687.



GBE expense capita (0.19*). Refer to Table 42 and Appendix R, Figure A691.



GBE equity ratio (0.30*). Refer to Table 42 and Appendix R, Figure A693.

A217

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population (continued)


GBE equity capita (0.41*). Refer to Table 42 and Appendix R, Figure A696.



GBE net income capita (-0.18*). Refer to Table 42 and Appendix R, Figure A698.

Nation Wellness
 Investment asset capita (0.20*). Refer to Table 41 and Appendix R, Figure A653.


Gross business sales capita (0.14*). Refer to Table 41 and Appendix R, Figure A663.



Business and economic development expense ratio (0.09*). Refer to Table 41 and
Appendix R, Figure A668.



Business and economic development expense capita (0.13*). Refer to Table 41 and
Appendix R, Figure A673.



GBE asset capita (0.17*). Refer to Table 42 and Appendix R, Figure A678.



GBE revenue ratio (0.12*). Refer to Table 42 and Appendix R, Figure A681.



GBE revenue capita (0.17*). Refer to Table 42 and Appendix R, Figure A685.



GBE expense ratio (0.12*). Refer to Table 42 and Appendix R, Figure A688.



GBE expense capita (0.18*). Refer to Table 42 and Appendix R, Figure A692.



GBE equity capita (0.14*). Refer to Table 42 and Appendix R, Figure A697.

Trust Activity Indicators and Demographic Indices
Workforce
 Trust revenue capita (0.12*). Refer to Table 43 and Appendix R, Figure A701. Note
that an outlier exaggerates this correlation.
Housing
 Trust fund assets ratio (-0.11*). Refer to Table 43 and Appendix R, Figure A699.
Note that an outlier exaggerates this correlation.
Nation Wellness
 Trust fund assets ratio (-0.11*). Refer to Table 43 and Appendix R, Figure A700.


Trust revenue capita (0.10*). Refer to Table 43 and Appendix R, Figure A702.

A218

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population (continued)

TCA Activity Indicators and Demographic Indices
Education
 TCA ratio (-0.19*). Refer to Table 44 and Appendix R, Figure A703. Note that the
correlation initially trends upward, and then trends downward.
Workforce
 TCA ratio (-0.23*). Refer to Table 44 and Appendix R, Figure A704.


TCA capita (0.24*). Refer to Table 44 and Appendix R, Figure A709.



Gross cash outflows from capital capita (-0.18*). Refer to Table 44 and Appendix R,
Figure A712.

Language
 TCA ratio (0.17*). Refer to Table 44 and Appendix R, Figure A705.


Gross cash outflows from capital ratio (0.12*). Refer to Table 44 and Appendix R,
Figure A711.

Housing
 TCA ratio (-0.19*). Refer to Table 44 and Appendix R, Figure A706.
Income
 TCA ratio (-0.43*). Refer to Table 44 and Appendix R, Figure A707.
Nation Wellness
 TCA ratio (-0.22*). Refer to Table 44 and Appendix R, Figure A708.


TCA capita (0.12*). Refer to Table 44 and Appendix R, Figure A710.

Other Activity Indicators and Demographic Indices
Education
 Earned & other revenue ratio (0.38*). Refer to Table 45 and Appendix R, Figure
A713.


Earned & other revenue capita (0.18*). Refer to Table 45 and Appendix R, Figure
A719.

A219

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population (continued)


Federal & provincial revenue ratio (-0.35*). Refer to Table 45 and Appendix R,
Figure A724.



Federal & provincial revenue capita (-0.11*). Refer to Table 45 and Appendix R,
Figure A730.

Workforce
 Earned & other revenue ratio (0.17*). Refer to Table 45 and Appendix R, Figure
A714.


Earned & other revenue capita (0.19*). Refer to Table 45 and Appendix R, Figure
A720.



Federal & provincial revenue ratio (-0.19*). Refer to Table 45 and Appendix R,
Figure A725.



Federal & provincial revenue capita (0.16*). Refer to Table 45 and Appendix R,
Figure A731.



Tribal government & other First Nation entity revenue capita (0.14*). Refer to Table
45 and Appendix R, Figure A733.

Language
 Earned & other revenue ratio (-0.33*). Refer to Table 45 and Appendix R, Figure
A715.


Earned & other revenue capita (-0.17*). Refer to Table 45 and Appendix R, Figure
A721.



Federal & provincial revenue ratio (0.29*). Refer to Table 45 and Appendix R, Figure
A726.

Housing
 Earned & other revenue ratio (0.31*). Refer to Table 45 and Appendix R, Figure
A716.


Earned & other revenue capita (0.14*). Refer to Table 45 and Appendix R, Figure
A722.

A220

Appendix P: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Total Population (continued)


Federal & provincial revenue ratio (-0.27*). Refer to Table 45 and Appendix R,
Figure A727.

Income
 Earned & other revenue ratio (0.26*). Refer to Table 45 and Appendix R, Figure
A717.


Federal & provincial revenue ratio (-0.27*). Refer to Table 45 and Appendix R,
Figure A728.



Federal & provincial revenue capita (-0.21*). Refer to Table 45 and Appendix R,
Figure A732.

Nation Wellness
 Earned & other revenue ratio (0.19*). Refer to Table 45 and Appendix R, Figure
A718.


Earned & other revenue capita (0.14*). Refer to Table 45 and Appendix R, Figure
A723.



Federal & provincial revenue ratio (-0.20*). Refer to Table 45 and Appendix R,
Figure A729.



Tribal government and other First Nation entity revenue capita (0.12*). Refer to
Table 45 and Appendix R, Figure A734.

A221

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups
Note that r results with an asterisk indicate that the correlation is statistically significant at
the 5% level. The r value is presented along with an * when statistical significance is present.

Between Business Activity Indicators/GBE Activity Indicators and Demographic
Indices
Education Index
 GBE activity indicators correlation for subgroup SC: GBE asset ratio/capita (0.47*,
0.40*), GBE revenue ratio/capita (0.48*, 0.47*), and GBE expense ratio/capita
(0.51*, 0.55*). Refer to Appendix K, Figure A335 and Appendix R Figures A393 –
A398.


GBE activity indicators correlation for subgroup SR: GBE asset ratio (-0.50*), and
GBE net income ratio (-0.59*). Refer to Appendix K, Figure A337 and Appendix R
Figures A403 and A405.



GBE activity indicators correlation for subgroup LR: GBE revenue capita (0.63*),
GBE expense capita (0.68*), and GBE net income ratio (-0.61*). Refer to Appendix
K, Figure A343 and Appendix R, Figures A441 and A446, and A447.

Workforce Index
 GBE activity indicators for subgroup SM: GBE asset capita (0.43*), GBE revenue
ratio/capita (0.33*, 0.41*), GBE expense ratio/capita (0.35*, 0.40*), and GBE equity
capita (0.44*). Refer to Appendix K, Figure A336 and Appendix R Figures A399 –
A402. Note that these correlations are exaggerated by one outlier, even though a
general positive correlation still exists.


Business activity indicators for subgroup MM: investment asset capita (0.27*), gross
business sales ratio/capita (0.19*, 0.23*), and business & economic development
expense ratio/capita (0.23*, 0.23*). Refer to Appendix J, Figure A329.



Business activity indicators for subgroup LR: a positive weak correlation exists (but
not statistically significant) for investment asset ratio/capita (0.45, 0.40). Refer to
Appendix J, Figure A333 and Appendix R Figures A384-A385.

A222

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


GBE activity indicators for subgroup LR: the following non-statistically significant
correlations are present – GBE revenue capita (0.44), and GBE expense capita (0.44).
Refer to Appendix K, Figure A343 and Appendix R, Figures A442 and A448.

Income Index
 Business activity indicators for subgroup MC: investment asset ratio/capita (0.27*,
0.28*). Refer to Appendix J, Figure A328.


GBE activity indicators for subgroup MC: GBE asset capita (0.27*), GBE expense
ratio (0.26*), and GBE equity ratio/capita (0.30*, 0.32*). Refer to Appendix K,
Figure A338.



Business activity indicators for subgroup MM: investment asset ratio/capita (0.24*,
0.37*), and gross business sales ratio/capita (0.24*, 0.25*). Refer to Appendix J,
Figure A329.



GBE activity indicators for subgroup MM: GBE asset ratio/capita (0.27*, 0.23*),
GBE revenue ratio/capita (0.38*, 0.40*), GBE expense ratio/capita (0.34*, 0.40*),
and GBE equity ratio/capita (0.32*, 0.56*). Refer to Appendix K, Figure A339 and
Appendix R, Figures A417 – A419.



GBE activity indicators for subgroup MR: GBE revenue ratio (0.40*), GBE equity
ratio (0.52*), and GBE net income capita (0.35*). Refer to Appendix K, Figure A340
and Appendix R, Figures A424 and A426.



GBE activity indicators for subgroup LC: GBE asset capita (0.43*), and GBE equity
ratio/capita (0.35*, 0.43*). Refer to Appendix K, Figure A341 and Appendix R,
Figures A427 and A428.



GBE activity indicators for subgroup LM: GBE revenue capita (0.50*), and GBE
expense ratio/capita (0.43*, 0.53*). Refer to Appendix K, Figure A342 and Appendix
R, Figures A429-A431.



Business activity indicators for subgroup LR: investment asset ratio/capita (0.62*,
0.74*). Refer to Appendix J, Figure A333 and Appendix R, Figures A388 – A389.
Note that one outlier exaggerates the correlation for the investment asset capita.
A223

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


GBE activity indicators for subgroup LR: GBE revenue capita (0.61*) and GBE
expense capita (0.64*). The following non-statistically significant relations exist:
GBE asset capita (0.47), and GBE net income ratio (-0.43). Refer to Appendix K,
Figure A343 and Appendix R, Figures A432, A445, A451, and A456.

Housing Index
 Business activity indicators for subgroup SC: gross business sales ratio/capita (0.49*,
0.55*), and business & economic development expense ratio/capita (0.50*, 0.58*).
Refer to Appendix J, Figure A325 and Appendix R, Figures A374 – A377.


Business activity indicators for subgroup SR: investment asset capita (0.52*), and
gross business sales capita (-0.46*). Refer to Appendix J, Figure A327 and Appendix
R, Figures A379 and A380.



GBE activity indicators for subgroup SR: statistically significant correlations exist for
all GBE indicators * except for the GBE net income ratio. Refer to Appendix K,
Figure A337 and Appendix R, Figures A406 – A416.



Business activity indicators for subgroup MM: investment asset ratio (0.20*), gross
business sales capita (0.20*), and business & economic development expense
ratio/capita (0.24*, 0.25*). Refer to Appendix J, Figure A329.



GBE activity indicators for subgroup MM: GBE revenue capita (0.21*), and GBE
expense capita (0.21*). Refer to Appendix K, Figure A339.



GBE activity indicators for subgroup MR: GBE revenue ratio (0.42*), and GBE
expense ratio (0.43*). Refer to Appendix K, Figure A340 and Appendix R, Figures
A423, and A425.



GBE activity indicators for subgroup LR: non-statistically significant correlations
exist for GBE revenue capita (0.47) and GBE expense capita (0.51). Refer to
Appendix K, Figure A343 and Appendix R, Figures A444, and A450.

A224

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)
Language Index
 Business activity indicators for subgroup MR: gross business sales ratio/capita
(-0.30*, -0.33*), and business & economic development expense ratio/capita (-0.43*,
-0.41*). Refer to Appendix J, Figure A330 and Appendix R, Figures A381 and A382.


Business activity indicators for subgroup LR: business & economic development
expense ratio/capita (-0.55*, -0.64*). Refer to Appendix J, Figure A333 and
Appendix R, Figures A386 and A387.



GBE activity indicators for subgroup LR: GBE net income capita (0.59*). The
following non-statistically significant correlations exist: GBE revenue capita (-0.42),
GBE expense capita (-0.49), GBE equity ratio (0.46), GBE equity capita (0.45), and
GBE net income ratio (0.56). Refer to Appendix K, Figure A343 and Appendix R,
Figures A443, A449, A452, A453, A455, and A458. A unique trend emerges in most
of these indicators. As the language index increases, the trend line is negative, but
then trends positively.

Nation Wellness Index
 Business activity indicators for subgroup SC: gross business sales ratio/capita (0.38*,
0.44*) and business & economic development expense capita (0.38*). Refer to
Appendix J, Figure A325 and Appendix R, Figure A378.


GBE activity indicators for subgroup SM: GBE asset capita (0.30*), GBE revenue
capita (0.31*), and GBE expense capita (0.32*). Refer to Appendix K, Figure A336.



Business activity indicators for subgroup MM: investment asset ratio/capita (0.19*,
0.21*), gross business sales ratio/capita (0.23*, 0.27*), and business & economic
development expense ratio/capita (0.22*, 0.20*). Refer to Appendix J, Figure A329.



GBE activity indicators for subgroup MM: GBE revenue ratio/capita (0.19*, 0.23*),
GBE expense capita (0.23*), and GBE equity capita (0.24*). Refer to Appendix K,
Figure A339.



GBE activity indicators for subgroup LC: GBE asset capita (0.33*), and GBE equity
ratio/capita (0.34*, 0.37*). Refer to Appendix K, Figure A341.
A225

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


Business activity indicators for subgroup LR: business & economic development
expense ratio/capita (-0.67*, -0.66*). Refer to Appendix J, Figure A333 and
Appendix R, Figures A390 and A391.



GBE activity indicators for subgroup LR: GBE asset capita (0.65*), and GBE equity
capita (not statistically significant of 0.43). Refer to Appendix K, Figure A343 and
Appendix R, Figures A433 and A459.

Between Trust Activity Indicators and Demographic Indices
Education Index
 Subgroup MM: trust fund assets ratio/capita (-0.25*, -0.21*). Refer to Appendix L,
Figure A349.


Subgroup LC: trust revenue ratio/capita (-0.33*, -0.31*). Refer to Appendix L, Figure
A351.



Subgroup LR: trust fund assets ratio (not statistically significant at 0.52) and trust
fund asset capita (0.60*). Refer to Appendix L, Figure A353 and Appendix R,
Figures A474 and A476.

Workforce Index
 Subgroup SR: trust fund assets ratio/capita (-0.46*, -0.56*), trust revenue ratio/capita
(-0.59*, -0.65*). Refer to Appendix L, Figure A347 and Appendix R, Figures A460,
A463, A467, and A469.


Subgroup LR: trust fund asset capita (not statistically significant at 0.46). Refer to
Appendix L, Figure A353 and Appendix R, Figure A477. This correlation is caused
by an outlier.

Income Index
 Subgroup LM: trust fund asset ratio/capita (0.38*, 0.52*). Refer to Appendix L,
Figure A352 and Appendix R, Figure A473.


Subgroup LR: trust fund asset capita (not statistically significant at 0.44). Refer to
Appendix L, Figure A353 and Appendix R, Figure A479. This correlation is caused
by an outlier.

A226

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)
Housing Index
 Subgroup SR: trust fund assets ratio/capita (-0.46*, -0.47*). Refer to Appendix L,
Figure A347 and Appendix R Figures A461 and A465.


Subgroup LC: trust fund assets capita (-0.34*), and trust revenue ratio/capita (-0.45*,
-0.42*). Refer to Appendix L, Figure A351 and Appendix R, Figures A471-A472.

Language Index
 Subgroup SR: trust fund assets capita (-0.47*). Refer to Appendix L, Figure A347
and Appendix R, Figure A464.


Subgroup MC: trust revenue ratio (0.30*). Refer to Appendix L, Figure A348.



Subgroup LR: trust fund assets ratio (not statistically significant at -0.52) and trust
fund assets capita (-0.55*). Refer to Appendix L, Figure A353 and Appendix R,
Figures A475 and A478.

Nation Wellness Index
 Subgroup SR: trust fund assets ratio/capita (-0.46*, -0.70*), and trust fund revenue
ratio/capita (-0.53*, -0.70*). Refer to Appendix L, Figure A347 and Appendix R,
Figures A462, A466, A468, and A470.


Subgroup MR: trust revenue ratio/capita (0.34*, 0.31*). Refer to Appendix L, Figure
A350.

Between Tangible Capital Asset (TCA) Activity Indicators and Demographic Indices
Education Index
 Subgroup LC: TCA ratio (-0.45*). Refer to Appendix M, Figure A361 and Appendix
R, Figure A499.


Subgroup LR: gross cash outflows from capital ratio (-0.61*). Refer to Appendix M,
Figure A363 and Appendix R, Figure A502.

Workforce Index
 Subgroup SM: TCA ratio (-0.31*), and gross cash outflows from capital capita
(-0.33*). Refer to Appendix M, Figure A356.


Subgroup MM: TCA ratio (-0.40*). Refer to Appendix M, Figure A359 and
Appendix R, Figure A495.
A227

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


Subgroup LR: gross cash outflows from capital ratio (not statistically significant at
-0.50). Refer to Appendix M, Figure A363 and Appendix R, Figure A503.

Income Index
 No income data is available for subgroups SC, SM, and SR due to data quality issues
for small population groups, and as such no correlation can be conducted for these
subgroups.


Subgroup MC: TCA ratio/capita (-0.30*, 0.25*). Refer to Appendix M, Figure A358.



Subgroup MM: TCA ratio/capita (-0.46*, 0.28*). Refer to Appendix M, Figure A359
and Appendix R, Figure A496.



Subgroup MR: TCA ratio (-0.43*), and gross cash outflows from capital ratio
(-0.47*). Refer to Appendix M, Figure A360 and Appendix R, Figures A497 and
A501.



Subgroup LC: TCA ratio (-0.48*). Refer to Appendix M, Figure A361 and Appendix
R, Figure A498.



Subgroup LR: TCA ratio (not statistically significant at -0.59) and gross cash
outflows from capital ratio (not statistically significant at -0.57). Refer to Appendix
M, Figure A363 and Appendix R, Figures A500 and A505.

Language Index
 Subgroup SR: TCA capita (-0.62*), and gross cash outflows from capital capita
(0.58*). Refer to Appendix M, Figure A357 and Appendix R, Figures A483, and
A489.


Subgroup LR: gross cash outflows from capital ratio (not statistically significant at
0.53). Refer to Appendix M, Figure A363 and Appendix R, Figure A504.

Housing Index
 Subgroup SC: TCA capita (0.46*). Refer to Appendix M, Figure A355 and Appendix
R, Figure A481.


Subgroup SR: TCA capita (-0.61*), and gross cash outflows from capital capita
(0.59*). Refer to Appendix M, Figure A357 and Appendix R, Figures A484 and
A490.
A228

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)
Nation Wellness Index
 Subgroup SR: TCA capita (-0.62*), and gross cash outflows from capital capita
(0.57*). Refer to Appendix M, Figure A357 and Appendix R, Figures A485 and
A491.

Between Other Activity Indicators and Demographic Indices
Education
 Subgroup SC: earned & other revenue ratio/capita (0.44*, 0.35*), and federal &
provincial revenue ratio (-0.42*). Refer to Appendix N, Figure A365 and Appendix
R, Figures A520 and A522.


Subgroup SM: earned & other revenue ratio (0.28*). Refer to Appendix N, Figure
A366.



Subgroup SR: Tribal gov’t & other FN entity revenue ratio (0.47*), and Tribal gov’t
& other FN entity revenue capita (not statistically significant at 0.46). Refer to
Appendix N, Figure A367 and Appendix R, Figures A528 and A529.



Subgroup MC: earned & other revenue ratio (0.36*), and fed & prov revenue ratio
(-0.28*). Refer to Appendix N, Fig. A368.



Subgroup MM: earned & other revenue ratio/capita (0.35*, 0.22*), and federal &
provincial revenue ratio (-0.19*). Refer to Appendix N, Figure A369.



Subgroup MR: earned & other revenue capita (0.29*), and federal & provincial
revenue ratio/capita (-0.30*, -0.38*). Refer to Appendix N, Figure A370.



Subgroup LC: earned & other revenue ratio (0.52*). Refer to Appendix N, Figure
A371 and Appendix R, Figure A537.



Subgroup LM: earned & other revenue ratio/capita (0.36*, 0.36*), and federal &
provincial revenue ratio (-0.46*). Refer to Appendix N, Figure A372 and Appendix
R, Figure A541.

A229

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


Subgroup LR: the following maintain non-statistically significant correlations –
earned & other revenue ratio/capita (0.53, 0.49) and a negative weak correlation for
federal & provincial revenue ratio (-0.46). Refer to Appendix N, Figure A373 and
Appendix R, Figures A556, A560, A566.

Workforce Index
 Subgroup SM: federal & provincial revenue ratio (-0.26*), and Tribal government &
other First Nation entity revenue capita (0.29*). Refer to Appendix N, Figure A366.


Subgroup MC: federal & provincial revenue capita (0.29*). Refer to Appendix N,
Figure A368.



Subgroup MM: earned & other revenue ratio/capita (0.28*, 0.29*), and federal &
provincial revenue ratio (-0.19*). Refer to Appendix N, Figure A369.



Subgroup LC: federal & provincial revenue ratio (-0.31*). Refer to Appendix N,
Figure A371.



Subgroup LR: earned & other revenue ratio/capita (0.79*, 0.63*), and federal &
provincial revenue ratio (-0.80*). Refer to Appendix N, Figure A373 and Appendix
R, Figures A557, A561, and A567. A non-statistically significant correlation exists
for Tribal government & other First Nation entity revenue capita (0.42). Refer to
Appendix N, Figure A373 and Appendix R, and Figure A564.

Income Index
 Subgroup MM: earned & other revenue ratio/capita (0.27*, 0.21*), and federal &
provincial revenue ratio (-0.25*). Refer to Appendix N, Figure A369.


Subgroup MR: federal & provincial revenue capita (-0.48*), and Tribal government
& other First Nation entity revenue ratio (0.32*). Refer to Appendix N, Figure A370
and Appendix R, Figure A534.



Subgroup LC: earned & other revenue ratio (0.37*), and federal & provincial revenue
ratio (-0.35*). Refer to Appendix N, Figure A371.

A230

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


Subgroup LR: earned & other revenue ratio/capita (0.66*, 0.69*), and federal &
provincial revenue ratio (-0.66*). A non-statistically significant correlation exists for
Tribal government & other First Nation entity revenue capita (0.41). Refer to
Appendix N, Figure A373 and Appendix R, Figures A559, A563, A569, and A565.

Language Index
 Subgroup SR: federal & provincial revenue capita (-0.49*). Refer to Appendix N,
Figure A367 and Appendix R, Figure A530.


Subgroup MC: earned & other revenue ratio (-0.31*), and federal & provincial
revenue ratio (0.23*). Refer to Appendix N, Figure A368.



Subgroup MM: Tribal government & other First Nation entity revenue ratio/capita
(0.25*, 0.30*). Refer to Appendix N, Figure A369.



Subgroup MR: earned & other revenue ratio (-0.43*), and federal & provincial
revenue ratio (0.38*). Refer to Appendix N, Figure A370 and Appendix R, Figure
A533.



Subgroup LC: earned & other revenue ratio (-0.40*), and federal & provincial
revenue capita (0.34*). Refer to Appendix N, Figure A371 and Appendix R, Figure
A538.



Subgroup LR: earned & other revenue ratio/capita (-0.65*, -0.68*), and federal &
provincial revenue ratio (0.56*). Refer to Appendix N, Figure A373 and Appendix R,
Figures A558, A562, and A568.

Housing Index
 Subgroup SC: earned & other revenue capita (0.43*). Refer to Appendix N, Figure
A365 and Appendix R, Figure A521.


Subgroup MC: earned & other revenue ratio (0.40*), and federal & provincial
revenue capita (-0.33*). Refer to Appendix N, Figure A368 and Appendix R, Figure
A531.



Subgroup MM: earned & other revenue ratio/capita (0.28*, 0.30*), and federal &
provincial revenue ratio (-0.22*). Refer to Appendix N, Figure A369.
A231

Appendix Q: Correlational Analysis, Results, and Referencing – Between Financial
Indicators and Demographic Indices for the Subgroups (continued)


Subgroup LC: earned & other revenue ratio (0.53*), and federal & provincial revenue
ratio (-0.31*). Refer to Appendix N, Figure A371 and Appendix R, Figure A539.



Subgroup LM: federal & provincial revenue ratio (-0.40*). Refer to Appendix N,
Figure A372 and Appendix R, Figure A542.

Nation Wellness Index
 Subgroup SC: earned & other revenue capita (0.35*). Refer to Appendix N, Figure
A365.


Subgroup MC: earned & other revenue ratio (0.25*). Refer to Appendix N, Figure
A368.



Subgroup MM: earned & other revenue ratio/capita (0.31*, 0.31*), and federal &
provincial revenue ratio (0.27*). Refer to Appendix N, Figure A369.



Subgroup LC: earned & other revenue ratio (0.38*). Refer to Appendix N, Figure
A371.

A232

A233

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Appendix S: Relationship of the Language Index with the Nation Wellness Index (NWI)
This appendix evaluates the relationship of the language index and the other subindices
included in the Nation wellness index. Table 31 presents the Pearson correlation coefficients
between the language index and the other subindices (education, workforce, housing, and
income). The Pearson correlation coefficients demonstrate statistically significant negative
correlations between the language index and all of the other subindices. This negative
correlation is distinct to the language index, as most of the other subindices maintain positive
correlations with each other. Tables 41 – 45 present the Pearson correlation coefficients
between the financial indicators and the demographic subindices. A curious trend emerges in
that the relationship of the language index to the financial indicators is often converse to the
relationship between the other subindices and the financial indicators. This means that when
the language index maintains a positive correlation with a given financial indicator, there is
often a negative correlation for the other subindices and vice-versa. Based on the
relationships found in Tables 31 and 41 – 45, there appears to be a statistically significant
relationship between the language index, the other sub-indices, and the financial indicators.
To better understand this relationship, two additional multiple linear regressions are
performed.
Multiple Linear Regression – Nation Wellness Index without the Language Index
The first regression evaluates the Nation wellness index calculated without the
language index (NwoL). For the sake of comparison, the original Nation wellness index (N)
with the language index is also presented in the regression results. Refer to Figure A735 for
the linear regression models, Table 8 for the description of the independent variables, and
Figure A736 for the regression results.
Figure A735: Linear Regression Models of Nation Wellness Index with (N) and without
(NwoL) the Language Index
Dependent Variable
Nation Wellness Index with Language
Index, same as Table 7 (N)
Nation Wellness Index without Language
Index, same calculation as per Appendix B
but excluding the Language Index (NwoL)

Regression Model
N= β0N + β1NX1 + β2NX2 + β3NX3 + β4NX4 +
β5NX5 + β6NX6 + β7NX7 + β8NX8 +β9NX9 + ε
NwoL= β0NwoL + β1 NwoLX1 + β2 NwoLX2 + β3
NwoLX3 + β4NwoLX4 + β5NwoLX5 + β6NwoLX6 +
β7NwoLX7 + β8NwoLX8 +β9NwoLX9

A324

Appendix S: Relationship of the Language Index with the NWI (continued)
Figure A736: Multiple Linear Regression – Average Marginal Effects of Variables on the
Nation Wellness Index with (N) and without (NwoL) the Language Index

Variable
Category

Variable

Earned & other revenue ratio
(per 0.1 change in ratio) (X1)
Federal & provincial revenue capita
(per $1,000) (X2)
Tribal Gov't and other FN entity
revenue capita (per $1,000) (X3)
Financial
GBE expense capita
(per $1,000) (X4)
Trust fund asset ratio
(per 0.1 change in ratio) (X5)
TCA assets ratio
(per 0.1 change in ratio) (X6)
Community Population
Population
(per 100 people) (X7)
Geographically medium differential
(from geographically close) (X8)
Geographic
Geographically remote differential
(from geographically close) (X9)
N
R-squared

1.63*
(0.27)
0.10
(0.04)
0.48*
(0.10)
0.03*
(0.01)
-0.73*
(0.26)
-1.24*
(0.27)
-0.36*
(0.07)
-4.72*
(1.23)
-12.33*
(1.63)

Nation Wellness
Index with
Language Index
(as per Table
46), N
0.77*
(0.26)
0.05
(0.05)
0.35*
(0.13)
0.03*
(0.00)
-0.68*
(0.25)
-0.84*
(0.24)
-0.07
(0.05)
-1.69
(1.12)
-1.16
(1.61)

446
0.35

446
0.13

Nation Wellness
Index without
Language Index,
NwoL

Notes:
1. Robust standard errors are reported in parentheses.
2. * indicates significance at the 5% level.

Multiple Linear Regression Results (N and NwoL) Discussion
The first regression compares the Nation wellness index without the language index
(NwoL) and the Nation wellness index with the language index (N). The results of this
regression are presented in Figure A736. The regression of NwoL maintains a much higher rsquared value of 0.35, compared to N at 0.13. Most of the financial indicators for NwoL
maintain higher beta coefficients compared to N. This is consistent with Tables 41 – 45,
which demonstrate that the language index often maintains a converse relationship with the
financial indicators compared to the other sub-indices. A partial “cancelling out” effect is

A325

Appendix S: Relationship of the Language Index with the NWI (continued)
present when the language index is included in the NWI.
A more pronounced difference between NwoL and N is present when comparing the
population and geographic variables. The community population beta coefficient for NwoL
is -0.36*, compared to N of -0.07. The geographically medium differential for NwoL is
-4.72* compared to N of -1.69. Likewise, the geographically remote differential is -12.33*,
compared to N of -1.16. These results demonstrate that the presence of the language index in
the Nation wellness index significantly reduces the explanatory power of the regression
model. A key reason for this is that many of the independent variables have a converse
relationship with the language index compared to the other subindices. Knowledge of
Indigenous language is an important aspect of cultural identity, so this theme is troubling. It
would be valuable to try and understand what factors influence the level of Indigenous
language knowledge. We have previously discussed that a statistically significant
relationship exists between the language index and the other subindices. To better understand
this relationship, a second regression is conducted in the following section. This regression
maintains the language index as the dependent variable and includes additional independent
variables.
Multiple Linear Regression – Language Index Including Additional Independent Variables
A second regression is performed with the language index as the dependent variable,
and includes additional independent variables. All aspects of this regression are the same as
the language index regression presented in Table 46, but include the additional independent
variables of the education index, workforce index, housing index, income index, and % of
population that are registered Indians (term as used by Indigenous Services Canada). As
additional independent variables are used in the second regression, the adjusted r-squared
values are reported. For the sake of comparison, the original language index regression from
Table 46 is also presented. Refer to Figure A737 for the linear regression models, Table 8 for
the description of the independent variables for the original language index (L), Figure A738
for the description of the independent variables for the recalculated language index (L2), and
Figure A739 for the regression results.

A326

Appendix S: Relationship of the Language Index with the NWI (continued)
Figure A737: Linear Regression Models of Language Index with (L2) and without (L) the
Additional Independent Variables
Dependent Variable
Language Index as originally
calculated, same as Table 7 (L)
Language Index with additional
independent variables (L2)

Regression Model
L= β0L + β1LX1 + β2LX2 + β3LX3 + β4LX4 + β5LX5 +
β6LX6 + β7LX7 + β8LX8 +β9LX9 + ε
L2= β0L2+ + β1L2X1 + β2L2X2 + β3L2X3 + β4L2X4 +
β5L2X5 + β6L2X6 + β7L2X7 + β8L2X8 + β9L2X9 +
β10L2X10 + β11L2X11 + β12L2X12 + β13L2X13 + β14L2X14
+ε

A327

Appendix S: Relationship of the Language Index with the NWI (continued)
Figure A738: Description of Independent Variables for the Language Index (L2) with the
Additional Independent Variables
Variable
Variable Name
Description of the Variable
Category
Earned & other revenue (Earned revenue + other revenue) / total
ratio (X1)
revenue 1
Federal & provincial
(Federal revenue + provincial revenue) /
revenue capita (X2)
community population 1, 2
Tribal Gov't and other
(Tribal government revenue + revenue from
First Nation entity
other FN entities) / community population 1, 2
revenue capita (X3)
Financial
GBE expense capita
Expenses in government business entities /
(X4)
community population 2, 3
Trust fund asset ratio
Trust funds assets / total financial assets 1
(X5)
TCA assets ratio (X6)
Tangible capital assets / total assets 1
Community population
(X7)
Population

Geographic

Demographic
Subindices

Population of people living on First Nation's
reserve land or associated Crown land.
Population figures are as per the 2016 Census.
% of population who
Population of people living on First Nation’s
are registered Indians
reserve land or associated Crown land that are
(X14)
registered Indians. Population figures are as
per the 2016 Census. Calculated as:
(Registered Indian) / (Total All Persons)
Geographically medium If First Nation community is geographically
differential (X8)
medium then 1; otherwise 0 4
Geographically remote If First Nation community is geographically
differential (X9)
remote then 1; otherwise 0 4
Education Index (X10)
Refer to Appendix B
Workforce Index (X11) Refer to Appendix B
Housing Index (X12)
Refer to Appendix B
Income Index (X13)
Refer to Appendix B

Notes:
1. Financial information to calculate the financial figures are taken from the audited 2016 First Nation
financial statements. Refer to Appendix A for further details about how each financial ratio and capita
measure if calculated.
2. Community population is based off of the population of people living on the First Nation’s reserve land or
associated Crown land. These figures are taken from the 2016 Census, which are prepared by Statistics
Canada.
3. Government business entity (GBE) figures are disclosed in the notes of the financial statements. The
expense in GBEs conveys the total expenses incurred in the First Nation’s GBEs for the year.
4. Indigenous Services Canada rates the level of geographic remoteness for each First Nation community from
zones 1-4. Refer to Appendix C for detailed definitions of these zones, and the geographic definitions used in
this study.

A328

Appendix S: Relationship of the Language Index with the NWI (continued)
Figure A739: Multiple Linear Regression – Average Marginal Effects of Variables on the
Language Index with (L2) and without (L) the Additional Independent Variables

Variable
Category

Financial

Population

Geographic

Variable

Earned & other revenue ratio
(per 0.1 change in ratio) (X1)
Federal & provincial revenue
capita (per $1,000) (X2)
Tribal Gov't and other FN entity
revenue capita (per $1,000) (X3)
GBE expense capita
(per $1,000) (X4)
Trust fund asset ratio
(per 0.1 change in ratio) (X5)
TCA assets ratio
(per 0.1 change in ratio) (X6)
Community population
(per 100 people) (X7)
% of population who are registered
Indians (per 1%) (X14)
Geographically medium
differential (from geographically
close) (X8)
Geographically remote differential
(from geographically close) (X9)
Education Index (X10)

Workforce Index (X11)
Demographic
Subindices Housing Index (X12)
Income Index (X13)

N
R-squared
Adjusted r-squared

Language Index
(with additional
independent
variables), L2
-1.01*
(0.41)
-0.20*
(0.07)
-0.14
(0.15)
0.00
(0.01)
-0.75
(0.39)
0.70*
(0.35)
0.83*
(0.13)
0.33*
(0.05)

Language Index
(without
additional
independent
variables, as per
Table 46), L
-2.29*
(0.44)
-0.13
(0.09)
-0.17
(0.17)
0.01*
(0.00)
-0.08
(0.42)
1.07*
(0.38)
0.78*
(0.15)
n/a

3.89*
(1.91)
18.62*
(3.54)
-0.46*
(0.09)
-0.11
(0.09)
-0.14*
(0.06)
0.42*
(0.09)

9.26*
(1.93)
30.62*
(3.43)

446
0.48
0.46

446
0.37
0.35

n/a
n/a
n/a
n/a

Notes:
1. Robust standard errors are reported in parentheses.
2. * indicates significance at the 5% level.

A329

Appendix S: Relationship of the Language Index with the NWI (continued)
Multiple Linear Regression Results (L and L2) Discussion
The expanded multiple regression of the language index includes the additional
independent variables of the education index, workforce index, housing index, income index,
and % of population who are registered Indians. This expanded regression of the language
index is labelled as L2, while the original language index is labelled as L. The results of this
regression are presented in Figure A739.
There are several benefits of including the additional variables in the language index
regression model. First, we can determine what relationship exists between the language
index and the additional variables. Second, we can gain a more accurate understanding of the
relationship between the language index and the variables from the original language index.
Third, we can provide a regression model with a higher level of explanatory value regarding
the dependent variable variation. As discussed in the literature review, Indigenous language
is a key aspect of First Nations culture. Clearly understanding the relationships between
knowledge of Indigenous language and the expanded list of independent variables provide
greater insight into the role of Indigenous language knowledge and community wellbeing.
The adjusted r-squared for L2 is higher at 0.46, compared to L at 0.35. This
demonstrates that L2 explains a higher amount of the dependent variable variation in the
regression model. Of the additional variables, the education index has the largest coefficient
and suggests that a 1 unit increase in the education index is associated with the language
index decreasing by 0.46. The housing index coefficient indicates that a 1 unit increase in
this index is associated with a 0.14 decrease in the language index. Also, a 1 unit increase in
the income index is associated with a 0.42 increase in the language index. Interestingly, no
statistically significant relationship exists between the workforce index and the language
index. L2 also includes the variable of % of population who are registered as Indians, which
demonstrates that a 1% increase in registered Indians is linked to a 0.33 increase in the
language index.
Knowledge and use of Indigenous language are an important part of Indigenous
culture. Given this, the finding that the language index substantially decreases when the
education index increases is troubling. This may demonstrate that further efforts are required

A330

Appendix S: Relationship of the Language Index with the NWI (continued)
to encourage the use and practice of Indigenous language within educational institutions.
Gomashie (2019) discusses a successful bilingual elementary and secondary school that
teaches classes in both English and Kanien’keha, which is actively increasing the number of
fluent Kanien’keha speakers in this First Nation community. Integrating Indigenous language
into formal educational institutions is possible, and has been successful. Emulating these
successes amoung other Indigenous communities may be an important component of
Indigenous language renewal. The positive relationship of income with knowledge of
Indigenous language is an interesting observation. The presence of higher income levels may
provide a greater ability to focus resources towards cultural activities, such as the passing on
and preservation of Indigenous languages. Better understanding this relation would be an
interesting area for future research. Finally, the positive association between the % of
registered Indians and knowledge of Indigenous language is expected. This association is
intuitive, as Indigenous people would be more likely to have knowledge of Indigenous
language compared to non-Indigenous people.
Note that the beta coefficients of L2 compared to L for the financial indicator variables
are mixed, with some variables increasing and others decreasing. The most notable change is
the coefficient for the earned & other revenue ratio, which is -1.01* for L2, and is -2.29* for
L. This demonstrates that the earned & other revenue ratio still maintains a negative
association with the language index, but not to such an extensive degree once the additional
independent variables are considered. The geographically medium coefficient for L2 is
3.89*, compared to 9.26* for L. The geographically remote coefficient for L2 is 18.62*,
compared to 30.62* for L. This demonstrates that the underlying effect of geographic
remoteness is lessened once the additional independent variables are considered. The total
community population variable is nearly unchanged.
By adding the additional independent variables, we can gain a clearer understanding of
the financial, population, and geographic variables effect on the language index. It is
beneficial to know that the financial and geographic variables actually have less explanatory
power, but that many of the other demographic subindex variables provide a high level of
explanatory power. The reason for this increased accuracy is that the effect of each

A331

Appendix S: Relationship of the Language Index with the NWI (continued)
independent variable is held constant for all other independent variables in the regression
model. Effectively, this means that L2 provides a more accurate understanding of the
explanatory power behind all of the independent variables presented in the L2 regression
model.

A332

Appendix T: Professional Experience of Author
The author obtained a Chartered Professional Accounting designation through the
Chartered Professional Accountants of British Columbia in 2015, and has worked as an
accounting and audit manager for several years. The author worked as a manager for the
accounting public practice firms of MNP, LLP in Prince George, BC, and later at KPMG,
LLP in Fort St. John, BC. The author has worked with clients in the areas of municipal
government, First Nations government, government business entities, not-for-profit
organizations, and private enterprise. This provided a strong background in Accounting
Standards for Private Enterprise (e.g. private business) and Public Sector Accounting
Standards (e.g. government).
The author has worked with several First Nation governments in northern and central
British Columbia, and has conducted external financial statement audits for many of these
clients. This has provided a strong background for understanding financial reporting
standards for First Nation governments, common issues faced by First Nation governments,
and on-the-ground knowledge of several First Nation communities in British Columbia. As
part of the fiscal year-end audit process, the author would lead an audit team on-site at the
local First Nation’s office. This provided the opportunity to visit multiple First Nation
communities, discuss issues with management and Chief and Council, and gain a direct
understanding of the realities faced by many First Nation communities.
The work of this manuscript combines the above-mentioned professional experience
with the academic knowledge obtained throughout the Masters of Business Administration
(MBA) program at Thompson Rivers University. This thesis manuscript is being completed
as a partial requirement for this MBA program.

A333

Appendix U: Stratified Trust Activity Correlational Analysis
This appendix provides an analysis between of the stratified trust activity financial
indicators and the demographic indices. There is a large spread in the level of trust fund
assets held by First Nations. The majority of First Nations hold zero or a low level of trust
fund assets, some hold a moderate level, and a small number of First Nations hold a high
level of trust fund assets. The First Nations are stratified on the basis of trust fund assets per
capita, which are defined as follows. First Nations are considered to have low trust assets if
the trust asset capita measure is $0 – $4,999, moderate trust assets if the capita measure is
$5,000 - $39,999, and high trust assets if the capita measure is $40,000 or higher.
After evaluating the correlational scatterplots in Appendix R, it appeared possible that
a distinct correlation may exists based on the above defined stratifications. To determine if
distinct correlations exist, a Pearson correlation coefficient will be calculated between trust
financial indicators and the demographic indices by each stratification group. The
correlational results can be found on the follow page in Figures A740 – A742. Note that
statistical significance at the 5% level is indicated with an * in Figures A740 – A742. When
statistically significant correlations are present, or when trends are identified, correlational
scatterplot and line of best fit graphs are evaluated.
Recall that few statistically significant correlations were found between the trust
activity financial indicators and the demographic indices for the total population, as per
Table 43. Conducting this stratified correlational analysis will provide a better understanding
of relationships based on the stratified groups of low trust assets, moderate trust assets, and
high trust assets. This appendix conducts the correlational analysis in the following format.
First are the R summary tables by stratification group that present the Pearson correlation
coefficients. Second is the analysis of the results, which makes reference to both the R
summary tables and the scatterplots/line of best fit graphs. Third are the scatterplot and line
of best fit graphs that present the findings in graphical format. Note that a high-level
discussion of these findings is summarized in Chapter 4 under the subheading R Results and
Discussion Between Financial Indicators and Demographic Indices.

A334

Appendix U: Stratified Trust Activity Correlational Analysis (continued)
Figure A740: R Summary Between Trust Activity Financial Indicators and Demographic
Indices – Low Trust Assets (390 First Nation Communities)
Financial
Demographic Indices
Indicators
Nation
Education Workforce Language Housing
Income
Wellness
Trust Fund
0.02
-0.06
-0.04
-0.06
-0.05
-0.07
Assets Ratio
Trust Fund
0.13*
0.13*
-0.14*
0.03
0.10
0.07
Assets Capita
Trust Revenue
-0.07
-0.11*
0.02
-0.07
-0.06
-0.11*
Ratio
Trust Revenue
-0.03
0.01
-0.02
0.06
0.02
0.02
Capita
Figure A741: R Summary Between Trust Activity Financial Indicators and Demographic
Indices – Moderate Trust Assets (38 First Nation Communities)
Financial
Demographic Indices
Indicators
Nation
Education Workforce Language Housing
Income
Wellness
Trust Fund
-0.19
-0.38*
0.31
-0.60*
-0.39
-0.46
Assets Ratio
Trust Fund
-0.05
0.04
0.08
-0.07
-0.04
0.01
Assets Capita
Trust Revenue
0.08
0.33*
-0.01
-0.09
-0.09
0.11
Ratio
Trust Revenue
0.16
0.50*
0.03
0.21
-0.12
0.38*
Capita
Figure A742: R Summary Between Trust Activity Financial Indicators and Demographic
Indices – High Trust Assets (18 First Nation Communities)
Financial
Demographic Indices
Indicators
Nation
Education Workforce Language Housing
Income
Wellness
Trust Fund
-0.27
-0.55*
0.33
-0.56*
-0.73*
-0.63*
Assets Ratio
Trust Fund
0.30
0.16
-0.14
-0.17
-0.15
-0.03
Assets Capita
Trust Revenue
-0.04
-0.03
0.25
-0.14
-0.05
-0.02
Ratio
Trust Revenue
-0.06
-0.05
0.30
-0.16
-0.10
-0.04
Capita
A335

Appendix U: Stratified Trust Activity Correlational Analysis (continued)
Very distinct correlations are present between the stratification categories. The low
trust asset First Nations maintain the lowest correlation as presented in Figure A740. Note
that 390 First Nations are included in this category, as most First Nations hold a low amount
of trust fund assets. Positive and statistically significant correlations are present between trust
fund assets capita and the education and workforce indices. A negative and statistically
significant correlation exists between trust fund asset capita and the language index.
Likewise, negative and statistically significant correlations exist between trust revenue ratio
and the workforce and Nation wellness indices. While these correlations are statistically
significant, all of the Pearson correlation coefficients are low (range from -0.14 to 0.13).
Stronger and statistically significant correlations are present for First Nations that
maintain a moderate or high level of trust assets. Note that 38 First Nations are included in
the moderate trust asset category, with 18 First Nations included in the high trust asset
category. Even with the smaller number of Nations in each category, distinctive trends have
been identified in the Pearson correlation coefficient results in Figures A741 – A742 and the
relating scatterplot/line of best fit graphs in Figures A743 – A761. The key trends are
discussed below.
The first trend for moderate and high trust assets Nations is a negative correlation
between the workforce index and the trust fund assets ratio. Moderate trust assets Nations
maintain a correlation of -0.38*. The relating graph can be found in Figure A744, which
demonstrates a negative trend in the line of best fit. High trust assets Nations maintain a
correlation of -0.55*. The relating graph can be found in Figure A745. In comparison, low
trust assets Nations maintain a correlation of -0.06, which is not statistically significant. The
key trend demonstrates that Nations with high or moderate levels of trust fund assets per
capita maintain negative correlation with the workforce index.
The second trend for moderate and high trust assets Nations is a negative correlation
between the housing index and the trust fund assets ratio. Moderate trust assets Nations have
a correlation of -0.60*. The relating graph can be found in Figure A747, which indicates a
negative trend in the line of best fit. High trust assets Nations maintain a correlation of
-0.56*. The relating graph can be found in Figure A748. Note that low trust assets Nations
A336

Appendix U: Stratified Trust Activity Correlational Analysis (continued)
have a non-statistically significant correlation of -0.06. This trend indicates that Nations with
high or moderate levels of trust fund assets per capita maintain negative correlations with the
housing index.
A third trend is found for Nations with low trust assets when evaluating trust fund
assets capita. This capita measure maintains statistically significant correlations with the
education index (0.13*), workforce index (0.13*), and the language index (-0.14*). The
relating graphs can be found in Figures A755 – A757. Note that these correlation coefficients
have low values, but the lines of best fit indicate that a general trend is present. No
statistically significant trends were found in the relating correlations for moderate or high
trust assets Nations. Additional scatterplot and line of best fit graphs are presented in the
following section. While some trends can be evaluated, the trends appear to be weaker and
may be skewed by outliers. As such, the remaining correlational coefficients and relating
graphs will not be discussed further.
This stratified sample analysis provides evidence that distinct relationships exist
between First Nations with low, moderate, and high levels of trust assets per capita. This
makes intuitive sense, as low levels of trust assets may not be sufficient to make a
meaningful impact within a First Nation community. The limited number of statistically
significant observations and the low value of correlation coefficients for the low trust assets
sample supports this. A less intuitive finding is the negative correlation between the trust
fund assets ratio and the workforce/housing indices for Nations with moderate and high trust
assets per capita. Nations holding higher levels of trust assets would be expected to have
greater resources to promote wellbeing within their communities. It is important to not draw
causal conclusions based on this analysis, as it is possible that other variables could explain
the correlation. For example, a higher trust fund assets ratio means that a greater percentage
of the Nation’s assets are tied up in trust funds. A higher percentage of trust assets may mean
that less assets are invested in tangible capital assets such as community housing. Likewise, a
higher percentage of trust assets may mean that there is less investment in Nation owned
businesses that could provide employment opportunities. Better understanding the trends
uncovered in this analysis would be an interest area of future research.
A337

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