International Scholarly Research Network
ISRN Economics
Volume 2012, Article ID 421789, 6 pages
doi:10.5402/2012/421789

Research Article
Price Elasticities of Charitable Giving across Donation
Sectors in Canada: Is the Tax Incentive Effective?
Belayet Hossain and Laura Lamb
Department of Economics, Thompson Rivers University, 900 McGill Road, Kamloops, BC, Canada V2C 0C8
Correspondence should be addressed to Belayet Hossain, bhossain@tru.ca
Received 15 November 2012; Accepted 4 December 2012
Academic Editors: M. T. Leung and K. P. Upadhyaya
Copyright © 2012 B. Hossain and L. Lamb. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
The effectiveness of tax incentives on charitable donation expenditures in Canada is explored, and the analysis is extended to
compare the effectiveness across different donation sectors. Price elasticities are estimated with data from the 2007 Canada Survey
of Giving, Volunteering and Participating. Results suggest that specific charitable sectors are affected differently by Canada’s tax
credit system. The findings have implications for public policy.

1. Introduction
As do most governments of developed nations, the Canadian
government provides a tax incentive to encourage charitable
giving. There is a healthy body of literature assessing the
effectiveness of tax incentive policies on charitable giving
[1–10], although few Canadian studies have compared
the effectiveness across the different donation sectors. The
current research attempts to fill this void by exploring two
facets of the effectiveness of tax incentives on charitable
giving in Canada. First, it evaluates the effectiveness of tax
incentives on an individual’s total donation expenditure.
Second, the analysis is broadened to assess and compare the
effectiveness of tax incentives across four donation sectors.
Much of the existing literature is grounded in the
assumption that the responsiveness of charitable giving
expenditures to tax incentives is equivalent across all donation sectors, except for two studies on donation expenditures
in the U.S. [2, 5] and one in Taiwan [4]. To our knowledge,
this assumption has not been tested for Canadian donation
expenditures, except for Hossain and Lamb [1] who examined the effectiveness of tax policy on the decision to donate
across donation sectors, and Kitchen and Dalton [11] and
Kitchen [12] who explored the effectiveness of tax policy on
donation expenditures to the religious sector.

This study tests two hypotheses. The first hypothesis is
that a change in the price of the donation will affect an
individual’s total donation expenditure. The second hypothesis is that the effectiveness of the tax incentive varies across
donation sectors, as revealed by price elasticities. Among
the past studies, there is no clear consensus on how price
elasticities of charitable donations vary among the different
sectors. Kitchen [12] found the demand for total charitable
giving in Canada to be price elastic but price to have no
effect on religious giving. Brooks [2] reported total donations
and donations to the health sector to be price inelastic,
and donations to the religious, education and social welfare
sectors to be price elastic in the U.S. while Chang [4] found
total donations as well as donations to all specific donation
sectors to be price elastic in Taiwan.
The purpose of this research is to inform public policy
decisions. For instance, if tax incentives are effective for
some sectors and not others, then direct government support
rather than tax credits may be a more appropriate method
of providing the goods and services of those sectors. The
remainder of the paper is organized as follows. Section 2
consists of a description of the methodology including the
model, econometric techniques for analysis, data, and variables. Section 3 is a discussion of the empirical results followed
by a discussion of policy implications and a conclusion in
Section 4.

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2. Methodology
Past studies on charitable giving expenditures have considered an array of socioeconomic variables, such as gender, age,
education, income, number of dependents, marital status,
employment status, after-tax price of donation, volunteer
status, and religious status [3–5]. This study includes those
variables plus geographic influences, as was done in previous
Canadian studies [11, 12]. In addition, it has been suggested
that attending religious meetings and immigrant status may
be relevant variables [1, 14].
The proposed determinants of charitable donation
expenditures are organized into three categories: economic,
sociodemographic, and geographic. The economic factors
include household income, price of donation, and employment status. The price of donation is the key variable of
interest in the model, as its estimated value will determine
the effectiveness of Canadian tax policy on charitable giving
expenditures. The results of testing the two hypotheses will
indicate whether and to what extent the current tax policy
is effective at generating contributions to charitable and
nonprofit organizations in Canada.
The sociodemographic characteristics include age, gender, marital status, education, religious attendance, presence
of children, country of birth, and participation in volunteer
activities. The geographic factors include regional specific
influences as defined by the following five regions: British
Columbia, the Prairies, Ontario, Quebec, and the Atlantic
region.
The Canadian Survey of Giving, Volunteering and Participating [13] categorizes registered charitable and nonprofit organizations into twelve sectors according to the
International Classification of Nonprofit Organizations. The
current analysis covers the following four largest donation sectors, according to the value of total donations,
in descending order: religious, health, social services, and
international. It is noted that potential overlap between
charitable donation sectors poses a limitation to this analysis.
For instance, religious organizations often allocate funding to
social services and international aid.
Since 1988, tax incentives for charitable giving have been
provided to Canadian tax payers through a tax credit system,
different from the more common tax deduction system.
Under the deduction system, the value of the tax benefit
depends on the donor’s level of income whereas, under the
credit system, the value of the benefit depends on the total
amount of charitable donations claimed in the particular tax
year [15]. The Canadian tax credit system is a two-tier system
such that there are two levels of tax credits at both the federal
and provincial levels, one for annual donation expenditures
of up to $200 and a higher one for the annual amount of
donation expenditure over $200.
2.1. Econometric Model. Each of the two hypotheses is
tested with an econometric model. The first model (1)
tests the effectiveness of tax incentives on total charitable

ISRN Economics
expenditures and a second model (2) compares the effectiveness across four charitable donation sectors.


Di =

f (Xi , Zi , Gi ),
0,

if DS = g(Xi , Zi , Gi ) > 0,
otherwise,

(1)

where Di represents the total donation expenditure made
by the ith individual; Xi is the vector of economic variables
applicable to the ith individual, which includes the price
of donation; Zi is the vector of all sociodemographic
characteristics relevant to the ith individual; Gi is the vector
of variables relating to the region of residence of the ith
individual; DS is the donor status, which is 1 (donor) or 0
(nondonor).


Di j =

f (Xi , Zi , Gi ),
0,

if DS = g(Xi , Zi , Gi ) > 0,
otherwise,

(2)

where Di j is the donation expenditure by the ith individual
to the jth charitable sector; j can be 1 to 4, representing each
of the four sectors under study.
Note that the estimation of both models requires the
inclusion of all people irrespective of whether or not the
individual made a charitable donation. Each donor may
make more than one donation and may donate to more than
one charitable sector.
In both models (described by (1) and (2)) the dependent
variable, Di or Di j , is observed only if a respondent makes
a donation. Consider Ui to be the unobserved utility an
individual receives when making a donation. Ui is expected
to be determined by the set of variables, Xi , Zi , and Gi ,
although we do not observe Ui . We observe a dichotomous
variable DS, the donor status, with a value 1 if the respondent
is a donor (Ui > 0) and zero otherwise, referred to as the
selection equation. The error terms in both parts of each
model are expected to be correlated. However, if the selection
equation is omitted, the parameter estimates of the donation
expenditure equations will be biased and inconsistent. Since
the donors are self-selected and thereby do not comprise a
random sample, the error will not be distributed normally.
For example, the preference for making a donation to
a particular organization is higher for donors than for
the general population. The Heckman selection model is
appropriate for addressing this issue of selection bias [8].
Heckman’s selection model is a two-step procedure.
In the first step, the selection equation is estimated by
the maximum likelihood approach (MLE), and the inverse
Mills ratio (λi ) is then estimated with the MLE parameter
estimates. In the second step, λi is included along with all
other explanatory variables to estimate Di or Di j . Adding
λi as a regressor results in the problem of hetroskedasticity
which is resolved by using robust standard errors. Thus,
the Heckman selection model estimates both the donation
expenditure and donation status simultaneously in order to
address possible selection bias and is used for each model.
2.2. Data and Variables. The study uses data from the 2007
Canada Survey of Giving, Volunteering and Participating

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3

published by Statistics Canada. The target population is all
persons 15 years of age or over living in the ten provinces.
After the variables for the models are identified, observations
with missing values are excluded from the analysis, leaving
18 457 observations for analysis. Table 1 presents frequency
and percentage distributions of sample member characteristics of those who make charitable donations. The summary
of donation expenditure by sector and price of donation are
shown in Table 2.
The economic, sociodemographic, and geographic characteristics are listed and described in Table 3. The price
of donation is a measure of the price per dollar of the
donation expenditure after the tax incentive is considered.
For each sample member, the price can be considered to be
equal to one minus the tax credit, which is determined by
their donation expenditure and the federal and provincial
tax credit rates. However, given that this measurement of
price is determined by the amount of donation expenditure,
the variable would be endogenous and would result in
inconsistent estimates of the two models. A proxy variable
is used to overcome the endogeneity issue, as was used in
Hossain and Lamb [1] (Instrument variables are typically
used to address the problems associated with endogenous
variables; however, the sample selection model does not
allow for the use of instrument variables.). It is calculated as
one minus the sum of the federal and provincial marginal
income tax rates for each sample member, based on the
median of the sample member’s personal income bracket.
The donation expenditure and the proxy for price of
donation are measured in natural logarithms in order to
interpret the coefficients as elasticities.

Table 1: Frequency and percentage distributions of sample members characteristics who make charitable donations (n = 16, 565).

3. Empirical Results

Source: [13].

The results of the two models are illustrated in Table 4. The
reported results are the marginal effects of the explanatory
variables on donation expenditures. Note that model 1
estimates the total donation expenditure while model 2
estimates the donation expenditure for each of the four
charitable donation sectors.
Overall, the specifications of all models are found to be
robust, as evidenced by the Wald statistic. In line with the
a-priori expectation, the coefficient for price of donation is
both negative and significant for total donation expenditures
as well as for each of the four donation sectors. In fact, among
all the variables for all five equations, price of donation has
the largest marginal effect on donation expenditures.
The estimated price elasticity of total donations is −1.68,
implying that a 10 cent (or 10%) decrease in price of
donation (or increase in the tax incentive) increases the total
donation expenditure by close to 17 cents (or 17%). For the
donation sectors, the price elasticity varies between −0.81 for
religious donations and −2.21 for international donations.
All price elasticities are elastic, except for religion, suggesting
that a marginal increase in the tax credit will result in a
proportionately larger increase in the level of donations for
total donation expenditures and for the health, social service,

Variables
Participation in
charitable giving
Household income

Age

Education

Gender

Category

<$60 000
$60 000–$100 000
$100 000+
15–34
35–54
55+
Maximum high
school diploma
Some postsecondary/diploma to
university degree
Female
Male

Born in Canada
Marital status
Preschool children
School age children

Regions

Religious attendance
Employment status
Volunteer status

Married
≥1
≥1
Atlantic
Quebec
Ontario
Prairies
British Columbia
≥Weekly
Employed
Participate

Frequency

%

16,565

89.7%

8,379
4,445
3,741
3,762
6,710
6,093

50.6%
26.8%
22.6%
22.7%
40.5%
36.8%

4,817

29.1%

11,748

70.9%

9,596
6,969
14,330

57.9%
42.1%
86.5%

9,852
1,943
4,201
4,183
3,051
3,061
3,838
2,432
5,649
10,621
11,328

59.5%
11.7%
25.4%
25.3%
18.4%
18.5%
23.2%
14.7%
31.1%
64.1%
68.4%

Table 2: Summary of donation and price statistics for sample members who make charitable donations (n = 16, 565).
Variable
Total charitable donations
Religious donations
Health donations
Social service donations
International donations
Price of donation

Mean
$544.87
$261.94
$100.12
$51.24
$34.77
0.70

Standard deviation
1376.78
928.92
382.57
316.22
329.97
0.07

Source: [13].

and international sectors. And the amount of the tax revenue
forgone will be less than the rise in donation expenditures for
all sectors except religion.
Estimated price elasticities in this study are in the
same range as those of other studies in USA and Canada,
as illustrated in Table 5. Using 1982 Canadian household
expenditure survey data Kitchen and Dalton [11] estimated
the price elasticity of total donations to be −1.07, while
Kitchen [12] with 1984 Canadian household expenditure
survey data found the price elasticity to be −2.29. This study’s
estimate of price elasticity for total donation expenditures

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Table 3: Description of variables.
Categories

Economic

Sociodemographic

Variable name
Price of donation
Income
Income 1
Income 2
Employed
Age
Age 1
Age 2
High education
Male
Married
Religious

Geographic

Canadian born
Preschool children
School age children
Volunteer
Regions
Quebec
Atlantic
Prairies
British Columbia (BC)

Description of the variable
The price per dollar of donation
(Base category: less than $60 000)
If respondent has household income from $60 000 to $100 000, then 1; otherwise 0
If respondent has household income more than $100 000, then 1; otherwise 0
If the respondent is employed, then 1; otherwise 0
(Base category: age 15–34)
If respondent’s age is between 35 years and 55 years, then 1; otherwise 0
If respondent’s age is greater than 55 years, then 1; otherwise 0
If respondent has postsecondary education, then 1; otherwise 0
If respondent is male, then 1 and 0 for female
If respondent is married, then 1; otherwise 0
If respondent attends religious gathering or meetings at least once a week, then 1;
otherwise 0
If respondent is born in Canada, then 1; otherwise 0
If respondent’s household has preschool age children, then 1; otherwise 0
If respondent’s household has school age children, then 1; otherwise 0
If respondent participates in volunteer activities, then 1; otherwise 0
(Base category: Ontario)
If the respondent is a resident of Quebec, then 1; otherwise 0
If the respondent is a resident of Atlantic, then 1; otherwise 0
If the respondent is a resident of Prairies, then 1; otherwise 0
If the respondent is a resident of BC, then 1; otherwise 0

Table 4: Average marginal effects for total donation expenditures and by sector.
Variable
Price of donation
Age1
Age2
High education
Income 1
Income 2
Religious attendance
Employed
Married
Canadian born
Male
Volunteer
Preschool children
School age children
Quebec
Atlantic
Prairies
British Columbia
Wald statistic
Rho

Total donation

Religion

Health

Social services

International

−1.677∗∗ (0.187)

−0.814∗∗ (0.332)

−1.490∗∗ (0.170)

−1.710∗∗ (0.249)

−2.205∗∗ (0.504)

0.636∗∗ (0.049)
1.183∗∗ (0.056)
0.421∗∗ (0.044)
0.193∗∗ (0.051)
0.591∗∗ (0.054)
0.066∗∗ (0.012)
0.117∗∗ (0.013)
0.149∗∗ (0.043)
−0.071 (0.058)
−0.108∗∗ (0.039)
0.208∗∗ (0.008)
0.154∗∗ (0.063)
−0.124∗∗ (0.045)
−0.676∗∗ (0.049)
−0.107∗ (0.052)
0.105∗ (0.055)
0.197∗∗ (0.065)
173.03
−0.606 (0.034)

0.551∗∗ (0.097)
1.088∗∗ (0.122)
0.173∗ (0.086)
0.200∗ (0.087)
0.225∗ (0.097)
0.037∗∗ (0.004)
0.028∗∗ (0.004)
0.091 (0.081)
−0.080 (0.087)
0.009 (0.071)
0.061∗∗ (0.003)
0.114 (0.104)
−0.094 (0.077)
−1.456∗∗ (0.082)
−0.159 (0.088)
0.245∗∗ (0.094)
0.528∗∗ (0.117)
0.443
−0.094 (0.142)

0.375∗∗ (0.046)
0.761∗∗ (0.053)
0.291∗∗ (0.039)
0.218∗∗ (0.046)
0.608∗∗ (0.054)
0.054∗∗ (0.008)
0.079∗∗ (0.009)
−0.001 (0.039)
0.146∗∗ (0.048)
−0.110∗∗ (0.036)
0.128∗∗ (0.006)
−0.051 (0.052)
−0.220∗∗ (0.041)
−0.557∗∗ (0.048)
−0.381∗∗ (0.045)
−0.093∗ (0.046)
0.114∗ (0.058)
61.74
−0.432 (0.048)

0.491∗∗ (0.007)
0.809∗∗ (0.080)
0.243∗∗ (0.054)
0.046 (0.060)
0.382∗∗ (0.075)
0.062∗∗ (0.011)
0.079∗∗ (0.012)
−0.170∗∗ (0.056)
0.026 (0.069)
−0.064 (0.051)
0.142∗∗ (0.008)
0.158∗ (0.075)
−0.141∗∗ (0.056)
−0.414∗∗ (0.063)
−0.143∗ (0.062)
0.260∗∗ (0.068)
0.584∗∗ (0.080)
36.31
−0.363 (0.055)

0.511∗∗ (0.145)
0.629∗∗ (0.174)
0.294 (0.163)
0.171 (0.139)
0.301 (0.164)
0.069 (0.014)
0.083∗∗ (0.017)
0.155 (0.120)
−0.277∗∗ (0.114)
0.013 (0.123)
0.183∗∗ (0.012)
0.281∗ (0.148)
−0.471∗∗ (0.127)
−0.489∗∗ (0.168)
−0.084 (0.186)
0.412∗∗ (0.145)
0.480∗∗ (0.145)
2.72
−0.221 (0.129)

(1) Robust standard errors are reported in parentheses.
(2) ∗∗ indicates the level of significance at less than 0.05 and ∗ indicates the level of significance at less than 0.1 level.
(3) The estimates of the Heckman sample selection model are significantly superior to those of the standard tobit model (at 0.05 levels) for all equations except
religion and international donation expenditures, as demonstrated by the Rho statistics. Accordingly, religion and International equations are estimated with
a tobit model.

ISRN Economics

5
Table 5: Comparison of price elasticities of donation expenditure estimates across similar studies.

Studies/authors
Present study (Canada)
Brooks (USA, 2007) [2]
Chang (Taiwan, 2005) [4]
Kitchen and Dalton (Canada, 1990) [11]
Kitchen (Canada, 1992) [12]

All sectors
−1.68
−2.70
−5.25
−1.07
−2.29

Religion
−0.81
−1.16
−6.32
−2.37
—

Health
−1.49
−0.58
−1.38
—
—

Social services
−1.71
−1.33
−4.99
—
—

Education
—
−1.21
−3.36
—
—

International
−2.21
—
—
—
—

Table 6: Hypothesis tests of the equivalence of price elasticities of donation expenditures.
Hypothesis: equivalent elasticity among sectors
Unit elasticity
Elasticity for total donation expenditures
Elasticity for religious donation expenditures
Elasticity for health donation expenditures
Elasticity for social service donation expenditures

Total donation
∗∗∗

Religion
X
∗∗∗

Level of significance
Health
Social service

International

∗

∗

∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗

∗∗∗
∗∗∗

All hypothesis test results are chi-square results. The null hypothesis of unit price elasticity is rejected for total donation expenditure and for each sector, except
religion where the elasticity is indistinguishable from one. The null hypothesis of equivalent elasticity is rejected for total donations and across all sectors.
X: statistically indistinguishable. ∗∗∗ indicates statistically distinguishable at the .01 level and ∗ indicates distinguishable at the 0.10 level.

lies in between the two previous Canadian studies. In
contrast to the two previous Canadian studies, the present
paper finds the price elasticity of donations to religious
organizations to be negative and significant, but inelastic.
The present results are relatively closer to those of Brooks [2]
than those of Chang [4], not surprising given the relatively
strong similarities between Canadian and US economies and
cultures, as compared with those of Taiwan.
Hypothesis test results, in Table 6, illustrate that all price
elasticities are statistically distinguishable from the value of
one (unit elasticity), except for the religious sector where
elasticity is not different from unit elasticity. Price elasticities are also statistically distinguishable from one another,
providing support for the hypothesis that the responsiveness
of charitable donations to tax incentives varies across the
different charitable sectors.
Among the other economic characteristics, household
income and employment are positive and significant. As
expected household income has a positive effect on total
donation expenditures and on donation expenditures for
religion, health, and social services. Individuals with household income in the range of $60 000 to $100 000 are likely
to donate more to religious and health sectors than those
with household incomes less than $60 000. Similarly, those
with household income greater than $100 000 are likely to
donate more than those with household incomes in the
range of $60 000 to $100 000, to all donation sectors, except
international ones. Being employed has a positive impact on
donation expenditures, irrespective of donation sector. Most
of the sociodemographic characteristics have a significant
impact on total donation expenditures as well as on the four
sectors. Age has a positive and significant effect on total
donations as well as on each of the four sectors.
Female respondents are more likely to make larger total
donations and health donations than males. The results
imply that gender does not have a significant effect on the

amount of donations to religion, social services, or international organizations. Married respondents are more likely to
make larger total donations and larger donations to the social
service sector than those not married. An individual with at
least some postsecondary education is likely to contribute
more to each donation sector, except international ones,
than an individual with a maximum education of high
school graduation. Individuals born in Canada donate more
to health organizations than immigrants, but immigrants
donate more to international organizations than those born
in Canada. Participation in volunteer activities significantly
increases total donation expenditures as well as to all four
donation sectors as compared to those who do not volunteer.
Attending weekly religious services or meetings also tends to
increase total donations as well as for each sector, except for
international.
The presence of preschool children in the household is
associated with larger total donation expenditures as well
as larger expenditures to social service and international
organizations compared to individuals without preschool
children. On the other hand, the presence of school age
children tends to decrease total donation expenditures and
expenditures to health, social service, and international
organizations relative to those without school age children.
Four regional dummy variables are used to assess the
effect of the geographic regions on total donations, with
Ontario being the reference region. Other things being equal,
the residents of Quebec and the Atlantic regions donate less
than the residents of Ontario, and the residents of the Prairies
and British Columbia donate more than those of Ontario
(The coefficients for the regional variables are found to be
significantly different from each other at the .05 level.).

4. Policy Implications and Conclusion
The empirical results suggest that tax incentives have a significant effect on charitable donation expenditures, implying

6
the ability of public policy to affect changes in the level of
donation expenditures in Canada. The tax credit appears
to be fiscally efficient (Fiscal efficiency as it relates to tax
incentives is defined as the case where an increase in donation
expenditures is greater than the loss of tax revenue due
to the tax incentive [2].), as indicated by elastic demand
for charitable donations. An increase in the tax credit is
expected to lead to a loss of tax revenue to the public sector
which would be more than fully compensated by the rise in
donation expenditures. Donations to religious organizations
are not price elastic suggesting that the tax credit may
not be fiscally efficient for the religious sector. Given that
Canadians tend to donate to more than one charitable sector,
on average the tax credit system for charitable donations can
be considered to be fiscally efficient.
The significance of volunteering suggests that donating
and volunteering are complements rather than substitutes.
It may be the case that participating in volunteer activities
raises awareness of the importance of the goods and services
provided by charities and non-profits resulting in larger
financial donations. The recognition of this relationship suggests that governments can indirectly encourage donations
through the support of volunteer activities.
Given the distinguishable price elasticities for each of
the four charitable sectors, there are concerns about policy
decisions made under the assumption that all donation
sectors are equally affected by the tax credit. For instance,
an increase in the tax credit is expected to lead to a rise in
international donations more than social service donations,
health, and religious organizations. These results inevitably
lead to normative discussions about which types of
organizations provide the goods and services most valued by
society. Public policy could be used to tailor tax credit rates to
reflect society’s preferences and needs by setting unique tax
credit rates for the different donation sectors. For example, if
the goods and services provided by social services donations
are valued more highly than those provided by religious
organizations, the tax credit rate for social service donations
could be increased and/or reduced for religious donations.
In sum, both provincial and federal governments have
the ability to influence charitable donation expenditures
by adjusting the tax credit rates. Government also has the
ability to influence the expenditure levels of specific types of
donations by setting individual tax credit rates for each sector
for the purpose of encouraging the provision of public goods
and services most valued by society. In addition, the results
indicate international donations to be most responsive to
potential changes in tax credits and religious giving to be least
responsive, thereby suggesting the need for policy makers to
be cognizant of the varying levels of responsiveness of each
sector to potential changes in tax incentives.

References
[1] B. Hossain and L. Lamb, “Does the effectiveness of tax incentives on the decision to give charitable donations vary across
donation sectors in Canada?” Applied Economics Letters, vol.
19, no. 15, pp. 1487–1491, 2012.

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[2] A. C. Brooks, “Income tax policy and charitable giving,” Journal of Policy Analysis and Management, vol. 26, no. 3, pp. 599–
612, 2007.
[3] J. Carroll, S. McCarthy, and C. Newman, “An econometric
analysis of charitable donations in the Republic of Ireland,”
Economic and Social Review, vol. 36, no. 3, pp. 229–249, 2005.
[4] W. C. Chang, “Determinants of donations: empirical evidence
from Taiwan,” Developing Economies, vol. 43, no. 2, pp. 217–
234, 2005.
[5] N. E. Feldman and J. R. Hines Jr., “Tax credit and charitable
contributions in Michigan,” Working Paper, University of
Michigan, Ann Arbor, Mich, USA, 2003.
[6] J. Peloza and P. Steel, “The price elasticities of charitable contributions: a meta-analysis,” Journal of Public Policy and Marketing, vol. 24, no. 2, pp. 260–272, 2005.
[7] G. E. Auten, H. Sieg, and C. T. Clotfelter, “Charitable giving,
income, and taxes: an analysis of panel data,” American Economic Review, vol. 92, no. 1, pp. 371–382, 2002.
[8] I. Garcı́a and C. Marcuello, “A household model of charitable
contributions and tax incentives,” Annals of Public and Cooperative Economics, vol. 72, no. 2, pp. 159–181, 2001.
[9] A. Jones and J. Posnett, “Charitable Donations by UK households: evidence from the family expenditure survey,” Applied
Economics, vol. 23, pp. 343–351, 1991.
[10] C. T. Clotfelter, Federal Tax Policy and Charitable Giving,
NBER, 1985.
[11] H. Kitchen and R. Dalton, “Determinants of charitable donations by families in Canada: a regional analysis,” Applied Economics, vol. 22, pp. 285–299, 1990.
[12] H. Kitchen, “Determinants of charitable donations in Canada:
a comparison over time,” Applied Economics, vol. 24, pp. 709–
713, 1992.
[13] Statistics Canada, Canada Survey of Giving, Volunteering and
Participating (CSGVP), Public Use Microdata File, 2007.
[14] Statistics Canada, Caring Canadians, Involved Canadians:
Highlights From the 2007 Canada Survey of Giving, Volunteering and Participating, Statistics Canada, Ottawa, Canada, 2009.
[15] D. Duff, “Charitable contribution and the personal income
tax: evaluating the canadian credit,” in Between State and Market: Essay on Charities Law and Policy in Canada, J. Phillips,
B. Chapman, and D. Stevens, Eds., McGill-Queen’s University
Press, 2001.

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