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.
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 [
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. [
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 [
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
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 [
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 [
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 [
Each of the two hypotheses is tested with an econometric model. The first model (1) tests the effectiveness of tax incentives on total charitable expenditures and a second model (2) compares the effectiveness across four charitable donation sectors.
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 (
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 (
The study uses data from the 2007 Canada Survey of Giving, Volunteering and Participating 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
Frequency and percentage distributions of sample members characteristics who make charitable donations (
Variables | Category | Frequency | % |
---|---|---|---|
Participation in charitable giving | 16,565 | 89.7% | |
Household income | <$60 000 | 8,379 | 50.6% |
$60 000–$100 000 | 4,445 | 26.8% | |
$100 000+ | 3,741 | 22.6% | |
Age | 15–34 | 3,762 | 22.7% |
35–54 | 6,710 | 40.5% | |
55+ | 6,093 | 36.8% | |
Education | Maximum high school diploma | 4,817 | 29.1% |
Some post-secondary/diploma to university degree | 11,748 |
70.9% |
|
Gender | Female | 9,596 | 57.9% |
Male | 6,969 | 42.1% | |
Born in Canada | 14,330 | 86.5% | |
Marital status | Married | 9,852 | 59.5% |
Preschool children | ≥1 | 1,943 | 11.7% |
School age children | ≥1 | 4,201 | 25.4% |
Regions | Atlantic | 4,183 | 25.3% |
Quebec | 3,051 | 18.4% | |
Ontario | 3,061 | 18.5% | |
Prairies | 3,838 | 23.2% | |
British Columbia | 2,432 | 14.7% | |
Religious attendance | ≥Weekly | 5,649 | 31.1% |
Employment status | Employed | 10,621 | 64.1% |
Volunteer status | Participate | 11,328 | 68.4% |
Source: [
Summary of donation and price statistics for sample members who make charitable donations (
Variable | Mean | Standard deviation |
---|---|---|
Total charitable donations | $544.87 | 1376.78 |
Religious donations | $261.94 | 928.92 |
Health donations | $100.12 | 382.57 |
Social service donations | $51.24 | 316.22 |
International donations | $34.77 | 329.97 |
Price of donation | 0.70 | 0.07 |
Source: [
The economic, sociodemographic, and geographic characteristics are listed and described in Table
Description of variables.
Categories | Variable name | Description of the variable |
---|---|---|
Economic |
Price of donation | The price per dollar of donation |
Income | (Base category: less than $60 000) | |
Income 1 | If respondent has household income from $60 000 to $100 000, then 1; otherwise 0 | |
Income 2 | If respondent has household income more than $100 000, then 1; otherwise 0 | |
Employed | If the respondent is employed, then 1; otherwise 0 | |
| ||
Sociodemographic | Age | (Base category: age 15–34) |
Age 1 | If respondent’s age is between 35 years and 55 years, then 1; otherwise 0 | |
Age 2 | If respondent’s age is greater than 55 years, then 1; otherwise 0 | |
High education | If respondent has postsecondary education, then 1; otherwise 0 | |
Male | If respondent is male, then 1 and 0 for female | |
Married | If respondent is married, then 1; otherwise 0 | |
Religious | If respondent attends religious gathering or meetings at least once a week, then 1; otherwise 0 | |
Canadian born | If respondent is born in Canada, then 1; otherwise 0 | |
Preschool children | If respondent’s household has preschool age children, then 1; otherwise 0 | |
School age children | If respondent’s household has school age children, then 1; otherwise 0 | |
Volunteer | If respondent participates in volunteer activities, then 1; otherwise 0 | |
| ||
Geographic | Regions | (Base category: Ontario) |
Quebec | If the respondent is a resident of Quebec, then 1; otherwise 0 | |
Atlantic | If the respondent is a resident of Atlantic, then 1; otherwise 0 | |
Prairies | If the respondent is a resident of Prairies, then 1; otherwise 0 | |
British Columbia (BC) |
If the respondent is a resident of BC, then 1; otherwise 0 |
The results of the two models are illustrated in Table
Average marginal effects for total donation expenditures and by sector.
Variable | Total donation | Religion | Health | Social services | International |
---|---|---|---|---|---|
Price of donation | −1.677** (0.187) | −0.814** (0.332) | −1.490** (0.170) | −1.710** (0.249) | −2.205** (0.504) |
Age1 | 0.636** (0.049) | 0.551** (0.097) | 0.375** (0.046) | 0.491** (0.007) | 0.511** (0.145) |
Age2 | 1.183** (0.056) | 1.088** (0.122) | 0.761** (0.053) | 0.809** (0.080) | 0.629** (0.174) |
High education | 0.421** (0.044) | 0.173* (0.086) | 0.291** (0.039) | 0.243** (0.054) | 0.294 (0.163) |
Income 1 | 0.193** (0.051) | 0.200* (0.087) | 0.218** (0.046) | 0.046 (0.060) | 0.171 (0.139) |
Income 2 | 0.591** (0.054) | 0.225* (0.097) | 0.608** (0.054) | 0.382** (0.075) | 0.301 (0.164) |
Religious attendance | 0.066** (0.012) | 0.037** (0.004) | 0.054** (0.008) | 0.062** (0.011) | 0.069 (0.014) |
Employed | 0.117** (0.013) | 0.028** (0.004) | 0.079** (0.009) | 0.079** (0.012) | 0.083** (0.017) |
Married | 0.149** (0.043) | 0.091 (0.081) | −0.001 (0.039) | −0.170** (0.056) | 0.155 (0.120) |
Canadian born | −0.071 (0.058) | −0.080 (0.087) | 0.146** (0.048) | 0.026 (0.069) | −0.277** (0.114) |
Male | −0.108** (0.039) | 0.009 (0.071) | −0.110** (0.036) | −0.064 (0.051) | 0.013 (0.123) |
Volunteer | 0.208** (0.008) | 0.061** (0.003) | 0.128** (0.006) | 0.142** (0.008) | 0.183** (0.012) |
Preschool children | 0.154** (0.063) | 0.114 (0.104) | −0.051 (0.052) | 0.158* (0.075) | 0.281* (0.148) |
School age children | −0.124** (0.045) | −0.094 (0.077) | −0.220** (0.041) | −0.141** (0.056) | −0.471** (0.127) |
Quebec | −0.676** (0.049) | −1.456** (0.082) | −0.557** (0.048) | −0.414** (0.063) | −0.489** (0.168) |
Atlantic | −0.107* (0.052) | −0.159 (0.088) | −0.381** (0.045) | −0.143* (0.062) | −0.084 (0.186) |
Prairies | 0.105* (0.055) | 0.245** (0.094) | −0.093* (0.046) | 0.260** (0.068) | 0.412** (0.145) |
British Columbia | 0.197** (0.065) | 0.528** (0.117) | 0.114* (0.058) | 0.584** (0.080) | 0.480** (0.145) |
Wald statistic | 173.03 | 0.443 | 61.74 | 36.31 | 2.72 |
Rho | −0.606 (0.034) | −0.094 (0.142) | −0.432 (0.048) | −0.363 (0.055) | −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.
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, 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
Comparison of price elasticities of donation expenditure estimates across similar studies.
Studies/authors | All sectors | Religion | Health | Social services | Education | International |
---|---|---|---|---|---|---|
Present study (Canada) |
−1.68 | −0.81 | −1.49 | −1.71 | — |
−2.21 |
Brooks (USA, 2007) [ |
−2.70 | −1.16 | −0.58 | −1.33 | −1.21 | — |
Chang (Taiwan, 2005) [ |
−5.25 |
−6.32 |
−1.38 |
−4.99 |
−3.36 |
— |
Kitchen and Dalton (Canada, 1990) [ |
−1.07 |
|
— | — | — | — |
Kitchen (Canada, 1992) [ |
−2.29 | — | — | — | — | — |
Hypothesis test results, in Table
Hypothesis tests of the equivalence of price elasticities of donation expenditures.
Hypothesis: |
Level of significance | ||||
---|---|---|---|---|---|
Total donation | Religion | Health | Social service | International | |
Unit elasticity | *** | X | * | * | * |
Elasticity for total donation expenditures | *** | *** | *** | *** | |
Elasticity for religious donation expenditures | *** | *** | *** | ||
Elasticity for health donation expenditures | *** | *** | |||
Elasticity for social service donation expenditures | *** |
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.
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.).
The empirical results suggest that tax incentives have a significant effect on charitable donation expenditures, implying 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 [
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.