1. Look who's crowding-out!
Arjen de Wit
René Bekkers
ARNOVA 42nd Annual Conference
Hartford, CT
November 21, 2013

3. Crowding-out Lower government contributions, higher private donations
Previous studies are not conclusive
Estimated effects of a change in government contributions vary strongly between studies

4. Two questions 1. Why do previous studies find different results?
2. How do individuals differ in their response to changes in government contributions?

5. Our first question 1. Why do previous studies find different results?
2. How do individuals differ in their response to changes in government contributions?

6. Meta-analysis Systematic literature review
We collect effect sizes published in previous research
We seek to explain differences in effect sizes between studies by characteristics of samples and publications

7. Meta-analysis: collecting studies
Y = Amount of private donations
X = Government contribution
Retrieval in Web of Science through EndNote
Our search now extends back to 2007
We include only original empirical quantitative results
N = 218 estimates from 34 articles

10. Our meta-analysis sample

11. Our meta-analysis sample
Books
Our meta-analysis sample

12. Our meta-analysis sample
Books
Dissertations
Our meta-analysis sample

13. Our meta-analysis sample
Books
Dissertations
Theses
Our meta-analysis sample

14. Our meta-analysis sample
Books
Dissertations
Theses
Not in Web of Science
Our meta-analysis sample

15. Our meta-analysis sample
Books
Dissertations
Theses
Not in Web of Science
Not accepted
Our meta-analysis sample

16. Our meta-analysis sample
Books
Dissertations
Theses
Not in Web of Science
Not accepted
Not submitted
Our meta-analysis sample

17. Our meta-analysis sample
Books
Dissertations
Theses
Not in Web of Science
Not accepted
Not submitted
Our meta-analysis sample
Non-English

18. Crowding-out estimates

19. Mean crowding-out effect

20. Findings
Analyses of tax records and lab experiments produce more crowding out than surveys and field experiments.
Analyses of organizational level data produce more crowding out than individual level data.
Studies from Europe find the weaker estimates of crowding out than US studies.

21. Units of analysis

22. Type of government contribution

23. Awareness

24. Discussion Random sample?
Should tax and price elasticities be included?
Are we comparing apples and oranges?
‘Bad studies’ in the sample?

25. Our second question 1. Why do previous studies find different results?
2. How do individuals differ in their response to changes in government contributions?

26. The Civic Voluntarism Model
Resources
Change in contribution
Engagement
Recruitment

27. The scenario experiment
In the Giving in the Netherlands Panel Survey we included a scenario experiment.
1,448 participants evaluated 3 scenarios, constructed randomly by combining information on budget cut levels and sectors.
Participants were reminded of their households’ contribution in the past year.

28. Example of scenario
“With your household you donated €100 to health in the past year. If the government cuts 5% in this area, how would you react?”
Response categories:
I will give the same as last year
I am willing to give more
I will also give less
[if more/less] What will be the new amount?

29. How the Dutch respond to cutbacks
Average response across all 4,344 scenarios

30. Responses vary by sector

32. Support for the civic voluntarism model
Odds ratios from logistic regression of willingness to contribute more after government cutback in at least one scenario (GINPS12, n=1,478; including controls for gender, age, income from wealth, home ownership, number of donation areas)

33. Values, reputation and efficacy
Odds ratios from logistic regression of willingness to contribute more after government cutback in at least one scenario (GINPS12, n=1,478)

34. Conclusions of meta-analysis
On average, a $1 reduction in government support is associated with a $0.28 increase in private contributions.
However, crowding-out estimates vary considerably from study to study.
Differences in the methodology used to measure the influence of government contributions on private giving are driving these differences.

35. Conclusions of scenario experiment
Individuals also vary systematically in their responses to changes in government contributions.
Those with more resources, receiving more solicitations and more generous donors are more likely to contribute more after government cutbacks.
The principle of care, reputation and charitable confidence are key mechanisms in crowding-out.
The principle of care is the only characteristic predicting the level of crowding-out.

36. Contact details
René Bekkers, and Arjen de Wit,
‘Giving in the Netherlands’, Center for Philanthropic Studies, Faculty of Social Sciences, VU University Amsterdam,