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Look who's crowding-out!

Arjen de Wit René Bekkers ARNOVA 42 nd Annual Conference Hartford, CT November 21, 2013. Look who's crowding-out!. Crowding-out. Lower government contributions, higher private donations Previous studies are not conclusive

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Look who's crowding-out!

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

  2. 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

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

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

  5. 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

  6. 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

  7. Our meta-analysis sample

  8. Books Our meta-analysis sample

  9. Books Dissertations Our meta-analysis sample

  10. Books Dissertations Theses Our meta-analysis sample

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

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

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

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

  15. Crowding-out estimates

  16. Mean crowding-out effect

  17. 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.

  18. Units of analysis

  19. Type of government contribution

  20. Awareness

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

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

  23. The Civic Voluntarism Model

  24. The scenario experiment • In the Giving in the Netherlands Panel Survey 2012 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.

  25. 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?

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

  27. Responses vary by sector

  28. 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)

  29. 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)

  30. 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.

  31. 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.

  32. Contact details • René Bekkers, r.bekkers@vu.nl and Arjen de Wit, a.de.wit@vu.nl • ‘Giving in the Netherlands’, Center for Philanthropic Studies, Faculty of Social Sciences, VU University Amsterdam, www.giving.nl

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