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Some stuff we're working on
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Some stuff we're working on Arjen de Wit IUPUI School of Philanthropy June 5, 2014
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Indiana University Lilly School of Philanthropy, Indianapolis, IN - June 5, 2014
Transcript of Some stuff we're working on
Some stuff we're working on
Arjen de Wit
IUPUI School of Philanthropy
June 5, 2014
This is where we work
This is where we work
Crowding-Out: A Meta-Analysis
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
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 1990 We include only original empirical quantitative
results N = 259 estimates from 47 articles
Crowding-out estimates
Mean crowding-out estimate
Mean effect of $1 increase in govt support
(N=190) – 0.231 (0,502)
Stronger crowding-out in lab experiments...
Mean effect of $1 increase in govt support
Lab experiments (N=49) – 0.628 (0.320)
Archival or survey data (N=141)
– 0.093 (0.481)
...models using instrumental variables...
Mean effect of $1 increase in govt support
Instrumental variables (N=43)
– 0.280 (0.711)
Other regression models (N=97)
– 0.019 (0.296)
(Lab experiments excluded)
...in the USA...
Mean effect of $1 increase in govt support
USA (N=159) – 0.227 (0.504)
Europe (N=141) 0.071 (0.435)
...and in the social sector.
Mean effect of $1 increase in govt support
Health (N=13) 0.033 (0.156)
International aid (N=11) – 0.035 (0.111)
Education (N=42) 0.061 (0.581)
Culture (N=21) 0.032 (0.392)
Social benefits (N=23) – 0.334 (0.292)
No big differences between regression models...
Mean effect of $1 increase in govt support
Fixed-effects / First-difference (N=95)
– 0.093 (0.551)
Other regression models (N=45)
– 0.112 (0.266)
(Lab experiments excluded)
...or the way government contributes.
Mean effect of $1 increase in govt support
Subsidies (N=128) – 0.099 (0.495)
Expenditures (N=13) – 0.041 (0.317)
(Lab experiments excluded)
Estimates nested in studies
Random-effects model
(Constant) – 0.281 (0.066)
Between-study SD 0.340
Rho 0.544
No. of studies 35
Observations 190
There is evidence for moderate crowding-out Finding strongly dependent on research design
Discussion
Crowding-Out in the Dutch Voluntary Sector
Giving in the Netherlands Panel Survey 2004 – 2012 (N=2,025)
Donations to 17 big charities Organizational information from Dutch Bureau
on Fundraising (CBF) Matching these data enables testing both
crowding-out and moderating effects
Longitudinal data
Trends in subsidies and donations (1)
Trends in subsidies and donations (2)
Trends in subsidies and donations (3)
Decreases (increases) in subsidies are not necessarily followed by increases (decreases) in donations
Instead, subsidies and donations often show the same pattern
Discussion
Estimate crowding-out in regression models Examine individual heterogeneity
–Altruistic values
– Income
–Political engagement
To do
Giving in the Netherlands Panel Survey (GINPS)
Deleted: scales on life satisfaction, joy-of-giving, crowding-out, modesty, self-reported altruism
New reciprocity measure More variables on culture Variables on active citizenship
What's new in GINPS14 – households
Second sample New reciprocity measure Even more variables on culture More variables on relation with charities
What's new in GINPS14 – HNW
Deleted: Measures of giving attitudes, self-reported altruism, social pressure, awareness of need, contact with country of origin, voting, subjective health
Variables on active citizenship Better measure of zakat and sadaqah
What's new in GINPS14 – immigrants
Zakat = obligation to give
–49% of muslims pays via mosque–33% pays through other method–18% doesn't pay zakat
Sadaqah = voluntary charitable contribution
–44% of muslims gives via mosque–29% gives through other method–27% doesn't give sadaqah
Zakat and sadaqah
We're more than happy to share our data User manual at www.giving.nl E-mail us with any questions
GINPS Data Use
Social innovation of the Third Sector in Europe (ITSSOIN)
European Commission FP7 project 10 research partners across Europe,
coordinated by U of Heidelberg What Third Sector characteristics drive social
innovation? Theory, quantitative analyses, case studies www.itssoin.eu
ITSSOIN
That's some stuff we're working on!
Contact
• Arjen de Wit, [email protected]• Center for Philanthropic Studies, VU University
Amsterdam, www.giving.nl
