This study examines the effects of race and gender on philanthropy and interaction effects between race or gender and survey methodologies. Results indicate differences in philanthropic behaviors by gender but not by race. We also find significant interaction effects between survey methodologies and race and gender, which may have important implications for social science research in which race and/or gender explain or predict behaviors. Economic theory dictates that public goods and goods with large externalities can lead to market failures that can be ameliorated by taxes, subsidies, or regulation. Private philanthropy can play an important role in addressing these market failures, especially for smaller, less politically powerful groups (Weisbrod, 1975) whose preferences are not reflected in the outcomes of majority voting. Conditional on their ability to overcome free riding, marginalized groups, such as women and minorities, can use the nonprofit sector as a substitute for government-supplied public goods. We test whether race and/or gender affects charitable giving by American households as measured under commonly adopted survey methodologies.
How much does survey methodology matter when measuring volunteering? Every 4 years, the Center on Philanthropy at Indiana University conducts a telephone survey (called "Indiana Gives") How do you measure volunteering? It seems to be a straightforward question. But in the United States at least, the most frequently used methods of measuring giving and volunteering-most of which are based on surveys-produce surprisingly disparate results. Most researchers agree that more precise ways of estimating how much time and money people give are needed. This issue is important because many fund-raisers, nonprofit leaders, and public policy makers often use such estimates to understand how much and why people do volunteer work and how and why they donate to charity, as well as to see how Note: The authors would like to thank Paul Schervish, who helped design the overall study, and Brian Vargus and the Public Opinion Laboratory at IUPUI for helping with the data collection. We also would like to acknowledge Richard Steinberg and Mark Wilhelm for their invaluable input. An earlier version of this article was presented at ARNOVA, and we would like to thank the session members for several good suggestions.
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