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Feb 24, 2013

A Welcome Data Approach to Understanding Philanthropy

I recently had an energizing conversation with Professor Michael Price, a young assistant professor at Georgia State University.  The reason for our meeting was his participation in a new, research-oriented study of what drives philanthropy, called the Science of Philanthropy Initiative.  It is a joint effort of the University of Chicago, Georgia State, and University of Wisconsin.

Here is the skinny from their website:    The Science of Philanthropy Initiative (SPI) is a research and outreach project that utilizes rigorous quantitative methods and partnerships with the philanthropic community to explore the motivations behind charitable giving.

Funded by a generous grant from The John Templeton Foundation, the overarching goal of SPI is to develop a deeper understanding of the types of social preferences that shape philanthropic giving and to apply this knowledge to both practitioners and policymakers interested in philanthropy and the private provision of public goods.

This is a most welcome initiative and is especially timely given the worry about any changes in the tax deductibility of charitable contributions.  Most of this worry now must base its concerns on anecdotal information and survey results, none of which can be persuasive to dueling parties.  We need to have research that uses rigorous statistical methods and carefully measured data to understand what drives philanthropy.

I personally hope that the researchers can find a way to bring empirical methods to understanding what drives the “value” of philanthropy.  I can provide dozens of anecdotes to show where donor-imposed metrics and restrictions can erode or eliminate the benefit of a grant or donation to a nonprofit.  To have empirical data would either knock me off my high horse or give me a company of cavalry in my efforts to make philanthropy a stronger force in nonprofit empowerment.

Check out Science of Philanthropy, sign up for its newsletters, and hope they are successful in getting some useful empirical results.