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A New Strategy for Reducing Selection Bias in Nonexperimental Evaluations, and the Case of How Public Assistance Receipt Affects Charitable Giving

Authors

  • Laura R. Peck,

  • Ida D'Attoma,

  • Furio Camillo,

  • Chao Guo


  • We are grateful to the agencies that fund the Panel Study of Income Dynamics, Atlantic Philanthropies for funding the collection of data in the first four waves of the Center on Philanthropy Panel Study (COPPS), and the Bill and Melinda Gates Foundation for funding the 2007 and 2009 data collection of the Center Panel as well as the dissemination of the 2005 data. We appreciate the research assistance of Andrea Mayo at Arizona State University (ASU) and Will Huguenin at Abt Associates Inc. We also acknowledge participants in the Arizona State University School of Public Affairs Research Colloquium, in the ASU Center for Population Dynamics Colloquium, participants at our Fall 2011 panel at the Research Conference of the American Evaluation Association, and in Abt Associates' Journal Author Support Group for their useful input.

Abstract

Prior research considers the extent to which public assistance recipients' charitable activity differs from the habits of the general population. Although receiving public assistance is negatively associated with donating money, the relationship to volunteering is unclear. In response to challenges overcoming selection bias, we conducted a multivariate cluster-based subgroup analysis to reduce bias in our claims about the ways in which public assistance receipt affects charitable activity. This innovative approach to dealing with the problem of selection bias has implications and applications across the social sciences.

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