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

被引:8
|
作者
Peck, Laura R. [1 ]
D'Attoma, Ida [2 ]
Camillo, Furio [2 ]
Guo, Chao [3 ]
机构
[1] ABT Associates Inc, Social & Econ Policy Div, Cambridge, MA 02138 USA
[2] Univ Bologna, Dept Stat Sci, I-40126 Bologna, Italy
[3] Univ Georgia, Dept Publ Adm & Policy, Athens, GA 30602 USA
关键词
public assistance; welfare; charity; selection bias; cluster analysis; CLUSTERS; NUMBER; POLICY; OLDER; VOLUNTEERS; WELFARE; INDIANA; MODEL;
D O I
10.1111/j.1541-0072.2012.00466.x
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
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.
引用
收藏
页码:601 / 625
页数:25
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