Understanding Preferences for Income Redistribution

44 Pages Posted: 3 Dec 2004 Last revised: 24 Apr 2011

See all articles by Louise C. Keely

Louise C. Keely

University of Wisconsin - Madison - Department of Economics

Chih Ming Tan

University of North Dakota - College of Business & Public Administration - Department of Economics

Date Written: June 20, 2007

Abstract

Recent research suggests that income redistribution preferences vary across identity groups. We employ statistical learning methods which emphasize pattern recognition, classification and regression trees (CARTTM) and random forests (RandomForestsTM), to uncover what these groups are. Using data from the General Social Survey, we find that, out of a large set of identity markers, only race, gender, age, and socioeconomic class are important classifiers for income redistribution preferences. Further, the uncovered identity groupings are characterized by complex patterns of interaction amongst these salient classifiers. We explore the extent to which existing theories of income redistribution can explain our results, but conclude that current approaches do not fully explain the findings.

Keywords: Data mining, classification and regression trees, redistribution preferences, welfare, identity

JEL Classification: C45, C49, H50, H53

Suggested Citation

Keely, Louise and Tan, Chih Ming, Understanding Preferences for Income Redistribution (June 20, 2007). Journal of Public Economics, Vol. 92, 2008, Available at SSRN: https://ssrn.com/abstract=625686

Louise Keely

University of Wisconsin - Madison - Department of Economics ( email )

1180 Observatory Drive
Madison, WI 53706
United States
608 262 6723 (Phone)

HOME PAGE: http://www.ssc.wisc.edu/~lkeely

Chih Ming Tan (Contact Author)

University of North Dakota - College of Business & Public Administration - Department of Economics ( email )

293 Centennial Drive Stop 8369
Grand Forks, ND 58202-8369
United States

HOME PAGE: http://sites.google.com/site/chihmingtan/home

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