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Redistributive choices and increasing income inequality: experimental evidence for income as a signal of deservingness

Published online by Cambridge University Press:  14 March 2025

Laura K. Gee ,
Marco Migueis  and
Sahar Parsa
Laura K. Gee
Affiliation:
Tufts University, Medford, USA
Marco Migueis*
Affiliation:
Federal Reserve Board, Washington DC, USA
Sahar Parsa
Affiliation:
Tufts University, Medford, USA
*
mmigueis@gmail.com
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Abstract

We explore the relation between redistribution choices, source of income, and pre-redistribution inequality. Previous studies find that when income is earned through work there is less support for redistribution than when income is determined by luck. Using a lab experiment, we vary both the income-generating process (luck vs. performance) and the level of inequality (low vs. high). We find that an increase in inequality has less impact on redistribution choices when income is earned through performance than when income results from luck. This result is likely explained by individuals using income differences as a heuristic to infer relative deservingness. If people believe income inequality increases as a result of performance rather than luck, then they are likely to believe the poor deserve to stay poor and the rich deserve to stay rich.

Keywords

Income redistributionFairnessExperimental economics
Type
Original Paper
Information
Experimental Economics , Volume 20 , Issue 4 , December 2017 , pp. 894 - 923
Copyright
Copyright © 2017 Economic Science Association

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Footnotes

Electronic supplementary material The online version of this article (doi:https://doi.org/10.1007/s10683-017-9516-5) contains supplementary material, which is available to authorized users.

The opinions expressed in this manuscript belong to the authors and do not represent official positions of the Federal Reserve Board or the Federal Reserve System. We would like to thank Mariana Blanco for her kind assistance with this paper. In addition, we thank Christopher Anderson, Darcy Covert, Xinxin Lyu, Mike Manzi, Maria Morales-Loaiza, Eitan Scheinthal, Tom Tagliaferro, Isabelle Vrod, Kenneth Weitzman, and Qinyue Yu for excellent research assistance. Finally, we thank the editors, two anonymous referees, Kelsey Jack, Pablo Querubin, Debraj Ray, and Gregory DeAngelo for their helpful comments and suggestions. This research was supported in part by funds from the Tufts University Faculty Research Awards Committee.

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Performance-High Treatment (with Beliefs Elicitation)
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