Identifying the Distribution of Welfare from Discrete Choice

Bart Capéau, Liebrecht De Sadeleer and Sebastiaan S. Maes

No 2022-03, Working Papers ECARES from ULB -- Universite Libre de Bruxelles

Abstract: Empirical welfare analyses often impose stringent parametric assumptions on individuals' preferences and neglect unobserved preference heterogeneity. In this paper, we develop a framework to conduct individual and social welfare analysis for discrete choice that does not suffer from these drawbacks. We first adapt the class of individual welfare measures introduced by Fleurbaey (2009) to settings where individual choice is discrete. Allowing for unrestricted, unobserved preference heterogeneity, these measures become random variables. We then show that the distribution of these objects can be derived from choice probabilities, which can be estimated nonparametrically from cross-sectional data. In addition, we derive nonparametric results for the joint distribution of welfare and welfare differences, as well as for social welfare. The former is an important tool in determining whether the winners of a price change belong disproportionately to those groups who were initially well-off. An empirical illustration demonstrates the relevance of the methods and the importance of considering welfare instead of income.

Keywords: discrete choice; nonparametric welfare analysis; individual welfare; social welfare; money metric utility; compensating variation; equivalent variation (search for similar items in EconPapers)
Pages: 52 p.
Date: 2022-01
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-upt
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