De Gustibus non est Taxandum: Heterogeneity in preferences and optimal redistribution
Benjamin Lockwood and
Matthew Weinzierl ()
Journal of Public Economics, 2015, vol. 124, issue C, 74-80
Abstract:
The prominent but unproven intuition that preference heterogeneity reduces redistribution in a standard optimal tax model is shown to hold under the plausible condition that the distribution of preferences for consumption relative to leisure rises, in terms of first-order stochastic dominance, with income. Given familiar functional form assumptions on utility and the distributions of ability and preferences, a simple statistic for the effect of preference heterogeneity on marginal tax rates is derived. Numerical simulations and suggestive empirical evidence demonstrate the link between this potentially measurable statistic and the quantitative implications of preference heterogeneity for policy.
Keywords: Optimal taxation; Preference heterogeneity; Redistribution; Sufficient statistics (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (49)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047272715000134
Full text for ScienceDirect subscribers only
Related works:
Working Paper: De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution (2014) 
Working Paper: De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution (2012) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:pubeco:v:124:y:2015:i:c:p:74-80
DOI: 10.1016/j.jpubeco.2015.01.002
Access Statistics for this article
Journal of Public Economics is currently edited by R. Boadway and J. Poterba
More articles in Journal of Public Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().