Redistributive Taxation in the Roy Model
Casey Rothschild and
Florian Scheuer
The Quarterly Journal of Economics, 2013, vol. 128, issue 2, 623-668
Abstract:
We consider optimal redistribution in a model where individuals can self-select into one of several possible sectors based on heterogeneity in a multidimensional skill vector. We first show that when the government does not observe the sectoral choice or underlying skills of its citizens, the constrained Pareto frontier can be implemented with a single nonlinear income tax. We then characterize this optimal tax schedule. If sectoral inputs are complements, a many-sector model with self-selection leads to optimal income taxes that are less progressive than the corresponding taxes in a standard single-sector model under natural conditions. However, they are more progressive than in canonical multisector economies with discrete types and without occupational choice or overlapping sectoral wage distributions. JEL Codes: H2, D5, D8, E2, E6, J3, J6. Copyright 2013, Oxford University Press.
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (150)
Downloads: (external link)
http://hdl.handle.net/10.1093/qje/qjs076 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Redistributive Taxation in the Roy Model (2012) 
Working Paper: Redistributive Taxation in a Roy Model (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:oup:qjecon:v:128:y:2013:i:2:p:623-668
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
The Quarterly Journal of Economics is currently edited by Robert J. Barro, Lawrence F. Katz, Nathan Nunn, Andrei Shleifer and Stefanie Stantcheva
More articles in The Quarterly Journal of Economics from President and Fellows of Harvard College
Bibliographic data for series maintained by Oxford University Press ().