Optimal Income Taxation with a Stationarity Constraint in a Dynamic Stochastic Economy

Marcus Berliant and Shota Fujishima

MPRA Paper from University Library of Munich, Germany

Abstract: We consider the optimal nonlinear income taxation problem in a dynamic, stochastic environment when the government cannot change the tax rule as uncertainty resolves. Due to such a stationarity constraint, our taxation problem is reduced to a static one over an expanded type space that incorporates type evolution. We strengthen the argument in the static model that the zero top marginal tax rate result is of little practical importance because it only applies to the top of the expanded type space. If the maximal type increases over time, the person with top ability in any period but the last has a positive marginal tax rate.

Keywords: Optimal income taxation; New dynamic public finance (search for similar items in EconPapers)
JEL-codes: H21 (search for similar items in EconPapers)
Date: 2016-05-26
New Economics Papers: this item is included in nep-ore, nep-pbe and nep-pub
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/71625/1/MPRA_paper_71625.pdf original version (application/pdf)

Related works:
Journal Article: Optimal income taxation with a stationarity constraint in a dynamic stochastic economy (2017)
Working Paper: Optimal income taxation with a stationarity constraint in a dynamic stochastic economy (2016)
Working Paper: Optimal Income Taxation with a Stationarity Constraint in a Dynamic Stochastic Economy (2015)
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:pra:mprapa:71625

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().