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Personal Income Tax Reforms: a Genetic Algorithm Approach

Matteo Morini and Simone Pellegrino ()

No 147, CeRP Working Papers from Center for Research on Pensions and Welfare Policies, Turin (Italy)

Abstract: Given a settled reduction in the present level of tax revenue, and by exploring a very large combinatorial space of tax structures, in this paper we employ a genetic algorithm in order to determine the ‘best’ structure of a real world personal income tax that allows for the maximization of the redistributive effect of the tax, while preventing all taxpayers being worse off than with the present tax structure. We take Italy as a case study.

New Economics Papers: this item is included in nep-cmp, nep-pbe and nep-pub
Date: 2014-12
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Related works:
Journal Article: Personal income tax reforms: A genetic algorithm approach (2018) Downloads
Working Paper: Personal Income Tax Reforms: A Genetic Algorithm Approach (2016) Downloads
Working Paper: Personal Income Tax Reforms: a Genetic Algorithm Approach (2014) Downloads
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