Personal income tax reforms: A genetic algorithm approach |
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| Authors: | Matteo Morini Simone Pellegrino |
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| Institution: | 1. ENS Lyon, Institut Rhône-Alpin des Systèmes Complexes (IXXI), Site Jacques Monod 46, allée d''Italie, 69007 Lyon, France;2. Department of Economics and Statistics, University of Torino, Corso Unione Sovietica 218 bis, 10134 Torino, Italy\n |
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| 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 maximisation 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. |
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| Keywords: | Genetic algorithms Personal income taxation Micro-simulation models Reynolds–Smolensky index Tax reforms |
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