Personal income tax reforms: a genetic algorithm approach

DOI10.1016/j.ejor.2016.07.059zbMath1375.90196OpenAlexW3124753870MaRDI QIDQ1681429

Matteo Morini, Simone Pellegrino

Publication date: 23 November 2017

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://hal.inria.fr/hal-01388958/file/MoPe_GA.pdf

zbMATH Keywords

genetic algorithmstax reformsmicro-simulation modelspersonal income taxationReynolds-smolensky index

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Macroeconomic theory (monetary models, models of taxation) (91B64) Case-oriented studies in operations research (90B90)

Related Items

Multi-objective optimization of a nonlinear batch time-delay system with minimum system sensitivity ⋮ On measuring axiom violations due to each tax instrument applied in a real-world personal income tax

Uses Software

• Pyevolve

Cites Work

• Unnamed Item
• Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms -- support vector regression forecast combinations
• Tackling real-coded genetic algorithms: operators and tools for behavioural analysis
• Genetic algorithms for portfolio selection problems with minimum transaction lots
• Using Elasticities to Derive Optimal Income Tax Rates
• Employment, Hours of Work and the Optimal Taxation of Low-Income Families
• Using a Microeconometric Model of Household Labour Supply to Design Optimal Income Taxes*
• An Exploration in the Theory of Optimum Income Taxation

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