Taxation, Corruption and Punishment: Integrating Evolutionary Game into the Optimal Control of Government Policy

Oliviero Carboni and Paolo Russu
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Paolo Russu: Department of Economics and Business, University of Sassari and CRENoS, Via Muroni 25, 07100 Sassari, Italy

International Game Theory Review (IGTR), 2021, vol. 23, issue 02, 1-22

Abstract: This work examines the issue of tax evasion through underreporting activity. The associated control problem for reducing the number of dishonest citizens and dishonest officers is explicitly analyzed. It is assumed that the social planner can choose the level of effort in order to control the dynamic system through the use of the specific countries’ characteristics q and p (the probability of punishing, respectively, a tax-evading citizen and a dishonest officer), and the level of public financial effort represented by taxation τ as control variables. The model implicitly considers that there is a direct correlation between these characteristics and the efficacy and the commitment of the institutional system in contrasting illegality. Hence, in the analysis, p and q are considered as the effective probabilities to be charged the fine. This study supplies a novel approach concerning the dynamic model underlying the optimal control, which is based on the strategic interaction of the economic agents’ choices. These latter are described by an evolutionary dynamic process which is strongly characterized by p and q. The analysis supplies a useful policy indication for the social planner in choosing the way to obtain a certain socially desirable target. Moreover, it helps the comprehension of the different corruption and evasion behavior observable in the real world, where countries with similar level of taxation may have different levels of corruption.

Keywords: Basin of attraction; corruption model; evolutionary dynamics; optimal control (search for similar items in EconPapers)
JEL-codes: C02 C61 C62 C73 H26 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S021919892050019X

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