Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/107085
Title: An evolutionary game model for understanding fraud in consumption taxes [Research Frontier]
Authors: Chica, Manuel
Hernández Guerra, Juan María 
Manrique De Lara Peñate, Casiano 
Chiong, Raymond
UNESCO Clasification: 530202 Modelos econométricos
530101 Política fiscal y deuda pública
Keywords: Tax compilance
Value added tax
Game models
Subjective probability
Issue Date: 2021
Journal: IEEE Computational Intelligence Magazine 
Abstract: This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. Each player's payoff is influenced by the amount evaded and the subjective probability of being inspected by tax authorities. Since transactions between companies must be declared by both the buyer and seller, a strategy adopted by one influences the other?s payoff. We study the model with a wellmixed population and different scalefree networks. Model parameters were calibrated using real-world data of VAT declarations by businesses registered in the Canary Islands region of Spain. We analyzed several scenarios of audit probabilities for high and low transactions and their prevalence in the population, as well as social rewards and penalties to find the most efficient policy to increase the proportion of cooperators. Two major insights were found. First, increasing the subjective audit probability for low transactions is more efficient than increasing this probability for high transactions. Second, favoring social rewards for cooperators or alternative penalties for defectors can be effective policies, but their success depends on the distribution of the audit probability for low and high transactions.
URI: http://hdl.handle.net/10553/107085
ISSN: 1556-603X
DOI: 10.1109/MCI.2021.3061878
Source: IEEE Computational Intelligence Magazine [ISSN 1556-603X], v. 16 (2), p. 62-76, (Mayo 2021)
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