학술논문

An Evolutionary Game Model for Understanding Fraud in Consumption Taxes [Research Frontier]
Document Type
Periodical
Source
IEEE Computational Intelligence Magazine IEEE Comput. Intell. Mag. Computational Intelligence Magazine, IEEE. 16(2):62-76 May, 2021
Subject
Computing and Processing
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Computational modeling
Social factors
Finance
Games
Companies
Data models
Statistics
Language
ISSN
1556-603X
1556-6048
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.