An Evolutionary Game Model for Understanding Fraud in Consumption Taxes
This work addresses tax fraud, a critical issue for governments and economies, but it is incremental as it applies an existing modeling approach to a specific domain with calibrated data.
The paper tackles the problem of understanding fraud dynamics in consumption tax systems by developing an evolutionary game model calibrated with real VAT data from the Canary Islands, finding that increasing subjective audit probabilities for low transactions is more efficient than for high transactions and that social rewards or penalties can be effective depending on audit distributions.
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 well-mixed population and different scale-free 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.