  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.
