Tax evasion behavior using finite automata: Experiments in Chile and Italy
In this paper, we use a Moore Automata with Binary Stochastic Output Function in order to capture the extensive decision regarding tax evasion made by subjects in experiments run in Chile and Italy. Firstly, we show how an hypothesis about subject behavior is converted into an automaton, and how we compute the probabilities of evading for every state of an automaton. We use this procedure in order to look for the automaton which is able to anticipate the highest number of decisions made by the subjects during the experiments. Finally, we show that automata with few states perform better than automata with many states, and that the bomb-crater effect described in Mittone (2006) is a well identified pattern of behavior in a subset of subjects.
tax evasion computational theory moore machine computational complexity