In this paper, we present a new agent-based model for the simulation of tax compliance and tax evasion behavior (SIMULFIS). The main novelties of the model are the introduction of a "behavioral filter approach" to model tax decisions, the combination of a set of different mechanisms to produce tax compliance (namely rational choice, normative commitments and social influence), and the use of the concept of "fraud opportunity use rate" (FOUR) as the main behavioral outcome. After describing the model in detail, we display the main behavioral and economic results of 1,920 simulations calibrated for the Spanish case and designed to test for the internal validity of SIMULFIS. The behavioral outcomes show that scenarios with strict rational agents strongly overestimate tax evasion, while the introduction of social influence and normative commitments allows to generate more plausible compliance levels under certain deterrence conditions. Interestingly, the relative effect of social influence is shown to be ambivalent: it optimizes * Corresponding author. 1350007-1 Advs. Complex Syst. 2013.16. Downloaded from www.worldscientific.com by AUSTRALIAN NATIONAL UNIVERSITY on 03/15/15. For personal use only.

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Els diversos corrents de la sociolo ia de la cihzcia sovint han dirigit la seva atenció exclusiva bé a léstudi dels dS zscursos cientifics, bé al de les

This paper is just a concept presentation to be discussed at the ECMS12, based on preliminary work of a research project funded by the Spanish Institute for Fiscal Studies (Ministry of Economy). This project aims to build an agent-based model (ABM) for the simulation of tax compliance and tax evasion behaviour, and to calibrate it empirically in order to generate some known patterns of tax behaviour among Spanish taxpayers. Here we present the state of the development for the formal model and our present ideas about the implementation methodology, with focus on a new algorithm-based in four different decisional mechanisms-so that it includes not just the usual expected utility optimization, but also other sociologically relevant features like social network structure, social influence, decisional heuristics, biases in the perception of the tax system, and heterogeneity of tax motivations and tax morale among the agents. The methodological discussion about this kind of "modularity" in implementing a decisional engine could be completed in Koblenz with some preliminary results based on experimentation with the initial parameters and decisional modules.