Abstract
Risk, audit frequency, expected utility, decision on the rate of tax evasion: probably these words occur to the reader first about tax evasion modeling. However, it can easily turn out in the real world that the ’everyday evader’ hasn’t got reliable information about the risks of evasion, about the possible amount of fine, or about the efficiency of the tax authorities. The TAXSIM agent-based tax evasion model was developed to understand the macro-level taxpayer behavior better with its help. The model and first simulation results were presented on the ESSA 2008 conference. The aim of this article is to present a sensitivity analysis of the model. We applied Design of Experiments method to reveal the main parameter-response correlations on a selected parameter domain and used two extreme parameter sets to examine on what level the contradictory factors can compensate each other.
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References
Allingham, M.G., Sandmo, A.: Income tax evasion: A theoretical analysis. Journal of Public Economics 1(3/4), 323–338 (1972)
Balsa, J.,Antunes, L., Respício, A., Coelho, H.: Tactical exploration of tax compliance decisions in multi-agent based simulation. In: Antunes, L., Takadama, K. (eds.) MABS 2006. LNCS (LNAI), vol. 4442, pp. 80–95. Springer, Heidelberg (2007)
Becker, G.S.: quotedblbaseCrime and punishment: an economic approach. Journal of Political Economy 76(2), 169–217 (1968)
Bloomquist, K.M.: A Comparison of Agent-Based Models of Income Tax Evasion. Social Science Computer Review 24(4), 411–425 (2006)
Box, G.E., Hunter, W.G., Hunter, J.S.: Statistics for Experimenters: Design, Innovation, and Discovery, 2nd edn. Wiley, Chichester (2005)
Czitrom, V.: One-Factor-at-a-Time Versus Designed Experiments. The American Statistician 53 (1999)
Davis, J.S., Hecht, G., Perkins, J.D.: Social Behaviors,Enforcement and Tax compliance Dynamics. Accounting Rev. 78, 39–69 (2003)
Erdős, P., Rényi, A.: On Random Graphs. I. Publicationes Mathematicae 6, 290–297 (1959)
Korobow, A., Johnson, C., Axtell, R.: An Agent-Based Model of Tax Compliance with Social Networks. National Taxc Journal (2007)
Ivanyi, M., Bocsi, R., Gulyas, L., Kozma, V., Legendi, R.: The Multi-Agent Simulation Suite. Emergent Agents and Socialities:Social and Organizational Aspects of Intelligence. Papers from the 2007 AAAI Fall Symposium, pp. 57–64 (2007)
Mittone, L., Petelli, P.: Imitative Behaviour in Tax Evasion. In: Stefansson, B., Luna, F. (eds.) Economic Modeling with Swarm. Kluwer, Amsterdam (2000)
NIST/SEMATECH e-Handbook of Statistical Methods (2009), http://www.itl.nist.gov/div898/handbook/
North, M.J., Collier, N.T., Vos, J.R.: Experiences Creating Three Implementations of the Repast Agent Modeling Toolkit. ACM Transactions on Modeling and Computer Simulation 16(1), 1–25 (2006)
Szabo, A., Gulyas, L., Toth, I.J.: TAXSIM Agent Based Tax Evasion Simulator. In: Proceedings ESSA 2008 Conference, Brescia, Italy (2008)
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Szabó, A., Gulyás, L., Tóth, I.J. (2009). Sensitivity Analysis of a Tax Evasion Model Applying Automated Design of Experiments. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_47
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DOI: https://doi.org/10.1007/978-3-642-04686-5_47
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