Tax Evasion Dynamics via Non-Equilibrium Model on Complex Networks

Francisco W. S. Lima

Dietrich Stauffer Computational Physics Lab, Departamento de Física Universidade Federal do Piauí, Teresina, Brazil.

DOI: 10.4236/tel.[phone]                

Abstract

The Zaklan model has become an excellent mechanism to control the tax evasion fluctuations (TEF) in a people- or agent-based community. Initially, the equilibrium Ising model (IM) had been used as a dynamic of temporal evolution of the Zaklan model near the critical point of the IM. On some complex network the IM presents no critical points or well-defined phase transitions. Then, through Monte Carlo simulations we study the recurring problem of the TEF control using the version of non-equilibrium Zaklan model as a control mechanism for TEF via agent-based non-equilibrium majority-vote model (MVM). Here we study the TEF on directed Barabási-Albert (BAD) and Apollonian (ANs) networks where the IM is not applied. We show that the Zaklan model can be also studied using non-equilibrium dynamics through of the non-equilibrium MVM on complex topologies cited above, giving the behavior of the TEF regardless of dynamic or topology used here.

Keywords

Opinion Dynamics, Sociophysics, Majority Vote, Non-Equilibrium

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Stauffer, D., de Oliveira, S.M., de Oliveira, P.M.C. and Martins, J.S.S. (2006) Biology, Sociology, Geology by Computational Physicists. Elsevier, Amsterdam.
[2]	Galam, S. (2012) Sociophysics: A Physicist’s Modeling of Psycho-Political Phenomena. Springer, Berlin-Heidelberg. http://dx.doi.org/10.1007/978-1-4614-2032-3
[3]	Ball, P. (2012) Why Society Is a Complex Matter? Springer, Berlin-Heidelberg. http://dx.doi.org/10.1007/978-3-642-29000-8
[4]	Helbing, D. (2012) Social Self-Organization: Agent-Based Simulations and Experiments to Study Emergent Social Behavior. Springer, Berlin-Heidelberg. http://dx.doi.org/10.1007/978-3-642-24004-1
[5]	Sen, P. and Chakrabarti, B.K. (2014) Sociophysics—An Introduction. Oxford University Press, Oxford.
[6]	Latané, B. (1981) The Psychology of Social Impact. American Psychologist, 36, 343. http://dx.doi.org/10.1037/0003-066X.36.4.343
[7]	Zaklan, G., Westerhoff, F. and Stauffer, D. (2008) Analysing Tax Evasion Dynamics via the Ising Model. Journal of Economic Interaction and Coordination, 4, 1. http://dx.doi.org/10.1007/s11403-008-0043-5
[8]	Zaklan, G., Lima, F.W.S. and Westerhoff, F. (2008) Controlling Tax Evasion Fluctuations. Physica A, 387, 5857. http://dx.doi.org/10.1016/j.physa.2008.06.036
[9]	Stauffer, D. (2013) A Biased Review of Sociophysics. Journal of Statistical Physics, 151, 9. http://dx.doi.org/10.1007/s10955-012-0604-9
[10]	Bloomquist, K. (2006) A Comparison of Agent-Based Models of Income Tax Evasion. Social Science Computer Review, 24, 411. http://dx.doi.org/10.1177/0894439306287021
[11]	Follmer, H. (1974) Random Economies with Many Interacting Agents. Journal of Mathematical Economics, 1, 51-62. http://dx.doi.org/10.1016/0304-4068(74)90035-4
[12]	Andreoni, J., Erard, B. and Feinstein, J. (1998) Tax Compliance. Journal of Economic Literature, 36, 818-860.
[13]	Lederman, L. (2003) The Interplay between Norms and Enforcement in Tax Compliance. Public Law Research Paper No. 49. http://dx.doi.org/10.2139/ssrn.391133
[14]	Slemrod, J. (2007) Cheating Ourselves: The Economics of Tax Evasion. Journal of Economic Perspective, 21, 25-48. http://dx.doi.org/10.1257/jep.21.1.25
[15]	Wintrobe, R. and Gerxhani, K. (2004) Tax Evasion and Trust: A Comparative Analysis. Proceedings of the Annual Meeting of the European Public Choice Society, Berlin, 15-18 April 2004.
[16]	Gachter, S. (2006) Conditional Cooperation: Behavioral Regularities from the Lab and the Field and Their Policy Implications. Discussion Papers 2006-03 CeDEx, University of Nottingham, Nottingham.
[17]	Frey, B.S. and Togler, B. (2006) Tax Evasion, Black Activities and Deterrence in Germany: An Institutional and Empirical Perspective. IEW-Working Papers 286, Institute for Empirical Research in Economics, University of Zurich, Zurich.
[18]	Lima, F.W.S. (2010) Analysing and Controlling the Tax Evasion Dynamics via Majority-Vote Model. Journal of Physics: Conference Series, 246, Article ID: 012033. http://dx.doi.org/10.1088/1742-6596/246/1/012033
[19]	Lima, F.W.S. (2012) Controlling the Tax Evasion Dynamics via Majority-Vote Model on Various Topologies. Theoretical Economics Letters, 2, 87-93. http://dx.doi.org/10.4236/tel.[phone]
[20]	Oliveira, M.J. (1992) Isotropic Majority-Vote Model on a Square Lattice. Journal of Statistical Physics, 66, 273-281. http://dx.doi.org/10.1007/BF01060069
[21]	Andrade, R.S.F. and Herrmann, H.J. (2005) Magnetic Models on Apollonian Networks. Physical Review E, 71, Article ID: 056131. http://dx.doi.org/10.1103/PhysRevE.71.056131
[22]	Andrade, R.S.F., Andrade Jr., J.S. and Herrmann, H.J. (2009) Ising Model on the Apollonian Network with Node-Dependent Interactions. Physical Review E, 79, Article ID: 036105. http://dx.doi.org/10.1103/PhysRevE.79.036105
[23]	Sumour, M.A. and Shabat, M.M. (2005) Monte Carlo Simulation of Ising Model on Directed Barabasi-Albert Networks. International Journal of Modern Physics C, 16, 585-589. http://dx.doi.org/10.1142/S0129183105007352
[24]	Aleksiejuk, A., Holyst, J.A. and Stauffer, D. (2002) Ferromagnetic Phase Transition in Barabási-Albert Networks. Physica A, 310, 260-266. http://dx.doi.org/10.1016/S0378-4371(02)00740-9
[25]	Albert, R., Jeong, H. and Barabási, A.-L. (1999) Internet: Diameter of the World-Wide Web. Nature, 401, 130-131. http://dx.doi.org/10.1038/43601
[26]	Watts, D.J. and Strogatz, S.H. (1998) Collective Dynamics of “Small-World” Networks. Nature, 393, 440-442. http://dx.doi.org/10.1038/30918
[27]	Lima, F.W.S., Moreira, A.A. and Araújo, A.D. (2012) Nonequilibrium Model on Apollonian Networks. Physical Review E, 86, Article ID: 056109. http://dx.doi.org/10.1103/PhysRevE.86.056109