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Identity, Authority and Evolution of Order: the trajectory of dueling simulated

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  • Behrooz Hassani-Mahmooei, Behrooz
  • Vahabi, Mehrdad

Abstract

Borrowing from public choice literature, while aristocratic civil wars can be regarded as anarchy, and the monopoly of violence by the state as Leviathan, duel of honor is an orderly anarchy. The sudden or gradual withering of duel of honor as an institution marks the transition to the monopoly of violence by the state in Europe. In this paper, we endeavor to capture this transition by introducing a computational model where a simulated agent considers three sets of factors to make its dueling decision: 1) its own characteristics such as dueling skill; 2) its identity such as the reaction received from other members of its own social group; and finally 3) the reaction of the authority such as the possible punishment that could be inflicted by the state against dueler. These factors then interact through a dynamic utility function affected by both optimization and learning processes. The results of our agent-based computational model which are validated against the historical evidence from England, France, and Germany show that a complex, aggregative historical process may be consistently explained on the basis of rational choice of heterogeneous individual agents conditioned by their group identity and authority (organizational) influence.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 48219.

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Date of creation: Jan 2013
Date of revision: 10 Jul 2013
Handle: RePEc:pra:mprapa:48219

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Keywords: Agent-based Computational Economics; Conflict theory; Duel of honor; Identity Economics; Orderly anarchy;

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  1. George A. Akerlof & Rachel E. Kranton, 2000. "Economics And Identity," The Quarterly Journal of Economics, MIT Press, vol. 115(3), pages 715-753, August.
  2. Christopher G. Kingston & Robert E. Wright, 2010. "The Deadliest of Games: The Institution of Dueling," Southern Economic Journal, Southern Economic Association, vol. 76(4), pages 1094-1106, April.
  3. Richard Wallick, 2012. "Agent-based modeling, public choice, and the legacy of Gordon Tullock," Public Choice, Springer, vol. 152(1), pages 223-244, July.
  4. Benjamin Powell & Edward Stringham, 2009. "Public choice and the economic analysis of anarchy: a survey," Public Choice, Springer, vol. 140(3), pages 503-538, September.
  5. Stergios Skaperdas, 1996. "Contest success functions (*)," Economic Theory, Springer, vol. 7(2), pages 283-290.
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  7. Jack Hirshleifer, 1989. "Conflict and rent-seeking success functions: Ratio vs. difference models of relative success," Public Choice, Springer, vol. 63(2), pages 101-112, November.
  8. Garfinkel, Michelle R. & Skaperdas, Stergios, 2007. "Economics of Conflict: An Overview," Handbook of Defense Economics, Elsevier.
  9. Blake LeBaron & Leigh Tesfatsion, 2008. "Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents," American Economic Review, American Economic Association, vol. 98(2), pages 246-50, May.
  10. Kooreman, Peter & Schoonbeek, Lambert, 1997. "The specification of the probability functions in Tullock's rent-seeking contest," Economics Letters, Elsevier, vol. 56(1), pages 59-61, September.
  11. Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2008. "Schumpeter Meeting Keynes: A Policy-Friendly Model of Endogenous Growth and Business Cycles," Working Papers 50/2008, University of Verona, Department of Economics.
  12. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
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