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Lottery markets design, micro-structure, and macro-behavior: An ACE approach

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  • Chen, Shu-Heng
  • Chie, Bin-Tzong

Abstract

An agent-based computational modeling of the lottery market is established in this paper to study the design issue, in terms of the lottery tax rate, as well as the emerging market behavior. By using genetic algorithms and fuzzy logic, lottery participants are modeled as autonomous agents who may endogenously adapt to exhibit behavioral properties consistent with well-noticed behavior of lottery markets. Three major findings are presented. First, as anticipated, a Laffer curve is found in this model; nonetheless, the Laffer curve has a flat top, which indicates the non-uniqueness of the optimal lottery tax rate. Second, conscious selection behavior is also observed, but it becomes weaker as time goes on. Third, for the halo effect, we observe exactly the opposite. Each of these three findings are then compared with available empirical results, and the mechanism of genetic algorithms is further examined in light of the anti-halo effect.

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  • Chen, Shu-Heng & Chie, Bin-Tzong, 2008. "Lottery markets design, micro-structure, and macro-behavior: An ACE approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 463-480, August.
  • Handle: RePEc:eee:jeborg:v:67:y:2008:i:2:p:463-480
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    References listed on IDEAS

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    1. Mikesell, John L., 1994. "State Lottery Sales and Economic Activity," National Tax Journal, National Tax Association, vol. 47(1), pages 165-71, March.
    2. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
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    7. Scoggins, John F., 1995. "The Lotto and Expected Net Revenue," National Tax Journal, National Tax Association, vol. 48(1), pages 61-70, March.
    8. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947 Elsevier.
    9. Beenstock, Michael & Goldin, Ephraim & Haitovsky, Yoel, 2000. "What jackpot? The optimal lottery tax," European Journal of Political Economy, Elsevier, vol. 16(4), pages 655-671, November.
    10. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011 Elsevier.
    11. Farrell, Lisa & Morgenroth, Edgar & Walker, Ian, 1999. " A Time Series Analysis of U.K. Lottery Sales: Long and Short Run Price Elasticities," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 513-526, November.
    12. Mikesell, John L., 1994. "State Lottery Sales and Economic Activity," National Tax Journal, National Tax Association;National Tax Journal, vol. 47(1), pages 165-171, March.
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    15. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233 Elsevier.
    16. Ian Walker, 1998. "The economic analysis of lotteries," Economic Policy, CEPR;CES;MSH, vol. 13(27), pages 357-402, October.
    17. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
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    Cited by:

    1. Coronel-Brizio, H.F. & Hernández-Montoya, A.R. & Rapallo, F. & Scalas, E., 2008. "Statistical auditing and randomness test of lotto k/N-type games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6385-6390.
    2. Gabrielyan, Gnel & Just, David R., 2017. "Economic Factors Affecting Lottery Sales: An Examination of Maine State Lottery Sales," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258419, Agricultural and Applied Economics Association.
    3. Kent Grote & Victor Matheson, 2011. "The Economics of Lotteries: A Survey of the Literature," Working Papers 1109, College of the Holy Cross, Department of Economics.
    4. G. Fagiolo & A. Roventini., 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 6.
    5. Rose Baker & David Forrest & Levi Pérez, 2016. "The compatriot win effect on national sales of a multicountry lottery," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 603-618, August.
    6. Alexis DIRER, 2010. "Equilibrium Lottery Games and Preferences Under Risk," LEO Working Papers / DR LEO 550, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    7. Michael Coon & Gwyneth Whieldon, 2016. "Elasticity of Demand and Optimal Prize Distribution for Instant Lottery Games," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(4), pages 457-469, December.

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