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Inferring strategies from observed actions: a nonparametric, binary tree classification approach

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  • Engle-Warnick, Jim

Abstract

This paper introduces a nonparametric binary classification tree approach to inferring unobserved strategies from the observed actions of economic agents. The strategies are in the form of possibly nested if- then statements. We apply our approach to experimental data from the repeated ultimatum game, which was conducted in four different countries by Roth et al. (1991). We find that strategy inference is consistent with existing inference, provides new explanations for subject behavior, and provides new empirically--based hypotheses regarding ultimatum game strategies. We conclude that strategy inference is potentially useful as a complementary method of statistical inference in applied research.
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Suggested Citation

  • Engle-Warnick, Jim, 2003. "Inferring strategies from observed actions: a nonparametric, binary tree classification approach," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2151-2170, September.
    • Handle: RePEc:eee:dyncon:v:27:y:2003:i:11-12:p:2151-2170
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    References listed on IDEAS

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    1. Jim Engle-Warnick & Robert Slonim, 2006. "Inferring repeated-game strategies from actions: evidence from trust game experiments," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 603-632, August.
    2. Roth, Alvin E. & Vesna Prasnikar & Masahiro Okuno-Fujiwara & Shmuel Zamir, 1991. "Bargaining and Market Behavior in Jerusalem, Ljubljana, Pittsburgh, and Tokyo: An Experimental Study," American Economic Review, American Economic Association, vol. 81(5), pages 1068-1095, December.
    3. Duffy, John & Engle-Warnick, Jim, 2006. "Multiple Regimes in U.S. Monetary Policy? A Nonparametric Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1363-1377, August.
    4. Durlauf, Steven N & Johnson, Paul A, 1995. "Multiple Regimes and Cross-Country Growth Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 365-384, Oct.-Dec..
    5. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    6. Cooper, Suzanne J, 1998. "Multiple Regimes in U.S. Output Fluctuations," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 92-100, January.
    7. John Duffy & Jim Warnick, 1999. "Using Symbolic Regression to Infer Strategies from Experimental Data," Computing in Economics and Finance 1999 1033, Society for Computational Economics.
    8. Jim Engle-Warnick & Bradley Ruffle, 2006. "The Strategies Behind Their Actions: A Method To Infer Repeated-Game Strategies And An Application To Buyer Behavior," Departmental Working Papers 2005-04, McGill University, Department of Economics.
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    Cited by:

    1. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, May.
    2. Jim Engle-Warnick & Bradley Ruffle, 2006. "The Strategies Behind Their Actions: A Method To Infer Repeated-Game Strategies And An Application To Buyer Behavior," Departmental Working Papers 2005-04, McGill University, Department of Economics.
    3. Franz Rothlauf & Daniel Schunk & Jella Pfeiffer, 2005. "Classification of Human Decision Behavior: Finding Modular Decision Rules with Genetic Algorithms," MEA discussion paper series 05079, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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