Behavior in a dynamic decision problem: An analysis of experimental evidence using a bayesian type classification algorithm
AbstractIt has been long recognized that different people may use different strategies, or decision rules, when playing games or dealing with other complex decision problems. We provide a new Bayesian procedure for drawing inferences about the nature and number of decision rules that are present in a population of agents. We show that the algorithm performs well in both a Monte Carlo study and in an empirical application. We apply our procedure to analyze the actual behavior of subjects who are confronted with a difficult dynamic stochastic decision problem in a laboratory setting. The procedure does an excellent job of grouping the subjects into easily interpretable types. Given the difficultly of the decision problem, we were surprised to find that nearly a third of subjects were a “Near Rational” type that played a good approximation to the optimal decision rule. More than 40% of subjects followed a rule that we describe as “fatalistic,” since they play as if they don’t appreciate the extent to which payoffs are a controlled stochastic process. And about a quarter of the subjects are classified as “Confused,” since they play the game quite poorly. Interestingly, we find that those subjects who practiced most before playing the game for money were the most likely to play poorly. Thus, lack of effort does not seem to account for poor performance. It is our hope that, in future work, our type classification algorithm will facilitate the positive analysis of peoples’ behavior in many types of complex decision problems.
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Bibliographic InfoPaper provided by EconWPA in its series Experimental with number 0211001.
Length: 60 pages
Date of creation: 11 Nov 2002
Date of revision:
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behavioral experiments type-classification bayesian;
Other versions of this item:
- 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, 05.
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-11-18 (All new papers)
- NEP-CMP-2002-11-18 (Computational Economics)
- NEP-ECM-2002-11-18 (Econometrics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Cyert, Richard M & DeGroot, Morris H, 1974. "Rational Expectations and Bayesian Analysis," Journal of Political Economy, University of Chicago Press, vol. 82(3), pages 521-36, May/June.
- Ellison, Glenn & Fudenberg, Drew, 1992.
"Rules of Thumb for Social Learning,"
IDEI Working Papers
17, Institut d'Économie Industrielle (IDEI), Toulouse.
- Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Scholarly Articles 3196332, Harvard University Department of Economics.
- Allison, G. & Fudenberg, D., 1992. "Rules of Thumb for Social Learning," Working papers 92-12, Massachusetts Institute of Technology (MIT), Department of Economics.
- G. Ellison & D. Fudenberg, 2010. "Rules of Thumb for Social Learning," Levine's Working Paper Archive 435, David K. Levine.
- John Haltiwanger & Michael Waldman, 1983.
"Rational Expectations and the Limits of Rationality: An Analysis of Heterogeneity,"
UCLA Economics Working Papers
303, UCLA Department of Economics.
- Haltiwanger, John & Waldman, Michael, 1985. "Rational Expectations and the Limits of Rationality: An Analysis of Heterogeneity," American Economic Review, American Economic Association, vol. 75(3), pages 326-40, June.
- repec:att:wimass:9309 is not listed on IDEAS
- Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-86, June.
- Palfrey, Thomas R. & Goeree, Jacob & Holt, Charles, 2000.
"Quantal Response Equilibrium and Overbidding in Private-value Auctions,"
1073, California Institute of Technology, Division of the Humanities and Social Sciences.
- Goeree, Jacob K. & Holt, Charles A. & Palfrey, Thomas R., 2002. "Quantal Response Equilibrium and Overbidding in Private-Value Auctions," Journal of Economic Theory, Elsevier, vol. 104(1), pages 247-272, May.
- Jacob K. Goeree & Charles A. Holt & Thomas R. Palfrey, 2000. "Quantal Response Equilibrium and Overbidding in Private-Value Auctions," Virginia Economics Online Papers 345, University of Virginia, Department of Economics.
- McCabe, Kevin & Houser, Daniel & Ryan, Lee & Smith, Vernon & Trouard, Ted, 2001. "A Functional Imaging Study of Cooperation in Two-Person reciprocal Exchange," MPRA Paper 5172, University Library of Munich, Germany.
- Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
- Charles A. Holt & Jacob K. Goeree, 1999. "Stochastic Game Theory: For Playing Games, Not Just for Doing Theory," Virginia Economics Online Papers 306, University of Virginia, Department of Economics.
- Michael P. Keane & Kenneth I. Wolpin, 1994.
"The solution and estimation of discrete choice dynamic programming models by simulation and interpolation: Monte Carlo evidence,"
181, Federal Reserve Bank of Minneapolis.
- Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-72, November.
- Harald Uhlig & Martin Lettau, 1999. "Rules of Thumb versus Dynamic Programming," American Economic Review, American Economic Association, vol. 89(1), pages 148-174, March.
- Cox, James C & Oaxaca, Ronald L, 1989. " Laboratory Experiments with a Finite-Horizon Job-Search Model," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 301-29, September.
- Goeree, Jacob K. & Holt, Charles A. & Palfrey, Thomas R., 2003. "Risk averse behavior in generalized matching pennies games," Games and Economic Behavior, Elsevier, vol. 45(1), pages 97-113, October.
- Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
- Daniel Houser & Joachim Winter, 2002.
"How Do Behavioral Assumptions Affect Structural Inference? Evidence From A Laboratory Experiment,"
MEA discussion paper series
02005, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
- Houser, Daniel & Winter, Joachim, 2004. "How Do Behavioral Assumptions Affect Structural Inference? Evidence from a Laboratory Experiment," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 64-79, January.
- Michael P. Keane & Kenneth I. Wolpin, 1995.
"The career decisions of young men,"
559, Federal Reserve Bank of Minneapolis.
- Andreoni, James, 1995.
"Cooperation in Public-Goods Experiments: Kindness or Confusion?,"
American Economic Review,
American Economic Association, vol. 85(4), pages 891-904, September.
- Daniel Houser & Robert Kurzban, 2002. "Revisiting Kindness and Confusion in Public Goods Experiments," American Economic Review, American Economic Association, vol. 92(4), pages 1062-1069, September.
- 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.
- Jim Engle-Warnick, 2001. "Inferring Strategies from Observed Actions: A Nonparametric, Binary Tree Classification Approach," Economics Papers 2001-W14, Economics Group, Nuffield College, University of Oxford.
- Jim Engle-Warnick, 2000. "Inferring Strategies from Observed Actions: A Nonparametric Binary Tree Classification Approach," Econometrics 0004002, EconWPA, revised 02 Aug 2001.
- El-Gamal, Mahmoud A. & Palfrey, Thomas R., 1995. "Vertigo: Comparing structural models of imperfect behavior in experimental games," Games and Economic Behavior, Elsevier, vol. 8(2), pages 322-348.
- Cox, James C & Oaxaca, Ronald L, 1992. "Direct Tests of the Reservation Wage Property," Economic Journal, Royal Economic Society, vol. 102(415), pages 1423-32, November.
- El-Gamal, Mahmoud A. & Grether, David M., 1995. "Are People Bayesian? Uncovering Behavioral Strategies," Working Papers 919, California Institute of Technology, Division of the Humanities and Social Sciences.
- Houser, Daniel, 2003. "Bayesian analysis of a dynamic stochastic model of labor supply and saving," Journal of Econometrics, Elsevier, vol. 113(2), pages 289-335, April.
- Hey, John D., 1987. "Still searching," Journal of Economic Behavior & Organization, Elsevier, vol. 8(1), pages 137-144, March.
- McKelvey, Richard D & Palfrey, Thomas R, 1992. "An Experimental Study of the Centipede Game," Econometrica, Econometric Society, vol. 60(4), pages 803-36, July.
- Geweke, John & Keane, Michael, 2001. "Computationally intensive methods for integration in econometrics," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 56, pages 3463-3568 Elsevier.
- McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
- Braunstein, Yale M & Schotter, Andrew, 1982. "Labor Market Search: An Experimental Study," Economic Inquiry, Western Economic Association International, vol. 20(1), pages 133-44, January.
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