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Nonparametric learning rules from bandit experiments: the eyes have it!

  • Yingyao Hu

    (Institute for Fiscal Studies and Johns Hopkins University)

  • Yutaka Kayaba
  • Matt Shum

We estimate nonparametric learning rules using data from dynamic two-armed bandit (probabilistic reversal learning) experiments, supplemented with auxiliary eye-movement measures of subjects' beliefs. We apply recent econometric developments in the estimation of dynamic models. The direct estimation of learning rules differs from the usual modus operandi of the experimental literature. The estimated choice probabilities and learning rules from our nonparametric models have some distinctive features; notably that subjects tend to update in a non-smooth manner following positive 'exploitative' choices (those made in accordance with current beliefs). Simulation results show how the estimated nonparametric learning rules fit aspects of subjects' observed choice sequences better than alternative parameterized learning rules from Bayesian and reinforcement learning models.

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File URL: http://cemmap.ifs.org.uk/wps/cwp1510.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP15/10.

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Date of creation: Jun 2010
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Handle: RePEc:ifs:cemmap:15/10
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  1. Costa-Gomes, Miguel & Crawford, Vincent P. & Broseta, Bruno, 1998. "Cognition and Behavior in Normal-Form Games: An Experimental Study," University of California at San Diego, Economics Working Paper Series qt1vn4h7x5, Department of Economics, UC San Diego.
  2. Vincent P. Crawford & Nagore Iriberri, 2007. "Level-k Auctions: Can a Nonequilibrium Model of Strategic Thinking Explain the Winner's Curse and Overbidding in Private-Value Auctions?," Econometrica, Econometric Society, vol. 75(6), pages 1721-1770, November.
  3. Pakes, Ariel & McGuire, Paul, 2001. "Stochastic Algorithms, Symmetric Markov Perfect Equilibrium, and the 'Curse' of Dimensionality," Econometrica, Econometric Society, vol. 69(5), pages 1261-81, September.
  4. Alexander L. Brown & Colin F. Camerer & Dan Lovallo, 2012. "To Review or Not to Review? Limited Strategic Thinking at the Movie Box Office," American Economic Journal: Microeconomics, American Economic Association, vol. 4(2), pages 1-26, May.
  5. Kuhnen, Camelia & Knutson, Brian, 2008. "The Influence of Affect on Beliefs, Preferences and Financial Decisions," MPRA Paper 10410, University Library of Munich, Germany.
  6. Daniel T. Knoepfle & Joseph Tao-yi Wang & Colin F. Camerer, 2009. "Studying Learning in Games Using Eye-Tracking," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 388-398, 04-05.
  7. Yaw Nyarko & Andrew Schotter, 2002. "An Experimental Study of Belief Learning Using Elicited Beliefs," Econometrica, Econometric Society, vol. 70(3), pages 971-1005, May.
  8. Nathaniel T Wilcox, 2006. "Theories of Learning in Games and Heterogeneity Bias," Econometrica, Econometric Society, vol. 74(5), pages 1271-1292, 09.
  9. Bergemann, Dirk & Hege, Ulrich, 1997. "Venture Capital Financing, Moral Hazard and Learning," CEPR Discussion Papers 1738, C.E.P.R. Discussion Papers.
  10. Brocas, Isabelle & Camerer, Colin & Carrillo, Juan D & Wang, Stephanie W., 2009. "Measuring attention and strategic behavior in games with private information," CEPR Discussion Papers 7529, C.E.P.R. Discussion Papers.
  11. Metrick, Andrew & Laibson, David I. & Choi, James J. & Madrian, Brigitte, 2009. "Reinforcement Learning and Savings Behavior," Scholarly Articles 4686777, Harvard University Department of Economics.
  12. Robert J. Meyer & Yong Shi, 1995. "Sequential Choice Under Ambiguity: Intuitive Solutions to the Armed-Bandit Problem," Management Science, INFORMS, vol. 41(5), pages 817-834, May.
  13. K. Carrie Armel & Antonio Rangel, 2008. "The Impact of Computation Time and Experience on Decision Values," American Economic Review, American Economic Association, vol. 98(2), pages 163-68, May.
  14. Yingyao Hu & Matthew Shum, 2008. "Nonparametric Identification of Dynamic Models with Unobserved State Variables," Economics Working Paper Archive 543, The Johns Hopkins University,Department of Economics.
  15. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-54, May.
  16. Patrick Bajari & Ali Hortacsu, 2003. "Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data," Working Papers 03002, Stanford University, Department of Economics.
  17. Vincent P. Crawford & Miguel A. Costa-Gomes, 2006. "Cognition and Behavior in Two-Person Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 96(5), pages 1737-1768, December.
  18. Susumu Imai & Neelam Jain & Andrew Ching, 2009. "Bayesian Estimation of Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 77(6), pages 1865-1899, November.
  19. Charness, Gary & Levin, Dan, 2003. "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect," University of California at Santa Barbara, Economics Working Paper Series qt7g63k28w, Department of Economics, UC Santa Barbara.
  20. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
  21. Joseph Tao-yi Wang & Michael Spezio & Colin F. Camerer, 2010. "Pinocchio's Pupil: Using Eyetracking and Pupil Dilation to Understand Truth Telling and Deception in Sender-Receiver Games," American Economic Review, American Economic Association, vol. 100(3), pages 984-1007, June.
  22. K. Carrie Armel & Aurelie Beaumel & Antonio Rangel, 2008. "Biasing simple choices by manipulating relative visual attention," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3, pages 396-403, June.
  23. Christopher Anderson, 2012. "Ambiguity aversion in multi-armed bandit problems," Theory and Decision, Springer, vol. 72(1), pages 15-33, January.
  24. Jovanovic, Boyan, 1979. "Job Matching and the Theory of Turnover," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 972-90, October.
  25. Avi Goldfarb & Mo Xiao, 2008. "Who thinks about the competition? Managerial ability and strategic entry in US local telephone markets," Working Papers 08-21, NET Institute, revised Oct 2008.
  26. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
  27. Andrew Caplin & Mark Dean & Paul W. Glimcher & Robb B. Rutledge, 2010. "Measuring Beliefs and Rewards: A Neuroeconomic Approach," The Quarterly Journal of Economics, MIT Press, vol. 125(3), pages 923-960, August.
  28. Noah Gans & George Knox & Rachel Croson, 2007. "Simple Models of Discrete Choice and Their Performance in Bandit Experiments," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 383-408, December.
  29. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
  30. Tat Y. Chan & Barton H. Hamilton, 2006. "Learning, Private Information, and the Economic Evaluation of Randomized Experiments," Journal of Political Economy, University of Chicago Press, vol. 114(6), pages 997-1040, December.
  31. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
  32. Johnson, Eric J. & Camerer, Colin & Sen, Sankar & Rymon, Talia, 2002. "Detecting Failures of Backward Induction: Monitoring Information Search in Sequential Bargaining," Journal of Economic Theory, Elsevier, vol. 104(1), pages 16-47, May.
  33. Jeffrey Banks & David Porter & Mark Olson, 1997. "An experimental analysis of the bandit problem," Economic Theory, Springer, vol. 10(1), pages 55-77.
  34. Elena Reutskaja & Rosemarie Nagel & Colin F. Camerer & Antonio Rangel, 2011. "Search Dynamics in Consumer Choice under Time Pressure: An Eye-Tracking Study," American Economic Review, American Economic Association, vol. 101(2), pages 900-926, April.
  35. Miller, Robert A, 1984. "Job Matching and Occupational Choice," Journal of Political Economy, University of Chicago Press, vol. 92(6), pages 1086-120, December.
  36. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, 07.
  37. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, 08.
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