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Non-Bayesian Learning

Author

Listed:
  • Epstein Larry G

    () (Boston University)

  • Noor Jawwad

    () (Boston University)

  • Sandroni Alvaro

    () (University of Pennsylvania)

Abstract

A series of experiments suggest that, compared to the Bayesian benchmark, people may either underreact or overreact to new information. We consider a setting where agents repeatedly process new data. Our main result shows a basic distinction between the long-run beliefs of agents who underreact to information and agents who overreact to information. Like Bayesian learners, non-Bayesian updaters who underreact to observations eventually forecast accurately. Hence, underreaction may be a transient phenomenon. Non-Bayesian updaters who overreact to observations eventually forecast accurately with positive probability but may also, with positive probability, converge to incorrect forecasts. Hence, overreaction may have long-run consequences.

Suggested Citation

  • Epstein Larry G & Noor Jawwad & Sandroni Alvaro, 2010. "Non-Bayesian Learning," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 10(1), pages 1-20, January.
  • Handle: RePEc:bpj:bejtec:v:10:y:2010:i:1:n:3
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    References listed on IDEAS

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    1. I. Gilboa & A. W. Postlewaite & D. Schmeidler., 2009. "Probability and Uncertainty in Economic Modeling," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 10.
    2. Gilboa, Itzhak & Postlewaite, Andrew & Schmeidler, David, 2009. "Is It Always Rational To Satisfy Savage'S Axioms?," Economics and Philosophy, Cambridge University Press, vol. 25(03), pages 285-296, November.
    3. S. Nageeb Ali, 2011. "Learning Self-Control," The Quarterly Journal of Economics, Oxford University Press, vol. 126(2), pages 857-893.
    4. Epstein, Larry G. & Noor, Jawwad & Sandroni, Alvaro, 2008. "Non-Bayesian updating: A theoretical framework," Theoretical Economics, Econometric Society, vol. 3(2), June.
    5. Larry G. Epstein, 2006. "An Axiomatic Model of Non-Bayesian Updating," Review of Economic Studies, Oxford University Press, vol. 73(2), pages 413-436.
    6. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
    7. Larry G. Epstein & Jawwad Noor & Alvaro Sandroni, 2008. "Supplementary Appendix for ‘Non-Bayesian Updating: A Theoretical Framework’," PIER Working Paper Archive 08-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 595-621.
    9. Lehrer, Ehud & Smorodinsky, Rann, 1997. "Repeated Large Games with Incomplete Information," Games and Economic Behavior, Elsevier, vol. 18(1), pages 116-134, January.
    10. Matthew Rabin, 1998. "Psychology and Economics," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 11-46, March.
    11. Camerer, Colin F, 1989. "Does the Basketball Market Believe in the 'Hot Hand'?," American Economic Review, American Economic Association, vol. 79(5), pages 1257-1261, December.
    12. Jordan, J. S., 1992. "The exponential convergence of Bayesian learning in normal form games," Games and Economic Behavior, Elsevier, vol. 4(2), pages 202-217, April.
    13. Kalai, Ehud & Lehrer, Ehud, 1993. "Subjective Equilibrium in Repeated Games," Econometrica, Econometric Society, vol. 61(5), pages 1231-1240, September.
    14. Sandroni, Alvaro, 1998. "Necessary and Sufficient Conditions for Convergence to Nash Equilibrium: The Almost Absolute Continuity Hypothesis," Games and Economic Behavior, Elsevier, vol. 22(1), pages 121-147, January.
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    Cited by:

    1. Zhang, Hanzhe, 2013. "Evolutionary justifications for non-Bayesian beliefs," Economics Letters, Elsevier, vol. 121(2), pages 198-201.
    2. Füllbrunn, Sascha & Rau, Holger A. & Weitzel, Utz, 2014. "Does ambiguity aversion survive in experimental asset markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 810-826.
    3. Alexander Ludwig & Alexander Zimper, 2013. "A decision-theoretic model of asset-price underreaction and overreaction to dividend news," Annals of Finance, Springer, vol. 9(4), pages 625-665, November.
    4. Bohren, J. Aislinn, 2016. "Informational herding with model misspecification," Journal of Economic Theory, Elsevier, vol. 163(C), pages 222-247.
    5. Füllbrunn, Sascha & Rau, Holger & Weitzel, Utz, 2013. "Do ambiguity effects survive in experimental asset markets?," MPRA Paper 44700, University Library of Munich, Germany.
    6. Iuliia Brushko, 2013. "Financial Signaling and Earnings Forecasts," CERGE-EI Working Papers wp498, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    7. repec:eee:mateco:v:70:y:2017:i:c:p:90-104 is not listed on IDEAS
    8. Kwon, Seokbeom & Motohashi, Kazuyuki, 2017. "How institutional arrangements in the National Innovation System affect industrial competitiveness: A study of Japan and the U.S. with multiagent simulation," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 221-235.
    9. Qiu, Jianying & Weitzel, Utz, 2013. "Experimental Evidence on Valuation and Learning with Multiple Priors," MPRA Paper 43974, University Library of Munich, Germany.
    10. Vilen Lipatov, 2014. "Compliance Dynamics Generated by Social Interaction Rules," CESifo Working Paper Series 4767, CESifo Group Munich.
    11. Bradford L. Barham & Jean-Paul Chavas & Dylan Fitz & Vanessa Ríos-Salas & Laura Schechter, 2015. "Risk, learning, and technology adoption," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 11-24, January.
    12. Ali Jadbabaie & Pooya Molavi & Alvaro Sandroni & Alireza Tahbaz-Salehi, 2009. "Non-Bayesian Social Learning, Third Version," PIER Working Paper Archive 11-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 05 Aug 2011.

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