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Supplementary Appendix for ‘Non-Bayesian Updating: A Theoretical Framework’

Author

Listed:
  • Larry G. Epstein

    (Department of Economics, Boston University)

  • Jawwad Noor

    (Department of Economics, Boston University)

  • Alvaro Sandroni

    (Department of Economics, University of Pennsylvania)

Abstract

This appendix applies the model in †Non-Bayesian Updating: A Theoretical Frame-Work†to address the question: What do non-Bayesian updaters learn?

Suggested Citation

  • 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.
    • Handle: RePEc:pen:papers:08-017
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    File URL: https://economics.sas.upenn.edu/sites/default/files/filevault/working-papers/08-017.pdf
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    References listed on IDEAS

    as
    1. Mitchel Y. Abolafia (ed.), 2005. "Markets," Books, Edward Elgar Publishing, number 2788, March.
    2. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
    3. Lawrence Blume & David Easley, 2006. "If You're so Smart, why Aren't You Rich? Belief Selection in Complete and Incomplete Markets," Econometrica, Econometric Society, vol. 74(4), pages 929-966, July.
    4. Alvaro Sandroni, 2000. "Do Markets Favor Agents Able to Make Accurate Predicitions?," Econometrica, Econometric Society, vol. 68(6), pages 1303-1342, November.
    5. N/A, 1996. "Note:," Foreign Trade Review, , vol. 31(1-2), pages 1-1, January.
    6. Alvaro Sandroni, 2005. "Efficient markets and Bayes’ rule," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 26(4), pages 741-764, November.
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    Cited by:

    1. 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.
    2. Igor Kopylov & Jawwad Noor, 2018. "Commitments and weak resolve," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 66(1), pages 1-19, July.
    3. KWON Seokbeom & MOTOHASHI Kazuyuki, 2015. "How Institutional Arrangements in the National Innovation System Affect Industrial Competitiveness: A study of Japan and the United States with multiagent simulation," Discussion papers 15065, Research Institute of Economy, Trade and Industry (RIETI).
    4. 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.
    5. Sun, Lan, 2016. "Hypothesis testing equilibrium in signaling games," Center for Mathematical Economics Working Papers 557, Center for Mathematical Economics, Bielefeld University.
    6. He, Xue Dong & Xiao, Di, 2017. "Processing consistency in non-Bayesian inference," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 90-104.

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    More about this item

    Keywords

    Non-Bayesian Learning;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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