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Learning the fundamentals in a stationary environment

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  • Al-Najjar, Nabil I.
  • Shmaya, Eran

Abstract

A Bayesian agent relies on past observations to learn the structure of a stationary process. We show that the agent's predictions about near-horizon events become arbitrarily close to those he would have made if he knew the long-run empirical frequencies of the process.

Suggested Citation

  • Al-Najjar, Nabil I. & Shmaya, Eran, 2018. "Learning the fundamentals in a stationary environment," Games and Economic Behavior, Elsevier, vol. 109(C), pages 616-624.
  • Handle: RePEc:eee:gamebe:v:109:y:2018:i:c:p:616-624
    DOI: 10.1016/j.geb.2018.02.007
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    References listed on IDEAS

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    1. Kalai, Ehud & Lehrer, Ehud, 1994. "Weak and strong merging of opinions," Journal of Mathematical Economics, Elsevier, vol. 23(1), pages 73-86, January.
    2. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
    3. Matthew O. Jackson & Ehud Kalai & Rann Smorodinsky, 1999. "Bayesian Representation of Stochastic Processes under Learning: de Finetti Revisited," Econometrica, Econometric Society, vol. 67(4), pages 875-894, July.
    4. Kalai, Ehud & Lehrer, Ehud & Smorodinsky, Rann, 1999. "Calibrated Forecasting and Merging," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 151-169, October.
    5. Nabil I. Al-Najjar & Eran Shmaya, 2015. "Uncertainty and Disagreement in Equilibrium Models," Journal of Political Economy, University of Chicago Press, vol. 123(4), pages 778-808.
    6. Lehrer, Ehud & Smorodinsky, Rann, 2000. "Relative entropy in sequential decision problems1," Journal of Mathematical Economics, Elsevier, vol. 33(4), pages 425-439, May.
    7. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
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    Cited by:

    1. Doria, Serena, 2024. "Merging of coherent upper conditional probabilities defined by Hausdorff outer measures," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    2. Al-Najjar, Nabil I. & Shmaya, Eran, 2019. "Recursive utility and parameter uncertainty," Journal of Economic Theory, Elsevier, vol. 181(C), pages 274-288.

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    More about this item

    Keywords

    Learning; Merging; Stationarity;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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