Learning the fundamentals in a stationary environment

Nabil I. Al-Najjar and Eran Shmaya

Games and Economic Behavior, 2018, vol. 109, issue C, 616-624

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.

Keywords: Learning; Merging; Stationarity (search for similar items in EconPapers)
JEL-codes: C61 D83 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:109:y:2018:i:c:p:616-624

DOI: 10.1016/j.geb.2018.02.007

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