Bayesian Learning

Isaac Baley and Laura Veldkamp

No 1287, Working Papers from Barcelona School of Economics

Abstract: We survey work using Bayesian learning in macroeconomics, highlighting common themes and new directions. First, we present many of the common types of learning problems agents face-signal extraction problems-and trace out their effects on macro aggregates, in different strategic settings. Then we review different perspectives on how agents get their information. Models differ in their motives for information acquisition and the cost of information, or learning technology. Finally, we survey the growing literature on the data economy, where economic activity generates data and the information in data feeds back to affect economic activity.

Keywords: Bayes’ law; passive learning; active learning; signal extraction; information choice; sticky information; rational inattention; experimentation; data economy; coordination games (search for similar items in EconPapers)
JEL-codes: D80 D81 D83 D84 E20 E30 (search for similar items in EconPapers)
Date: 2021-09
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https://bse.eu/sites/default/files/working_paper_pdfs/1287.pdf (application/pdf)

Related works:
Working Paper: Bayesian Learning (2021)
Working Paper: Bayesian Learning (2021)
Working Paper: Bayesian learning (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:bge:wpaper:1287

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