Bayesian Learning

No 29338, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: E0 G14 (search for similar items in EconPapers)
Date: 2021-10
New Economics Papers: this item is included in nep-cwa, nep-mac and nep-ore
Note: AP EFG
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Related works:
Working Paper: Bayesian Learning (2021)
Working Paper: Bayesian Learning (2021)
Working Paper: Bayesian learning (2021)
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