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Bayesian Learning

Author

Listed:
  • Isaac Baley
  • Laura Veldkamp

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.

Suggested Citation

  • Isaac Baley & Laura Veldkamp, 2021. "Bayesian Learning," NBER Working Papers 29338, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29338
    Note: AP EFG
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    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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