Working Paper: NBER ID: w29338
Authors: 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.
Keywords: Bayesian learning; macroeconomics; signal extraction; information acquisition; data economy
JEL Codes: E0; G14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| agents' beliefs formed through Bayesian updating (D83) | economic decisions (G11) |
| economic decisions (G11) | macroeconomic aggregates (E10) |
| type of learning (passive or active) (C92) | agents' expectations and actions (D84) |
| agents' inability to distinguish between permanent and transitory shocks (D89) | suboptimal economic decisions (D91) |
| agents' information sets and economic actions (D82) | feedback loop that can amplify or dampen economic shocks (E32) |