Robust Predictions for DSGE Models with Incomplete Information
American Economic Journal: Macroeconomics
vol. 15,
no. 1, January 2023
(pp. 173-208)
Abstract
We provide predictions for DSGE models with incomplete information that are robust across information structures. Our approach maps an incomplete-information model into a full-information economy with time-varying expectation wedges and provides conditions that ensure the wedges are rationalizable by some information structure. Using our approach, we quantify the potential importance of information as a source of business cycle fluctuations in an otherwise frictionless model. Our approach uncovers a central role for firm-specific demand shocks in supporting aggregate confidence fluctuations. Only if firms face unobserved local demand shocks can confidence fluctuations account for a significant portion of the US business cycle.Citation
Chahrour, Ryan, and Robert Ulbricht. 2023. "Robust Predictions for DSGE Models with Incomplete Information." American Economic Journal: Macroeconomics, 15 (1): 173-208. DOI: 10.1257/mac.20200053Additional Materials
JEL Classification
- D82 Asymmetric and Private Information; Mechanism Design
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- E13 General Aggregative Models: Neoclassical
- E31 Price Level; Inflation; Deflation
- E32 Business Fluctuations; Cycles
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