Robust Predictions for DSGE Models with Incomplete Information
Ryan Chahrour and
Robert Ulbricht
American Economic Journal: Macroeconomics, 2023, vol. 15, issue 1, 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.
JEL-codes: D82 D83 E13 E31 E32 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)
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Working Paper: Robust Predictions for DSGE Models with Incomplete Information (2021) 
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Persistent link: https://EconPapers.repec.org/RePEc:aea:aejmac:v:15:y:2023:i:1:p:173-208
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DOI: 10.1257/mac.20200053
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