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Data and Code for: Robust Predictions for DSGE Models with Incomplete Information

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ICPSR2022-01-01 更新2026-04-16 收录
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Replication files for numerical results in AEJ:Macro article. Abstract of article:<br><br>We provide predictions for DSGE models with incomplete information that arerobust across information structures. Our approach maps an incomplete-informationmodel 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.

提供机构:
Boston College
创建时间:
2022-01-01
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