Identifying the Sources of Model Misspecification

Barbara Rossi, Atsushi Inoue and Chun-Hung Kuo

No 10140, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: In this paper we propose empirical methods for detecting and identifying misspecifications in DSGE models. We introduce wedges in a DSGE model and identify potential misspecification via forecast error variance decomposition (FEVD) and marginal likelihood analyses. Our simulation results based on a small-scale DSGE model demonstrate that our method can correctly identify the source of misspecification. Our empirical results show that the medium-scale New Keynesian DSGE model that incorporates features in the recent empirical macro literature is still very much misspecified; our analysis highlights that the asset and labor markets may be the source of the misspecification.

Keywords: Dsge models; Empirical macroeconomics; Model misspecification (search for similar items in EconPapers)
JEL-codes: C32 E32 (search for similar items in EconPapers)
Date: 2014-09
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-mac
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Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Identifying the sources of model misspecification (2020)
Working Paper: Identifying the sources of model misspecification (2018)
Working Paper: Identifying the Sources of Model Misspecification (2015)
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