2026-04-17T18:57:06Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/233902025-12-23T02:15:30Zcom_2072_6col_2072_452953

00925njm 22002777a 4500 dc Inoue, Atsushi author Kuo, Chun-Hung author Rossi, Barbara, 1971- author 2017-07-26T10:51:10Z 2017-07-26T10:51:10Z 2015-02-01 2017-07-23T02:16:57Z In this paper we propose an empirical method for detecting and identifying misspecification in structural economic models. Our approach formalizes the common practice of adding "shocks" in the model, and identifies potential misspecification via forecast error variance decomposition and marginal likelihood analyses. The 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 state-of-the-art medium-scale New Keynesian DSGE models remain misspecified, pointing to asset and labor markets as the sources of the misspecification. dsge models marginal likelihood misspecification. Macroeconomics and International Economics Statistics, Econometrics and Quantitative Methods Identifying the sources of model misspecification