Identifying the sources of model misspecification

• 成果类型: Article
• 署名作者: Inoue, Atsushi; Kuo, Chun-Hung; Rossi, Barbara
• 署名单位: Vanderbilt University; National Tsing Hua University; Pompeu Fabra University; Barcelona School of Economics; ICREA; Pompeu Fabra University; Centre de Recerca en Economia Internacional (CREI); ICREA
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2019.01.003
• 发表日期: 2020
• 页码: 1-18
• 关键词: Misspecification; DSGE models; Forecast error variance decomposition; marginal likelihood

摘要

Conventional macroeconomic models fail to predict to the Great Recession. Is it because they are misspecified? 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. (C) 2019 Elsevier B.V. All rights reserved.