Identifying the sources of model misspecification

Recognition Program

Authors: Atsushi Inoue, Chun-Huong Kuo and Barbara Rossi

Journal of Monetary Economics, Vol. 110, 1-18, April, 2020

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.

This paper originally appeared as Barcelona School of Economics Working Paper 821
This paper is acknowledged by the Barcelona School of Economics Recognition Program