Paper #1479

Title:

Identifying the sources of model misspecification

Authors:

Atsushi Inoue, Chun-Hung Kuo and Barbara Rossi

Date:

February 2015

Abstract:

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.

Keywords:

DSGE models, marginal likelihood, misspecification.

Area of Research:

Macroeconomics and International Economics / Statistics, Econometrics and Quantitative Methods

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