Selecting structural innovations in DSGE models

Ferroni, Filippo, Grassi, Stefano, Leon-Ledesma, Miguel A. (2019) Selecting structural innovations in DSGE models. Journal of Applied Econometrics, 34 (2). pp. 205-220. ISSN 0883-7252. E-ISSN 1099-1255. (doi:10.1002/jae.2664) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

PDF - Author's Accepted Manuscript
Restricted to Repository staff only until 24 October 2020.
Contact us about this Publication Download (435kB)
[img]
Official URL
http://doi.org/10.1002/jae.2664

Abstract

Dynamic stochastic general equilibrium (DSGE) models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are “nonexistent” and propose a method to select the economic shocks driving macroeconomic uncertainty. Forcing these nonexisting shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select shocks and estimate model parameters with high precision. We revisit the empirical evidence on an industry standard medium‐scale DSGE model and find that government and price markup shocks are innovations that do not generate statistically significant dynamics.

Item Type: Article
DOI/Identification number: 10.1002/jae.2664
Uncontrolled keywords: Reduced rank covariance matrix, DSGE models, stochastic dimension search
Divisions: Faculties > Social Sciences > School of Economics
Depositing User: Miguel Leon-Ledesma
Date Deposited: 12 Jun 2018 15:32 UTC
Last Modified: 29 May 2019 20:37 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67280 (The current URI for this page, for reference purposes)
Leon-Ledesma, Miguel A.: https://orcid.org/0000-0002-3558-2990
  • Depositors only (login required):

Downloads

Downloads per month over past year