Estimating Time-Varying DSGE Models Using Minimum Distance Methods

39 Pages Posted: 28 Aug 2014

See all articles by Liudas Giraitis

Liudas Giraitis

Queen Mary

George Kapetanios

King's College, London

Konstantinos Theodoridis

Cardiff University

Tony Yates

University of Bristol

Date Written: August 22, 2014

Abstract

This paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the US data set constructed by Smets and Wouters. We use an indirect inference method to map from this TV VAR to time variation in implied Dynamic Stochastic General Equilibrium (DSGE) parameters. We find that many parameters change substantially, particularly those defining nominal rigidities, habits and investment adjustment costs. In contrast to the ‘Great Moderation’ literature our monetary policy parameter estimates suggest that authorities tried to deliver a low and stable inflation from 1975 onwards. However, the severe adverse supply shocks in the 70s could have caused these policies to fail.

Keywords: DSGE, structural change, kernel estimation, time-varying VAR, monetary policy shocks

JEL Classification: E52, E61, E66, C14, C18

Suggested Citation

Giraitis, Liudas and Kapetanios, George and Theodoridis, Konstantinos and Yates, Tony, Estimating Time-Varying DSGE Models Using Minimum Distance Methods (August 22, 2014). Bank of England Working Paper No. 507, Available at SSRN: https://ssrn.com/abstract=2487806 or http://dx.doi.org/10.2139/ssrn.2487806

Liudas Giraitis

Queen Mary ( email )

Mile End Road
London, London E1 4NS
United Kingdom

HOME PAGE: http://www.econ.qmul.ac.uk/people/liudas-giraitis

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

Konstantinos Theodoridis (Contact Author)

Cardiff University ( email )

Aberconway Building
Colum Drive
Cardiff, Wales CF10 3EU
United Kingdom

Tony Yates

University of Bristol ( email )

University of Bristol,
Senate House, Tyndall Avenue
Bristol, BS8 ITH
United Kingdom

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