Forecasting Inflation Using Dynamic Model Averaging

Rimini Center for Economic Analysis, WP 34-09

30 Pages Posted: 26 Aug 2009 Last revised: 12 Jan 2010

See all articles by Gary Koop

Gary Koop

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics

Dimitris Korobilis

University of Glasgow - Adam Smith Business School

Multiple version iconThere are 2 versions of this paper

Date Written: August 24, 2009

Abstract

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coefficients to change over time, but also allow for the entire forecasting model to change over time. We find that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Keywords: Bayesian, State space model, Phillips curve

JEL Classification: E31, E37, C11, C53

Suggested Citation

Koop, Gary and Korobilis, Dimitris, Forecasting Inflation Using Dynamic Model Averaging (August 24, 2009). Rimini Center for Economic Analysis, WP 34-09. Available at SSRN: https://ssrn.com/abstract=1461151 or http://dx.doi.org/10.2139/ssrn.1461151

Gary Koop

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics ( email )

100 Cathedral Street
Glasgow G4 0LN
United Kingdom

Dimitris Korobilis (Contact Author)

University of Glasgow - Adam Smith Business School ( email )

40 University Avenue
Gilbert Scott Building
Glasgow, Scotland G12 8QQ
United Kingdom

HOME PAGE: http://https://sites.google.com/site/dimitriskorobilis/

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