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Forecasting Inflation Using Dynamic Model Averaging

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Author Info

  • Gary Koop

    ()
    (Department of Economics, University of Strathclyde)

  • Dimitris Korobilis

    ()
    (Center for Operations Research & Econometrics (CORE), Universite Catholique de Louvain)

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 coe¢ cients 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.

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File URL: http://www.strath.ac.uk/media/departments/economics/researchdiscussionpapers/2011/11-19Final.pdf
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Bibliographic Info

Paper provided by University of Strathclyde Business School, Department of Economics in its series Working Papers with number 1119.

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Length: 33 pages
Date of creation: Apr 2011
Date of revision:
Handle: RePEc:str:wpaper:1119

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Keywords: Bayesian; State space model; Phillips curve;

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