Forecasting inflation using dynamic model averaging

Gary Koop, Dimitris Korobilis

Research output: Contribution to journalArticlepeer-review

153 Citations (Scopus)


We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods that 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.
Original languageEnglish
Pages (from-to)867–886
Number of pages20
JournalInternational Economic Review
Issue number3
Early online date25 Jul 2012
Publication statusPublished - Aug 2012


  • forecasting
  • dynamic model averaging

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