Forecasting Inflation Using Dynamic Model Averaging

Gary Koop and Dimitris Korobilis

No 2011-40, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

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 nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Keywords: Bayesian; State space model; Phillips curve (search for similar items in EconPapers)
Date: 2011
New Economics Papers: this item is included in nep-cba, nep-for, nep-mac and nep-mon
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: FORECASTING INFLATION USING DYNAMIC MODEL AVERAGING (2012)
Working Paper: Forecasting Inflation Using Dynamic Model Averaging* (2011)
Working Paper: Forecasting Inflation Using Dynamic Model Averaging (2010)
Working Paper: Forecasting Inflation Using Dynamic Model Averaging (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:sirdps:281

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