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Forecasting Inflation Using Dynamic Model Averaging*

Gary Koop () and Dimitris Korobilis

No 1119, Working Papers from University of Strathclyde Business School, Department of Economics

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.

Keywords: Bayesian; State space model; Phillips curve (search for similar items in EconPapers)
JEL-codes: E31 E37 C11 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ets, nep-for, nep-mac and nep-mon
Date: 2011-04
References: View complete reference list from CitEc
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Related works:
Journal Article: FORECASTING INFLATION USING DYNAMIC MODEL AVERAGING (2012) Downloads
Working Paper: Forecasting Inflation Using Dynamic Model Averaging (2011) Downloads
Working Paper: Forecasting Inflation Using Dynamic Model Averaging (2010) Downloads
Working Paper: Forecasting Inflation Using Dynamic Model Averaging (2009) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:str:wpaper:1119

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