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Forecasting inflation with the New Keynesian Phillips curve : Frequency matters

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  • Martins, Manuel M. F.
  • Verona, Fabio

Abstract

We show that the New Keynesian Phillips Curve (NKPC) outperforms standard benchmarks in forecasting U.S. inflation once frequency-domain information is taken into account. We do so by decomposing the time series (of inflation and its predictors) into several frequency bands and forecasting separately each frequency component of inflation. The largest statistically significant forecasting gains are achieved with a model that forecasts the lowest frequency component of inflation (corresponding to cycles longer than 16 years) flexibly using information from all frequency components of the NKPC inflation predictors. Its performance is particularly good in the returning to recovery from the Great Recession.

Suggested Citation

  • Martins, Manuel M. F. & Verona, Fabio, 2020. "Forecasting inflation with the New Keynesian Phillips curve : Frequency matters," Research Discussion Papers 4/2020, Bank of Finland.
  • Handle: RePEc:bof:bofrdp:2020_004
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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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