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Forecasting inflation with the New Keynesian Phillips curve: Frequency matters

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  • Martins, Manuel Mota Freitas
  • 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 Mota Freitas & Verona, Fabio, 2020. "Forecasting inflation with the New Keynesian Phillips curve: Frequency matters," Bank of Finland Research Discussion Papers 4/2020, Bank of Finland.
    • Handle: RePEc:zbw:bofrdp:rdp2020_004
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    References listed on IDEAS

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    More about this item

    Keywords

    inflation forecasting; new Keynesian Phillips curve; frequency domain; wavelets;
    All these keywords.

    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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