Forecasting inflation with the New Keynesian Phillips curve: Frequency matters

Manuel Mota Freitas Martins and Fabio Verona

No 4/2020, Bank of Finland Research Discussion Papers from Bank of Finland

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.

Keywords: inflation forecasting; new Keynesian Phillips curve; frequency domain; wavelets (search for similar items in EconPapers)
JEL-codes: C53 E31 E37 (search for similar items in EconPapers)
Date: 2020
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Working Paper: Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:bofrdp:rdp2020_004

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