Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters

36 Pages Posted: 31 Jan 2020

See all articles by Manuel M. F. Martins

Manuel M. F. Martins

University of Porto, cef.up, Faculdade de Economia

Fabio Verona

Bank of Finland - Research

Date Written: May 6, 2020

Abstract

We show that the New Keynesian Phillips Curve (NKPC) outperforms standard bench marks 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

JEL Classification: C53, E31, E37

Suggested Citation

Mota Freitas Martins, Manuel and Verona, Fabio, Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters (May 6, 2020). Bank of Finland Research Discussion Paper No. 4/2020, Available at SSRN: https://ssrn.com/abstract=3594397 or http://dx.doi.org/10.2139/ssrn.3594397

Manuel Mota Freitas Martins

University of Porto, cef.up, Faculdade de Economia ( email )

4200-464 Porto
Portugal

Fabio Verona (Contact Author)

Bank of Finland - Research ( email )

P.O. Box 160
FIN-00101 Helsinki
Finland

HOME PAGE: http://bofcris.solenovo.fi/crisyp/disp/_/en/cr_redir_all/fet/fet/sea?direction=3&id=3827426

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