Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend
Stephen McKnight (),
Alexander Mihailov () and
Fabio Rumler ()
Economic Modelling, 2020, vol. 87, issue C, 383-393
Does theory aid inflation forecasting? To address this question, we develop a novel forecasting procedure based upon a New Keynesian Phillips Curve that incorporates time-varying trend inflation, to capture shifts in central bank preferences and monetary policy frameworks. We generate theory-implied predictions for both the trend and cyclical components of inflation, and recombine them to obtain an overall inflation forecast. Using quarterly data for the Euro Area and the United States that cover almost half a century, we compare our inflation forecasting procedure against the most popular time series models. We find that our theory-based forecasts outperform these benchmarks that previous studies found difficult to beat. Our results are shown to be robust to structural breaks, geographic areas, and variants of the econometric specification. Our findings suggest that the scepticism concerning the use of theory in forecasting is unwarranted, and theory should continue to play an important role in policymaking.
Keywords: Inflation forecasting; Predictive accuracy; New Keynesian Phillips Curve; Time-varying trend (search for similar items in EconPapers)
JEL-codes: C53 D43 E31 E37 F41 F47 (search for similar items in EconPapers)
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