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Do Phillips Curves Conditionally Help to Forecast Inflation?

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Listed:
  • Michael Dotsey
  • Shigeru Fujita
  • Tom Stark

Abstract

This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. Significantly, we also find conditional inferiority, with some exceptions. When we do find improvement, it is asymmetric - Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. Any improvement we find, however, vanished over the post-1984 period.

Suggested Citation

  • Michael Dotsey & Shigeru Fujita & Tom Stark, 2017. "Do Phillips Curves Conditionally Help to Forecast Inflation?," Working Papers 17-26, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:17-26
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    References listed on IDEAS

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    More about this item

    Keywords

    Phillips curve; unemployment gap; conditional predictive ability;
    All these keywords.

    JEL classification:

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

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