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Do Phillips Curves Conditionally Help to Forecast Inflation?

Author

Listed:
  • Michael Dotsey

    (Federal Reserve Bank of Philadelphia)

  • Shigeru Fujita

    (Federal Reserve Bank of Philadelphia)

  • Tom Stark

    (Federal Reserve Bank of Philadelphia)

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, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
    • Handle: RePEc:ijc:ijcjou:y:2018:q:3:a:2
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    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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