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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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    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    3. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    4. Orphanides, Athanasios & Williams, John C., 2005. "The decline of activist stabilization policy: Natural rate misperceptions, learning, and expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1927-1950, November.
    5. Dalibor Stevanovic & Rachidi Kotchoni, 2016. "Forecasting U.S. Recessions and Economic Activity," CIRANO Working Papers 2016s-36, CIRANO.
    6. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    7. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    8. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 669-705.
    9. Flint Brayton & John M. Roberts & John C. Williams, 1999. "What's happened to the Phillips curve?," Finance and Economics Discussion Series 1999-49, Board of Governors of the Federal Reserve System (U.S.).
    10. Olivier J. Blanchard & Lawrence H. Summers, 1986. "Hysteresis and the European Unemployment Problem," NBER Chapters, in: NBER Macroeconomics Annual 1986, Volume 1, pages 15-90, National Bureau of Economic Research, Inc.
    11. Michael Dotsey & Tom Stark, 2005. "The relationship between capacity utilization and inflation," Business Review, Federal Reserve Bank of Philadelphia, issue Q2, pages 8-17.
    12. Kiley, Michael T., 2015. "An evaluation of the inflationary pressure associated with short- and long-term unemployment," Economics Letters, Elsevier, vol. 137(C), pages 5-9.
    13. Blanchard, Olivier J. & Summers, Lawrence H., 1987. "Hysteresis in unemployment," European Economic Review, Elsevier, vol. 31(1-2), pages 288-295.
    14. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    15. Jonas D. M. Fisher & Chin Te Liu & Ruilin Zhou, 2002. "When can we forecast inflation?," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 26(Q I), pages 32-44.
    16. Olivier Jean Blanchard & Peter Diamond, 1994. "Ranking, Unemployment Duration, and Wages," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(3), pages 417-434.
    17. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    18. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    19. Jeffrey C. Fuhrer & Giovanni P. Olivei, 2010. "The role of expectations and output in the inflation process: an empirical assessment," Public Policy Brief, Federal Reserve Bank of Boston.
    20. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    21. Pierpaolo Benigno & Luca Antonio Ricci, 2011. "The Inflation-Output Trade-Off with Downward Wage Rigidities," American Economic Review, American Economic Association, vol. 101(4), pages 1436-1466, June.
    22. Robert Shimer, 2005. "The Cyclical Behavior of Equilibrium Unemployment and Vacancies," American Economic Review, American Economic Association, vol. 95(1), pages 25-49, March.
    23. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    24. Llaudes, Ricardo, 2005. "The Phillips curve and long-term unemployment," Working Paper Series 441, European Central Bank.
    25. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    26. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    27. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
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    More about this item

    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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