IDEAS home Printed from https://ideas.repec.org/a/fip/fedbcp/y2008n53x2.html
   My bibliography  Save this article

Phillips curve inflation forecasts

Author

Listed:
  • James H. Stock
  • Mark W. Watson

Abstract

This paper surveys the literature since 1993 on pseudo out-of-sample evaluation of inflation forecasts in the United States and conducts an extensive empirical analysis that recapitulates and clarifies this literature using a consistent data set and methodology. The literature review and empirical results are gloomy and indicate that Phillips curve forecasts (broadly interpreted as forecasts using an activity variable) are better than other multivariate forecasts, but their performance is episodic, sometimes better than and sometimes worse than a good (not nave) univariate benchmark. The authors provide some preliminary evidence characterizing successful forecasting episodes.

Suggested Citation

  • James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
  • Handle: RePEc:fip:fedbcp:y:2008:n:53:x:2
    Note: Complete conference proceedings can be ordered from MIT Press.
    as

    Download full text from publisher

    File URL: https://www.bostonfed.org/news-and-events/events/economic-research-conference-series/understanding-inflation-and-the-implications-for-monetary-policy-a-phillips-curve-retrospective.aspx
    File Function: Summary
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    2. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    3. Michael F. Bryan & Stephen G. Cecchetti & Rodney L. Wiggins, 1997. "Efficient inflation estimation," Working Papers (Old Series) 9707, Federal Reserve Bank of Cleveland.
    4. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    5. Canova, Fabio, 2002. "G-7 Inflation Forecasts," CEPR Discussion Papers 3283, C.E.P.R. Discussion Papers.
    6. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(1), pages 1-30, February.
    7. Marie Diron & Benoit Mojon, 2008. "Are inflation targets good inflation forecasts?," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 32(Q II), pages 33-45.
    8. Arturo Estrella & Jeffrey C. Fuhrer, 2003. "Monetary Policy Shifts and the Stability of Monetary Policy Models," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 94-104, February.
    9. 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.
    10. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, July.
    11. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    12. 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.
    13. Antonello D’ Agostino & Domenico Giannone, 2012. "Comparing Alternative Predictors Based on Large‐Panel Factor Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 306-326, April.
    14. Dewachter, Hans & Lyrio, Marco, 2006. "Macro Factors and the Term Structure of Interest Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(1), pages 119-140, February.
    15. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    16. Berardi, Andrea, 2009. "Term Structure, Inflation, and Real Activity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 987-1011, August.
    17. Scott Brave & Jonas D. M. Fisher, 2004. "In search of a robust inflation forecast," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 28(Q IV), pages 12-31.
    18. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    19. Stephen G. Cecchetti & Rita S. Chu & Charles Steindel, 2000. "The unreliability of inflation indicators," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 6(Apr).
    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. Banerjee, Anindya & Marcellino, Massimiliano, 2006. "Are there any reliable leading indicators for US inflation and GDP growth?," International Journal of Forecasting, Elsevier, vol. 22(1), pages 137-151.
    22. Wu, Tao, 2006. "Macro Factors and the Affine Term Structure of Interest Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(7), pages 1847-1875, October.
    23. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Chapters, in: NBER Macroeconomics Annual 1995, Volume 10, pages 189-236, National Bureau of Economic Research, Inc.
    24. G. Ascari & E. Marrocu, 2003. "Forecasting inflation: a comparison of linear Phillips curve models and nonlinear time serie models," Working Paper CRENoS 200307, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    25. Barsky, Robert B., 1987. "The Fisher hypothesis and the forecastability and persistence of inflation," Journal of Monetary Economics, Elsevier, vol. 19(1), pages 3-24, January.
    26. Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219, National Bureau of Economic Research, Inc.
    27. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank.
    28. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    29. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
    30. Laurence M. Ball, 2006. "Has Globalization Changed Inflation?," NBER Working Papers 12687, National Bureau of Economic Research, Inc.
    31. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    4. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    5. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    6. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    7. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    8. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
    9. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    10. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    11. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    12. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    13. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29, January.
    14. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    15. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    16. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    17. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    18. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
    19. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    20. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.

    More about this item

    Keywords

    Unemployment; Inflation (Finance); Phillips curve;
    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedbcp:y:2008:n:53:x:2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Spozio (email available below). General contact details of provider: https://edirc.repec.org/data/frbbous.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.