Do Phillips curves conditionally help to forecast inflation?
The Phillips curve has long been used as a foundation for forecasting inflation. Yet numerous studies indicate that over the past 20 years or so, inflation forecasts based on the Phillips curve generally do not predict inflation any better than a univariate forecasting model. In this paper, the authors take a deeper look at the forecasting ability of Phillips curves from both an unconditional and a conditional view. Namely, they use the test results developed by Giacomini and White (2006) to examine the forecasting ability of Phillips curve models. The authors' main results indicate that forecasts from their Phillips curve models are unconditionally inferior to those of their univariate forecasting models and sometimes the difference is statistically significant. However, the authors do find that conditioning on various measures of the state of the economy does at times improve the performance of the Phillips curve model in a statistically significant way. Of interest is that improvement is more likely to occur at longer forecasting horizons and over the sample period 1984Q1—2010Q3. Strikingly, the improvement is asymmetric — Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. It, therefore, appears that forecasters should not fully discount the inflation forecasts of Phillips curve-based models when the economy is weak. Superseded by WP15-16.
|Date of creation:||2011|
|Contact details of provider:|| Postal: 10 Independence Mall, Philadelphia, PA 19106-1574|
Web page: http://www.philadelphiafed.org/
More information through EDIRC
|Order Information:|| Web: http://www.phil.frb.org/econ/wps/index.html Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
- 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.
- Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.).
- Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
- 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.
- Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," CEPR Discussion Papers 4830, C.E.P.R. Discussion Papers.
- Athanasios Orphanides & Simon van Norden, 2003. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," CIRANO Working Papers 2003s-01, CIRANO.
- Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
- 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.
- Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
- Todd E. Clark & Michael W. McCracken, 2003. "The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence," Research Working Paper RWP 03-06, Federal Reserve Bank of Kansas City.
- Jonas D. M. Fisher & Chin Te Liu & Ruilin Zhou, 2002. "When can we forecast inflation?," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q I, pages 32-44.
- 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.
When requesting a correction, please mention this item's handle: RePEc:fip:fedpwp:11-40. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Beth Paul)
If references are entirely missing, you can add them using this form.