IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

G-7 Inflation forecasts

  • Canova, Fabio

This paper compares the forecasting performance of some leading models of inflation for the cross section of G-7 countries. We show that bivariate and trivariate models suggested by economic theory or statistical analysis are hardly better than univariate models. Phillips curve specifications fit well into this class. Significant improvements in both the MSE of the forecasts and turning point prediction are obtained with time varying coefficients models which exploit international interdependencies. The performance of the latter class of models is independent of the sample, while it is not the case for standard specificiations. JEL Classification: E0, E5

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp151.pdf
Download Restriction: no

Paper provided by European Central Bank in its series Working Paper Series with number 0151.

as
in new window

Length:
Date of creation: Jun 2002
Date of revision:
Handle: RePEc:ecb:ecbwps:20020151
Contact details of provider: Postal: 60640 Frankfurt am Main, Germany
Phone: +49 69 1344 0
Fax: +49 69 1344 6000
Web page: http://www.ecb.europa.eu/
Email:


More information through EDIRC

References listed on IDEAS
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.:

as in new window
  1. Canova, Fabio, 1993. "Modelling and forecasting exchange rates with a Bayesian time-varying coefficient model," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 233-261.
  2. Mankiw, N Gregory, 2001. "The Inexorable and Mysterious Tradeoff between Inflation and Unemployment," Economic Journal, Royal Economic Society, vol. 111(471), pages C45-61, May.
  3. Canova, Fabio & Ciccarelli, Matteo, 2001. "Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model," CEPR Discussion Papers 2961, C.E.P.R. Discussion Papers.
  4. Massimiliano Marcellino & James H. Stock & Mark W. Watson, . "Macroeconomic Forecasting in the Euro Area: Country Specific versus Area-Wide Information," Working Papers 201, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  5. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  6. Jordi Gali & Mark Gertler, 2000. "Inflation Dynamics: A Structural Econometric Analysis," NBER Working Papers 7551, National Bureau of Economic Research, Inc.
  7. James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
  8. Fuhrer, Jeff & Moore, George, 1995. "Inflation Persistence," The Quarterly Journal of Economics, MIT Press, vol. 110(1), pages 127-59, February.
  9. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  10. Jeffrey A. Frankel, 1993. "On Exchange Rates," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061546, June.
  11. 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).
  12. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
  13. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
  14. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  15. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  16. Ivanov, Ventzislav & Kilian, Lutz, 2001. "A Practitioner's Guide to Lag-Order Selection for Vector Autoregressions," CEPR Discussion Papers 2685, C.E.P.R. Discussion Papers.
  17. Blinder, Alan S, 1997. "Is There a Core of Practical Macroeconomics That We Should All Believe?," American Economic Review, American Economic Association, vol. 87(2), pages 240-43, May.
  18. Canova, Fabio, 1992. "An Alternative Approach to Modeling and Forecasting Seasonal Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 97-108, January.
  19. Plosser, Charles I. & Geert Rouwenhorst, K., 1994. "International term structures and real economic growth," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 133-155, February.
  20. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  21. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ecb:ecbwps:20020151. 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: (Official Publications)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.