Advanced Search
MyIDEAS: Login

What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation: Some US Evidence

Contents:

Author Info

  • Pierre Siklos

    () (Wilfrid Laurier University)

Abstract

The empirical properties of benchmark revisions to key U.S. macroeconomic aggregates are examined. News versus noise impact of revisions is interpreted via the cointegration property of successive benchmark revisions. Cointegration breaks in the last two years before a benchmark revision. Hence, we conclude that there is some information content in benchmark revisions. The last point is illustrated by reporting that inflation forecasts could be improved by the addition of a time series that reflects benchmark revisions to real GDP. Standard backward and forward-looking Phillips curves are used to explore the statistical significance of benchmark revisions.

Download Info

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.wlu.ca/documents/22950/CompDataRev_Dec_2006.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Wilfrid Laurier University, Department of Economics in its series Working Papers with number eg0049.

as in new window
Length: 42
Date of creation: 2006
Date of revision: 2006
Handle: RePEc:wlu:wpaper:eg0049

Contact details of provider:
Postal: 75 University Ave. West, Waterloo, Ontario, N2L 3C5
Phone: (519) 884-0710 ext 2056
Fax: (519) 884-0201
Web page: http://www.wlu.ca/sbe/economics/
More information through EDIRC

Related research

Keywords: cointegration breakdown; real time data; Phillips curve;

Find related papers by JEL classification:

References

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. 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.).
  2. Donald Andrews & Jae-Young Kim, 2004. "End-of-Sample Conintegratio Breakdown Tests," Econometric Society 2004 Far Eastern Meetings 795, Econometric Society.
  3. Donald W.K. Andrews, 2002. "End-of-Sample Instability Tests," Cowles Foundation Discussion Papers 1369, Cowles Foundation for Research in Economics, Yale University.
  4. Anthony Garratt & Shaun P Vahey, 2005. "UK Real-Time Macro Data Characteristics," Birkbeck Working Papers in Economics and Finance 0502, Birkbeck, Department of Economics, Mathematics & Statistics.
  5. David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 3-12.
  6. Gregory, Allan W & Hansen, Bruce E, 1996. "Tests for Cointegration in Models with Regime and Trend Shifts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 555-60, August.
  7. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
  8. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  9. Sharon Kozicki, 2004. "How do data revisions affect the evaluation and conduct of monetary policy?," Economic Review, Federal Reserve Bank of Kansas City, issue Q I, pages 5-38.
  10. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  11. Dean Croushore & Charles L. Evans, 2000. "Data revisions and the identification of monetary policy shocks," Working Paper Series WP-00-26, Federal Reserve Bank of Chicago.
  12. Henrik Hansen & Søren Johansen, 1999. "Some tests for parameter constancy in cointegrated VAR-models," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 306-333.
  13. Siklos,Pierre L., 2006. "The Changing Face of Central Banking," Cambridge Books, Cambridge University Press, number 9780521034494.
  14. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  15. Joseph A. Ritter, 2000. "Feeding the national accounts," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 11-20.
  16. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
  17. Hall, Alastair R., 2004. "Generalized Method of Moments," OUP Catalogue, Oxford University Press, number 9780198775201, July.
  18. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
  19. Siklos, P.L. & Granger, C.W.J., 1997. "Regime Sensitive Cointegration with an Application to Interest rate Parity," Working Papers 97-5, Wilfrid Laurier University, Department of Economics.
  20. repec:cup:macdyn:v:1:y:1997:i:3:p:640-57 is not listed on IDEAS
  21. Herrmann, Heinz & Orphanides, Athanasios & Siklos, Pierre L., 2005. "Real-time data and monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 271-276, December.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo Group Munich.
  2. Juan Manuel Julio, . "Modeling Data Revisions," Borradores de Economia 641, Banco de la Republica de Colombia.
  3. Jan P.A.M. Jacobs & Jan-Egbert Sturm, 2008. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2008(2), pages 161-181.
  4. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
  5. Clements, Michael P. & Beatriz Galvão, Ana, 2010. "First announcements and real economic activity," European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:wlu:wpaper:eg0049

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shelagh Pepper).

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.