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

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  • 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.

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File URL: http://www.wlu.ca/documents/22950/CompDataRev_Dec_2006.pdf
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Bibliographic Info

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

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Length: 42
Date of creation: 2006
Date of revision: 2006
Handle: RePEc:wlu:wpaper:eg0049

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

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References

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  1. Donald W.K. Andrews, 2002. "End-of-Sample Instability Tests," Cowles Foundation Discussion Papers 1369, Cowles Foundation for Research in Economics, Yale University.
  2. 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.
  3. Donald Andrews & Jae-Young Kim, 2004. "End-of-Sample Conintegratio Breakdown Tests," Econometric Society 2004 Far Eastern Meetings 795, Econometric Society.
  4. Hall, Alastair R., 2004. "Generalized Method of Moments," OUP Catalogue, Oxford University Press, number 9780198775201, October.
  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. Joseph A. Ritter, 2000. "Feeding the national accounts," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 11-20.
  7. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  8. 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.
  9. Golinelli, Roberto & Parigi, Giuseppe, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  16. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  17. 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.
  18. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  19. Siklos, Pierre L. & Granger, Clive W.J., 1997. "Regime-Sensitive Cointegration With An Application To Interest-Rate Parity," Macroeconomic Dynamics, Cambridge University Press, vol. 1(03), pages 640-657, September.
  20. Siklos,Pierre L., 2002. "The Changing Face of Central Banking," Cambridge Books, Cambridge University Press, number 9780521780254.
  21. 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.
  22. repec:cup:macdyn:v:1:y:1997:i:3:p:640-57 is not listed on IDEAS
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Citations

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Cited by:
  1. Anthony Garratt & Gary Koop & Emi Mise & Shaun Vahey, 2008. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2008/13, Reserve Bank of New Zealand.
  2. Jan P.A.M. Jacobs & Sturm Jan-Egbert, 2008. "The information content of KOF indicators on Swiss current account data revisions," KOF Working papers 08-202, KOF Swiss Economic Institute, ETH Zurich.
  3. Juan Manuel Julio, . "Modeling Data Revisions," Borradores de Economia 641, Banco de la Republica de Colombia.
  4. 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.
  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.

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