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Estimating U.S. output growth with vintage data in a state-space framework

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  • Richard G. Anderson
  • Charles S. Gascon

Abstract

This study uses a state-space model to estimate the "true" unobserved measure of total output in the U.S. economy. The analysis uses the entire history (i.e., all vintages) of selected real-time data series to compute revisions and corresponding statistics for those series. The revision statistics, along with the most recent data vintage, are used in a state-space model to extract filtered estimates of the "true" series. Under certain assumptions, Monte Carlo simulations suggest this framework can improve published estimates by as much as 30 percent, lasting an average of 11 periods. Real-time experiments using a measure of real gross domestic product show improvement closer to 10 percent, lasting for 1 to 2 quarters.

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Bibliographic Info

Article provided by Federal Reserve Bank of St. Louis in its journal Review.

Volume (Year): (2009)
Issue (Month): Jul ()
Pages: 349-370

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Handle: RePEc:fip:fedlrv:y:2009:i:jul:p:349-370:n:v.91no.4

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Related research

Keywords: Economic development ; Economic conditions - United States;

References

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  1. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
  2. Howrey, E Philip, 1984. "Data Revision, Reconstruction, and Prediction: An Application to Inventory Investment," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 386-93, August.
  3. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-time measurement of business conditions," Working Papers 08-19, Federal Reserve Bank of Philadelphia.
  4. 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.
  5. Dean Croushore, 2008. "Revisions to PCE inflation measures: implications for monetary policy," Working Papers 08-8, Federal Reserve Bank of Philadelphia.
  6. Alastair Cunningham & Jana Eklund & Chris Jeffery & George Kapetanios & Vincent Labhard, 2009. "A State Space Approach to Extracting the Signal from Uncertain Data," Working Papers 637, Queen Mary, University of London, School of Economics and Finance.
  7. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2008. "Real-Time Representations of the Output Gap," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 792-804, November.
  8. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2006. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0617, Birkbeck, Department of Economics, Mathematics & Statistics.
  9. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-19, June.
  10. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  11. 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.
  12. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
  13. 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.
  14. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April.
  15. Howrey, E Philip, 1978. "The Use of Preliminary Data in Econometric Forecasting," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 193-200, May.
  16. 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.
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