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

  • Richard G. Anderson
  • Charles S. Gascon

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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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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  1. Alastair Cunningham & Jana Eklund & Christopher Jeffery & George Kapetanios & Vincent Labhard, 2007. "A state space approach to extracting the signal from uncertain data," Bank of England working papers 336, Bank of England.
  2. Dean Croushore, 2008. "Revisions to PCE inflation measures: implications for monetary policy," Working Papers 08-8, Federal Reserve Bank of Philadelphia.
  3. 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.).
  4. 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.
  5. 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.
  6. Kevin Lee & Emi Mise & Kalvinder Shields & Tony Garratt, 2005. "Real time Representations of the Output Gap," Money Macro and Finance (MMF) Research Group Conference 2005 26, Money Macro and Finance Research Group.
  7. 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.
  8. 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.
  9. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
  10. Dean Croushore & Charles L. Evans, 2000. "Data Revisions and the Identification of Monetary Policy Shocks," Econometric Society World Congress 2000 Contributed Papers 0842, Econometric Society.
  11. 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.
  12. 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.
  13. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, March.
  14. 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.
  15. 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.
  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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