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Applications of the Kalman filter to revisions in monthly retail sales estimates

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  • William Conrad
  • Carol Corrado

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Special Studies Papers with number 125.

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Date of creation: 1978
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Handle: RePEc:fip:fedgsp:125

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Cited by:
  1. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia.
  2. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-Time Measurement of Business Conditions," NBER Working Papers 14349, National Bureau of Economic Research, Inc.
  3. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
  4. Olivier Roodenburg, 2004. "On the predictability of GDP data revisions in the Netherlands," DNB Working Papers 004, Netherlands Central Bank, Research Department.
  5. Mason, Charles F. & Phillips, Owen R., 2001. "Dynamic learning in a two-person experimental game," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1305-1344, September.
  6. Dean Croushore, 2009. "Commentary on Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 371-382.
  7. B. Dianne Pauls, 1987. "Improving the forecast accuracy of provisional data: an application of the Kalman filter to retail sales estimates," International Finance Discussion Papers 318, Board of Governors of the Federal Reserve System (U.S.).
  8. Dean Croushore, 2008. "Revisions to PCE inflation measures: implications for monetary policy," Working Papers 08-8, Federal Reserve Bank of Philadelphia.
  9. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, 03.

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