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Calculating the Variance of Seasonally Adjusted Series

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  • Burridge, Peter
  • Wallis, Kenneth F

Abstract

This paper considers the use of the Kalam filter to perform the seasonal adjustment and to calculate the variance of the signal extraction error in model-based seasonal adjustment procedures. The steady-state filter covariance is seen to provide a convenient basis for obtaining the variances not only the current adjustment but also subsequent revisions. The method is applied to the unobserved-components model we have recently proposed as a justification of the X-11 method, and to a real economic time series.

Suggested Citation

  • Burridge, Peter & Wallis, Kenneth F, 1984. "Calculating the Variance of Seasonally Adjusted Series," The Warwick Economics Research Paper Series (TWERPS) 251, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:251
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    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/1978-1988/twerp251.pdf
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    Cited by:

    1. Siem Jan Koopman & Philip Hans Franses, 2002. "Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(5), pages 509-526, December.
    2. Maravall, Agustin & Planas, Christophe, 1999. "Estimation error and the specification of unobserved component models," Journal of Econometrics, Elsevier, vol. 92(2), pages 325-353, October.
    3. Francis X. Diebold & Lutz Kilian & Marc Nerlove, 2006. "Time Series Analysis," PIER Working Paper Archive 06-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
      • Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    4. William P. Cleveland, 2002. "Estimated variance of seasonally adjusted series," Finance and Economics Discussion Series 2002-15, Board of Governors of the Federal Reserve System (U.S.).
    5. Christophe Planas & Alessandro Rossi, 2004. "Can inflation data improve the real-time reliability of output gap estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 121-133.

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