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Calculating the Variance of Seasonally Adjusted Series

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Author Info
Burridge, Peter
Wallis, Kenneth F

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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.

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Publisher Info
Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 251.

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Length: 28 pages
Date of creation: 1984
Date of revision:
Handle: RePEc:wrk:warwec:251

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  1. 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.). [Downloadable!]
  2. S.J. Koopman & P.H.B.F. Franses, 2001. "Constructing seasonally adjusted data with time-varying confidence intervals," Econometric Institute Report 210, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  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. [Downloadable!]
    Other versions:
    • Diebold, F.X. & Kilian, L. & Nerlove, M., 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics. [Downloadable!]
  4. 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. [Downloadable!]
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