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Unobserved-Components Models for Seasonal Adjustment Filters

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  • Burridge, Peter
  • Wallis, Kenneth F

Abstract

Time series models are presented for which the seasonal component estimates delivered by linear least squares signal extraction closely approximate those of the standard option of the widely-used Cencus X-11 program. Earlier work is extended by consideration of a broader class of models and by examination of asymmetric filters in addition to the symmetric filter implicit in the adjustment of historical data. Various criteria that guide the specification of unobserved-component models are discussed, and a new preferred model is presented. Other models generate filters that approximate X-11 rather well, explaining the wide acceptance of the X-11 method.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Burridge, Peter & Wallis, Kenneth F, 1984. "Unobserved-Components Models for Seasonal Adjustment Filters," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 350-359, October.
    • Handle: RePEc:bes:jnlbes:v:2:y:1984:i:4:p:350-59
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    Cited by:

    1. Kaiser, Regina & Maravall, Agustin, 2005. "Combining filter design with model-based filtering (with an application to business-cycle estimation)," International Journal of Forecasting, Elsevier, vol. 21(4), pages 691-710.
    2. McElroy Tucker S, 2010. "A Nonlinear Algorithm for Seasonal Adjustment in Multiplicative Component Decompositions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-23, September.
    3. Irma Hindrayanto & Jan Jacobs & Denise Osborn, 2014. "On trend-cycle-seasonal interactions," DNB Working Papers 417, Netherlands Central Bank, Research Department.
    4. Maravall, Agustín, 2000. "Notes on time serie analysis, ARIMA models and signal extraction," DES - Working Papers. Statistics and Econometrics. WS 10058, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    6. Crafts, N. F. R. & Leybourne, S. J. & Mills, T. C., 1988. "Economic Growth In Nineteeth Century Britain: Comparisons With Europe In The Context Of Gerschenkron'S Hypotheses," Economic Research Papers 268342, University of Warwick - Department of Economics.
    7. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    8. Tom�s del Barrio Castro & Denise R. Osborn & A.M. Robert Taylor, 2016. "The Performance of Lag Selection and Detrending Methods for HEGY Seasonal Unit Root Tests," Econometric Reviews, Taylor & Francis Journals, vol. 35(1), pages 122-168, January.
    9. Luis J. Alvarez & Juan C. Delrieu & Antoni Espasa, 1992. "Aproximación lineal por tramos a comportamientos no lineales : estimación de señales de nivel y crecimiento," Working Papers 9226, Banco de España.
    10. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    11. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
    12. Osborn, Denise R. & Heravi, Saeed & Birchenhall, C. R., 1999. "Seasonal unit roots and forecasts of two-digit European industrial production," International Journal of Forecasting, Elsevier, vol. 15(1), pages 27-47, February.
    13. Maravall, Agustín, 1999. "Short-term and long-term trends, seasonal and the business cycle," DES - Working Papers. Statistics and Econometrics. WS 6291, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Huang, Tai-Hsin & Shen, Chung-Hua, 2002. "Seasonal cointegration and cross-equation restrictions on a forward-looking buffer stock model of money demand," Journal of Econometrics, Elsevier, vol. 111(1), pages 11-46, November.
    15. A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," Economics Discussion Paper Series 0304, Economics, The University of Manchester.
    16. Harris, Richard D.F. & Yilmaz, Fatih, 2008. "Retrieving seasonally adjusted quarterly growth rates from annual growth rates that are reported quarterly," European Journal of Operational Research, Elsevier, vol. 188(3), pages 846-853, August.
    17. Tomas del Barrio Castro & Denise R. Osborn, 2006. "A Random Walk through Seasonal Adjustment: Noninvertible Moving Averages and Unit Root Tests," Economics Discussion Paper Series 0612, Economics, The University of Manchester.
    18. Regina Kaiser & Agustín Maravall, 2000. "Notes on Time Series Analysis, ARIMA Models and Signal Extraction," Working Papers 0012, Banco de España.
    19. Webel, Karsten, 2016. "A data-driven selection of an appropriate seasonal adjustment approach," Discussion Papers 07/2016, Deutsche Bundesbank.
    20. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.

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