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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.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 2 (1984)
Issue (Month): 4 (October)
Pages: 350-59

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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. Irma Hindrayanto & Jan Jacobs & Denise Osborn, 2014. "On trend-cycle-seasonal interactions," DNB Working Papers 417, Netherlands Central Bank, Research Department.
  3. Regina Kaiser & Agustín Maravall, 2000. "Notes on Time Series Analysis, ARIMA Models and Signal Extraction," Banco de Espa�a Working Papers 0012, Banco de Espa�a.
  4. A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," The School of Economics Discussion Paper Series 0304, Economics, The University of Manchester.
  5. 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.
  6. 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.
  7. Eric Ghysels & Clive W.J. Granger & Pierre L. Siklos, 1995. "Is Seasonal Adjustment a Linear or Nonlinear Data Filtering Process?," CIRANO Working Papers 95s-19, CIRANO.
  8. 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.
  9. 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.
  10. 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.).

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