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A Non-linear Dynamic Model for Multiplicative Seasonal-Trend Decomposition

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  • Ozaki, Tohru
  • Thomson, Peter

Abstract

A non-linear dynamic model is introduced for multiplicative seasonal time series that follows and extends the X-11 paradigm where the observed time series is a product of trend, seasonal and irregular factors. A selection of standard seasonal and trend component models used in additive dynamic time series models are adapted for the multiplicative framework and a non-linear filtering procedure is proposed. The results are illustrated and compared to X-11 and log-additive models using real data. In particular it is shown that the new procedures do not suffer from the trend bias present in log-additive models. Copyright © 2002 by John Wiley & Sons, Ltd.

Suggested Citation

  • Ozaki, Tohru & Thomson, Peter, 2002. "A Non-linear Dynamic Model for Multiplicative Seasonal-Trend Decomposition," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(2), pages 107-124, March.
    • Handle: RePEc:jof:jforec:v:21:y:2002:i:2:p:107-24
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    Cited by:

    1. 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.
    2. Silhan, Peter A., 2014. "Income smoothing from a Census X-12 perspective," Advances in accounting, Elsevier, vol. 30(1), pages 106-115.

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