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Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies

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Author Info
Proietti, Tommaso
Riani, Marco

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Abstract

We address the problem of seasonal adjustment of a nonlinear transformation of the original time series, such as the Box-Cox transformation of a time series measured on a ratio scale, or the Aranda-Ordaz transformation of proportions, which aims at enforcing two essential features: additivity and orthogonality of the components. The posterior mean and variance of the seasonally adjusted series admit an analytic finite representation only for particular values of the transformation parameter, e.g. for a fractional Box-Cox transformation parameter. Even if available, the analytical derivation can be tedious and difficult. As an alternative we propose to compute the two conditional moments of the seasonally adjusted series by means of numerical and Monte Carlo integration. The former is both fast and reliable in univariate applications. The latter uses the algorithm known as the simulation smoother and it is most useful in multivariate applications. We present several case studies dealing with robust seasonal adjustment under the square root and the fourth root transformation, the seasonal adjustment of the ratio of two series, and the adjustment of time series of proportions. Our overall conclusion is that robust seasonal adjustment under transformations can be carried out routinely and that the possibility of transforming the scale ought to be considered as a further option for improving the quality of seasonal adjustment.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 7862.

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Date of creation: 03 Dec 2007
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Handle: RePEc:pra:mprapa:7862

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Related research
Keywords: Structural Time Series Models Box-Cox Transformation Aranda–Ordaz Transformation Simulation Smoother Forward Search Numerical Integration.

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
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  2. Marco Riani, 2004. "Extensions of the Forward Search to Time Series," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 8(2), pages 1208-1208. [Downloadable!] (restricted)
  3. [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 247-260. [Downloadable!] (restricted)
  4. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
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