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Is Seasonal Adjustment a Linear or Nonlinear Data Filtring Process

  • Ghysels, E.
  • Granger, C.W.J.
  • Siklos, P.L.

The authors investigate whether seasonal adjustment procedures are linear data transformations. This question was addressed by A. H. Young (1968) and is important for the estimation of regression models with seasonally adjustment data. The authors focus on the X-11 program and rely on simulation evidence, involving linear unobserved component autorgressive integrated moving average models. They define and test a set of properties for the adequacy of a linear approximation to a seasonal adjustment filter. Next, the authors study the effect of X-11 on regression statistics assessing the statistical significance between economic variables. Several empirical results involving economic data are also reported.

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Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 9517.

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Length: 31 pages
Date of creation: 1995
Date of revision:
Handle: RePEc:mtl:montde:9517
Contact details of provider: Postal: CP 6128, Succ. Centre-Ville, Montréal, Québec, H3C 3J7
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  1. Fisher, T.C.G. & Martel, J., 1994. "The Creditors' Financial Reorganization Decision: New Evidence from Canadian Data," Cahiers de recherche 9417, Universite de Montreal, Departement de sciences economiques.
  2. Ghysels, Eric, 1997. "Seasonal Adjustment and Other Data Transformations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 410-18, October.
  3. Ghysels, E. & Perron, P., 1990. "The Effect Of Seasonal Adjustment Filters On Tests For A Unit Root," Papers 355, Princeton, Department of Economics - Econometric Research Program.
  4. Boyer, M. & Laffont, J.J., 1995. "Environmental Risks and Bank Liability," Cahiers de recherche 9501, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  5. Ghysels, E. & Lieberman, O., 1993. "Dynamic Regression and Filtered Data Series: A Laplace Approximation to the Effects of Filtering in Small Samples," Cahiers de recherche 9335, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  6. Vogelsang, T.J. & Perron, P., 1994. "Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time," Cahiers de recherche 9422, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  7. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  8. David M. Grether & Marc Nerlove, 1968. "Some Properties of 'Optimal' Seasonal Adjustment," Cowles Foundation Discussion Papers 261, Cowles Foundation for Research in Economics, Yale University.
  9. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
  10. 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.
  11. Maravall, Agustin, 1988. "A note on minimum mean squared error estimation of signals with unit roots," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 589-593.
  12. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
  13. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April.
  14. Kathy Cannings & Sophie Mahseredjian & Claude Montmarquette, 1994. "Major Choices : Undergraduate Concentrations and the Probability of Graduation," CIRANO Working Papers 94s-09, CIRANO.
  15. 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.).
  16. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
  17. Burridge, Peter & Wallis, Kenneth F, 1983. "Unobserved-Components Models for Seasonal Adjustment Filters," The Warwick Economics Research Paper Series (TWERPS) 244, University of Warwick, Department of Economics.
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