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An application of the Tramo Seats automatic procedure; direct versus indirect adjustment

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  • Agustín Maravall

    ()
    (Banco de España)

Abstract

The ARIMA model based methodology of programs TRAMO and SEATS for seasonal adjustment and trend cycle estimation was applied to the exports, imports, and balance of trade Japanese series in Maravall (2002). The programs were used in an automatic mode, and the results analyzed. The present paper contains an extension of the work. First, some improvements in the automatic modelling procedure are illustrated, and the models for the seasonally adjusted series and its trend cycle component are discussed (in particular, their order of integration). It is further shown how the SEATS output can be of help in model selection. Finally, the important problem of the choice between direct and indirect adjustment of an aggregate is addressed. It is concluded that, because aggregation has a strong effect on the spectral shape of the series, and because seasonal adjustment is a non linear transformation of the original series, direct adjustment is preferable, even at the cost of destroying identities between the original series.

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File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/05/Fic/dt0524e.pdf
File Function: First version, August 2005
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Bibliographic Info

Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0524.

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Length: 34 pages
Date of creation: Aug 2005
Date of revision:
Handle: RePEc:bde:wpaper:0524

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Related research

Keywords: applied time series analysis; regression-arima models; seasonal adjustment; trend-cycle estimation; direct and indirect adjustment;

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  1. Dolado, Juan J. & Jansen, Marcel & Jimeno, Juan Francisco, 2005. "Dual Employment Protection Legislation: A Framework for Analysis," CEPR Discussion Papers 5033, C.E.P.R. Discussion Papers.
  2. Maravall, Agustin & Planas, Christophe, 1999. "Estimation error and the specification of unobserved component models," Journal of Econometrics, Elsevier, vol. 92(2), pages 325-353, October.
  3. Javier Andres & J. David López-Salido & Edward Nelson, 2005. "Sticky-price models and the natural rate hypothesis," Working Papers 2005-018, Federal Reserve Bank of St. Louis.
  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.
  5. David A. Pierce, 1978. "Seasonal Adjustment When Both Deterministic and Stochastic Seasonality Are Present," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 242-280 National Bureau of Economic Research, Inc.
  6. Fabio Canova & Matteo Ciccarelli & Eva Ortega, 2003. "Similarities and convergence in G-7 cycles," Economics Working Papers 924, Department of Economics and Business, Universitat Pompeu Fabra, revised Aug 2004.
  7. Enrique Alberola & Luis Molina & Daniel Navia, 2005. "Say You Fix, Enjoy And Relax The Deleterious Effect Of Peg Announcements On Fiscal Discipline," International Finance 0509001, EconWPA.
  8. David A. Pierce, 1978. "Seasonal adjustment when both deterministic and stochastic seasonality are present," Special Studies Papers 107, Board of Governors of the Federal Reserve System (U.S.).
  9. Camacho Maximo & Perez Quiros Gabriel, 2007. "Jump-and-Rest Effect of U.S. Business Cycles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-39, December.
  10. Pierce, David A., 1980. "Data revisions with moving average seasonal adjustment procedures," Journal of Econometrics, Elsevier, vol. 14(1), pages 95-114, September.
  11. D. S. G. Pollock, 2002. "A review of TSW: the Windows version of the TRAMO-SEATS program," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(3), pages 291-299.
  12. John Geweke, 1978. "The Temporal and Sectoral Aggregation of Seasonally Adjusted Time Series," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 411-432 National Bureau of Economic Research, Inc.
  13. Buisan, Ana & Caballero, Juan C. & Campa, Jose M. & Jimenez, Noelia, 2004. "La importancia de la histéresis en las exportaciones de manufacturas de los países de la UEM," IESE Research Papers D/561, IESE Business School.
  14. Ghysels, Eric, 1997. "Seasonal Adjustment and Other Data Transformations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 410-18, October.
  15. Hillmer, Steven C, 1985. "Measures of Variability for Model-based Seasonal Adjustment Procedures," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 60-68, January.
  16. Maravall, Agustin, 1987. "Minimum Mean Squared Error Estimation of the Noise in Unobserved Component Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 115-20, January.
  17. William R. Bell & Donald E. K. Martin, 2004. "Computation of asymmetric signal extraction filters and mean squared error for ARIMA component models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 603-623, 07.
  18. Andrés, Javier & López-Salido, J David & Nelson, Edward, 2004. "Tobin's Imperfect Asset Substitution in Optimizing General Equilibrium," CEPR Discussion Papers 4336, C.E.P.R. Discussion Papers.
  19. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521562607, October.
  20. Berben, Robert-Paul & Locarno, Alberto & Morgan, Julian & Vallés, Javier, 2004. "Cross-country differences in monetary policy transmission," Working Paper Series 0400, European Central Bank.
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Cited by:
  1. V. Eldon Ball & Carlos San Juan Mesonada & Camilo A. Ulloa, 2011. "Agricultural productivity in the United States: catching-up and the business cycle," Economics Working Papers we1116, Universidad Carlos III, Departamento de Economía.
  2. Agustín Maravall & Ana del Río, 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Banco de Espa�a Working Papers 0728, Banco de Espa�a.
  3. Aguilera, Ana M. & Escabias, Manuel & Valderrama, Mariano J., 2008. "Forecasting binary longitudinal data by a functional PC-ARIMA model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3187-3197, February.
  4. Bujosa, Marcos & Garcia-Ferrer, Antonio & Young, Peter C., 2007. "Linear dynamic harmonic regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 999-1024, October.
  5. Hayat, Aziz & Bhatti, M. Ishaq, 2013. "Masking of volatility by seasonal adjustment methods," Economic Modelling, Elsevier, vol. 33(C), pages 676-688.

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