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A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986-2009 with X-12-ARIMA

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  • Medel, Carlos A.

Abstract

It is well known among practitioners that the seasonal adjustment applied to economic time series could involve several decisions to be made by the econometrician. In this paper, I assess which aggregation strategy delivers the best results for the case of the Chilean GDP 1986-2009 quarterly dataset (base year: 2003). This is done by performing an aggregate-by-disaggregate analysis under different schemes, as the fixed base year dataset allows this fair comparison. The analysis is based exclusively on seasonal adjustment diagnostics contained in X-12-ARIMA program. A detailed description of the program and its quality assessment are also provided. The results show that it is preferred, in terms of stability, to use the first block of supply-side disaggregation as well as the direct mode.

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  • Medel, Carlos A., 2014. "A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986-2009 with X-12-ARIMA," MPRA Paper 57053, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:57053
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    References listed on IDEAS

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    1. Maravall, Agustin, 2006. "An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2167-2190, May.
    2. Clive W. J. Granger, 1979. "Seasonality: Causation, Interpretation, and Implications," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 33-56, National Bureau of Economic Research, Inc.
    3. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    4. Carlos A. Medel, 2018. "A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986–2009 with X-12-ARIMA," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 47-87, April.
    5. Arnold Zellner, 1979. "Seasonal Analysis of Economic Time Series," NBER Books, National Bureau of Economic Research, Inc, number zell79-1, December.
    6. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    7. Marcus Scheiblecker, 2014. "Direct Versus Indirect Approach in Seasonal Adjustment," WIFO Working Papers 460, WIFO.
    8. Michael Stanger, 2007. "Empalme del PIB y de los Componentes del Gasto: Series Anuales y Trimestrales 1986-2002, Base 2003," Economic Statistics Series 55, Central Bank of Chile.
    9. Carlos A. Medel, 2013. "How informative are in-sample information criteria to forecasting? The case of Chilean GDP," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 50(1), pages 133-161, May.
    10. Victor Gómez & Agustín Maravall, 1996. "Programs TRAMO and SEATS, Instruction for User (Beta Version: september 1996)," Working Papers 9628, Banco de España.
    11. W. Allen Wallis & Geoffrey H. Moore, 1941. "A Significance Test for Time Series and Other Ordered Observations," NBER Chapters, in: A Significance Test for Time Series and Other Ordered Observations, pages 1-67, National Bureau of Economic Research, Inc.
    12. Agustín Maravall, 2002. "An Application of TRAMO-SEATS: Automatic Procedure and Sectoral Aggregation," Working Papers 0207, Banco de España.
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    1. Carlos A. Medel, 2018. "A Comparison Between Direct and Indirect Seasonal Adjustment of the Chilean GDP 1986–2009 with X-12-ARIMA," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 47-87, April.

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    More about this item

    Keywords

    Seasonal adjustment; univariate time-series models; ARMA; X-12-ARIMA;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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