IDEAS home Printed from https://ideas.repec.org/a/spr/jbuscr/v14y2018i1d10.1007_s41549-018-0023-3.html
   My bibliography  Save this article

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

Author

Listed:
  • Carlos A. Medel

    (Central Bank of Chile)

Abstract

It is well known among practitioners that the seasonal adjustment applied to economic time series involves several decisions to be made by the econometrician. As such, it would always be desirable to have an informed opinion on the risks taken by each of those decisions. In this paper, I assess which disaggregation strategy delivers the best results for the case of the Chilean 1986–2009 GDP 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 on seasonal adjustment diagnostics contained in the X-12-ARIMA program plus some statistical tests for robustness. This exercise is relevant for conjunctural economic assessment, as it concerns signal extraction from seasonal, noisy series, direction of change detection, and econometric applications based on reliable and accurate unobserved variables. The results show that it is preferable, in terms of stability, to use the first block of supply-side disaggregation, while demand-side disaggregation tends to be less reliable. This result carries important implications for policymakers aiming to evaluate its short-term effectiveness in both households and firms.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jbuscr:v:14:y:2018:i:1:d:10.1007_s41549-018-0023-3
    DOI: 10.1007/s41549-018-0023-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41549-018-0023-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s41549-018-0023-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    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. 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.
    6. Arnold Zellner, 1979. "Seasonal Analysis of Economic Time Series," NBER Books, National Bureau of Economic Research, Inc, number zell79-1, December.
    7. 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.
    8. 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.
    9. Marcus Scheiblecker, 2014. "Direct Versus Indirect Approach in Seasonal Adjustment," WIFO Working Papers 460, WIFO.
    10. 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.
    11. Agustín Maravall, 2002. "An Application of TRAMO-SEATS: Automatic Procedure and Sectoral Aggregation," Working Papers 0207, Banco de España.
    12. W. Allen Wallis & Geoffrey H. Moore, 1941. "A Significance Test for Time Series and Other Ordered Observations," NBER Books, National Bureau of Economic Research, Inc, number wall41-1, March.
    13. Clements, Michael P & Hendry, David F, 1996. "Intercept Corrections and Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 475-494, Sept.-Oct.
    14. Victor Gómez & Agustín Maravall, 1996. "Programs TRAMO and SEATS, Instruction for User (Beta Version: september 1996)," Working Papers 9628, Banco de España.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thornton, Michael A., 2013. "Removing seasonality under a changing regime: Filtering new car sales," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 4-14.
    2. Kirchner, Robert, 1999. "Auswirkungen des neuen Saisonbereinigungsverfahrens Census X-12-ARIMA auf die aktuelle Wirtschaftsanalyse in Deutschland," Discussion Paper Series 1: Economic Studies 1999,07, Deutsche Bundesbank.
    3. Tucker McElroy, 2018. "Seasonal adjustment subject to accounting constraints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 574-589, November.
    4. S.M.Husnain Bokhari & Ishaque Ahmed Ansari, 2009. "Seasonal Adjustment Of Some Financial Indicators Of Pakistan," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 5(2), pages 107-123.
    5. Massimiliano Giacalone & Raffaele Mattera & Eugenia Nissi, 2020. "Economic indicators forecasting in presence of seasonal patterns: time series revision and prediction accuracy," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 67-84, February.
    6. Charles F. Manski, 2014. "Communicating Uncertainty in Official Economic Statistics," NBER Working Papers 20098, National Bureau of Economic Research, Inc.
    7. Medel, Carlos A., 2014. "The Typical Spectral Shape of an Economic Variable: A Visual Guide with 100 Examples," MPRA Paper 53584, University Library of Munich, Germany.
    8. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Kaiser Remiro, Regina & Maravall, Agustín, 2000. "Notes on time serie analysis, ARIMA models and signal extraction," DES - Working Papers. Statistics and Econometrics. WS 10058, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. S. M. Husnain Bokhari & Ishaque Ahmed Ansari, 2009. "Seasonal Adjustment Of Some Financial Indicators Of Pakistan," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 5(2), pages 5-3.
    11. Phinikarides, Alexander & Makrides, George & Zinsser, Bastian & Schubert, Markus & Georghiou, George E., 2015. "Analysis of photovoltaic system performance time series: Seasonality and performance loss," Renewable Energy, Elsevier, vol. 77(C), pages 51-63.
    12. Proietti, Tommaso & Riani, Marco, 2007. "Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies," MPRA Paper 7862, University Library of Munich, Germany.
    13. Edoardo Otrano & Umberto Triacca, 2007. "Testing for Equal Predictability of Stationary ARMA Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1091-1108.
    14. Kaiser Remiro, Regina & Maravall, Agustín, 2000. "An application of tramo-seats: changes in seasonality and current trend-cycle assesment: the german retail trade turnover series," DES - Working Papers. Statistics and Econometrics. WS 10010, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Giancarlo Bruno & Edoardo Otranto, 2006. "The choice of time interval in seasonal adjustment: A heuristic approach," Statistical Papers, Springer, vol. 47(3), pages 393-417, June.
    16. Mauricio Gallardo & Hernán Rubio, 2009. "Diagnóstico de estacionalidad con X-12-ARIMA," Economic Statistics Series 76, Central Bank of Chile.
    17. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    18. Kroes, James R. & Manikas, Andrew S. & Gattiker, Thomas F., 2018. "Operational leanness and retail firm performance since 1980," International Journal of Production Economics, Elsevier, vol. 197(C), pages 262-274.
    19. Quenneville, Benoit & Ladiray, Dominique & Lefrancois, Bernard, 2003. "A note on Musgrave asymmetrical trend-cycle filters," International Journal of Forecasting, Elsevier, vol. 19(4), pages 727-734.
    20. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.

    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
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jbuscr:v:14:y:2018:i:1:d:10.1007_s41549-018-0023-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.