IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/0402008.html
   My bibliography  Save this paper

The Choice of Time Interval in Seasonal Adjustment: A Heuristic Approach

Author

Listed:
  • Giancarlo bruno

    (ISAE, Roma)

  • Edoardo Otranto

    (DEIR, Sassari)

Abstract

A typical problem of the seasonal adjustment procedures arises when the series to be adjusted is subject to structural breaks. In fact, using the full span of the series can result in a biased estimation of the ”true” seasonal adjusted series, with unclear evidence showed by the usual diagnostic tests. In these cases the researcher has to decide where to cut-o the observed series to obtain a homogeneous span; this is generally performed by a simple visual inspection studies of the graph of the series and/or using a-priori information about the occurrence of the break. In this paper we propose a statistical criterion based on a distance measure between filters, evaluating its performance with Monte Carlo experiments.

Suggested Citation

  • Giancarlo bruno & Edoardo Otranto, 2004. "The Choice of Time Interval in Seasonal Adjustment: A Heuristic Approach," Econometrics 0402008, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0402008
    Note: Type of Document - pdf; prepared on WinXP; to print on Laser witer II NP; pages: 14; figures: 4 figures in the document. PDF document submitted via ftp
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0402/0402008.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ghysels, Eric & Perron, Pierre, 1996. "The effect of linear filters on dynamic time series with structural change," Journal of Econometrics, Elsevier, vol. 70(1), pages 69-97, January.
    2. Ghysels, Eric & Perron, Pierre, 1993. "The effect of seasonal adjustment filters on tests for a unit root," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 57-98.
    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. 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.
    5. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Domenico Piccolo, 1990. "A Distance Measure For Classifying Arima Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(2), pages 153-164, March.
    8. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 396-397, July.
    9. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    10. Agustín Maravall, 1996. "Unobserved Components in Economic Time Series," Working Papers 9609, 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. Bhattacharya, Rudrani & Pandey, Radhika & Patnaik, Ila & Shah, Ajay, 2016. "Seasonal adjustment of Indian macroeconomic time-series," Working Papers 16/160, National Institute of Public Finance and Policy.

    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. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    2. Denise R. Osborn & Marianne Sensier, 2009. "Uk Inflation: Persistence, Seasonality And Monetary Policy," Scottish Journal of Political Economy, Scottish Economic Society, vol. 56(1), pages 24-44, February.
    3. 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.
    4. Caraballo Pou, M. Angeles & Dabus, Carlos, 2008. "Nominal rigidities, skewness and inflation regimes," Research in Economics, Elsevier, vol. 62(1), pages 16-33, March.
    5. D R Osborn & M Sensier, 2004. "Modelling UK Inflation: Persistence, Seasonality and Monetary Policy," Centre for Growth and Business Cycle Research Discussion Paper Series 46, Economics, The University of Manchester.
    6. Giorgio Canarella & Rangan Gupta & Stephen M. Miller & Stephen K. Pollard, 2019. "Unemployment rate hysteresis and the great recession: exploring the metropolitan evidence," Empirical Economics, Springer, vol. 56(1), pages 61-79, January.
    7. A Matas-Mir & D R Osborn, 2003. "Seasonal Adjustment and the Detection of Business Cycle Phases," Economics Discussion Paper Series 0304, Economics, The University of Manchester.
    8. Mª Ángeles Caraballo Pou & Carlos Dabús, 2005. "Nominal rigidities, relative prices and skewness," Economic Working Papers at Centro de Estudios Andaluces E2005/17, Centro de Estudios Andaluces.
    9. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5.
    10. Zesheng Sun & Bianxia Sun, 2017. "Impact of Monetary Supply on Chinese Nonferrous Metal Price Movement-super-," Asian Economic Journal, East Asian Economic Association, vol. 31(1), pages 17-37, March.
    11. Thomas Windberger & Achim Zeileis, 2011. "Structural Breaks in Inflation Dynamics within the European Monetary Union," Working Papers 2011-12, Faculty of Economics and Statistics, Universität Innsbruck.
    12. Qin, Meng & Su, Yun Hsuan & Zhao, Zhengtang & Mirza, Nawazish, 2023. "The politics of climate: Does factionalism impede U.S. carbon neutrality?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 954-966.
    13. Cappelli, Carmela & Penny, Richard N. & Rea, William S. & Reale, Marco, 2008. "Detecting multiple mean breaks at unknown points in official time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 351-356.
    14. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
    15. Anne Morrison Piehl & Suzanne J. Cooper & Anthony A. Braga & David M. Kennedy, 2003. "Testing for Structural Breaks in the Evaluation of Programs," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 550-558, August.
    16. Sun, Yanpeng & Song, Yuru & Long, Chi & Qin, Meng & Lobonţ, Oana-Ramona, 2023. "How to improve global environmental governance? Lessons learned from climate risk and climate policy uncertainty," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1666-1676.
    17. Jan Gottschalk & Ulrich Fritsche, 2005. "The New Keynesian Model and the Long-Run Vertical Phillips Curve: Does It Hold for Germany?," Discussion Papers of DIW Berlin 521, DIW Berlin, German Institute for Economic Research.
    18. Candelon, Bertrand & Lieb, Lenard, 2013. "Fiscal policy in good and bad times," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2679-2694.
    19. Hyeongwoo Kim & Ying Lin, 2018. "Exchange Rate Pass-Through to Consumer Prices and the Role of Energy Prices," Auburn Economics Working Paper Series auwp2018-05, Department of Economics, Auburn University.
    20. Zhang, Haoran & Yu, Xiaohong & Gao, Zixuan, 2025. "Is the end of AI in photovoltaic power? Evidence from China," Energy Economics, Elsevier, vol. 145(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:wpa:wuwpem:0402008. 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: EconWPA The email address of this maintainer does not seem to be valid anymore. Please ask EconWPA to update the entry or send us the correct address (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.