IDEAS home Printed from
   My bibliography  Save this article

WIFO's New Seasonal Adjustment Procedure


  • Michael Wüger



Economic time series are submitted to seasonal adjustment procedures in order to facilitate the analysis of the data. Originally, deterministic approaches were adopted for the non-observable components like trend, seasonal factors, etc. Later on, they were replaced by the calculation of moving averages. Best known are "Census X–11" for seasonal and "HP filter" for trend adjustment. The advantage of such ad-hoc filters lies in their easy applicability, their disadvantage is that "they take a look at the world from a particular perspective", with possibly far-reaching negative consequences. Also, the lack of a statistical model detracts from a meaningful application of ad-hoc filters. In order to eliminate the problems attached to ad-hoc filters, new ways of estimating the non-observable components have been developed over the last 15 years. With the ARIMA model-based approaches, one first identifies a model of the observable time series and then derives from it models for the particular non-observable components (trend, season, irregular component) which are compatible with the global model. For the selection of an optimal seasonal adjustment method, both theoretical and empirical criteria should be applied. In a comprehensive study, Eurostat has examined five different seasonal adjustment procedures using more than 80 time series. TRAMO/SEATS – an ARIMA model based approach – proved to be the most sophisticated theoretical method and also performed best in most empirical tests. The TRAMO/SEATS program set allows the modeling of a time series via the combined estimation of ARIMA approaches and outlier as well as special effects, while also protecting against over- or underdifferentiation. It also allows a comparison between the components derived from the theoretical model and the empirical estimators, thereby facilitating the diagnosis. Furthermore, it offers a number of analytical tools which form the basis for statistically robust conclusions. Application of TRAMO/SEATS to time series of retail sales and consumption expenditure shows that it produces appropriate models for the explanation of these data. The outliers identified in these time series are readily explained by the expected effects of discretionary fiscal measures and changes in the statistical base. The theoretically obtained components correspond to a high degree to the empirically estimated ones. The series seasonally adjusted with TRAMO/SEATS exhibit markedly weaker variations in growth rates than those adjusted with X11, which makes interpretation of the data easier. The empirical record so far as well as test results of Eurostat suggest that this approach should be adopted for seasonal adjustment also in Austria.

Suggested Citation

  • Michael Wüger, 1995. "WIFO's New Seasonal Adjustment Procedure," WIFO Monatsberichte (monthly reports), WIFO, vol. 68(10), pages 625-635, October.
  • Handle: RePEc:wfo:monber:y:1995:i:10:p:625-635

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Payment required

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

    References listed on IDEAS

    1. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
    2. R. I. D. Harris & A. Liu, 1999. "Verdoorn's law and increasing returns to scale: country estimates based on the cointegration approach," Applied Economics Letters, Taylor & Francis Journals, vol. 6(1), pages 29-33.
    3. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    4. repec:taf:irapec:v:32:y:2018:i:2:p:237-258 is not listed on IDEAS
    5. Gustavo Adler & Romain A Duval & Davide Furceri & Sinem Kılıç Çelik & Ksenia Koloskova & Marcos Poplawski-Ribeiro, 2017. "Gone with the Headwinds; Global Productivity," IMF Staff Discussion Notes 17/04, International Monetary Fund.
    6. Laurence Ball & Daniel Leigh & Prakash Loungani, 2017. "Okun's Law: Fit at 50?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(7), pages 1413-1441, October.
    7. John S. L. McCombie & Marta R. M. Spreafico, 2016. "Kaldor’s ‘technical progress function’ and Verdoorn’s law revisited," Cambridge Journal of Economics, Oxford University Press, vol. 40(4), pages 1117-1136.
    8. Laurence M. Ball & Daniel Leigh & Prakash Loungani, 2013. "Okun's Law: Fit at Fifty?," NBER Working Papers 18668, National Bureau of Economic Research, Inc.
    9. Millemaci, Emanuele & Ofria, Ferdinando, 2016. "Supply and demand-side determinants of productivity growth in Italian regions," Structural Change and Economic Dynamics, Elsevier, vol. 37(C), pages 138-146.
    Full references (including those not matched with items on IDEAS)


    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:wfo:monber:y:1995:i:10:p:625-635. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ilse Schulz). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.