IDEAS home Printed from https://ideas.repec.org/a/bla/ecorec/v54y1978i2p229-236.html
   My bibliography  Save this article

Short Term Econometric Forecasting and Seasonal Adjustment

Author

Listed:
  • GEORGE BABICH
  • JOHN GOODHEW

Abstract

Seasonal behaviour in the variables of an econometric model is usually handled in one of two ways—either the data are adjusted prior to estimation, or seasonal binary variables are included in the specification and estimation of the model. Although the literature on the subject is extensive, it is not obvious which of these procedures is best for forecasting. This paper compares the forecasting ability of a small model of the Australian economy for each of the alternative approaches to seasonal adjustment.

Suggested Citation

  • George Babich & John Goodhew, 1978. "Short Term Econometric Forecasting and Seasonal Adjustment," The Economic Record, The Economic Society of Australia, vol. 54(2), pages 229-236, August.
    • Handle: RePEc:bla:ecorec:v:54:y:1978:i:2:p:229-236
    DOI: 10.1111/j.1475-4932.1978.tb00332.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1475-4932.1978.tb00332.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1475-4932.1978.tb00332.x?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
    ---><---

    References listed on IDEAS

    as
    1. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    2. Michael C. Lovell, 1963. "Seasonal Adjustment of Economic Time Series and Multiple Regression," Cowles Foundation Discussion Papers 151, Cowles Foundation for Research in Economics, Yale University.
    3. Pagan, Adrian, 1974. "A Generalised Approach to the Treatment of Autocorrelation," Australian Economic Papers, Wiley Blackwell, vol. 13(23), pages 267-280, December.
    4. Wallis, Kenneth F, 1972. "Testing for Fourth Order Autocorrelation in Qtrly Regression Equations," Econometrica, Econometric Society, vol. 40(4), pages 617-636, July.
    Full references (including those not matched with items on IDEAS)

    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. Becker, Ralf & Clements, Adam E., 2008. "Are combination forecasts of S&P 500 volatility statistically superior?," International Journal of Forecasting, Elsevier, vol. 24(1), pages 122-133.
    2. Uk Heo, 1998. "Modeling the Defense-Growth Relationship around the Globe," Journal of Conflict Resolution, Peace Science Society (International), vol. 42(5), pages 637-657, October.
    3. Jason Allen & Robert Amano & David P. Byrne & Allan W. Gregory, 2009. "Canadian city housing prices and urban market segmentation," Canadian Journal of Economics, Canadian Economics Association, vol. 42(3), pages 1132-1149, August.
    4. Benchimol, Jonathan & El-Shagi, Makram & Saadon, Yossi, 2022. "Do expert experience and characteristics affect inflation forecasts?," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 205-226.
    5. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    6. N. Antonakakis & J. Darby, 2013. "Forecasting volatility in developing countries' nominal exchange returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(21), pages 1675-1691, November.
    7. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    8. Jan Jacobs & Jan-Egbert Sturm, 2009. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
    9. Christina Ziegler, 2009. "Testing Predicitive Ability of Business Cycle Indicators for the Euro Area," ifo Working Paper Series 69, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. repec:kap:iaecre:v:14:y:2008:i:1:p:112-124 is not listed on IDEAS
    11. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
    12. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisionen der deutschen Industrieproduktion und die ifo Indikatoren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
    13. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    14. Baris Soybilgen & Ege Yazgan, 2017. "An evaluation of inflation expectations in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(1), pages 31-38.
    15. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    16. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    17. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    18. Pericoli, Marcello & Taboga, Marco, 2012. "Bond risk premia, macroeconomic fundamentals and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 42-65.
    19. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
    20. John W. Freebairn, 1975. "Forecasting For Australian Agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 19(3), pages 154-174, December.
    21. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.

    More about this item

    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:bla:ecorec:v:54:y:1978:i:2:p:229-236. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/esausea.html .

    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.