IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v10y1979i1p57-69.html
   My bibliography  Save this article

Experience with using the Box-Cox transformation when forecasting economic time series

Author

Listed:
  • Nelson, Harold Jr.
  • Granger, C. W. J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Nelson, Harold Jr. & Granger, C. W. J., 1979. "Experience with using the Box-Cox transformation when forecasting economic time series," Journal of Econometrics, Elsevier, vol. 10(1), pages 57-69, April.
    • Handle: RePEc:eee:econom:v:10:y:1979:i:1:p:57-69
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0304-4076(79)90064-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    Citations

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


    Cited by:

    1. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
    2. Stephen J. Taylor & Brian G. Kingsman, 1979. "An Analysis of the Variance and Distribution of Commodity Price Changes," Australian Journal of Management, Australian School of Business, vol. 4(2), pages 135-149, October.
    3. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    4. Alexandros E. Milionis & Nikolaos G. Galanopoulos, 2018. "Time series with interdependent level and second moment: statistical testing and applications with Greek external trade and simulated data," Working Papers 246, Bank of Greece.
    5. Beaumont, Adrian N., 2014. "Data transforms with exponential smoothing methods of forecasting," International Journal of Forecasting, Elsevier, vol. 30(4), pages 918-927.
    6. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.
    7. Alexandros E. Milionis & Nikolaos G. Galanopoulos, 2020. "A study of the effect of data transformation and «linearization» on time series forecasts. A practical approach," Working Papers 280, Bank of Greece.
    8. Alexandros E. Milionis & Nikolaos G. Galanopoulos & Peter Hatzopoulos & Aliki Sagianou, 2022. "Forecasting actuarial time series: a practical study of the effect of statistical pre-adjustments," Working Papers 297, Bank of Greece.
    9. Mahmood, Talat, 1990. "Die Dynamik der Rentabilität als stochastischer Prozess: eine empirische Zeitreihenanalyse von ausgewählten deutschen und amerikanischen Unternehmen. Vom Fachbereich 20 Informatik der Technischen Univ," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 112236, June.
    10. Alexandros E. Milionis, 2003. "Modelling Economic Time Series in the Presence of Variance Non-Stationarity: A Practical Approach," Working Papers 07, Bank of Greece.
    11. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
    12. Kwan, Andy C.C. & Sim, Ah-Boon & Wu, Yangru, 2005. "A comparative study of the finite-sample performance of some portmanteau tests for randomness of a time series," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 391-413, February.
    13. Sarkar, Nityananda, 2000. "Arch model with Box-Cox transformed dependent variable," Statistics & Probability Letters, Elsevier, vol. 50(4), pages 365-374, December.
    14. Andy Kwan & Ah-Boon Sim & Yangru Wu, 2005. "On the size and power of normalized autocorrelation coefficients," Applied Financial Economics, Taylor & Francis Journals, vol. 15(1), pages 1-11.
    15. Heuts, R.M.J., 1982. "The use of non-linear transformations in ARIMA-models when the data are non-Gaussian distributed," Other publications TiSEM f4ccef9b-24f6-4179-883c-9, Tilburg University, School of Economics and Management.
    16. Georgios Tsiotas, 2020. "On the use of power transformations in CAViaR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 296-312, March.

    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:eee:econom:v:10:y:1979:i:1:p:57-69. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.