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

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Author Info

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

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File URL: http://www.sciencedirect.com/science/article/B6VC0-4582HGD-10/2/0ab7a6439f97dd32240a28b9f6661c60
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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 10 (1979)
Issue (Month): 1 (April)
Pages: 57-69

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

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Web page: http://www.elsevier.com/locate/jeconom

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Cited by:
  1. 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.
  2. Lütkepohl, Helmut & Proietti, Tommaso, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," Working Papers 1 OMEWP, University of Sydney Business School, Discipline of Business Analytics.
  3. 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.
  4. Sarkar, Nityananda, 2000. "Arch model with Box-Cox transformed dependent variable," Statistics & Probability Letters, Elsevier, vol. 50(4), pages 365-374, December.
  5. 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.
  6. Alexandros E. Milionis, 2003. "Modelling Economic Time Series in the Presence of Variance Non-Stationarity: A Practical Approach," Working Papers 07, Bank of Greece.

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