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Trends, Lead Times and Forecasting

  • Saligari, G.R.
  • Snyder, R.D.

The local linear trend and global linear trend models embody extreme assumptions about trends. According to the local linear trend formulation the level and growth rate are allowed to rapidly adapt to changes in the data path. On the other hand, the Glaobal linear trend model makes no allowance for structural change. In this paper we introduce a new model that, as well as encompassing the global linear trend and local linear trend models, allows for a range of "in between" cases.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 1/96.

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Length: 40 pages
Date of creation: 1996
Date of revision:
Handle: RePEc:msh:ebswps:1996-1
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  1. Schotman, Peter C & van Dijk, Herman K, 1991. "On Bayesian Routes to Unit Roots," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec..
  2. P. J. Harrison, 1967. "Exponential Smoothing and Short-Term Sales Forecasting," Management Science, INFORMS, vol. 13(11), pages 821-842, July.
  3. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  4. Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
  5. Gersch, Will & Kitagawa, Genshiro, 1983. "The Prediction of Time Series with Trends and Seasonalities," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 253-64, July.
  6. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-27, June.
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