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Predictive Densities for Shire Level Wheat Yield in Western Australia

Author

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  • Griffiths, William E.
  • Newton, Lisa S.
  • O'Donnell, Christopher J.

Abstract

Rainfall during the germination, growing and flowering periods is a major determinant of wheat yield. The degree of uncertainty attached to a wheat-yield prediction depends on whether the prediction is made before or after the rainfall in each period has been realised. Bayesian predictive densities that reflect the different levels of uncertainty in wheat-yield predictions made at four different points in time are derived for five shires in Western Australia.

Suggested Citation

  • Griffiths, William E. & Newton, Lisa S. & O'Donnell, Christopher J., 2001. "Predictive Densities for Shire Level Wheat Yield in Western Australia," 2001 Conference (45th), January 23-25, 2001, Adelaide 125645, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare01:125645
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    File URL: http://purl.umn.edu/125645
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    References listed on IDEAS

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    1. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    2. Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-141, April.
    3. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
    4. Coelli, Tim J., 1992. "Forecasting Wheat Production Using Shire Level Data," 1992 Conference (36th), February 10-13, 1992, Canberra, Australia 146430, Australian Agricultural and Resource Economics Society.
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    Cited by:

    1. William Griffiths, 2002. "A Gibbs’ Sampler for the Parameters of a Truncated Multivariate Normal Distribution," Department of Economics - Working Papers Series 856, The University of Melbourne.
    2. Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne.

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