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A comparison of selected methods for forecasting monthly alfalfa hay prices

Author

Listed:
  • R. K. Skaggs

    (New Mexico State University Department of Agricultural Economics and Agricultural Business)

  • Donald L. Snyder

    (Utah State University Department of Economics)

Abstract

Alfalfa hay is one of the most important field crops in the United States; however, data limitations make it difficult to analyze and forecast hay prices. This research applied nine alternative procedures to generate postsample forecasts of California alfalfa hay prices. The procedures tested were: classical decomposition, exponential smoothing, univariate stochastic, multiple regression, bivariate stochastic, vector autoregression (unrestricted, Bayesian restricted and stepwise variable selection), and a structurally based system. Postsample predictive accuracy was evaluated; results indicated the simple procedures performed well in forecasting hay prices and limited improvement in accuracy with increased model complexity and information set.© 1992 John Wiley & Sons. Inc.

Suggested Citation

  • R. K. Skaggs & Donald L. Snyder, 1992. "A comparison of selected methods for forecasting monthly alfalfa hay prices," Agribusiness, John Wiley & Sons, Ltd., vol. 8(4), pages 309-321.
  • Handle: RePEc:wly:agribz:v:8:y:1992:i:4:p:309-321
    DOI: 10.1002/1520-6297(199207)8:4<309::AID-AGR2720080404>3.0.CO;2-M
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    References listed on IDEAS

    as
    1. Steven C. Blank & Harry W. Ayer, 1987. "Government policy cross effects: The cotton and dairy programs' influence on alfalfa hay markets," Agribusiness, John Wiley & Sons, Ltd., vol. 3(4), pages 385-392.
    2. Kazim Konyar & Keith Knapp, 1988. "Market analysis of alfalfa hay: California case," Agribusiness, John Wiley & Sons, Ltd., vol. 4(3), pages 271-284.
    3. Blake, Martin J. & Clevenger, Tom, 1984. "A Linked Annual And Monthly Model For Forecasting Alfalfa Hay Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(1), pages 1-5, July.
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