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Forecasting Short-Run Fed Beef Supplies with Estimated Data

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  • James N. Trapp

Abstract

Unknown aggregate data series for the placement weight, growth rate, and sex composition of cattle placed on feed are estimated. The estimates are made by treating the unknown data as time-varying parameters of a cattle-on-feed growth and inventory stimulation model. A nonlinear optimization algorithm is used to estimate the unknown parameter series that optimize the model's simulation accuracy. Incorporation of the estimated series into a traditional econometric fed-beef-supply forecast model improved the model's forecast accuracy. The methodology used provides a general procedure for estimating unknown aggregate data using simulation models based upon microrelationships.

Suggested Citation

  • James N. Trapp, 1981. "Forecasting Short-Run Fed Beef Supplies with Estimated Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(3), pages 457-465.
  • Handle: RePEc:oup:ajagec:v:63:y:1981:i:3:p:457-465.
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    File URL: http://hdl.handle.net/10.2307/1240536
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    Cited by:

    1. Probst, Joel Keith, 1982. "Monthly cattle supply and price forecasting models," ISU General Staff Papers 1982010108000018043, Iowa State University, Department of Economics.
    2. Lawrence, John D., 1986. "Livestock-feed consumption relationships as indicators of feed demand," ISU General Staff Papers 1986010108000017557, Iowa State University, Department of Economics.

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