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A Generalized Supply Response/Factor Demand Model And Its Application To The Feeder Cattle Market

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  • Shonkwiler, John Scott
  • Hinckley, Suzanne

Abstract

The appropriate specification of expectations in empirical models of supply response or factor demand is discussed. A general model that admits both extrapolative and rational expectations is formulated and analyzed. The model is used to investigate the decision making process of cattle feeders by incorporating information on futures prices (as representations of rational forecasts) and lagged prices. The findings provide some evidence that cattle feeders form their expectations of future prices using both types of information.

Suggested Citation

  • Shonkwiler, John Scott & Hinckley, Suzanne, 1985. "A Generalized Supply Response/Factor Demand Model And Its Application To The Feeder Cattle Market," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 10(2), pages 1-9, December.
    • Handle: RePEc:ags:wjagec:32322
    DOI: 10.22004/ag.econ.32322
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    References listed on IDEAS

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    Cited by:

    1. Smith, Rodney B.W. & Gardner, Bruce L., 1989. "Expectations, Futures Prices, and Feedlot Operator Behavior," Working Papers 197622, University of Maryland, Department of Agricultural and Resource Economics.
    2. Burton, Diana M. & Love, H. Alan, 1996. "A Review of Alternative Expectations Regimes in Commodity Markets: Specification, Estimation, and Hypothesis Testing Using Structural Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 25(2), pages 213-231, October.
    3. Melissa G. S. McKendree & Glynn T. Tonsor & Ted C. Schroeder & Nathan P. Hendricks, 2020. "Impacts of Retail and Export Demand on United States Cattle Producers," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 866-883, May.
    4. Marsh, John M., 2001. "U.S. Feeder Cattle Prices: Effects Of Finance And Risk, Cow-Calf And Feedlot Technologies, And Mexican Feeder Imports," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 26(2), pages 1-15, December.
    5. Li, Yunhan & Shonkwiler, Scott, 2016. "A Dynamic Model of U. S. Beef Cow Inventories," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235385, Agricultural and Applied Economics Association.
    6. Anbes Tenaye, 2020. "New Evidence Using a Dynamic Panel Data Approach: Cereal Supply Response in Smallholder Agriculture in Ethiopia," Economies, MDPI, vol. 8(3), pages 1-24, July.
    7. Mbaga, Msafiri Daudi & Coyle, Barry T., 2003. "Beef Supply Response Under Uncertainty: An Autoregressive Distributed Lag Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(3), pages 1-21, December.
    8. Smith, Rodney B.W. & Gardner, Bruce L., 1993. "Expectations, Futures Prices, And Feedlot Behavior," Staff Papers 13444, University of Minnesota, Department of Applied Economics.
    9. Emilio Galdeano-Gómez, 2007. "Composite price expectations: An empirical analysis for the Spanish horticultural sector," Agribusiness, John Wiley & Sons, Ltd., vol. 23(1), pages 57-83.
    10. Shengying Zhai & Qihui Chen & Wenxin Wang, 2019. "What Drives Green Fodder Supply in China?—A Nerlovian Analysis with LASSO Variable Selection," Sustainability, MDPI, vol. 11(23), pages 1-17, November.

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