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Probabilistic Models of Yield, Price, and Revenue Risks for Fed Cattle Production

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  • Belasco, Eric J.
  • Taylor, Mykel R.
  • Goodwin, Barry K.
  • Schroeder, Ted C.

Abstract

Cattle feeding enterprises operate amid variability originating in prices and production. This research explicitly models yield risks related to cattle feeding by relating the mean and variance of yield performance factors to observable conditioning variables. The results demonstrate that pen characteristics, such as entry weight, gender, placement season, and location influence the mean and variability of yield factors, defined as dry matter feed conversion, average daily gain, mortality, and animal health costs. Ex ante profit distributions, conditional on cattle placement characteristics, are derived through simulation methods to evaluate the effects of price or yield shocks on the distributional characteristics of expected profits.

Suggested Citation

  • Belasco, Eric J. & Taylor, Mykel R. & Goodwin, Barry K. & Schroeder, Ted C., 2009. "Probabilistic Models of Yield, Price, and Revenue Risks for Fed Cattle Production," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(1), pages 91-105, April.
    • Handle: RePEc:cup:jagaec:v:41:y:2009:i:01:p:91-105_00
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    References listed on IDEAS

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    Cited by:

    1. Christopher N. Boyer & Karen L. DeLong & Andrew P. Griffith & Charles C. Martinez, 2024. "Factors influencing United States cattle producers use of livestock risk protection," Agricultural Economics, International Association of Agricultural Economists, vol. 55(4), pages 677-689, July.
    2. Boyer, Christopher N. & DeLong, Karen L. & Griffith, Andrew P. & Martinez, Charles, 2024. "Examining how Risk Preferences and Information Affect Livestock Risk Protection Use," 2024 Annual Meeting, July 28-30, New Orleans, LA 343568, Agricultural and Applied Economics Association.
    3. Kumar, Anjani & Kumar, Pramod & Sharma, Alakh N., 2012. "Crop Diversification in Eastern India: Status and Determinants," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 67(4), pages 1-17.
    4. repec:ags:aaea22:335429 is not listed on IDEAS
    5. McKendree, Melissa G.S. & Tonsor, Glynn T. & Schulz, Lee, 2017. "Feedlot operators’ decision making regarding price and animal health risk," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258462, Agricultural and Applied Economics Association.
    6. Watten, Asa & Hennessy, David A. & Zhao, Jinhua, 2018. "Insurance and American Options in Intra-season Cropping Choices with Applications," 2018 Annual Meeting, August 5-7, Washington, D.C. 274480, Agricultural and Applied Economics Association.
    7. Belasco, Eric J. & Cheng, Yuanshan & Schroeder, Ted C., 2015. "The Impact of Extreme Weather on Cattle Feeding Profits," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 40(2), pages 1-21, May.
    8. Braelyn Moltz & Mark Yu & Edward Osei & W. Brandon Smith & Brant Poe, 2019. "The Economic Analysis of Corn Grain Optimization and Price Variation for Cattle on Feed in Texas," Agriculture, MDPI, vol. 9(7), pages 1-12, July.
    9. Yu, Chin-Hsien & Park, Seong Cheol & McCarl, Bruce A. & Amosson, Stephen H., 2012. "Feedlots, Air Quality and Dust Control-Benefit Estimation under Climate Change," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124736, Agricultural and Applied Economics Association.

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    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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