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Price Discovery in Nebraska Cattle Markets


  • Stockton, Matthew C.
  • Bessler, David A.
  • Wilson, Roger K.


Monthly observations on prices from 10 weight/gender classifications of Nebraska beef cattle are studied in an error correction model (ECM) framework. This study attempts a replication of the 2003 paper on Texas prices by Bessler and Davis, where they find medium heifers (600–700 lb) at the center of price discovery. Using the ECM results Nebraska light steers are found to be weakly exogenous, with the innovation accounting results showing marked differences. Industry structure, production choices, and animal type and breeding herd differences between Texas and Nebraska are proposed as plausible reasons for partial (or incomplete) success at replication.

Suggested Citation

  • Stockton, Matthew C. & Bessler, David A. & Wilson, Roger K., 2010. "Price Discovery in Nebraska Cattle Markets," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 42(01), February.
  • Handle: RePEc:ags:joaaec:57149

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    References listed on IDEAS

    1. Benjamin Sexauer, 1977. "The Role of Habits and Stocks in Consumer Expenditure," The Quarterly Journal of Economics, Oxford University Press, vol. 91(1), pages 127-142.
    2. Karagiannis, Giannis & Katranidis, Stelios D. & Velentzas, K., 2000. "An error correction almost ideal demand system for meat in Greece," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 22(1), January.
    3. Balcombe, Kelvin George & Davis, J.R., 1996. "An application of cointegration theory in the estimation of the Almost Ideal Demand system for food consumption in Bulgaria," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 15(1), September.
    4. Seale, James L., Jr. & Sparks, Amy L. & Buxton, Boyd M., 1992. "A Rotterdam Application To International Trade In Fresh Apples: A Differential Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 17(01), July.
    5. Arnade, Carlos Anthony & Pick, Daniel H. & Vasavada, Utpal, 1993. "Testing Dynamic Specifications For Import Demand Models: The Case Of Cotton," Working Papers 51119, International Agricultural Trade Research Consortium.
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    7. Mahmoud A. M. Bushehri, 2003. "Dynamic generalization of the Rotterdam model," Applied Economics Letters, Taylor & Francis Journals, vol. 10(5), pages 303-306, April.
    8. James L. Seale & Mary A. Marchant & Alberto Basso, 2003. "Imports versus Domestic Production: A Demand System Analysis of the U.S. Red Wine Market," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(1), pages 187-202.
    9. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, March.
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    Cited by:

    1. Kim, Man-Keun & Tejeda, Hernan & Yu, T. Edward, 2016. "Dynamic and Spatial Relationships in US Rice Markets," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229784, Southern Agricultural Economics Association.

    More about this item


    Bernanke factorization; cattle prices; cointegration; directed acyclical graphs; error correction; PC algorithm; price discovery; Agribusiness; Demand and Price Analysis; Industrial Organization; Livestock Production/Industries; Production Economics; Research Methods/ Statistical Methods; C49; Q13;

    JEL classification:

    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness


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