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Estimating Desirable Cattle Traits Using Latent Class and Mixed Logit Models: A Choice Modeling Application to the U.S. Grass-Fed Beef Industry

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  • Sitienei, Isaac
  • Gillespie, Jeffrey
  • Harrison, Robert
  • Scaglia, Guillermo

Abstract

This study examines preferences for cattle traits using mixed logit and latent class models. Choice experiment data from a 2013 mail survey of 1,052 U.S. grass-fed beef producers were used. Preliminary results indicate that producers prefer lower-priced, heavy, black, and easy-to-handle feeders backgrounded from their own cows.

Suggested Citation

  • Sitienei, Isaac & Gillespie, Jeffrey & Harrison, Robert & Scaglia, Guillermo, 2015. "Estimating Desirable Cattle Traits Using Latent Class and Mixed Logit Models: A Choice Modeling Application to the U.S. Grass-Fed Beef Industry," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196706, Southern Agricultural Economics Association.
    • Handle: RePEc:ags:saea15:196706
    DOI: 10.22004/ag.econ.196706
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    References listed on IDEAS

    as
    1. McCluskey, Jill J. & Wahl, Thomas I. & Li, Quan & Wandschneider, Philip R., 2005. "U.S. Grass-Fed Beef: Marketing Health Benefits," Journal of Food Distribution Research, Food Distribution Research Society, vol. 36(3), pages 1-8, November.
    2. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    3. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    4. Harrison, R. Wes & Stringer, Timothy & Prinyawiwatkul, Witoon, 2002. "An Analysis of Consumer Preferences for Value-Added Seafood Products Derived from Crawfish," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 31(2), pages 1-14, October.
    5. Daniele Pacifico, 2010. "Estimating nonparametric mixed logit models via EM algorithm," Center for the Analysis of Public Policies (CAPP) 0072, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    6. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    8. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
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    Keywords

    Farm Management; Livestock Production/Industries; Production Economics; Research Methods/ Statistical Methods;
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