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Technical and scale efficiencies of meat goat farms in the USA

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  • B. Qushim
  • J. Gillespie
  • K. Paudel
  • K. Mcmillin

Abstract

This study determines i) scale and technical efficiencies, ii) marginal productive contributions for inputs and outputs and iii) efficiency drivers of meat goat farms in the USA. We estimate an input distance function (IDF) using a stochastic production frontier (SPF) technique. The average technical efficiency (TE) for the USA meat goat whole farm was 0.74. The operator education level, percentage of annual net farm income from the goat operation, regional differences and holding of an off farm job are the efficiency drivers of USA meat goat farms. We find increasing returns to scale (RTS) for USA meat goat farms. Our results suggest that USA meat goat farms can be scale efficient if their optimal size of operation is greater than approximately 64 goats or greater than 40 breeding does. Empirical Monte Carlo (MC) simulation techniques show the consistency of finite-sample properties for the input distance function.

Suggested Citation

  • B. Qushim & J. Gillespie & K. Paudel & K. Mcmillin, 2016. "Technical and scale efficiencies of meat goat farms in the USA," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 608-620, February.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:7:p:608-620
    DOI: 10.1080/00036846.2015.1083531
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    References listed on IDEAS

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    1. Catherine Paul & Richard Nehring & David Banker & Agapi Somwaru, 2004. "Scale Economies and Efficiency in U.S. Agriculture: Are Traditional Farms History?," Journal of Productivity Analysis, Springer, vol. 22(3), pages 185-205, November.
    2. V. Eldon Ball & W. A. Lindamood & Richard Nehring & Carlos San Juan Mesonada, 2008. "Capital as a factor of production in OECD agriculture: measurement and data," Applied Economics, Taylor & Francis Journals, vol. 40(10), pages 1253-1277.
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    4. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    5. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    6. Peter Schmidt, 2011. "One-step and two-step estimation in SFA models," Journal of Productivity Analysis, Springer, vol. 36(2), pages 201-203, October.
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    Cited by:

    1. Jeffrey Gillespie & Narayan Nyaupane & Brittany Dunn & Kenneth McMillin, 2016. "Why do farmers decide to produce meat goats? Evidence from the United States," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 33(4), pages 911-927, December.
    2. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.
    3. Qushim, Berdikul & Gillespie, Jeffrey, 2016. "Women Farm Operators in the U.S. Meat Goat Production: Who is More Productive?," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230004, Southern Agricultural Economics Association.

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