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Technological differences in South African sheep production: a stochastic meta-frontier analysis

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  • Matthews, Nicolette
  • Conradie, Beatrice
  • Piesse, Jenifer

Abstract

This study compared four South African sheep producing districts relative to each other and a common metafrontier to analyse within and between group efficiency and explored what could be learnt from this technique compared to simple frontiers. A sample was compiled from sources that were previously successfully used in local benchmarking exercises, and despite very modest sample sizes at the group level and minimal information on how groups differ, the group models performed adequately while the meta-model performed very well. The results revealed that while within group performances were comparable across districts, there were huge differences in between group performance. These differences are partly attributable to natural resource endowments, but institutional arrangements also contribute significantly to local success. This suggests that to achieve rural regeneration public–private partnerships are necessary to address this issue. State support is insufficient and producer organisations have a major role in promoting institutional innovation.

Suggested Citation

  • Matthews, Nicolette & Conradie, Beatrice & Piesse, Jenifer, 2023. "Technological differences in South African sheep production: a stochastic meta-frontier analysis," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 62(1), January.
    • Handle: RePEc:ags:agreko:348182
    DOI: 10.22004/ag.econ.348182
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    References listed on IDEAS

    as
    1. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    2. Galloway, Craig & Conradie, Beatrice & Prozesky, Heidi & Esler, Karen, 2018. "Opportunities to improve sustainability on commercial pasture-based dairy farms by assessing environmental impact," Agricultural Systems, Elsevier, vol. 166(C), pages 1-9.
    3. Omphile Temoso & David Hadley & Renato Villano, 2015. "Performance Measurement of Extensive Beef Cattle Farms in Botswana," Agrekon, Taylor & Francis Journals, vol. 54(4), pages 87-112, November.
    4. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    5. Yong Sebastian Nyam & Nicolette Matthews & Yonas Tesfamariam Bahta, 2020. "Improving livelihoods of smallholder farmers through region specific strategies: a case study of South African sheep production," Agrekon, Taylor & Francis Journals, vol. 59(1), pages 1-15, January.
    6. Nick Vink & Beatrice Conradie & Nicolette Matthews, 2022. "The Economics of Agricultural Productivity in South Africa," Annual Review of Resource Economics, Annual Reviews, vol. 14(1), pages 131-149, October.
    7. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    Full references (including those not matched with items on IDEAS)

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