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Adoption of genetically modified crops in South Africa: Effects on wholesale maize prices

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  • Babatunde O Abidoye
  • Edward Mabaya

Abstract

The ability of genetically modified (GM) crops to increase yields and reduce use of pesticides is well established. Based on food security needs and the central role of agriculture, Africa may stand to benefit from green biotechnology given the low agricultural productivity and the looming food crises in most urban areas. However, the adoption of GM crops in Africa has been slow and limited to a handful of countries. The primary objective of this paper is to evaluate the impact of GM maize adoption in South Africa by looking at wholesale spot prices. We apply a threshold autoregressive model to time series data on the price of maize and GM adoption rates in South Africa to address the following questions: (1) Does the adoption of GM maize excite the growth rate of price of maize in South Africa; (2) Does the error variance of the maize price growth rate exhibit regime-switching behaviour to impact the volatility? The results show evidence that the adoption of GM maize influences the dynamics of the maize price growth rate in South Africa. Further, there is strong evidence that the error variance exhibits regime-switching behaviour with the posterior mean for the error variance in the first regime about twice as large as that of the second regime.

Suggested Citation

  • Babatunde O Abidoye & Edward Mabaya, 2014. "Adoption of genetically modified crops in South Africa: Effects on wholesale maize prices," Agrekon, Taylor & Francis Journals, vol. 53(1), pages 104-123, March.
  • Handle: RePEc:taf:ragrxx:v:53:y:2014:i:1:p:104-123
    DOI: 10.1080/03031853.2014.887907
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    References listed on IDEAS

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    1. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
    2. Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9780521671736, June.
    3. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108423380, September.
    4. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108437493, September.
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    1. Sinyolo, Sikhulumile, 2020. "Technology adoption and household food security among rural households in South Africa: The role of improved maize varieties," Technology in Society, Elsevier, vol. 60(C).
    2. Andrzejczak, Katarzyna & Przysiecka, Łucja, 2016. "Genetic Technology Transfer to Kenyan Agriculture in the Context of Biotechnology Research," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 16(31), pages 1-11, December.
    3. Malaiarasan, Umanath & Paramasivam, R & Saravanakumar, V, 2022. "Choice of millets cultivation in India: an evidence from farm household survey data," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 35(Conferenc), December.
    4. Catherine Nkirote Kunyanga & Morten Fibieger Byskov & Keith Hyams & Samuel Mburu & Grace Werikhe & Cecilia Moraa Onyango, 2023. "Perceptions of the Governance of the Technological Risks of Food Innovations for Addressing Food Security," Sustainability, MDPI, vol. 15(15), pages 1-24, July.

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