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The effects of climate change on the farm sector in the Western Cape


  • Erasmus, Barend
  • van Jaarsveld, Albert
  • van Zyl, Johan
  • Vink, Nick


This paper links two different methodologies to determine the effects of climate change on the Western Cape farm sector. First, it uses a general circulation model (GCM) to model future climate change in the Western Cape, particularly with respect to precipitation. Second, a sector mathematical programming model of the Western Cape farm sector is used to incorporate the predicted climate change, specifically rainfall, from the GCM to determine the effects on key variables of the regional farm economy. In summary, results indicate that future climate change will lead to lower precipitation, which implies that less water will be available to agriculture in the Western Cape. This will have a negative overall effect on the Western Cape farm economy. Both producer welfare and consumer welfare will decrease. Total employment in the farm sector will also decrease as producers switch to a more extensive production pattern. The total decline in welfare, therefore, will fall disproportionately on the poor.

Suggested Citation

  • Erasmus, Barend & van Jaarsveld, Albert & van Zyl, Johan & Vink, Nick, 2000. "The effects of climate change on the farm sector in the Western Cape," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 39(4), December.
  • Handle: RePEc:ags:agreko:54217

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    References listed on IDEAS

    1. P. B. R. Hazell, 1971. "A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(1), pages 53-62.
    2. Dinar, A. & Mendelsohn, R. & Evenson, R. & Parikh, J. & Sanghi, A. & Kumar, K. & McKinsey, J. & Lonergen, S., 1998. "Measuring the Impact of CLimate Change on Indian Agriculture," Papers 402, World Bank - Technical Papers.
    3. P. B. R. Hazell & P. L. Scandizzo, 1974. "Competitive Demand Structures under Risk in Agricultural Linear Programming Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 56(2), pages 235-244.
    4. B. Curtis Eaves, 1971. "On Quadratic Programming," Management Science, INFORMS, vol. 17(11), pages 698-711, July.
    5. Johann Kirsten & Julian May & Sheryl Hendriks & Charles L. Machethe & Cecelia Punt & Mike Lyne, 2007. "South Africa," Chapters,in: Beyond Food Production, chapter 8 Edward Elgar Publishing.
      • Nick Vink & Gavin Williams & Johann Kirsten, 2004. "South Africa," Chapters,in: The World's Wine Markets, chapter 12 Edward Elgar Publishing.
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    Cited by:

    1. Sushenjit Bandyopadhyay & Limin Wang & Marcus Wijnen, 2011. "Improving Household Survey Instruments for Understanding Agricultural Household Adaptation to Climate Change : Water Stress and Variability," World Bank Other Operational Studies 12764, The World Bank.
    2. Gbetibouo, Glwadys Aymone & Ringler, Claudia, 2009. "Mapping South African farming sector vulnerability to climate change and variability: A subnational assessment," IFPRI discussion papers 885, International Food Policy Research Institute (IFPRI).
    3. Deressa, T. & Hassan, Rashid M. & Poonyth, Daneswar, 2005. "Measuring the impact of climate change on South African agriculture: The case of sugar-cane growing regions," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(4), December.

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