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Mathematical modeling of the South African land redistribution for development policy


  • Olubode-Awosola, O.O.
  • van Schalkwyk, H.D.
  • Jooste, A.


The ineffectiveness of policy advice in most African countries could be attributed, amongst others, to the problem of scientists not being able to present or communicate a holistic solutions to policy challenges. As a result, the potential and actual consequences of policies are seldom indicated. It may be demanding to use a more comprehensive and quantitative research method in policy analysis because of limited resources to integrate technical, biophysical with the socio-economic and political variables when analysing policy effects. To exemplify this phenomenon, a forward-looking and prescriptive economic analysis that is being widely used for ex-ante policy analyses was used to make a contribution to the discussion on land redistribution, which is presently not only one of the most definitive political and development issues, but perhaps the most intractable in South Africa. The study develops and uses a mathematical model for regionalised farm-level resource use and output supply response to show that the current policy requires more economic imperatives, as it tends towards smallholder agriculture that has elements of low capital threshold trap. After 30% of the farmland will have been transferred from the large farm type to settle more units of small farm type by 2015, the decrease in the number of large farm units from about 8531 units in the base year to about 7112 farm units will lead to a decline in crop and animal product supplies. Such declines (about 15.3%) will overwhelm the increase of more than 1600% in supplies as a result of increased small farm units. Given the challenges of a free market and the fact that the current farm settlement arrangement lacks appreciable efficiency, the study prescribes land redistribution strategies that consider efficiency along with equity. Taking size as an indication of efficiency, an increase in technical progress at 1, 5 and 10% is expected to shift the supply curves to the right for less risky crop and animal enterprises meaning having more farmland, which may imply reduced lack of capital constraints would not necessarily imply a general increase in all the production activities because of relative risks in revenues. The study however, suggests that agricultural land can act as a safety net for the poor, where the efficiency argument does not hold.

Suggested Citation

  • Olubode-Awosola, O.O. & van Schalkwyk, H.D. & Jooste, A., 2008. "Mathematical modeling of the South African land redistribution for development policy," Journal of Policy Modeling, Elsevier, vol. 30(5), pages 841-855.
  • Handle: RePEc:eee:jpolmo:v:30:y:2008:i:5:p:841-855

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    References listed on IDEAS

    1. Paul Mosley & Abrar Suleiman, 2007. "Aid, Agriculture and Poverty in Developing Countries," Review of Development Economics, Wiley Blackwell, vol. 11(1), pages 139-158, February.
    2. Rutstrom, E. Elisabet & Redmond, Willie J., 1997. "A quantification of lobbying benefits with an application to the common agricultural policy," Journal of Policy Modeling, Elsevier, vol. 19(6), pages 635-659, December.
    3. Storm, Servaas, 1994. "The macroeconomic impact of agricultural policy: A CGE analysis for India," Journal of Policy Modeling, Elsevier, vol. 16(1), pages 55-95, February.
    4. Stifel, David C. & Randrianarisoa, Jean-Claude, 2006. "Agricultural policy in Madagascar: A seasonal multi-market model," Journal of Policy Modeling, Elsevier, vol. 28(9), pages 1023-1027, December.
    5. Kilkenny, Maureen & Robinson, Sherman, 1990. "Computable general equilibrium analysis of agricultural liberalization: Factor mobility and macro closure," Journal of Policy Modeling, Elsevier, vol. 12(3), pages 527-556.
    6. Just, Richard E., 1993. "Discovering Production and Supply Relationships: Present Status and Future Opportunities," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 01), pages 1-30, April.
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