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Modelling risk in farm planning

Author

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  • Visagie, S.E.
  • Ghebretsadik, A.H.

Abstract

In this article a mathematical model is presented to assist management decisions on an integrated crop and livestock farm. Risk is incorporated into the model as the negative deviation of the actual gross income from the expected value of an activity's gross income. The model includes crop production (permitting and optimising a crop rotation system), dairy production and wool sheep production. Relevant data from a farm in the Swartland region of the Western Cape were used to test and validate the model. The results show that the adoption of crop rotation is superior in terms of gross margin to that generated from a mono-crop strategy. Empirical results also indicate that the complex interrelationships involved in a mixed crop-livestock farm operation play a major role in determining optimal farm plans. These complex interrelationships favour the introduction of crop rotation in the crop production activities of the farm under investigation. Solutions of the model with risk indicate that the crop rotation strategy and animal production levels are sensitive to different risk levels, and that the incorporation of risk greatly affects the level of land allocation to crop rotation and animal production level of the farm. Finally, the results suggest that the introduction of crop rotation is of paramount importance in improving the profitability and sustainability of the farm, thus the inclusion of forage crops such as medics into the integrated crop-livestock production is beneficial for sustained profitability.

Suggested Citation

  • Visagie, S.E. & Ghebretsadik, A.H., 2005. "Modelling risk in farm planning," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 44(4), December.
  • Handle: RePEc:ags:agreko:31702
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    File URL: http://purl.umn.edu/31702
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    References listed on IDEAS

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    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. Munford, Alan G., 1989. "A microcomputer system for formulating animal diets which may involve liquid raw materials," European Journal of Operational Research, Elsevier, vol. 41(3), pages 270-276, August.
    3. B. Curtis Eaves, 1971. "On Quadratic Programming," Management Science, INFORMS, vol. 17(11), pages 698-711, July.
    4. Visagie, S.E., 2004. "Optimering van wisselboustelsels," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 43(3), September.
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    Cited by:

    1. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Working Papers JRC108693, Joint Research Centre (Seville site).

    More about this item

    Keywords

    Farm Management; Risk and Uncertainty;

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