Journal of
Development and Agricultural Economics

  • Abbreviation: J. Dev. Agric. Econ.
  • Language: English
  • ISSN: 2006-9774
  • DOI: 10.5897/JDAE
  • Start Year: 2009
  • Published Articles: 552

Full Length Research Paper

Comparative analysis of poverty effects of various candidate biofuel crops in South Africa

Nicholas N. Ngepah
Competition Commission South Africa, Private Bag X23, Lynnwood Ridge 0040, and University of Johannesburg, Johannesburg, South Africa.
Email: [email protected]

  •  Published: 28 February 2010


The aim of this study was to investigate the poverty reduction impact of various potential biofuel crops in South Africa. A simple pro-poor development framework (in which income is substituted for by its function) is specified. After analysis for outliers with considerable leverage, a robust regression option was used to carry out estimations for physical output, values and inputs of each crop. For reasons of data availability, the crops considered were maize, wheat, sorghum and sugarcane for bioethanol, and groundnuts, soybeans and sunflower for biodiesel. The results suggest that various crops have different impacts on the different poverty measures. If a biofuel strategy’s intent is to promote (income) poverty reduction, then for South Africa sugarcane should be prioritised for bioethanol and groundnut for biodiesel. Other crops like maize and sunflower would require stronger support to small farmers. The finding also suggests that poverty reduction comes mainly by employment of the poor in commercial farming. There is suggestion that investment in farming by the poor is often inadequate and would generally result to poverty exacerbation. The implication is that the capital base of the poor must be broadened for them to effectively participate in farming. This has to be done without stifling commercial farming which is simultaneously contributing to poverty reduction through employment. These recommendations hold for sugarcane, groundnut and maize. However, a weakness worth mentioning is that the data is likely to underestimate or completely ignore most of the subsistence producers whose production is mainly for own consumption. Therefore, poverty impact could equally experience a downward bias in the models estimated here.


Key words: Biofuel crops, comparative analysis, poverty effect, South Africa.