Public spending on agriculture and poverty in Eastern Cape province, South Africa

Efforts to meet the Millennium Development Goal 1 (MDG1), which was to reduce by half the proportion of the population living below the poverty line by 2015, and the demands of democratization in South Africa have directed attention at the agricultural sector's potential for reducing poverty. Expectedly, agriculture has attracted considerable interest and public investment. This article explores the linkages between public spending in agriculture, agricultural growth, and poverty in the Eastern Cape Province of South Africa. The identification of the critical linkages will contribute to improving decision making on the use of public funds in agriculture. Methodologically, the study simulates the required agricultural investment and required agricultural growth rate that is sufficient to meet MDG1 by 2025 by employing partial equilibrium modeling based on the System Dynamics Analyses approach. This entailed the application of growth decomposition technique and growth elasticity of poverty concepts with a specific emphasis on policy interventions for promoting agricultural growth. The drivers and cause-effect relationships between agriculture and poverty reduction were investigated. The employed models allowed for an exploration of plausible future growth in public spending in agriculture, agricultural growth elasticity of poverty, and the possibility of reducing poverty levels in the province while evaluating strategies for meeting the MDG1 by 2025. Estimates for the required agricultural growth rate and the increase in public spending on agriculture required in order to reach MDG1 by 2025 were calculated for each district municipality in the Eastern Cape Province. All the district municipalities were then evaluated in terms of their need to increase public investment in agriculture and the ability to achieve MDG1 by 2025 and beyond. Estimates for both the required public spending and the required agricultural growth were then calculated following both the business-as-usual scenario and the best-case scenario.