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dc.contributor.advisorSpies, D.C.en_US
dc.contributor.authorAdeyemi, O.A.en_US
dc.date.accessioned2020-02-14T15:06:26Z
dc.date.available2020-02-14T15:06:26Z
dc.date.issued2019en_US
dc.identifier.urihttps://orcid.org/0000-0002-1922-4253en_US
dc.identifier.urihttp://hdl.handle.net/10394/34122
dc.descriptionPhD (Agricultural Economics), North-West University, Potchefstroom Campus
dc.description.abstractExisting empirical evidence on agricultural supply response is very mixed, ambiguous and generally assumed to be inelastic. This study develops an econometric framework to test the hypothesis that supply is inelastic and extend our understanding of field-crop farmers' resource allocation decisions, within the context of structural change in the past four decades. This thesis research provides new estimates and a perspective on the agricultural supply response in South Africa following the agricultural policy reforms initiated from the early 1980s, through the 1990s and the 2000s. Using time series data for the period 1970 — 2012, this study employed a vector error correction model and co-integration to assess the responsiveness of field-crops farmers to price and non-price factors. These techniques provide a more intuitive way of modelling the optimisation and rational behaviour of farmers, and the important field crops used for this study are maize, sugar cane, wheat, sorghum and barley. Furthermore, the study provides innovative/beneficial insights on the role of exchange rate volatility on agricultural supply response and trade flows. This is achieved by estimating an exchange rate volatility measure through using an exponential autoregressive conditional heteroscedasticity (EGARCH) technique on South African exchange rate annual time series data for period 1970–2012. The computed exchange rate volatility measure was used to capture production risk and trade flow effects. The results from study indicate that supply response is high and positive in the long run, with the exception of sugar cane, which has a very low supply response, as non-price factors are more important. The estimated price elasticities in the short run are maize (0.15), wheat (0.45), sugar cane (0.02), barley (0.04) and sorghum (0.45), while in the long run, the price elasticities are maize (0.67), sugar cane (0.02), and barley (1.0), respectively. Furthermore, the results of the aggregate supply are 0.78 in the short run and 1.0 in the long run. These results confirm the preponderance of econometric evidence from the empirical literature review that supply response is high and elastic. The study further identify the important factors influencing agricultural supply response in South Africa, which are producer prices, intermediate input prices, price of substitute/complementary crops, yield, exchange rate volatility, climate (drought) and agricultural policy. For the aggregate supply model, they are gross capital formation, price of farm requisition, exchange rate volatility and agricultural policy. Besides price, the study further identify other non-price factors such as yield, drought, and agricultural policy as other important factors. The findings of this study are significant in terms of model specification (methodology) and policy implications in terms of government intervention and effective policy implementation. Failure to address the problem of effective policy implementation would lead to sub-optimal performance in the agricultural sector. Furthermore, the differences in the crop-specific supply elasticities support a differentiated agricultural policy, rather than a one-size fits all centralised agricultural policy. At the same time, policy choices have to be made based on empirical, cutting-edge research on how to maintain increasing productivity, investment and competitiveness of the field-crop industry. However, solace is provided by the new economic growth theory, suggesting that a country's comparative advantage is in a "knowledge—capital base", as opposed to the classical theory of relying on natural resource endowments alone. There are still ample opportunities for agriculture in South Africa. Future research should explore applying vector error correction models to other sector-specific analyses, such as for the livestock, horticulture and vegetable industries, by using time series, panel and cross-sectional data.en_US
dc.language.isoenen_US
dc.publisherNorth-West Universityen_US
dc.subjectSupply Responseen_US
dc.subjectCo-integrationen_US
dc.subjectVector Error Correction Model (VECM)en_US
dc.subjectEGARCHen_US
dc.subjectAgricultureen_US
dc.subjectExchange Rate Volatilityen_US
dc.subjectAgricultural Policyen_US
dc.titleSupply Response of Field Crops in South Africaen_US
dc.typeThesisen_US
dc.description.thesistypeDoctoralen_US
dc.contributor.researchID22709053 - Spies, David Cornelius (Supervisor)en_US


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