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dc.contributor.advisor Belete, A.
dc.contributor.author Shoko, Rangarirai Roy
dc.contributor.other Mongale, I. P.
dc.date.accessioned 2022-05-20T10:16:07Z
dc.date.available 2022-05-20T10:16:07Z
dc.date.issued 2021
dc.identifier.uri http://hdl.handle.net/10386/3792
dc.description (Ph. D. (Agricultural Economics)) -- University of Limpopo, 2021 en_US
dc.description.abstract The issues regarding the determinants of agricultural production and food supply are currently of great interest in developing countries. This, in turn, has led to the undertaking of this study focusing on the effectiveness of incentives that can be offered within the agricultural sector to boost production. The study aims to model the supply response of key agricultural commodities to price incentives, price risk and non-price incentives. Special focus is given to four major grain crops, namely; maize, wheat, sorghum and barley, which are of strategic interest to South Africa. The emphasis of the study is on two significant aspects of agricultural supply response: First, an attempt is made to determine the level of price risk among the selected grain crops using two distinct price risk measures. Second, the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) approach to cointegration is used to estimate the responsiveness of grain producers to price risk, price incentives and non-price incentives. Annual historical time series data of 49 observations for the period 1970 to 2018 is used in the analysis. Data is tested for stationarity using the Augmented Dickey-Fuller test and the Dickey-Fuller Generalised Least Square (DF-GLS) detrending test. The empirical results reveal that grain supply in South Africa is reasonably responsive to price incentives. However, the degree of responsiveness is low and varies among different crops. Depending on the crop, the results show that own price supply elasticities range from about 0.24 to 0.75. Supply elasticities for nonprice factors are much higher, indicating that non-price incentives (i.e. rainfall, fertiliser, technology) are better production drivers than price incentives in South Africa. Thus, instead of regarding price mechanisms as being the only tools to promote agricultural production, it is concluded that further expansion of irrigation facilities and encouraging the adoption of drought-resistant varieties will stimulate grain production. The results underscore the relevance of price risk in determining production output and show that greater price risk leads to reduced production levels, particularly for maize and barley. In light of such evidence, any policy initiatives undertaken to stabilise the grain industry should look into proposing packages (i.e., forward contracts, futures contracts, contract farming) that reduce the negative impacts of price volatility in grain commodity markets en_US
dc.format.extent xi, 138 leaves en_US
dc.language.iso en en_US
dc.relation.requires PDF en_US
dc.subject Supply response en_US
dc.subject Autoregressive Distributed Lag-Error Correctional Model en_US
dc.subject Price factors en_US
dc.subject Non-price factors en_US
dc.subject Price risk en_US
dc.subject.lcsh Grain en_US
dc.subject.lcsh Crops en_US
dc.subject.lcsh Food supply en_US
dc.subject.lcsh Food security -- South Africa en_US
dc.subject.lcsh Food prices -- South Africa en_US
dc.title Analysing the supply response and price risk of major grain crops in South Africa en_US
dc.type Thesis en_US


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