A Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science, 2012. / The purpose of this study is to investigate if the International Comparison Program (ICP) methodology could be used to examine the different buying power (worth) of the currency on the same products or goods amongst South African provinces. The method will be tested on the Consumer Price Index (CPI) food data collected from January 2006 to December 2006 from the main cities in the provinces. The food basket is obtained via the Income and Expenditure Survey (IES), which is generally updated every 5 years. South Africa (SA) has disparities and differentials in economic indicators such as the CPI, Gross Domestic Product and employment, amongst the provinces which are caused by among other things geographic set-up, urbanisation, inflation rates, and expenditure patterns. We use the monthly data to do an inter-provincial comparison of food prices by deriving annual purchasing power parities (PPPs) for each of the provinces, using the Country Product Dummy (CPD) method recommended as best practice by the World Bank. The CPI data is validated using the SEMPER software developed by the African Development Bank (AfDB). The validated data is examined for variability over the months and between the provinces using Analysis of Variance. Significant price differences are found for various products over the months and between provinces. The validated data was used to compute PPPs at the group and basic heading level. PPPs were investigated for differences in the provinces on grouped level of food products using Analysis of Variance. The reliability of PPPs between provinces is investigated both at grouped and basic heading level of products using the Cronbach-alpha statistic. The results show that there are no significant variations in PPPs across provinces. This could be due to the similar business opportunities or developments in the provinces or due to the aggregation of prices from the individual product (basic heading) to the main product group level. This implies that the cost of the food basket is the same across provinces.

(Ph. D. (Agricultural Economics)) -- University of Limpopo, 2021 / 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