Masters Degrees (Agricultural Economics)
Permanent URI for this collection
Browse
Browsing Masters Degrees (Agricultural Economics) by browse.metadata.advisor "Greyling, Jan C."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
- ItemAssessing consumer post-response to a food safety scare in South Africa using behavioural game theory(Stellenbosch : Stellenbosch University, 2021-12) Hadebe, Ziyanda Precious; Punt, Cecilia; Greyling, Jan C.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Agricultural Economics.ENGLISH SUMMARY : The consumer response to the Listeria outbreak in South Africa (SA) was noticeable and reasonable. However, the post food scare effects are still predicted and it is not certain to what degree the outbreak affected rational decisions of consumers when buying processed meat products, especially the implicated ones. Thus, it is vital to capture and quantify the level of trust that South African consumers have toward processed meat products after the Listeria outbreak. Since the market is consumer-orientated, this study analysed the consumer behaviour towards the implicated product after the Listeria outbreak through behavioural economics and game theory. The study used 111 subjects with 50 control and 61 treatment participants from the Cape Wineland District in Western Cape Province. The participants consisted of both student and non-student participants, which enabled broad socio-economic characteristics to investigate the factors that influenced consumer behaviour after the outbreak. The experimental game theory chosen for the study is the Vickrey fourth-price auction used to collect willingness to pay (WTP) data. The Vickrey fourth-price auction consisted of three rounds where each participant was requested to bid for 500g viennas online through an oTree online platform after receiving negative and/or positive information about the Listeria outbreak. The winning bidders received food vouchers equivalent to the 500g viennas retail price after the experiment. After the auction, a survey and evaluation were conducted to collect data based on demographic characteristics, shopping habits, knowledge or attitude about food safety, salience, social pressure resulting from the outbreak and the level of trust for the implicated products. All the data and information that was collected from the auction, survey and evaluation were further analysed using a Tobit regression model, an integrative model of behavioural prediction (IMBP) and partial least squares structural equation modelling (PLS-SEM) to assess the consumer behaviour after the outbreak. Most participants indicated that they stopped consuming or reduced their consumption of the products implicated during the outbreak. Moreover, the negative information had a more significant impact on consumer behaviour than positive information about the outbreak. Negative information caused a major decrease in the consumption of ready-to-eat (RTE) meat products during and after the outbreak. Lastly, real intention of buying the implicated products, trust and shopping habit had the greatest influence on WTP compared to other variables. Real intention mainly increased the WTP of participants whilst trust either decreased or increased the WTP after the recall. Since the purchasing behaviour of consumers changed after the outbreak, shopping habits had the most negative effect on WTP. Thus, one may conclude that most consumers change their choice of purchase and frequency of buying RTE meat products, especially for implicated products after a food scare.
- ItemEstimating returns to education and experience in the South African agricultural industry(Stellenbosch : Stellenbosch University, 2021-03) Daniels, Tasneem; Greyling, Jan C.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Agricultural Economics.ENGLISH SUMMARY : Education is an important tool for economic growth and eradicating poverty. As the topic of returns to education has been researched extensively in South Africa, this study followed a slightly different direction. Literature determining the returns to education and experience in specific industries is scarce in South Africa. An increase in capital investments or supply of factor inputs creates an increase in the demand for skilled workers over time as an economy develops (Bhorat and Hodge, 1999). The primary objective of this study was to determine the returns to education and experience for the agricultural labour force using Mincer’s earnings functions. The objective of Mincer’s equation is to quantify returns to education and experience received by an individual for each additional year of education and experience in the workforce completed. The Mincer equations also have the capacity to include additional background and individual characteristics into the model, determining the influence these may have on earnings. The returns to education and experience for workers employed in the agricultural industry were analysed and compared to those in the mining and manufacturing sectors. To this end the level of education and experience of individuals, together with other factors that influence the monthly earnings, were considered. This study made use of the data provided by the Post-Apartheid Labour Market Series between the years of 2010 and 2017. If compared to other studies on the returns to education and experience in South Africa, this study is novel, since it both distinguishes between the industries in which individuals are employed and the skill levels at which they are employed. The main analysis in this study is based on the Ordinary Least Squares regression of the adjusted Mincer equation. Besides the standard regressors in the equation – education and experience – other dummy variables were included such as gender, union membership, marital status, and area type. Fixed effects were also included in the model for the period analysed in the study – 2010 to 2017 – and provincial fixed effects, to determine the impact of an individual’s location on wages. The findings are, firstly, that entry-level workers in the agricultural industry receive the lowest returns to education. A possible reason for this observation is that agricultural workers do not require more than basic education to complete simple and frequent tasks. Secondly, professional agricultural workers gain the highest returns to education compared to their peers in mining and manufacturing. Thus, higher levels of education lead to higher returns. Thirdly, female workers in the agricultural sector earn considerably lower monthly wages compared to males, regardless of their level of skill. The estimates of the additional variables included are in line with other studies analysing returns to education. Positive returns on education in the agricultural industry prove that there are gains to be had if there is an increase in educational attainment. These results provide policy makers with insight into where to invest, while pertinently considering that female education is more profitable and that more educational opportunities be provided for workers in the rural areas.
- ItemThe risk-return trade-off to diversified agriculture in Malawi : a quadratic programming approach(Stellenbosch : Stellenbosch University, 2021-03) Pyman, Dylan Harvey; Greyling, Jan C.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Agricultural Economics.ENGLISH SUMMARY : The rapid growth in the human population has sparked shifts in the way agricultural sectors have evolved in different countries. Most developed countries and those with a commercially driven agricultural sector have placed emphasis on increasing productivity in a bid to ‘produce more for less’. Developing countries, by contrast, are often dominated by subsistence agriculture where the focus lies on ensuring household food security rather than profit maximisation. Malawi falls into this category with a vast majority of the working population involved in agriculture – more specifically, in the smallholder sub-sector. The risk of crop losses in these countries has dire consequences for people reliant on these crops for their everyday meal. Minimizing such risk in countries like Malawi is therefore of paramount importance. Many studies, such as the one conducted by Ibrahim (2015), place diversification at the heart of risk management within the agricultural context. Consequently, this study investigated the use of diversification as a tool to minimise the levels of risk faced by smallholder farmers in Malawi. Studies by Mango, Makate, Mapemba and Sopo (2018) and Kankwamba, Mapila and Pauw (2013) analysed the determinants of diversification in Malawian agriculture and the current levels of diversification within the country’s agricultural sector. Their results provided insight into the factors influencing diversification and indicated a bimodal distribution for the number of crops grown – peaking at three as well as one. Evidently, the importance of diversification has already reached Malawian smallholder farmers. However, minimal research has been done into the optimum diversification strategies for these farmers to implement on the smallholder level. Some success optimising cropping portfolios for smallholder farmers in Malawi was found using Quadratic Risk Programming. However, that particular research called for an updated and more data accurate investigation. Accordingly, this study implemented the Quadratic Risk Programming model on a large sample of smallholder farmers in the southern region of Malawi. Six models were created, varying the size of the smallholder field and the capacity of the farmer to apply inorganic fertiliser. Five primary crops, namely maize, soybeans, groundnuts, common beans and sweet potatoes, were identified and their performance was analysed over three consecutive years. Each model included a variance-covariance matrix, incorporating the relationships between crops to derive optimized cropping portfolios according to the desired level of risk exposure. For small farms, the results showed that, of the available 2 acres, 1,3 acres should be allocated to maize and the balance shared between groundnuts and beans. A ratio favouring beans gave lower risk than when groundnuts were favoured. However, models for medium and large farms recommended an average allocation of 50 percent of their arable land to groundnut production. In consideration of food security, all models contained a minimum threshold for maize growth. The results for all fertilised farm models indicated sweet potato growth at the maximum constraint, prompting the recommendation for improved storage and marketing facilities for this crop in Malawi. Finally, recommendations were made regarding the use of the state-owned marketing platform, ADMARC, to protect farmgate prices and stimulate an agricultural environment conducive to the findings of this thesis.
- ItemA stochastic frontier analysis of factors affecting productivity and technical efficiency of dairy farmers in the Kingdom of Eswatini(Stellenbosch : Stellenbosch University, 2023-03) Mdluli, Bandile Banele; Greyling, Jan C.; Conradie, Beatrice; Stellenbosch University. Faculty of AgriSciences. Dept. of Agricultural Economics.ENGLISH SUMMARY: Dairy farming is a vital sector for the economy of Eswatini, but the country's low productivity means it still relies on milk imports from neighbouring countries. To assess the level of technical efficiency among local dairy farmers, this study was conducted using Battese and Coelli's stochastic frontier production function model. The research aimed to identify factors influencing technical inefficiency and attempted to test Henderson's two hypotheses explaining the inverse relationship between farm size and productivity. Data were collected from 118 dairy farmers using a structured questionnaire, and a single-stage modelling stochastic production frontier of the translog functional form was used for analysis. The study found that the mean technical efficiency of farmers was 71%, indicating a potential 29% increase in output if resources were used efficiently. All explanatory variables had positive coefficients and were statistically significant. The research segmented the sample into small, medium, and large farmers based on the number of cows in milk to test the technical efficiency hypothesis. The study showed that small farmers were the most efficient (78.5%), followed by medium (75.9%) and large (75.1%) farmers. The research identified that dairy farmers who used hired labour were less efficient than those who used their own or family labour, supporting the labour market imperfections hypothesis. The study found that using a proper record-keeping system was statistically significant in reducing inefficiency. Farmers who used this system had an average technical efficiency of 74.8% compared to those who did not, at 65.5%. The research recommended that the government and dairy development agencies focus on improving labour management training as part of their extension offering, as this would impact efficiency as farm size increases.