Estimating returns to education and experience in the South African agricultural industry

Type Thesis or Dissertation - Masters Thesis
Title Estimating returns to education and experience in the South African agricultural industry
Publication (Day/Month/Year) 2021
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.

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