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Education is generally considered to be the core source of individuals’ better life and countries' economic and social development. Consequently, attending university and getting high qualifications are perceived as tools that generate and enhance economic growth. The current study aimed to analyse the effect of various educational levels on South African economic growth. The study employed quarterly data from 1995Q1 to 2021Q4. The autoregressive distributed lag (ARDL) model was employed to assess both long-run and short-run relationships among variables. The long-run results revealed that people who completed their grade 12 (with matric certificate) and bachelor's degrees contribute positively to South African economic growth. However, honours and higher degrees (master's and PhD) were found to have an inverse relationship with economic growth in South Africa. On the other hand, the short-run relationship indicated that all education levels contribute to economic growth in the short term. Based on these findings, the author suggests that the South African higher education curriculum should be revised as the negative effect of high education towards economic growth should be resulting in growing unemployment and graduates waiting to be employed rather than creating jobs themselves. Additionally, increasing job creation for graduates with higher qualifications would reduce the number of graduates that leave the country looking for employment abroad.

Labour, entrepreneurship, and technology are important components in the success of GDP Per capita, the existing workforce is not only fixated by numbers but also must be focused on quality to have a significant impact, in addition to the ability and desire of a nation to grow interested in becoming entrepreneurs. This research base on Solow and Swan's Theory said that economic growth was influenced by the growth of production factors such as population, labor, and capital accumulation, as well as the level of technological progress described in the development of knowledge. There is an element of technological progress in the Solow-Swan model which is the main differentiator from the Harrod-Domar growth model.  This study used 42 observers consisting of 7 ASEAN countries, namely; Singapore, Thailand, Malaysia, Indonesia, Philippines, Vietnam, and Cambodia, using multiple linear regression and using classical assumption test. The research method in this study uses multiple linear regression of panel data, using the classical assumption test. To get the best model, the data will be tested for Pool Effect, Fix Effect and Random Effects Models, while the determination of the best model is based on the results of the Chow and Hausman tests. The results are shown that labor does not have a significant influence on GDP Per Capita revenue, while the entrepreneurship Index (GEI) and Technology Index (GII) variables have a positive and significant impact on GDP Per Capita revenue. The workforce hasn't affected, which is broadly described in this study because the absorption of labor has not been optimal or the provision of jobs whose proportions are not balanced with the number of the workforce.

Education is generally considered to be the core source of individuals’ better life and countries' economic and social development. Consequently, attending university and getting high qualifications are perceived as tools that generate and enhance economic growth. The current study aimed to analyse the effect of various educational levels on South African economic growth. The study employed quarterly data from 1995Q1 to 2021Q4. The autoregressive distributed lag (ARDL) model was employed to assess both long-run and short-run relationships among variables. The long-run results revealed that people who completed their grade 12 (with matric certificate) and bachelor's degrees contribute positively to South African economic growth. However, honours and higher degrees (master's and PhD) were found to have an inverse relationship with economic growth in South Africa. On the other hand, the short-run relationship indicated that all education levels contribute to economic growth in the short term. Based on these findings, the author suggests that the South African higher education curriculum should be revised as the negative effect of high education towards economic growth should be resulting in growing unemployment and graduates waiting to be employed rather than creating jobs themselves. Additionally, increasing job creation for graduates with higher qualifications would reduce the number of graduates that leave the country looking for employment abroad.

Labour, entrepreneurship, and technology are important components in the success of GDP Per capita, the existing workforce is not only fixated by numbers but also must be focused on quality to have a significant impact, in addition to the ability and desire of a nation to grow interested in becoming entrepreneurs. This research base on Solow and Swan's Theory said that economic growth was influenced by the growth of production factors such as population, labor, and capital accumulation, as well as the level of technological progress described in the development of knowledge. There is an element of technological progress in the Solow-Swan model which is the main differentiator from the Harrod-Domar growth model.  This study used 42 observers consisting of 7 ASEAN countries, namely; Singapore, Thailand, Malaysia, Indonesia, Philippines, Vietnam, and Cambodia, using multiple linear regression and using classical assumption test. The research method in this study uses multiple linear regression of panel data, using the classical assumption test. To get the best model, the data will be tested for Pool Effect, Fix Effect and Random Effects Models, while the determination of the best model is based on the results of the Chow and Hausman tests. The results are shown that labor does not have a significant influence on GDP Per Capita revenue, while the entrepreneurship Index (GEI) and Technology Index (GII) variables have a positive and significant impact on GDP Per Capita revenue. The workforce hasn't affected, which is broadly described in this study because the absorption of labor has not been optimal or the provision of jobs whose proportions are not balanced with the number of the workforce.