Thesis( M.Com. (Economics)) -- University of Limpopo, 2019 / The concepts of economic growth and unemployment are at the beginning of the most important variables in the sense that all economies are choosing and implementing economic policies. The study examined the relationship between economic growth and unemployment in South Africa during 2005 to 2016 using the quarterly time series data. Cointegration test, Vector Error Correction Model (VECM) and granger causality test were employed in the analysis. The variables utilized in the investigation include the gross domestic product (LGDP), unemployment rate (UN), labour productivity (LP) and government budget deficit (GD). Stationarity test was conducted and the results indicated that all the variables were found stationary at first difference. Johansen Cointegration test confirmed that the long run relationship exist among variables under the study. More so, the VECM results showed that unemployment (UN) has a negative and insignificant impact on the gross domestic product (LGDP). Finally, the study also tested the granger causality between the variables to determine the short run relationship. Based on the findings above, the study therefore recommends that the government needs to cut taxes for businesses and individuals to increase investment spending to stimulate economic growth. Moreover, government should as a matter of urgency create more employment opportunities to absorb the teeming population of the unemployed labour force in the country through modernization of the agricultural sector, bring in modern equipment in the facilities of agriculture to make the sector more attractive to all citizens despite one’s qualifications and professions, as that alone would go a long way in reducing unemployment level in the country.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ul/oai:ulspace.ul.ac.za:10386/3339 |
| Date | January 2019 |
| Creators | Mashamaite, Precious, Mapheyaha |
| Contributors | lloray, R., Zhanje, S. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ix,125 leaves |
| Relation |
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