Access to reliable energy that is especially modern and affordable, is a prerequisite for economic growth and improved quality of life. Accordingly, energy is an essential input for economic activity and human well-being. Estimates for technological advances in energy systems show that less than 30 percent of the population in sub Saharan Africa has access to affordable, reliable and modern forms of energy compared to 65 percent in South Asia and at least 90 percent in East Asia. Additionally, only 24.7 percent of the households in the southern most region of sub Saharan Africa have access to electricity, with biomass remaining the primary energy source. Focusing primarily on the Southern African region, this study used the time series analysis to investigate the causal relationship between energy consumption and economic growth in selected countries between 1980 and 2016. Regression analysis was used to establish the nature of the relationship between the variables. Lastly, the study predicted a 5-year energy consumption and economic growth using forecast models in Microsoft Excel. Variables were tested for statistical significance using granger causality tests. Results showed that there was a causality relationship between the two variables for Botswana and Zimbabwe. South Africa did not show any significance for analysis following the Granger causality test. Zimbabwe showed a very weak and negative linear relationship between energy consumption and economic growth. Overall, the results revealed that, in the short run, there was a bidirectional causality relationship between GDP per capita and electric power consumption per capita, and in the long run a unidirectional relationship running from GDP per capita to electric power consumption per capita. The overall findings of the study show that there is a corresponding relationship between energy consumption and economic growth. Therefore, improvements in energy generation are important for the economic development of SADC countries. Future studies may need to employ cointegration analyses to identify the degree to which variables are sensitive to the same average price over a specific period of time.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/30389 |
| Date | 31 July 2019 |
| Creators | Magombedze, Simbarashe |
| Contributors | Shumba, Dorcas |
| Publisher | Faculty of Commerce, Graduate School of Business (GSB) |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MComm |
| Format | application/pdf |
Page generated in 0.0091 seconds