Analysis of Investment in Energy: A Case of Electricity in Ghana

Abstract

This thesis analysed investments in electricity generation by employing a combination of Autoregressive Distributed Lag (ARDL) technique Mean Variance Portfolio (MVP) analysis. With annual time series data on Ghana from 1970 to 2009, the study used the ARDL technique to analyse investment, cost and demand equations. First, the investment equation examined the relationship between investment in electricity generation, interest rate, output, price, and demand uncertainty. Second, the cost equation investigated the effect of output, interest rate, wage rate, and capacity utilisation on cost of electricity generation. Third, the demand equation focused on the impact of price of electricity, price of light crude oil, income, population, and consumption efficiency on demand for electricity. Finally, the thesis used the MVP analysis to evaluate the cost risk of Ghana5s projected electricity generation mix fbr 2015. The results showed that investment in electricity generation depends on interest rate, output, price, and demand uncertainty. Besides, the results demonstrated that output, interest rate and capacity utilisation significantly affect the cost of electricity generation. Again, the study confirmed that price of electricity, income, population and consumption efficiency have a significant effect on demand for electricity. Finally, the thesis established that increase in the share of renewable energy reduces the cost risk of electricity generation mix. The results implied that increase in electricity price can increase investments in electricity generation in Ghana.