Energy generation has received a little or no attention over a period of time. Most scholars are focused on energy consumption and economic growth. This study empirically examined the asymmetric impact of energy generation on aggregate output in Nigeria between 1980 and 2019 using Nonlinear Autoregressive Distributed Lag (NARDL) Model. The stationarity test was conducted on the variables employed to avoid spurious regression. The result revealed that the variables were mixed at level and the first difference. The bound test result revealed that the variables are not cointegrated in the long run. Also, Wald test indicates that energy generation has short run impact on aggregate output in Nigeria. As revealed from the empirical results, from all sources of significant energy generation in Nigeria, gas generation brings the desired result to aggregate output in Nigeria. The study therefore suggests that action should refocus on the gas production subsector. This subsector needs to be developed carefully to avoid wasting this energy source by incineration. Also, the government should redirect those subsidies for petroleum products to the gas generation subsector.
This study empirically examined the energy access andhousehold income in Sub-Saharan African countries between1990 and 2015. The study employed five variables:energy access, per capita income, energy price, FDI andtrade openness, as well as panel unit root test using twocriteria to test stationarity. Panel cointegration test wasalso conducted to test long-run cointegration between thevariables employed. Panel granger causality test was employedto check the degree of causality between the dependentand explanatory variables and Auto RegressiveDistributive Lag method of estimation was employed tocheck the long-run and short-run relationships between thevariables. The results of the panel unit root test from theLLC and IPS methods show that the order of integrationsis mixed with some of the variables being stationary atlevels (household income, Foreign Direct Investment andTrade Openness) and first difference (Energy Access andFuel Price) at the same time. The result of Pedroni cointegrationtest indicated the bivariate long-run cointegrationequation between the variables employed except forEA and GDPPC. The panel granger causality test revealedthat there is causality between these three variables (EA,GDPPC and FUELP) and the direction of causality onlyflows from these variables to energy access. The ARDLresult revealed that all explanatory variables accountedfor 60% variation of energy access in SSA. However,the study made the following policy implications: energypolicy needs to be orientated in favor of expanding thesupply of energy to reach an enhanced degree of sustainableeconomic growth and development, and governmentsin this region can subsidize energy products to increaseits consumption and promote the welfare of their citizens.
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