Philip Kofi Adom

Time‐Varying Analysis of Aggregate Electricity Demand in Ghana: A Rolling Analysis

Using the rolling regression technique, the study investigated how the effects of income, economic structure and industry efficiency on aggregate electricity demand vary with time. The Quandt–Andrews test was used to examine the presence or otherwise of structural breaks in the data set. The long‐run estimate of aggregate electricity demand based on fully modified ordinary least squares reveals that the variables carried their a priori expectations with the positive income effect playing the most significant role followed by industry efficiency with structural effect playing the least role. The result of the Quandt–Andrews test showed rejection of the null hypothesis of no structural breaks with the maximum statistic occurring in 1987, which is the most likely breakpoint location. The rolling regression result revealed evidence of constant shifting of poles of the estimated demand model. The plot of the evolution of demand elasticities showed variations over time with some evidence of strong linkages with periods of policy regime changes. Changing economic structure, improving energy efficiency and integrating electricity production, distribution and transmission into the overall macroeconomic planning will go a long way to stabilise the situation in the electricity market.

Urbanization, regime type and durability, and environmental degradation in Ghana

This study examines the effect of urbanization, income, trade openness, and institutional quality (i.e., regime type and durability) on environmental degradation in Ghana over the period 1965–2011. Using the bounds test approach to cointegration and the Fully Modified Phillip-Hansen (FMPH) technique, the findings show that urbanization, income, trade openness, and institutional quality have long-run cointegration with environmental degradation. Further, the results show that income, trade openness, and institutional quality are negatively associated with environmental degradation. This suggests that income, trade openness, and institutional quality enhance environmental performance. Urbanization, however, is positively related to environmental degradation. Additionally, long-run estimates conditioned on institutional quality reveal that the extent to which trade openness and urbanization enhance environmental performance is largely due to the presence of quality institutions (or democratic institutions). Finally, controlling for structural breaks, we find that trade openness, urbanization, and regime type (i.e., democracy) improve environmental performance significantly after the 1970s except for income.

Quality of institution and the FEG (forest, energy intensity, and globalization) -environment relationships in sub-Saharan Africa

The current share of sub-Saharan Africa in global carbon dioxide emissions is negligible compared to major contributors like Asia, Americas, and Europe. This trend is, however, likely to change given that both economic growth and rate of urbanization in the region are projected to be robust in the future. The current study contributes to the literature by examining both the direct and the indirect impacts of quality of institution on the environment. Specifically, we investigate whether the institutional setting in the region provides some sort of a complementary role in the environment-FEG relationships. We use the panel two-step system generalized method of moments (GMM) technique to deal with the simultaneity problem. Data consists of 43 sub-Saharan African countries. The result shows that energy inefficiency compromises environmental standards. However, the quality of the institutional setting helps moderate this negative consequences; countries with good institutions show greater prospects than countries with poor institutions. On the other hand, globalization of the region and increased forest size generate positive environmental outcomes in the region. Their impacts are, however, independent of the quality of institution. Afforestation programs, promotion of other clean energy types, and investment in energy efficiency, basic city infrastructure, and regulatory and institutional structures, are desirable policies to pursue to safeguard the environment.

The long-run impact of idiosyncratic and common shocks on industry output in Ghana

This study explores the long-run impact of idiosyncratic and common shocks on industry output in Ghana while controlling for the effects of investment. In order to deal with the second-order bias problem, this study employed canonical cointegration and fully modified ordinary least-squares (OLS) regressions, which are more robust to second-order bias problems. Different models are, therefore, specified and estimated. Fully modified OLS and canonical cointegration are extended in successive steps in order to verify if the inclusion of idiosyncratic and common shocks improves the statistical properties of the model. Secondly, a backward approach, in which idiosyncratic and common shocks are excluded successively, is also adopted. Preliminary findings showed signs of long-run equilibrium. The a priori expectation and the statistical importance of investment are established in both fully modified OLS and canonical cointegration models. This result is robust using both the Bartlett and Parzen kernels. However, while the elasticity value for investment is invariant to the model and kernel type used for fully modified OLS, the opposite result is found for canonical cointegration. Importantly, the absolute value of the investment elasticity is kept within the limits of 0 and 1. The impacts of idiosyncratic and common shocks are negative and statistically significant in the long run for both fully-modified OLS and canonical cointegration. This result is robust to the Bartlett and Parzen kernels. Result based on the fully modified OLS also showed that the sizes of the elasticity values for both idiosyncratic and common shocks are sensitive to the model type and kernel type used. Despite the differences in the elasticity values, result for both models are qualitatively similar.