This study examines the nexus between financial development and energy consumption/use in Sub-Saharan Africa (SSA) using a panel vector error correction model (VECM), cointegration, and Granger causality tests over the period ranging from 1975 to 2017. The annual panel time-series data generated from the World Bank database were tested for unit-roots processing using both the Levin–Lin–Chu and Im–Pesaran–Shin before proceeding to Johanson cointegration technique, the results of which motivated the choice of adopting the panel VECM rather than panel vector autoregression in the methodology. From the estimation result especially on the variables of interest, there exists a positive and statistically significant relationship between financial development and energy consumption in the long run, but not statistically significant in the short run. Further findings from the panel Granger causality test shows a unidirectional causality running from financial development to energy consumption, gross domestic product per capita, population growth to urbanization with no feedback. Among a series of policy recommendations, the monetary authorities in Sub-Saharan African countries should ensure optimal utilization of financial instruments and technologies available in the system to enhance more robust financial development to boost efficiency in energy consumption in the region in line with the sustainable growth theory.
This study investigates the effect of macroeconomic variables on income distribution in Africa using panel data from 2001 to 2016. This is motivated by the high degree of income inequality and poverty in the region. Twenty‐eight (28) African countries were selected to capture every region. The selection of countries and the choice of this period were informed by data availability. The variables of interest were income inequality obtained from the Standardized World Income Inequality Database (SWIID), while the Gross Domestic Product, Inflation, and Unemployment were obtained from the World Bank database. A dynamic panel model using the Generalized Method of Moment (GMM) estimator was used to control for both individual and time‐specific effects. The Heterogeneous aspect of the Augmented Dicky‐Fuller (ADF), the Levine‐Lin‐Chu test and, the Im‐Pesaran‐Shin (IPS) panel units root process were utilized to test for the stationarity of the panel data. The results of the General Method of Moment (GMM) indicate a significant negative relationship between income inequality and economic growth. The study rejected the existence of the Kuznets curve hypothesis, and concludes that Inflation rate, Wage rate and labour force impact negatively income inequality, while unemployment and education impact positively.
This study analyses population, urban agglomeration (UAG), and economic growths dynamics in Sub‐Saharan Africa (SSA) using the World Bank panel data ranging from 1970 to 2019. The study utilized a panel fixed effect (FE) model after verifying the suitability of the model using a Hausman test. The estimation result from the panel FE model reveals remarkable findings which conform to some extent, the theoretical a priori expectations. The result shows that growth in rural as well as urban population growth and total trade (TRD) have negative relationships with UAG. On the other hand, gross domestic product (GDP, a better proxy for income) and foreign direct investment (FDI) have a positive association with UAG in the economies of SSA thereby validating the existence of the Williamson–Kuznets hypothesis. Based on the findings, it is advised amongst other policy recommendations that the governments of the Sub‐Saharan African countries should pursue inward‐looking policies targeted toward encouraging the local processing of agricultural raw materials—possibly to finished products to boost foreign exchange earnings through trade in other to engender sustainability in both the economic growth and UAG in the region.
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