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Financial depth and electricity consumption in Africa: Does education matter?

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Abstract

This article estimates the effect of financial development on electricity consumption for economies with above and below mean human capital index in 45 African countries. The study applied the simultaneous system GMM estimator (adjusted for cross-sectional dependence) and the Aiken and West slope difference test. We performed further robustness checks, such as sample sensitivity analysis to address potential outlier problem. The result showed that the total effect of financial development on electricity consumption is negative, but the direct and indirect effects are different. While, directly, financial development increases electricity consumption, indirectly (via education), it reduces electricity consumption. The Aiken and West slope difference test revealed that the reduction in electricity consumption is twice bigger (in standard deviation terms) in economies with an above mean human capital than in economies with a below mean human capital. In maximum and minimum value terms, it is about seven times bigger for economies with maximum human capital than those with minimum human capital are. The computed country-specific conditional mean marginal effect estimates of financial development revealed significant heterogeneities between economies with well-developed and less-developed human capital. These results suggest that the level of education drives the technical effects associated with financial development, which leads to a reduction in electricity consumption. By implication, advancing the SDG4 goal in Africa is critical to achieving the SDG7 goal.

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Fig. 1

Source: Author’s own construction

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Notes

  1. Africa has made some significant progress in the financial sector in the past two decades. For example, sub-Saharan Africa’s median ratio of private sector credit as per cent of gross domestic product doubled from its 1995 level to about 21% in 2014. The banking sector asset also averaged at 57% (scaled in gross domestic product) at the end of 2014 (International Monetary Fund 2016). The composite index for financial development developed by Sahay et al. (2015) also reveals that the region has made meaningful progress in financial development.

  2. In Africa, lack of finance, among other things, is a major constraint to improving energy efficiency (Lyakurwa and Mkuna 2018; Katrina 2015).

  3. This study performed a correlation analysis on the independent variables. We found significant correlation among the indicators of financial development and in some cases between human capital index and some indicators of financial development. The rest of the variables did not show significant correlation, deemphasising the importance of multicollinearity. In the case of the high correlation among the indicators of financial development, we solved this problem by using these indicators independently in the regression. Later, in this study, we applied the principal component analysis to derive a composite index for financial development.

  4. Angola, Cameroon, Central Africa Republic, Chad, Democratic Republic of Congo, Gabon, Sao, Tome and Principe, Burundi, Comoros, Kenya, Madagascar, Malawi, Mauritius, Mozambique, Rwanda, Seychelles, Tanzania, Uganda, Zambia, Algeria, Egypt, Morocco, Sudan, Tunisia, Benin, Burkina Faso, Cape Verde, Cote d’lvoire, Gambia, Ghana, Equatorial Guinea, Guinea, Guinea Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, Togo, Botswana, Lesotho, Namibia, South Africa, and Eswatini.

  5. We used the Hadri LM unit root test that has stationarity of the series as the null against the alternative that there is unit root. For all the variables, the result showed that all series contain unit root at level. Except for income, population density and price, differencing the variables once results in stationarity of the series. Because second differencing do not really make economic sense, we stick to the results of the H-T unit root test. The results of the Hadri LM can be made available by the author upon request.

  6. We do not report the Hansen J-statistics since, in Stata, xtdpdsys code do not support it as a post-estimation command. We applied the xtabond2, which reports both the Sargan and Hansen instrument validity test. Although, we confirmed the validity of instruments, the instrument counts in this case were more than double the instrument used in the simultaneous system GMM.

  7. Estimated based on the uncorrected system GMM for cross-sectional dependence.

  8. Figures using the other indicators of financial development provided consistent results. Albeit, the mean conditional effect of financial development seems positive for some countries, generally, the effect is negative for most of the economies, with evidence of heterogeneities.

  9. In addition, we estimated the augment mean group model, which deals with cross-sectional dependence problem. While the results remain consistent, the statistical significance of the model parameters is weak. Interested readers can consult the author for the results obtained based on the augment mean group estimator.

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Acknowledgements

This manuscript has benefited from the useful comments of an anonymous reviewer. The author acknowledges comments received from participants of the seminar series of School of Research and Graduate Studies (SRGS) of the Ghana Institute of Management and Public Administration (GIMPA). This article also benefited from the useful comments from anonymous three reviewers from the 4th Annual APEEN Conference 2019, Energy Demand-Side Management and Electricity Markets, University of Beira Interior-Covilha, Portugal. Lastly, the author wishes to thank Sustainable Energy Transitions Initiative (SETI), DUKE University, USA, and Environment for Development (EfD), University of Gothenburg, Sweden, for their support.

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  1. Department of Development Policy, School of Public Service and Governance, Ghana Institute of Management and Public Administration, Accra, Ghana

    Philip Kofi Adom

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Adom, P.K. Financial depth and electricity consumption in Africa: Does education matter?. Empir Econ 61, 1985–2039 (2021). https://doi.org/10.1007/s00181-020-01924-1

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