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Regression Modelling of Electricity Distribution Statistics and Stock Exchange Market Capitalisation in a Developing Country: Evidence from Botswana (2012-2021)

DOI: 10.4236/oalib.1110366, PP. 1-24

Keywords: Stock Market Capitalisation, Electricity Distribution, Regression

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The stock exchange and its performance are important indicators of the economic health of an economy. Electricity generation capacity supports industrialisation. National electricity distribution on the other hand, however, even when mediated with electricity imports to augment a low generation capacity, can complicate both manufacturing and non-manufacturing companies’ desire to operate in an economy which is attempting to industrialise. This is compounded if generation is not matched to consumption patterns, electricity demand and is supported by a robust and efficient network facility that monitors the grid and balances generation, distribution, and demand while minimising leakages through unauthorised connections. The research aims to ascertain the relationship between electricity distribution and stock market performance in a developing country over a ten-year period (2012-2021). Stock market performance is measured using overall stock market capitalisation. The relationship between Botswana’s electricity distribution against the country’s stock market performance has not been studied and modelled prior. The data used for the regression modelling of electricity distribution was obtained from the official national statistics parastatal, Statistics Botswana. The data in quarters of a year, as mega-watt hours (MWH) per year from 2012 to 2021 was employed in this research. Natural logarithms, which do not inherently minimise the effects of skewness in a dataset, were used to minimise the effects of skewed distributions and heteroscedasticity of the data in this period. Similarly, natural logarithms were applied to quarterly Pula (millions) value total stock market capitalisation from the Botswana Stock Exchange (BSE) annual reports over the same period. The findings indicate that although electricity distribution is negatively correlated to stock market performance as measured by total market capitalisation, electricity generation can predict stock market performance to within a less than 6% variance level between predicted and actual quarterly measures of total stock market capitalisation. In the context of Botswana, a country classified as upper-middle income, but is still dependent on diamond mining, the limited job creation in the economy could be addressed by investigating the link between electricity distribution and stock market capitalisation in the wider efforts to industrialise and diversify the economy by attracting listed companies. The implication of the regression model developed from the findings and prediction of stock market performance through total market capitalisation is that, the power utility and government should manage electricity distribution with care and foresight so as to positively impact stock market performance as electricity distribution is a good macro-indicator of economic health and could be a crucial factor that multinationals (MNCs) looking to invest in Botswana would consider.


[1]  Vumbunu, T., Viviers, P.-A. and Du Plessis, E. (2022) Trends and Development of Tourism Product Diversification in Botswana: Lessons Learned. Journal of Environmental Management and Tourism, 13, 1016-1035.
[2]  Schiliro, D. (2022) Botswana’s Economy and the Question of Diversification. Munich Personal RePEc Archive (MPRA), MPRA Paper No. 115608.
[3]  African Development Bank Group (2022) Bank Group Country Strategy Paper 2022-26-Republic of Botswana. Revised Version, RDGS/ECCE (March 2022). 1-22.
[4]  Welsh, A. (1987) The Trimmed Mean in the Linear Model. The Annals of Statistics, 15, 20-36.
[5]  Najdi, N.F.N. and Ahad, N.A. (2019) Modification of ANOVA with Trimmed Mean. Malaysian Journal of Social Sciences and Humanities (MJSSH), 4, 109-118.
[6]  International Renewable Energy Agency (IRENA) (2021) Renewables Readiness Assessment Botswana. 1-94.
[7]  Statistics Botswana (2014-2022) Electricity Generation and Distribution, Stats Brief. Fourth Quarter 2022.
[8]  Botswana Stock Exchange (2012-2022) Annual Reports.
[9]  Tetteh, J.E., Amoah, A., Ofori-Boateng, K. and Hughes, G. (2022) Stock Market Response to COVID-19 Pandemic: A Comparative Evidence from Two Emerging Economies. Scientific Africa, 17, e01300.
[10]  Williamson, D.F., Parker, R.A. and Kendrick, J.S. (1989) The Box Plot: A Simple Visual Method to Interpret Data. Annals of Internal Medicine, 110, 916-921.
[11]  Castro, G.M., Klöckl, C., Regner P., Schmidt, J. and Pereira Jr., A.O. (2022) Improvements to Modern Portfolio Theory Based Models Applied to Electricity Systems. Energy Economics, 111, Article ID: 106047.
[12]  Lerede, D. and Savoldi, L. (2023) Might Future Electricity Generation Suffice to Meet the Global Demand? Energy Strategy Reviews, 47, Article ID: 101010.
[13]  Kumar, S.V., Prasad, J. and Samikannu, R. (2018) Barriers to Implementation of Smart Grids and Virtual Power Plant in Sub-Saharan Region—Focus Botswana. Energy Reports, 2, 119-128.
[14]  Turhan, B. and Dogan, N. (2021) Electricity Prices and Stock Market Performance: Evidence from Borsa Istanbul. Journal of Sustainable Economics and Management Studies, 2, 41-55.
[15]  Brown, S.P.A. and Yücel, M.K. (2002) Energy Prices and Aggregate Economic Activity: An Interpretative Survey. The Quarterly Review of Economics and Finance, 42, 193-208.
[16]  Kuvshinov, D. and Zimmermann, K. (2021) The Big Bang: Stock Market Capitalization in the Long Run. Journal of Financial Economics, 145, 527-552.
[17]  Souto, H.G. (2023) Time Series Forecasting Models for S&P 500 Financial Turbulence. Journal of Mathematical Finance, 13, 112-129.
[18]  Cong, R.-G. and Shen, S. (2013) Relationships among Energy Price Shocks, Stock Market, and the Macroeconomy: Evidence from China. The Scientific World Journal, 2013, Article ID: 171868.
[19]  Gaol, Y.L. and Faturohman (2016) Relationship between Crude Price and Indonesia Stock Market. Journal of Business and Management, 5, 510-517.
[20]  Kesikoglu, F. and Yildirim, E. (2014) The Causal Effect of Shifting Oil to Natural Gas Consumption on Current Account Balance and Economic Growth in 11 OECD Countries: Evidence from Bootstrap-Corrected Panel Causality Test. Procedia— Social and Behavioral Sciences, 143, 1064-1069.
[21]  Uri, N.D. and Boyd, R. (1997) An Evaluation of the Economic Effects of Higher Energy Prices in Mexico. Energy Policy, 25, 205-215.
[22]  Afful-Dadzie, A., Mensah, S.K. and Afful-Dadzie, E. (2022) Ghana Renewable Energy Master Plan: The Benefits of Private Sector Participation. Scientific African, 17, e01353.
[23]  Mwinaayelle, S.D.-U. (2023) Budget Deficits and Stock Market Performance in Emerging and Frontier Markets in Africa. Open Access Library Journal, 10, e9602.
[24]  Gurgen, E. and Norsworthy, J.R. (2001) Efficiency and Stock Market Performance in Electric Power Generating Companies. IEMC’01 Proceedings. Change Management and the New Industrial Revolution, Albany, 7-9 October 2001, 412-420.
[25]  Arshad, S. and Beyer, R.C.M. (2023) Tracking Economic Fluctuations with Electricity Consumption in Bangladesh. Energy Economics, 2023, Article ID: 106740.
[26]  Essah, E.A. and Ofetotse, L. (2014) Energy Supply, Consumption and Access Dynamics in Botswana. Sustainable Cities and Society, 12, 76-84.
[27]  Meloun, M. and Militky, J. (2011) The Exploratory and Confirmatory Analysis of Univariate Data. In: Meloun, M. and Militky, J., Eds., Statistical Data Analysis, Woodhead Publishing India, New Delhi, 25-71.
[28]  Dewan, I. and Kochar, S. (2013) Some New Applications of P-P Plots. Probability in the Engineering and Informational Sciences, 27, 353-366.
[29]  Yang, K., Tu, J. and Chen, T. (2019) Homoscedasticity: An Overlooked Critical Assumption for Linear Regression. General Psychiatry, 32, e100148.
[30]  Olatunde, P.S., Philiphs, I.M., Juliano, A.Y. and Imhansoeleva, T.M. (2015) Geochemical and Statistical Approach to Assessing Trace Metal Accumulations in Lagos Lagoon Sediments, South Western, Nigeria. Journal of Geography, Environment and Earth Science International, 3, JGEESI.20333.
[31]  Champion, R., Lenard, C.T. and Mills, T.M. (1998) Demonstrating the Durbin Watson Statistic. Journal of the Royal Statistical Society, Series D (The Statistician), 47, 643-644.
[32]  Potocnik, K., Verwaeren, B. and Nijstad, B. (2022) Tensions and Paradoxes in Creativity and Innovation. Journal of Work and Organisational Psychology, 38, 149-163.
[33]  Elsayed, E. (2012) Mean Absolute Deviation about Median as a Tool of Explanatory Data Analysis. International Journal of Research and Reviews in Applied Sciences, 11, 517-523.


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