Determinants of electricity consumption in South Africa: Insights from linear and nonlinear modeling approaches
Article Sidebar
Main Article Content
Abstract
Purpose: This study investigates the determinants of electricity consumption in South Africa, focusing on economic, demographic, and energy-related factors from 1980 to 2023.
Methodology: The study employs linear models (Dynamic Ordinary Least Squares and Canonical Cointegrating Regression) and a nonlinear Threshold Autoregressive (TAR) model to analyze the relationships between electricity consumption and its determinants.
Results: Economic growth, electricity prices, and income per capita are found to be positive determinants of electricity consumption, while population growth and inflation exhibit negative relationships. The TAR model reveals asymmetric effects of these determinants across different income regimes.
Theoretical contribution: This study extends the literature on electricity consumption determinants in developing countries by incorporating both linear and nonlinear modeling approaches, providing a more comprehensive understanding of the complex relationships involved.
Practical implications: The findings inform policymakers and energy stakeholders in South Africa on effective strategies for managing electricity demand, promoting energy efficiency, and addressing the ongoing challenges in the electricity sector.
Sustainable Development Goals (SDGs): SDG 7: Affordable and Clean Energy; SDG 9: Industry, Innovation and Infrastructure
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work (article) is licensed under a Creative Commons Attribution 4.0 International License.
References
Adom, P. K. (2015). Determinants of energy intensity in South Africa: Testing for structural effects in parameters. Energy, 89, 334–346. https://doi.org/10.1016/j.energy.2015.05.125
Al-Bajjali, S. K., & Shamayleh, A. Y. (2018). Estimating the determinants of electricity consumption in Jordan. Energy, 147, 1311–1320. https://doi.org/10.1016/j.energy.2018.01.010
Ali, S. S. S., Razman, M. R., Awang, A., Asyraf, M. R. M., Ishak, M. R., Ilyas, R. A., & Lawrence, R. J. (2021). Critical determinants of household electricity consumption in a rapidly growing city. Sustainability, 13(8), 4441. https://doi.org/10.3390/su13084441
Ateba, B. B., Prinsloo, J. J., & Gawlik, R. (2019). The significance of electricity supply sustainability to industrial growth in South Africa. Energy Reports, 5, 1324–1338. https://doi.org/10.1016/j.egyr.2019.09.041
Azam, M., Khan, A. Q., Zafeiriou, E., & Arabatzis, G. (2016). Socioeconomic determinants of energy consumption: An empirical survey for Greece. Renewable and Sustainable Energy Reviews, 57, 1556–1567. https://doi.org/10.1016/j.rser.2015.12.082
Baker, L., & Phillips, J. (2019). Tensions in the transition: The politics of electricity distribution in South Africa. Environment and Planning C: Politics and Space, 37(1), 177–196. https://doi.org/10.1177/2399654418778590
Bohlmann, J. A., & Inglesi-Lotz, R. (2021). Examining the determinants of electricity demand by South African households per income level. Energy Policy, 148, 111901. https://doi.org/10.1016/j.enpol.2020.111901
Bowman, A. (2020). Parastatals and economic transformation in South Africa: The political economy of the Eskom crisis. African Affairs, 119(476), 395–431. https://doi.org/10.1093/afraf/adaa013
Brock, W. A., Dechert, W., & Scheinkman, J. (1987). A test for independence based on the correlation dimension. Working paper, University of Wisconsin at Madison, University of Houston, and University of Chicago.
Chen, M., Ban-Weiss, G. A., & Sanders, K. T. (2018). The role of household level electricity data in improving estimates of the impacts of climate on building electricity use. Energy and Buildings, 180, 146–158. https://doi.org/10.1016/j.enbuild.2018.09.012
Choi, I., Park, J. Y., & Yu, B. (1997). Canonical cointegrating regression and testing for cointegration in the presence of I(1) and I(2) variables. Econometric Theory, 13(6), 850–876. https://doi.org/10.1017/S0266466600006290
Cobb, C. W., & Douglas, P. H. (1928). A theory of production. American Economic Review, 18, 139–165.
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/1912517
Dokas, I., Panagiotidis, M., Papadamou, S., & Spyromitros, E. (2022). The determinants of energy and electricity consumption in developed and developing countries: International evidence. Energies, 15(7), 2558. https://doi.org/10.3390/en15072558
du Venage, G. (2020). South Africa comes to standstill with Eskom's load shedding. Engineering and Mining Journal, 221(1), 18.
Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236
Erero, J. L. (2023). Impact of loadshedding in South Africa: A CGE analysis. Journal of Economics and Political Economy, 10(2), 78–94.
Ezesele, S. L. (2017). Dynamic relationships between sectoral electricity consumption, economic growth and electricity prices in South Africa (Doctoral dissertation, University of Zululand).
Gasealahwe, B. (2020). Relationship between electricity prices, consumption and economic growth in South Africa.
Gehringer, C., Rode, H., & Schomaker, M. (2018). The effect of electrical load shedding on pediatric hospital admissions in South Africa. Epidemiology, 29(6), 841–847. https://doi.org/10.1097/EDE.0000000000000905
Gregory, J. (2020). Governance, scale, scope: A review of six South African electricity generation infrastructure megaprojects. Utilities Policy, 66, 101103. https://doi.org/10.1016/j.jup.2020.101103
Hasanov, F. J., & Mikayilov, J. I. (2020). Revisiting energy demand relationship: Theory and empirical application. Sustainability, 12(7), 2919. https://doi.org/10.3390/su12072919
Hlongwane, N. W., & Daw, O. D. (2022). The challenges and opportunities of electricity generation on economic growth in South Africa: An ARDL approach. International Journal of Energy Economics and Policy, 12(2), 164–174. https://doi.org/10.32479/ijeep.12541
Huang, W. H. (2015). The determinants of household electricity consumption in Taiwan: Evidence from quantile regression. Energy, 87, 120–133. https://doi.org/10.1016/j.energy.2015.04.101
Inglesi-Lotz, R., & Pouris, A. (2016). On the causality and determinants of energy and electricity demand in South Africa: A review. Energy Sources, Part B: Economics, Planning, and Policy, 11(7), 626–636. https://doi.org/10.1080/15567249.2013.801536
Ismail, M. T., Mahmud, N., & Rahman, R. A. (2017). The determinants of electricity consumption for ASEAN countries. Malaysian Journal of Fundamental and Applied Sciences, 13(3), 331–339. https://doi.org/10.11113/mjfas.v13n4-1.877
Ismail, Z., & Khembo, P. (2015). Determinants of energy poverty in South Africa. Journal of Energy in Southern Africa, 26(3), 66–78. https://doi.org/10.17159/2413-3051/2015/v26i3a2130
Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2–3), 231–254. https://doi.org/10.1016/0165-1889(88)90041-3
Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551–1580. https://doi.org/10.2307/2938278
Johansen, S. (1995). A statistical analysis of cointegration for I(2) variables. Econometric Theory, 11(1), 25–59. https://doi.org/10.1017/S0266466600009026
Johansen, S. (2002). A small sample correction for the test of cointegrating rank in the vector autoregressive model. Econometrica, 70(5), 1929–1961. https://doi.org/10.1111/1468-0262.00358
Johansen, S. (2009). Cointegration: Overview and development. In T. G. Andersen, R. A. Davis, J.-P. Kreiss, & T. Mikosch (Eds.), Handbook of financial time series (pp. 671–693). Springer. https://doi.org/10.1007/978-3-540-71297-8_29
Kapstein, H. (2023). Power Failures: The Public Poetics of Eskom and Energy. ISLE: Interdisciplinary Studies in Literature and Environment, isad044. https://doi.org/10.1093/isle/isad044
Khobai, H., Mugano, G., & Le Roux, P. (2017). The impact of electricity price on economic growth in South Africa. International Journal of Energy Economics and Policy, 7(1), 108–116.
Kostakis, I. (2020). Socio-demographic determinants of household electricity consumption: Evidence from Greece using quantile regression analysis. Current Research in Environmental Sustainability, 1, 23–30. https://doi.org/10.1016/j.crsust.2020.04.001
Kotsila, D., & Polychronidou, P. (2021). Determinants of household electricity consumption in Greece: A statistical analysis. Journal of Innovation and Entrepreneurship, 10, 1–20. https://doi.org/10.1186/s13731-021-00161-9
Kwakwa, P. A., & Adusah-Poku, F. (2019). Determinants of electricity consumption and energy intensity in South Africa. Green Finance, 1(4), 387–404. https://doi.org/10.3934/GF.2019.4.387
Kwakwa, P. A. (2018). An analysis of the determinants of electricity consumption in Benin. Journal of Energy Management and Technology, 2(3), 42–59. https://doi.org/10.1111/opec.12105
Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of Econometrics, 54(1–3), 159–178. https://doi.org/10.1016/0304-4076(92)90104-Y
Lenoke, M. (2017). The impact of load shedding on the economic growth of South Africa (Doctoral dissertation, North-West University (South Africa)).
Louw, K., Conradie, B., Howells, M., & Dekenah, M. (2008). Determinants of electricity demand for newly electrified low-income African households. Energy Policy, 36(8), 2812–2818. https://doi.org/10.1016/j.enpol.2008.02.032
Marope, A., & Phiri, A. (2024). Does loadshedding affect the housing market in South Africa? Some empirical evidence. International Journal of Housing Markets and Analysis, 17(3), 859–874. https://doi.org/10.1108/IJHMA-10-2022-0148
Masih, R., & Masih, A. M. (1996). Stock-Watson dynamic OLS (DOLS) and error-correction modelling approaches to estimating long-and short-run elasticities in a demand function: New evidence and methodological implications from an application to the demand for coal in mainland China. Energy Economics, 18(4), 315–334. https://doi.org/10.1016/S0140-9883(96)00016-3
Medlock, K. B. (2009). Energy demand theory. In International handbook on the economics of energy. Edward Elgar Publishing. https://doi.org/10.4337/9781849801997.00010
Monyei, C. G., Oyedele, L. O., Akinade, O. O., Ajayi, A. O., & Luo, X. J. (2019). Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south. Energy Research & Social Science, 54, 113–116. https://doi.org/10.1016/j.erss.2019.04.005
Naidoo, C. (2023). The impact of load shedding on the South Africa economy. Journal of Public Administration, 58(1), 7–16.
Najeeb, A., Sridharan, S., Rao, A. B., Agnihotri, S. B., & Mishra, V. (2024). Determinants of residential electricity consumption in South, East and South East Asia: A systematic review. Renewable and Sustainable Energy Reviews, 198, 114400. https://doi.org/10.1016/j.rser.2024.114400
Ofetotse, E. L., Essah, E. A., & Yao, R. (2021). Evaluating the determinants of household electricity consumption using cluster analysis. Journal of Building Engineering, 43, 102487. https://doi.org/10.1016/j.jobe.2021.102487
Onisanwa, I. D., & Adaji, M. O. (2020). Electricity consumption and its determinants in Nigeria. Journal of Economics and Management, 41(3), 87–104. https://doi.org/10.22367/jem.2020.41.05
Park, J. Y. (1992). Canonical cointegrating regressions. Econometrica, 60(1), 119–143. https://doi.org/10.2307/2951679
Roy-Aikins, J. (2016, June). Challenges in meeting the electricity needs of South Africa. In ASME Power Conference (Vol. 50213, p. V001T05A002). American Society of Mechanical Engineers. https://doi.org/10.1115/POWER2016-59085
Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. https://doi.org/10.1093/biomet/71.3.599
Sakah, M., du Can, S. D. L. R., Diawuo, F. A., Sedzro, M. D., & Kuhn, C. (2019). A study of appliance ownership and electricity consumption determinants in urban Ghanaian households. Sustainable Cities and Society, 44, 559–581. https://doi.org/10.1016/j.scs.2018.10.019
Sehlapelo, T., & Inglesi‐Lotz, R. (2022). Examining the determinants of electricity consumption in the nine South African provinces: A panel data application. Energy Science & Engineering, 10(7), 2487–2496. https://doi.org/10.1002/ese3.1151
Sena, B., Zaki, S. A., Rijal, H. B., Ardila-Rey, J. A., Yusoff, N. M., Yakub, F., Ridwan, M. K., & Muhammad-Sukki, F. (2021). Determinant factors of electricity consumption for a Malaysian household based on a field survey. Sustainability, 13(2), 818. https://doi.org/10.3390/su13020818
Sharma, R., & Kautish, P. (2019). Dynamism between selected macroeconomic determinants and electricity consumption in India: An NARDL approach. International Journal of Social Economics, 46(6), 805–821. https://doi.org/10.1108/IJSE-11-2018-0586
Stock, J. H., & Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica, 61(4), 783–820. https://doi.org/10.2307/2951763
Todd, I., & McCauley, D. (2021). Assessing policy barriers to the energy transition in South Africa. Energy Policy, 158, 112529. https://doi.org/10.1016/j.enpol.2021.112529
Tong, H., & Lim, K. S. (1980). Threshold autoregression, limit cycles and cyclical data. Journal of the Royal Statistical Society: Series B (Methodological), 42(3), 245–268. https://doi.org/10.1111/j.2517-6161.1980.tb01126.x
Wahid, F., Ullah, H., Ali, S., Jan, S. A., Ali, A., Khan, A., Khan, I. A., & Bibi, M. (2021). The determinants and forecasting of electricity consumption in Pakistan. International Journal of Energy Economics and Policy, 11(1), 241–248. https://doi.org/10.32479/ijeep.10646
Walsh, K., Theron, R., & Reeders, C. (2021). Estimating the economic cost of load shedding in South Africa. In Paper submission to Biennial Conference of the Economic Society of South Africa (ESSA) (Vol. 22).
Wassie, Y. T., & Ahlgren, E. O. (2023). Determinants of electricity consumption from decentralized solar PV mini-grids in rural East Africa: An econometric analysis. Energy, 274, 127351. https://doi.org/10.1016/j.energy.2023.127351
Wiese, M., & van der Westhuizen, L. M. (2024). Impact of planned power outages (load shedding) on consumers in developing countries: Evidence from South Africa. Energy Policy, 187, 114033. https://doi.org/10.1016/j.enpol.2024.114033
Wright, J. G., Bischof-Niemz, T., Calitz, J. R., Mushwana, C., & Van Heerden, R. (2019). Long-term electricity sector expansion planning: A unique opportunity for a least cost energy transition in South Africa. Renewable Energy Focus, 30, 21–45. https://doi.org/10.1016/j.ref.2019.02.005
Ye, Y., Koch, S. F., & Zhang, J. (2018). Determinants of household electricity consumption in South Africa. Energy Economics, 75, 120–133. https://doi.org/10.1016/j.eneco.2018.08.005
Zaman, M., Shaheen, F., Haider, A., & Qamar, S. (2015). Examining relationship between electricity consumption and its major determinants in Pakistan. International Journal of Energy Economics and Policy, 5(4), 998–1009.
Zou, B., & Luo, B. (2019). Rural household energy consumption characteristics and determinants in China. Energy, 182, 814–823. https://doi.org/10.1016/j.energy.2019.06.048