Quality performance gaps and minimal electricity losses in East Africa

East Africa; Electricity losses; Quality performance gap; Business and International Management; Transportation; Sociology and Political Science; Economics and Econometrics; Economics, Econometrics and Finance (miscellaneous); Energy (all); Economics, Econometrics and Finance (all); Law; General Economics, Econometrics and Finance; General Energy

Abstract :

[en] The electricity sector in East Africa is characterized by high levels of electricity losses. The literature has extensively focused on investments and policy reforms that can potentially reduce losses. In this paper, we follow another approach by nonparametrically estimating the minimal losses given the actual inputs, outputs and electricity generation process. Minimal losses are then compared to actual losses to construct quality performance indicators. Using a tailored database for six East African countries over 10 years, we show that electricity losses could be reduced by 8%, representing savings of approximately $60 million per year.

Disciplines :

Microeconomics

Author, co-author :

Gautier, Axel ; Université de Liège - ULiège > HEC Liège : UER > UER Economie : Economie industrielle ; CESifo, Munich, Germany

Nsabimana, René ; Université de Liège - ULiège > HEC - Ecole de gestion de l'ULiège > Doct. scienc. écon. gest. (sciences économiques) ; Institut Supérieur des Cadres Militaires (ISCAM), Burundi

Walheer, Barnabé ; Université de Liège - ULiège > HEC Liège : UER > UER Economie : Microéconométrie et économétrie appliquée

Language :

English

Title :

Quality performance gaps and minimal electricity losses in East Africa

Publication date :

June 2023

Journal title :

Utilities Policy

ISSN :

0957-1787

Publisher :

Elsevier Ltd

Volume :

Pages :

101558

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S095717872300070X?httpAccept=text/xml

Funders :

F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]

Funding text :

This work is supported by the Fonds de la Recherche Scientifique (FNRS), Belgium under Grant No. J.0193.23.

Available on ORBi :

since 31 July 2023

Statistics

Number of views

69 (13 by ULiège)

Number of downloads

55 (5 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

Abbott, M., Cohen, B., Economics, ideology, and the creation and performance of state-owned electricity utilities in Australia, 1900 to 1950. Util. Policy, 77, 2022, 101380.
Adams, S., Atsu, F., Klobodu, E.M., Richmond, L., Electricity transmission, distribution losses and economic growth in South Africa. Heliyon, 6(11), 2020, e05564.
Arcos-Vargas, A., Núñez Hernández, F., Villa-Caro, G., A DEA analysis of electricity distribution in Spain: An industrial policy recommendation. Energy Policy 102 (2017), 583–592.
Arocena, P., Cost and quality gains from diversification and vertical integration in the electricity industry: A DEA approach. Energy Econ. 30:1 (2008), 39–58.
Asmild, M., Paradi, J.C., Aggarwall, V., Schaffnit, C., Combining DEA window analysis with the malmquist index approach in a study of the Canadian banking industry. J. Prod. Anal. 21:1 (2004), 67–89.
Bagdadioglu, N., Price, C.M.W., Weyman-Jones, T.G., Efficiency and ownership in electricity distribution: a non-parametric model of the Turkish experience. Energy Econ. 18:1–2 (1996), 1–23.
Balza, L., Jimenez, R., Mercado, J., Privatization, Institutional Reform, and Performance in the Latin American Electricity Sector., 2013, Inter-American Development Bank, Washington, DC.
Bongo, M.F., Ocampo, L.A., Magallano, Y.A.D., Manaban, G.A., Ramos, E.K.F., Input–output performance efficiency measurement of an electricity distribution utility using super-efficiency data envelopment analysis. Soft Comput. 22:22 (2018), 7339–7353.
Costa-Campi, M.T., Daví-Arderius, D., Trujillo-Baute, E., The economic impact of electricity losses. Energy Econ. 75 (2018), 309–322.
de Oliveira Ventura, L., Melo, J.D., Padilha-Feltrin, A., Pablo Fernandez-Gutiérrez, J., Sanchez Zuleta, C.C., Piedrahita Escobar, C.C., A new way for comparing solutions to non-technical electricity losses in South America. Util. Policy, 67, 2020, 101113.
Edvardsen, D.F., Forsund, F.R., International benchmarking of electricity distribution utilities. Resour. Energy Econ. 25:4 (2003), 353–371.
Fadzlan, S., Muhd-Zulkhibri, A.M., Singapore banking efficiency and its relation to stock returns: a DEA window analysis approach. Int. J. Bus. Stud. Publ. Fac. Bus. Adm. Edith Cowan Univ. 15:1 (2007), 83–106.
Forsund, F.R., Kittelsen, S.A., Productivity development of Norwegian electricity distribution utilities. Resour. Energy Econ. 20:3 (1998), 207–224.
Fourie, J.W., Calmeyer, J.E., A statistical method to minimize electrical energy losses in a local electricity distribution network. 2004 IEEE Africon. 7th Africon Conference in Africa (IEEE Cat. No. 04CH37590) Vol. 2, 2004, IEEE, 667–673.
Jain, S., Thakur, T., Efficiency assessment of state owned electricity generation companies in India using data envelopment analysis. Int. J. Emerg. Technol. 1:2 (2010), 32–35.
Jamasb, T., Pollitt, M., International benchmarking and regulation: an application to European electricity distribution utilities. Energy Policy 31:15 (2003), 1609–1622.
Jamil, F., Ahmad, E., Policy considerations for limiting electricity theft in the developing countries. Energy Policy 129 (2019), 452–458.
Kaufmann, D., Kraay, A., Mastruzzi, M., The worldwide governance indicators: Methodology and analytical issues. Policy Res. Work. Pap., 5430, 2010, 10.1017/S1876404511200046.
Leite, D., Pessanha, J., Simões, P., Calili, R., Souza, R., A stochastic frontier model for definition of non-technical loss targets. Energies, 13(12), 2020, 3227.
Meenakumari, R., Kamaraj, N., Measurement of relative efficiency of state owned electric utilities in India using data envelopment analysis. Mod. Appl. Sci. 2:5 (2008), 61–71.
Messinis, G.M., Hatziargyriou, N.D., Review of non-technical loss detection methods. Electr. Power Syst. Res. 158 (2018), 250–266.
Mohsin, M., Hanif, I., Taghizadeh-Hesary, F., Abbas, Q., Iqbal, W., Nexus between energy efficiency and electricity reforms: A DEA-based way forward for clean power development. Energy Policy, 149, 2021, 112052.
Mwaura, F.M., Adopting electricity prepayment billing system to reduce non-technical energy losses in Uganda: Lesson from Rwanda. Util. Policy 23 (2012), 72–79.
Nagayama, H., Impacts on investments, and transmission/distribution loss through power sector reforms. Energy Policy 38:7 (2010), 3453–3467.
Nepal, R., Jamasb, T., Caught between theory and practice: Government, market, and regulatory failure in electricity sector reforms. Econ. Anal. Policy 46 (2015), 16–24.
Nsabimana, R., 2020. Electricity sector organization and performance in Burundi. In: Multidisciplinary Digital Publishing Institute Proceedings, Vol. 58, No. 1. p. 26.
Pacudan, R., Hamdan, M., Electricity tariff reforms, welfare impacts, and energy poverty implications. Energy Policy 132 (2019), 332–343.
Pérez-Reyes, R., Tovar, B., Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms. Energy Policy 37:6 (2009), 2249–2261.
Petridis, K., Ünsal, M.G., Dey, P.K., Örkcü, H.H., A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies. Energy 174 (2019), 985–998.
Ramos-Real, F.J., Tovar, B., Iootty, M., De Almeida, E.F., Pinto, H.Q. Jr., The evolution and main determinants of productivity in Brazilian electricity distribution 1998–2005: An empirical analysis. Energy Econ. 31:2 (2009), 298–305.
REN21, East African community (EAC) renewable energy and energy efficiency status report. 2016 available at https://www.ren21.net/wp-content/uploads/2019/05/REN21-EAC-web-EN.pdf.pdf.
Sadovskaia, K., Bogdanov, D., Honkapuro, S., Breyer, C., Power transmission and distribution losses–A model based on available empirical data and future trends for all countries globally. Int. J. Electr. Power Energy Syst. 107 (2019), 98–109.
Salkuti, S.R., Minimization of losses in a distribution system with network reconfiguration, distributed generation and D-STATCOM. Int. J. Adv. Technol. Eng. Explor., 8(85), 2021, 1557.
Sanhueza, R., Rudnick, H., Lagunas, H., DEA efficiency for the determination of the electric power distribution added value. IEEE Trans. Power Syst. 19:2 (2004), 919–925.
Sen, A., Jamasb, T., Diversity in unity: An empirical analysis of electricity deregulation in Indian states. Energy J. 33:1 (2012), 83–130.
Smith, T.B., Electricity theft: a comparative analysis. Energy Policy 32:18 (2004), 2067–2076.
Sueyoshi, T., Goto, M., Sugiyama, M., DEA window analysis for environmental assessment in a dynamic time shift: Performance assessment of US coal-fired power plants. Energy Econ. 40 (2013), 845–857.
Sueyoshi, T., Yuan, Y., Li, A., Wang, D., Social sustainability of provinces in China: A data envelopment analysis (DEA) window analysis under the concepts of natural and managerial disposability. Sustainability, 9(11), 2017, 2078.
Susanty, A., Purwanggono, B., Al Faruq, C., Electricity distribution efficiency analysis using data envelopment analysis (DEA) and soft system methodology. Procedia Comput. Sci. 203 (2022), 342–349.
Tovar, B., Ramos-Real, F.J., De Almeida, E.F., Firm size and productivity, evidence from the electricity distribution industry in Brazil. Energy Policy 39:2 (2011), 826–833.
Vaninsky, A., Efficiency of electric power generation in the United States: analysis and forecast based on data envelopment analysis. Energy Econ. 28:3 (2006), 326–338.
Vaninsky, A.Y., Environmental efficiency of electric power industry of the United States: a data envelopment analysis approach. Int. J. Ind. Manuf. Eng. 2:4 (2008), 509–515.
Von Hirschhausen, C., Cullmann, A., Kappeler, A., Efficiency analysis of German electricity distribution utilities–non-parametric and parametric tests. Appl. Econ. 38:21 (2006), 2553–2566.
Walheer, B., Aggregation of metafrontier technology gap ratios: The case of European sectors in 1995–2015. European J. Oper. Res. 269:3 (2018), 1013–1026.
Walheer, B., Output, input, and undesirable output interconnections in Data Envelopment Analysis: convexity and returns-to-scale. Ann. Oper. Res. 284 (2020), 447–467.
Wang, J.B., Liu, L., Wang, C., Single machine SLK/DIF due window assignment problem with learning effect and deteriorating jobs. Appl. Math. Model., 37(18–19), 2013.
Xie, B.C., Gao, J., Chen, Y.F., Deng, N.Q., Measuring the efficiency of grid companies in China: A bootstrapping non-parametric meta-frontier approach. J. Clean. Prod. 174 (2018), 1381–1391, 10.1016/j.jclepro.2017.11.016.
Yakubu, O., Babu, N., Adjei, O., Electricity theft: Analysis of the underlying contributory factors in Ghana. Energy Policy 123 (2018), 611–618.
Yang, H.H., Chang, C.Y., Using DEA window analysis to measure efficiencies of Taiwan's integrated telecommunication firms. Telecommun. Policy 33:1–2 (2009), 98–108.
Yunos, J.M., Hawdon, D., The efficiency of the national electricity board in Malaysia: An intercountry comparison using DEA. Energy Econ. 19:2 (1997), 255–269.