Bridging the Energy Divide: An Analysis of the Socioeconomic and Technical Factors Influencing Electricity Theft in Kinshasa, DR Congo

Patrick Kankonde and Pitshou Bokoro ()
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Patrick Kankonde: Department of Basic Sciences, Faculty of Polytechnic, University of Kinshasa, Kinshasa P.O. Box 255, Democratic Republic of the Congo
Pitshou Bokoro: Department of Electrical and Electronic Engineering Technology, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2024, South Africa

Energies, 2025, vol. 18, issue 13, 1-25

Abstract: Electricity theft remains a persistent challenge, particularly in developing economies where infrastructure limitations and socioeconomic disparities contribute to illegal connections. This study analyzes the determinants influencing electricity theft in Kinshasa, the Democratic Republic of Congo, using a logistic regression model applied to 385 observations, which includes random bootstrapping sampling for enhanced stability and power analysis validation to confirm the adequacy of the sample size. The model achieved an AUC of 0.86, demonstrating strong discriminatory power, while the Hosmer–Lemeshow test ( p = 0.471) confirmed its robust fit. Our findings indicate that electricity supply quality, financial stress, tampering awareness, and billing transparency are key predictors of theft likelihood. Households experiencing unreliable service and economic hardship showed higher theft probability, while those receiving regular invoices and alternative legal energy solutions exhibited lower risk. Lasso regression was implemented to refine predictor selection, ensuring model efficiency. Based on these insights, a multifaceted policy approach—including grid modernization, prepaid billing systems, awareness campaigns, and regulatory enforcement—is recommended to mitigate electricity theft and promote sustainable energy access in urban environments.

Keywords: electricity theft; logistic regression; Kinshasa; random bootstrapping; socioeconomic disparities; energy infrastructure; tampering awareness; model evaluation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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