Analysis of the factors affecting electricity consumption in DR Congo using fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegrating regression (CCR) estimation approach

Abstract

Electricity is the basic necessity for daily life and a core component for a country's economic growth. However, in DR Congo access to electricity is less than 20%. This paper investigates various factors affecting electricity supply in DR Congo from 2000 to 2018. We utilized seven different determinants including economic growth, population, life expectancy, electricity production, access to electricity, labor force, and unemployment rate, to analyze their impact on electricity consumption. FMOLS (fully modified ordinary least square) and DOLS (dynamic ordinary least square) regression techniques were used to explore the relationship. While, canonical cointegrating regression (CCR) estimation was employed as robust estimator. The results indicate that economic growth, population, life expectancy, electricity production, access to electricity and labor force have a positive effect on and increase electricity consumption. However, unemployment rate has a negative impact, namely an increase in unemployment rate decreases electricity consumption. The results further indicate that access to electricity is the most prominent determinant among all and has the most severe impact on electricity consumption. Based on the results, this study puts forward several policy implications.