Carbon intensity, energy transition, and economic development in Africa: Evidence from a panel vector autoregression analysis

Abstract

. This study evaluates the dynamic correlations among carbon intensity, energy access, renewable energy consumption, population growth, economic development, energy intensity, and industrialization in Africa using panel data for 52 countries from 2005 to 2023. A Panel Vector Autoregression (PVAR) framework is used to capture the endogenous interactions and transmission mechanisms among environmental, demographic, and economic variables. The results uncover strong persistence in carbon intensity, energy intensity, population growth, GDP per capita, and industrialization, supporting the path-dependence and carbon lock-in perspectives. Energy intensity greatly increases carbon intensity, strongly supporting the energy-efficiency hypothesis, whereas population growth grows energy intensity levels, revealing the importance of demographic pressures in determining environmental outcomes. Economic growth directly determines industrialization, backing the structural transformation theory. Renewable energy consumption and energy access do not exert significant short-run effects on carbon intensity, suggesting that the environmental benefits of renewable energy materialize over longer horizons. Granger causality results indicate that improvements in energy access stimulate renewable energy consumption, while impulse response and variance decomposition analyses show that renewable energy and energy efficiency become increasingly important drivers of long-run carbon-intensity dynamics. The findings underscore the need for integrated policies that promote energy efficiency, renewable energy investment, demographic management, and green industrialization to advance sustainable development and climate resilience in Africa.