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Modelling Sustainable Energy Transition in BRICS+ Countries: A Smoothed Common Correlated Effects Instrumental Variable Quantile Regression Approach

Abankwah, Stephen Asare and Afriyie, Samuel Osei (2025): Modelling Sustainable Energy Transition in BRICS+ Countries: A Smoothed Common Correlated Effects Instrumental Variable Quantile Regression Approach.

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Abstract

The collective goal of achieving net-zero emissions in the coming decades has sparked considerable debate in recent years. The nature of the energy transition in fossil fuel-dependent economies suggests the presence of both implicit and explicit gaps in country-level commitments to the transition. Utilizing data from 1996 to 2019 from the BRICS+ bloc, this study investigates the heterogeneous effects of key economic and environmental factors on energy transition across the distribution of energy transition levels using a smoothed quantile instrumental variable regression model with common correlated effects (CCE) adjustments. The analysis incorporates macroeconomic, environmental and governance variables, while addressing endogeneity through instrumental variables, such as fossil fuel reserves and temperature anomalies. The results reveal significant heterogeneity in the relationships across quantiles. Specifically, CO2 emissions exhibit a consistently negative impact on energy transition, with the effect fluctuating across the distribution. GDP and population growth negatively influence energy transition, with stronger effects at higher quantiles, indicating structural constraints in high-transition countries. Notably, the heterogeneity of inflation effects, though insignificant, suggests dynamic economic pressures at varying energy transition levels. These findings underline the importance of targeted, quantile-specific policy interventions to accelerate energy transition, emphasizing decarbonization and market reforms. The CCE adjustments ensure robustness by accounting for cross-sectional dependence, and sensitivity analyses confirm the validity of the results. This study contributes to the growing literature on sustainable energy by providing novel insights into the distributional dynamics of energy transition drivers.

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