Discerning the role of renewable energy and energy efficiency in finding the path to cleaner consumption and production patterns: New insights from developing economies

This study provides empirical evidence on the relationship between energy efficiency and production- and-consumption based carbon emissions by assessing the impact of population size, income, and clean energy on the carbon dioxide (CO2) emissions function. Method of Moments Quantile Regression (MM-QR) and Augmented Mean Group (AMG) estimators are applied to observe long-term associations between the variables, and Dumitrescu-Hurlin (DH) Ganger causality test is used to identify the direction of causality. Findings reveal that, across all specifications, energy intensity and population size have positive (increasing) impact on both estimates of CO2 emissions while renewable energy use has a negatively significant impact and stronger on consumption-based estimates. The presence of an inverted U-shaped curve in the relationship between per capita income and CO2 emissions, as predicted by the Environment Kuznets curve (EKC) hypothesis, only exists when CO2 emissions are calculated based on production pattern. Further empirical analysis based on DH causality tests show a bidirectional causality between energy intensity and production-based CO2 emissions, population size and consumption-based CO2 emissions, per capita income and consumption-based CO2 emissions, and energy intensity and renewable energy use. In addition, a unidirectional causality runs from per capita income to production-based CO2 emissions, and from energy intensity and renewable energy use to consumption-based CO2 emissions. This analysis outlines a paradigm for the formulation of a green development strategy in developing economies via energy and environmental resources.