Analyzing the determinants of the load capacity factor in OECD countries: Evidence from advanced quantile panel data methods

Achieving the Sustainable Development Goals (SDGs) is one of the crucial matter on the agenda of decision makers in Organization for Economic Cooperation and Development (OECD) countries. The SDGs include many broad environmental goals, such as pollution of air, water, and soil, and the protection of natural resources to combat this pollution. To achieve these goals, carbon emissions and ecological footprint analyzes provide some guidance, but neglect the supply side of nature. The load capacity factor makes it possible to analyze biocapacity (the supply side of nature) and ecological footprint simultaneously to assess whether countries are exceeding the sustainability limit and what factors are influencing that limit. To address this issue and provide a comprehensive environmental assessment of OECD countries, this study examines the influence of human capital, income, natural resources, urbanization, and renewable energy on the load capacity factor for 26 OECD countries over the period 1980–2018. For this purpose, the study uses the newly developed quantile common correlated effects mean group (QMG) estimator and investigates the load capacity curve (LCC) hypothesis. Our results suggest that there is a U-shaped link between income and environmental quality and the LCC hypothesis is valid. The QMG estimator results show that human capital, resource rent, and renewable energy improve the load capacity factor, but urbanization adversely affects environmental quality. The overall results highlight the ecological role of renewable energy, resource rent, and human capital in achieving the SDGs of OECD countries, such as transitioning to a low-carbon economy and reducing water pollution.