Quantifying Environmental Degradation through Renewable Energy, Financial Development and Economic Sustainability: Insights from Panel Quantile Regression Analysis

The degradation of the environment is a global concern that needs serious attention, including the environmental Kuznets curve (EKC) hypothesis. This article examines the effects of renewable energy, financial development and economic sustainability on the environmental quality of newly industrialized countries (NICs) from 1998 to 2021 in light of the increasing severity of environmental problems associated with industrialization. This study utilized different panel cointegration estimation techniques and panel quantile regression (PQR) estimates to obtain robust findings by examining the variance of each quantile. The results of the cointegration tests confirm the long-run relationship among the variables. Nevertheless, the outcomes from the PQR unveiled that renewable energy negatively and significantly influences CO2 emissions in NICs, namely in the lower and middle quantiles (20th–50th). Financial development showed heterogeneity in the results of all the quantiles. It results in an increase in CO2 emissions from the 70th to 90th quantiles in NICs. The EKC hypothesis is relevant to these findings as this study presents the economic sustainability index, which postulates that when NICs achieve sustainability, they give greater importance to environmental preservation and sustainability. This shift is characterized by reduced emissions throughout all quantiles, ranging from the 10th to the 90th. Economic sustainability corresponds to the falling part of the U-shaped curve of the EKC, wherein sustainability gets priority, resulting in reduced CO2 emissions. Analogous results have been confirmed by comparing heterogeneous panel estimators; nonetheless, there was a significant variation in the intensity of their parameters. Moreover, the robustness analysis through quantile slope equality and symmetric quantiles tests proved legitimate results. The study’s findings offer policymakers with valuable policy recommendations.JEL Codes: C1, F36, F43, O44, Q56