Can effective environmental policies reduce the burden of natural resources exploitation in emerging economies? Evidence from quantile regression

Since the approval of sustainable development goals (SDGs) in 2015, there has been a growing debate about whether the prevailing environmental rules and policies can reduce environmental degradation to achieve the SDG targets by 2030. Therefore, the present study tries to empirically examine the impact of environmental policy stringency (EPS) on CO₂ emissions by incorporating the role of natural resources rent (NRR) and renewable energy consumption (REC). This study is the earliest attempt to investigate the combined impact of environmental policy stringency and natural resources rent on CO₂ emissions by using the STIRPAT model for the emerging six countries (China, India, Brazil, Turkey, Indonesia, and Russia) during 1996–2019. In doing so, we use second-generation estimation techniques and panel quantile regression to check the heterogeneous or separate impact of EPS, NRR, and REC at different quantiles (10th to 90th quantile) on carbon emissions. Unlike OLS regression, the panel quantile regression approach provides a more flexible and adaptive analysis as it does not assume a predefined distribution. Additionally, quantile regression shows that it may produce accurate and reliable results even when there are outliers. The empirical outcomes claim that environmental policy stringency reduces carbon emissions. Similarly, the interaction term of EPS and NRR also has a negative relationship with CO₂ emissions. Based on the empirical outcomes, this study proposes a comprehensive policy framework for achieving the targets of SDG-13 (climate change), SDG-08 (decent work and economic growth), SDG-09 (innovations), and SDG-12 (responsible consumption). Moreover, the governments of the E-6 economies should tighten up the environmental regulations.