Global warming has become a major concern for countries around the world. In this context, developed countries have decided to reduce global emissions to achieve sustainable development. The energy mix of OECD countries consists of 80% fossil fuels and accounts for about 35% of worldwide carbon emissions. Therefore, it is important to analyze how environmental factors affect carbon emissions in OECD countries. This study uses fossil energy, renewable energy (RE), and GDP for the period 1990–2019. Unlike previous studies, we will estimate two separate models for FFE and RE. To evaluate the empirical results, advanced panel data estimation methods using the cointegration test and the CS-ARDL estimation technique are employed to examine the long-run relationship between the variables. The results of the study demonstrate that fossil fuel use and GDP increase carbon emissions both in the short and long term. However, the use of RE hurts carbon emissions and is associated with sustainable development in OECD countries. Therefore, it is assumed that although fossil fuel use degrades the environment, economic growth helps it by reducing carbon emissions. Overall, our study shows that the use of RE is essential for OECD countries to achieve their environmental sustainability goals because it reduces the share of fossil fuels in the overall energy mix. Furthermore, in order to achieve a sustainable environment, OECD countries are recommended to begin long-term planning to reduce carbon emissions.

The study investigates the impact of trade openness on pollution in China by applying wavelet-coherence analysis, phase-difference technique and Breitung and Candelon (2006) causality test. The estimated results provide some dynamic association between trade openness and pollutant variables. The results indicate that trade openness has increased pollution in China especially after 2001 when China became member of WTO. It suggests that “pollution haven hypothesis” exists in China. These results imply that trade openness has increased exports which has increased domestic production by increasing the scale of industries, which in turn has increased pollution in the country. The findings of spectral domain causality test show that trade openness causes carbon emission both in short, medium and long runs. It indicates that trade openness forecast carbon emissions in China. The results suggest that China should take suitable measures while following trade openness policy to avoid pollution.

The study investigates the effect of financial development on major economic indicators, i.e., economic growth, inflation, and employment by applying System GMM estimation technique for a panel of 120 countries for the period 1997 to 2017. Four distinct proxies of financial development are used, i.e., private sector credit, liquid liabilities, money and quasi money, and bank credit. The results contradict the traditional supply-lending hypothesis and reveal negative impact of financial development on economic growth. Moreover, financial development is found to be positively associated with inflation and employment growth. It is suggested that there is need to reform and strengthen the supervision of financial intermediaries to ensure sound prudential lending practices. Furthermore, more credit needs to be allocated to highly productive firms.

By applying the wavelet tool, this study examines the effect of foreign direct investment (FDI) on pollution in China, for the period 1982 to 2016. Carbon dioxide and sulfur dioxide emissions are used as pollution variables. The results reveal that FDI positively affected pollution at high frequency (short term) during the 1980s and after 2000, and at low frequency (long term) but not at medium frequency (medium term) for the entire time period. It demonstrates that FDI increases pollution both in the short and long term, but not in the medium term. It indicates that FDI has created pollution havens in China. For robustness analysis, spectral causality test was applied. The results of this causality test indicate that FDI causes CO₂ emissions both in the short-run and long-run. This suggests that in China FDI predicts CO₂ emissions. Thus, stringent environmental rules are required to restrict the inflows of foreign dirty industries in China.

In this present age, innovation has become inextricably tied to both long-term economic growth and environmentally sound development. In this context, the impact that environmentally focused technological advancements or innovations have on environmental quality is of the utmost importance. Therefore, the main goal of the present study is to determine how Green innovation (GI) affects environmental degradation in the BRICS countries from 1992 to 2021. The ecological footprint (EFT) is an indicator used in the study to measure environmental degradation. The study divides the components that contribute to the explanation into two categories: the GI threshold variable and the independent variables RE, GDP, and population (POP). Additionally, this study investigates the indirect impact of RE, GDP, and POP through the threshold effect of GI. The stochastic impacts of the explanatory factors are explored using sophisticated panel data estimation methods and a panel threshold model. According to the findings of the study, an improvement in environmental quality occurs when the threshold level of GI is achieved, which indicates that innovation in the form of a lower EFT is responsible for the improvement. In light of the findings, recommendations for policymakers and stakeholders in BRICS countries are to promote RE and drive GI.