Environmental degradation is a natural and socioeconomic cause–effect phenomenon that is widespread all over the world. The current study investigates the impact of socioeconomic factors on dimensions of environmental degradation in Pakistan for the period of 1984 to 2017. The impact of socioeconomic factors on dimensions of environmental degradation is investigated using the augmented Dicky–Fuller unit root test and the autoregressive distributed lag bounds test. The cumulative sum of recursive residuals and the cumulative square sum of recursive residuals were used to check the stability of the socioeconomic parameters on dimensions of environmental degradation of three investigated models. The study observed a negative and significant impact on environmental degradation in all three models. The analysis incorporated that FDI, per capita GDP, industrialization and the total population have a positive and significant effect on environmental degradation in the long run; as FDI, per capita GDP and total population increase, this will cause environmental degradation to increase. The rural population and agricultural land have an insignificant association with environmental degradation. The present study also indicates that dimensions of the environmental degradation in Pakistan are mostly influenced by the governance. However, this research will help the policy makers to understand the importance of the governance and environmental degradation.

The aim of this study is to analyze the impact of financial inclusion on green economic growth in developing countries. For this purpose, 12 developing countries were selected based on the availability of data: Armenia, Egypt, Ethiopia, India, Indonesia, Iran, Jamaica, Kenya, Pakistan, Sri Lanka, Thailand, and Tunisia. Annual data for the period from 2004 to 2023 were used for this study. The focus of this study is on the achievement of Sustainable Development Goal 13 (SDG 13), which requires immediate intervention to address the challenges of climate change and its consequences. This study used principal component analysis (PCA) to construct the financial inclusion index. In this study, we conducted a unit root analysis using the second-generation unit root test. For long-run estimates, we used the Fully Modified Least Squares (FMOLS) model. According to the findings of the study, green innovation (β = 0.052 *), foreign direct investment (β = 0.438 *), and trade openness (β = 0.016 **) have positive and significant impacts on green economic growth (GEG). The extent of the positive effect of foreign direct investment (FDI) is greater, compared to green innovation and trade openness (TR). The results also indicate that financial inclusion (β = −0.241) and population (β = −0.291) have significantly detrimental impacts on GEG. However, the population impacts GEG to a greater extent, compared to financial inclusion. Similarly, results indicate that the negative impact of financial inclusion on GEG is greater than the positive impact of green innovation on GEG. On the basis of the findings of this study, policymakers are advised to promote green innovation, foreign direct investment, and trade openness to promote green economic growth. Moreover, this study suggests that green finance or financial inclusion constrained by environmental quality should be promoted to safeguard environmental quality.