This study examines the impact of remittance inflows, technological innovations, and financial development on environmental quality in Brazil, India, China, and South Africa (BICS) economies over 1990-2016. This study employed a comprehensive environment proxy, i.e., ecological footprint for environmental quality, and also considers more advanced and robust econometric (second-generation) techniques. The outcomes of the current study reveal that remittance inflows and financial development significantly deteriorate the environmental quality, while technological innovations are an essential factor for the reduction of ecological footprint level. Furthermore, the results of the interaction terms show a significantly adverse effect on the ecological footprint. Additionally, the findings of country-wise analysis reveal that remittance inflows and financial development worsen the environmental quality in each sample country, while the technological innovations promote the environmental sustainability that is steady with panel results. Besides, the environmental Kuznets curve (EKC) hypothesis was verified across the BICS economies. Consistent with the key findings, an inverted U-shaped relationship exists between economic growth and ecological footprint in the case of Brazil and South Africa. In contrast, the U-shaped EKC hypothesis exists in the case of China and India. For robust policy implication, the findings of this study highlighted the dire need for "green policy tools" that should be linked with the BICS economy policies and driver for sustained growth.

This paper studies the effects of income inequality and financial instability on CO2 emissions in the presence of fossil fuel energy, economic development, industrialization, and trade openness. Moreover, the present study is the first to examine the moderating role of financial instability between income inequality and CO2 emissions. We utilized panel data of forty-seven developing countries for the period 1980–2016 by utilizing the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model. The empirical outcomes in all models indicate that income inequality and industrialization significantly reduce environmental degradation, while fossil fuel, trade openness, and economic growth decrease the quality of the environment. However, financial instability (with interaction term) shows no significant link to environmental quality, whereas (with interaction term) it shows a significant negative effect on CO2 emissions. In addition, the result of the interaction variable reveals that an increase in inequality, ceteris paribus, in combination with the rise in financial instability, is expected to increase pollution. Furthermore, there exists a bidirectional causal association among income inequality, financial instability, fossil fuel, trade openness, industrialization, economic growth, and the interaction variable with CO2 emissions.

Concerns regarding environmental sustainability have generally been an important element in achieving long-term development objectives. However, developing countries struggle to deal with these concerns, which all require specific treatment. As a result, this study explores the interaction between financial development, renewable energy consumption, technological innovations, and CO2 emissions in India from 1980 to 2019, taking into account the critical role of economic progress and urbanization. The Autoregressive Distributed Lag (ARDL) model is used to quantify long-run dynamics, while the Vector Error Correction Model is used to identify causal direction (VECM). According to the study’s conclusions, financial development has a considerable positive impact on CO2 emissions. The coefficient of renewable energy consumption and technical innovations, on the other hand, is strongly negative in both the short and long run, indicating that increasing these measures will reduce CO2 emissions. Furthermore, economic expansion and urbanization have a negative impact on environmental quality since they emit a significant amount of CO2 into the atmosphere. The results of the robustness checks were obtained using the Fully Modified Ordinary Least Squares (FMOLS), the Dynamic Ordinary Least Squares (DOLS), and the Canonical Cointegration Regression (CCR) approaches to verify the findings. The VECM results reveal that there is long-run causality in CO2 emissions, financial development, renewable energy utilization, and urbanization. A range of diagnostic tests were also used to confirm the validity and reliability. This study delivers new findings that contribute to the existing literature and may be of particular interest to the country’s policymakers in light of the financial system and its role in environmental issues.

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