Green financial investment and its influence on economic and environmental sustainability: does privatization matter?

Green financial investment and privatization have been widely used as policy tools to promote economic growth and efficiency in many countries. However, their effects on environmental sustainability have been less explored. This study utilizes autoregressive distributed lag (ARDL) and quantile autoregressive distributed lag (QARDL) techniques to explore the effects of green financial investment and privatization on economic and environmental performance in China. Using data from 1995 to 2021, we analyze the impact of green financial investment and privatization on economic performance, measured by GDP per capita, and environmental performance, measured by CO2 emissions based on green finance and privatization theories. Our findings reveal that green financial investment has a beneficial effect on both economic and environmental performance. On the other hand, privatization has a positive impact on long-term economic performance, while also having negative consequences on environmental performance. These findings can inform evidence-based policies and strategies that promote both economic and environmental performance.

Country risk and its impact on renewable energy investment in highly polluted economies

The country's risk may significantly impact every sector of the economy, and the energy sector is no exception. However, no past study has empirically tested the relationship between country risk and renewable energy investment. Therefore, this study is an effort to investigate the relationship between country risk and renewable energy investment in highly polluted economies. We have employed different econometric techniques to analyze the relationship between renewable energy investment and country risk, including the OLS, 2SLS, GMM, and panel quantile regressions. The estimate of country risk influence renewable energy investment negatively in OLS, 2SLS, and GMM models. Similarly, the country's risk negatively impacts the renewable energy investment from the 10th to 60th quantiles in the panel quantile regression model. Moreover, the GDP, CO2 emissions, and technological development help promote renewable energy investment in OLS, 2SLS, and GMM models, while the human capital and financial development do not significantly impact the renewable energy investment. Furthermore, in the panel quantile regression model, the GDP and CO2 emission estimates are positively significant almost at all quantiles, and the estimate of technological development and human capital are positively significant at higher quantiles only. Therefore, the authorities in highly polluted economies should consider the respective countries' risk considerations while formulating rules about renewable energy.

Financial deepening, financial innovation, and education as new determinants of green growth in China

To address the issue of global warming, the agreed solution is to reduce GHG emissions. The plausible solution to reduce GHG emissions is to follow a green growth strategy that refers to the complete decoupling of economic growth from its environmental impact through the sustainable utilization of natural resources. Consistent with this view, this study investigates the impact of financial deepening, financial innovation, and education on green growth in China from 1996 to 2020. The empirical analysis of the model is conducted through quantile ARDL. The long-run estimated coefficients of financial institution deepening are positively significant across most quantiles, whereas the estimated coefficients of financial market deepening are positively significant in almost half quantiles. These results imply that the financial deepening of both financial markets and institutions can positively contribute to green growth. However, the estimates of financial innovations are significant and positive in higher quantiles, implying that financial innovation only contributes to the green when the rate of financial innovation is too high. The estimates of education are positively significant at higher quantiles. Our study highlights various policy suggestions that are aimed at instigating sustainable green growth in China.

Financial integration and renewable energy consumption in China: do education and digital economy development matter?

Renewable energy is considered vital to addressing the issue of climate change and energy poverty. In recent times, empirics have tried to find the determinants of renewable energy consumption. Hence, the primary focus of the analysis is to estimate the impact of financial integration, education, and ICT on renewable energy consumption in China. In order to get the estimate of the variables, the analysis has applied the quantile ARDL model. The long-run estimates of the financial integration are positively significant at most quantiles, confirming the positive impact of financial integration on renewable energy consumption. Similarly, the long-run estimates of ICT are positively significant in almost all quantiles, confirming that digitalization helps increase renewable energy consumption in China. The long-term effect of education is significant at the higher quantiles. In the short run, the estimated coefficients of financial integration are positively significant at almost all quantiles; however, the estimated coefficients of ICT are positively significant in half quantiles. The short-run results of education are insignificant at most quantiles. In line with these results, several appropriate financial integration, digitalization, and education policies are recommended.