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

High-frequency monitoring of China's green growth-at-risk

With industrialization and urbanization, China faces enormous challenges from energy security and environmental issues. To address these challenges, it is imperative to establish a green accounting system for economic growth and to measure the uncertainty of China's green GDP (GGDP) growth from a risk management perspective. With this in mind, we follow the idea of growth-at-risk (GaR) to propose the concept of green GaR (GGaR) and extend it to the mixed-frequency data environment. Specifically, we first measure China's annual GGDP using the System of Environmental Economic Accounting (SEEA), then construct China's monthly green financial index by a mixed-frequency dynamic factor model (MF-DFM), and finally monitor China's GGaR from 2008M1 to 2021M12 with the mixed data sampling-quantile regression (MIDAS-QR) method. The main findings are as follows: First, the proportion of China's GGDP to traditional GDP gradually increases from 81.97% in 2008 to 89.34% in 2021, which illustrates that the negative environmental externalities caused by China's economic growth are gradually decreasing. Second, the high-frequency GGaR has favorable predictive performance and is significantly superior to the common-frequency GGaR at most quantiles. Third, the high-frequency GGaR has good nowcasting performance, and its 90% and 95% confidence intervals include true value for all prediction horizons. Furthermore, it can provide early warning of economic downturns through probability density prediction. Overall, our main contribution lies in constructing a quantitative assessment and high-frequency monitoring of China's GGDP growth risk, which provides an effective tool for investors and companies to predict risk, and a reference for the Chinese government to better formulate sustainable development strategies.

Toward green growth in China: The role of green finance investment, technological capital, and renewable energy consumption

In recent times, the concept of green growth has emerged, which has a critical part to play in controlling the environmental impact of economic activities. In this analysis, we have explored three determinants of green growth: green finance investment, technological capital, and renewable energy. Moreover, this study focuses on the asymmetric impact of green finance investment, technological progress, and renewable energy on green growth in China during the period spanning from 1996 to 2020. To get the asymmetric short and long-run estimates across various quantiles, we have employed the nonlinear QARDL. The long-run estimates attached to a positive shock in green finance investment, renewable energy demand, and technological capital are positively significant at most quantiles. While, the long-run estimates attached to a negative shock in green finance investment, technological capital, and renewable energy demand are insignificant at most quantiles. In general, the findings suggest that the rise in green financial investment, technological capital, and renewable energy demand positively impacts green growth in the long run. The study offers a range of significant policy recommendations that can contribute to the advancement of sustainable green growth in China.