Against the backdrop of the pressing issue of global warming, the concept of green development, which emphasizes the rational utilization of resources and energy, has emerged as a viable model for future economic growth. Despite this, the interplay between big data technology and green development has yet to receive due consideration. This study aims to shed light on the role of big data in green development from the perspective of factor configuration distortion. To this end, a panel data analysis of 284 prefecture-level cities spanning from 2007 to 2020 was conducted, utilizing the Difference-in-Differences (DID) and Propensity Score Matching-Difference-in-Differences (PSM-DID) models to assess the impact of the establishment of the National Big Data Comprehensive Experimental Zone on green total factor productivity. The findings reveal that the establishment of the National Big Data Comprehensive Experimental Zone has a positive impact on green total factor productivity, primarily through optimizing the capital and labor allocation distortions, with the effect being more pronounced in areas with high levels of human capital, financial development, and economic activity. This research provides empirical evidence to evaluate the impact of the establishment of the National Big Data Comprehensive Experimental Zone and offers valuable policy implications for the pursuit of high-quality economic development.

In the context of a low-carbon economic transition and escalating uncertainties in financial markets, understanding the relationship between the long-term benefits of ESG (Environmental, Social, and Governance) investments and the stability of China’s financial markets emerges as a critical issue. This paper analyzes the risk contagion mechanisms within China’s financial system from the perspective of volatility spillovers associated with ESG investments. Initially, the study employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to calculate the variance decomposition spillover index, contrasting the dynamics and risk transmission mechanisms of market volatility between portfolios composed of ESG and conventional stocks. Building upon the analysis of risk spillover relations among financial sub-markets, the study utilizes the generalized forecast error variance decomposition method to construct a complex network of financial system risk spillovers, investigating the risk contagion characteristics within both financial systems through network topology. Empirical findings indicate a significant reduction in the risk and net spillover effects of China’s financial system when ESG stock indices replace conventional stock indices, with a notable mutation in the volatility spillover network structure during extreme risk events and even more substantial changes during the COVID-19 pandemic. Furthermore, based on volatility spillover analysis, the study computes optimal weights and hedging strategies for portfolios incorporating the ESG volatility index and other market volatility indices. The conclusions of this research are instrumental for regulatory authorities in establishing early warning mechanisms and for investors in avoiding financial investment risks.

This study utilizes a flexible estimation and simulation platform based on the GE-PPML model to analyze the trade and welfare implications of the Regional Comprehensive Economic Partnership (RCEP) for member countries, with a particular focus on China. Our findings suggest that RCEP has the potential to yield significant export gains for member economies. Furthermore, by considering heterogeneity in terms of sectors and product usage, our results indicate that RCEP holds significant potential for deepening value chain trade among member countries, particularly in the manufacturing industry. This study underscores the importance and uniqueness of examining the actual impact of RCEP on member countries’ trade and welfare. By providing clearer insights into these impacts, we aim to contribute to a better understanding of the potential benefits and challenges associated with RCEP implementation.