Understanding the impact of local government debt on economic development has emerged as a focal issue for both academic research and policymakers. This study adopts a financing structure perspective and utilizes panel data from 214 cities and 3,228 A-share listed companies in China (2017–2023) to empirically investigate the impact of local government debt on corporate “shift from virtual to real economy” and its underlying mechanisms. The expansion of local government debt significantly promotes enterprises “shift from virtual to real economy”. The positive impact of local government debt on enterprises” transition from financialization to the real economy is more pronounced among firms in first tier and new first-tier cities, non-state-owned enterprises, and labor-intensive industries. Further analysis indicates that local government debt drives capital reallocation from financial investments to real investments by alleviating corporate financing constraints. This study proposes policy recommendations including optimizing debt fund allocation, further optimizing the financing environment, implementing differentiated regulatory measures. These suggestions provide both a theoretical foundation and practical references for synergistically advancing debt governance and real economy revitalization.

The Excellence Initiatives represent a significant investment in higher education, yet little is known about the causal impact of these programs on doctoral students and future researchers. Using a comprehensive student-level dataset, we apply a difference-in-differences approach to identify how China’s Double World-Class (DWC) Project affects PhD students’ research productivity. Our results indicate that the DWC Project significantly increases both the quantity and the quality of research output among PhD students in supported disciplines, even after controlling for supervisor-related effects. In addition, these impacts vary significantly across institutional tiers and academic fields. Lower-tier universities experience considerable increases in publication volume with slight enhancements in quality, while top-tier institutions show no notable variation in either aspect. Disciplinary patterns also vary: Science and medicine show improvement in both measures, while engineering displays little change overall. These findings demonstrate how excellence initiatives influence human capital development via doctoral training and provide evidence-based recommendations for education policymakers aiming to maximize returns on strategic higher education investments worldwide.

How enterprises can leverage frontier technologies to achieve synergy between environmental governance and high-quality development has become a critical issue amid the deepening global push for sustainable development and the green economic transition. Based on micro-level data of Chinese enterprises from 2009 to 2023, this study systematically examines the impact of artificial intelligence (AI) on corporate green governance performance and explores the underlying mechanisms. The findings reveal that AI significantly enhances green governance performance at the enterprise level, and this effect remains robust after accounting for potential endogeneity. Mechanism analysis shows that AI empowers green transformation through a dual-path mechanism of “cognition–behavior,” by strengthening environmental tendency and increasing environmental investment. Further heterogeneity analysis indicates that the positive effects are more pronounced in nonheavy polluting industries and state-owned enterprises, suggesting that industry characteristics and ownership structure moderate the green governance impact of AI. This study contributes to the theoretical foundation of research at the intersection of digital technology and green governance, and provides empirical evidence and policy insights to support AI-driven green transformation in practice.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

This paper examines the effects of digital finance and corporate stock price crash risk, and the underlying mechanisms, using panel data from Chinese A-share listed companies between 2012 and 2021. Specifically, we focus on whether digital transformation and environmental, social, and governance (ESG) performance are intermediary channels through which digital finance mitigates corporate stock price crash risk. By employing panel regression and mediation effect models, we demonstrate that digital finance significantly reduces corporate stock price crash risk. This conclusion remains robust after a series of robustness tests, including the replacement of core explanatory variables, lagging digital finance by one period, using alternative dependent variables, applying the instrumental variables method, and system GMM estimation. More importantly, we find that digital finance curbs stock price crash risk by enhancing digital transformation and ESG performance. In addition, we reveal that digital finance has heterogeneous effects on corporate stock price crash risk. The inhibitory effect of digital finance on stock price crash risk is more pronounced in the central and western regions of China and for companies with lower internal control levels, higher information transparency, and higher financing constraints.

Employing an event study approach on the US-China trade conflict, we find that Chinese listed firms with institutional investor holdings exhibit smaller announcement loss than their counterparts. We also examine the heterogeneous effects of firms. Specifically, the positive effect of institutional investor holding is larger for firms with foreign exposure or in provinces with higher degree of marketization. Besides, institutional investor holding also reduces firms' financial cost of refinancing and improves their long-run performance given the same announcement loss. These findings help understand the role of institutional investor in achieving financial stability from the micro perspective.

Using a large sample of over 5,000 start-ups across various industries and 524 media outlets in China between 2000 and 2016, we examine the effects of media coverage of start-ups on VC investment decisions and performance. To the best of our knowledge, for the first time in the finance literature, we have discovered that media coverage of start-ups significantly affects VC investment decisions and exit performance. Specifically, such coverage, especially positive coverage, significantly increases the probability and amount of VC investments in start-ups. It also significantly improves the exit performance of VC investments. The significant effects of media coverage of start-ups on VC investments are driven by market-oriented instead of state-controlled media. We further find that VC investments in a focal start-up are significantly influenced by the average media coverage of other start-ups in the same industry or the same city. Our results are robust to a battery of robustness tests. Our research contributes to the behavioral finance literature by showing that an increasingly prominent type of institutional investors, venture capitalists, just like individual investors, are also subject to limited attention. Our research also extends the research by You, Zhang and Zhang (2018) by revealing the heterogeneous effects of market-oriented and state-controlled media on VC investments. Last but not the least, we are the first to discover that peer start-ups’ media coverage matters for VC investments in the focal firms, thereby pushing the frontier of research on the roles of media in finance.