Does digital financial inclusion alleviate poverty? This study investigates this question by integrating the Digital Financial Inclusion Index of Peking University with microdata from the China Family Panel Studies (CFPS) to examine how the expansion of digital financial inclusion affects household multidimensional poverty in China. Anchored in Amartya Sen ’ s capability approach and operationalized through the Alkire–Foster (A–F) framework, the study identifies multidimensional poverty across five key dimensions: income, health, education, insurance, and living standards. Probit models are employed to estimate how digital financial inclusion influences both the likelihood and structure of multidimensional poverty, while instrumental variable techniques are used to address potential endogeneity. Beyond the average effects, the study further explores the mechanisms through which digital financial inclusion contributes to poverty alleviation, focusing on three channels—promoting household consumption, increasing financial investment, and enhancing access to credit. The results reveal that digital financial inclusion significantly mitigates multidimensional poverty, particularly by improving income, living standards, and health outcomes, though its effects on education and insurance are limited. These findings underscore the transformative role of digital finance in fostering inclusive growth, suggesting that policies expanding digital financial infrastructure and literacy can amplify its poverty-reducing effects and advance equitable development.

This paper examines the impact of Chinese local government hidden debt on corporate ESG greenwashing. Extending fraud theory, we reveal that hidden debt shifts the boundary between government and market that drives the factors behind ESG greenwashing. Using the ESG greenwashing indicator of listed firms in the A-share market and the hidden debt-to-GDP ratio of 31 provinces from 2012 to 2023, we find that local government hidden debt is positively correlated with corporate ESG greenwashing. The impact is more significant for firms that are state-owned, without active primary-level Party organizations, or not on China’s key pollution supervisory list. Mechanism analysis indicates that expansion of local government hidden debt brings firms with higher LGFVs’ share-holding for the SOEs, heavier environmental tax burden, and less social responsibility preference, all of which are related with ESG greenwashing. Reducing local government special debt and improving tax compliance can help alleviate this impact. These findings highlight the necessity of fiscal risk management in achieving genuinely sustainable corporate development.

The commodity and financial characteristics of carbon emission allowances play a pivotal role within the Carbon Emission Trading Scheme (CETS). Evaluating the effectiveness of the scheme from the perspective of carbon price is critical, as it directly reflects the underlying value of carbon allowances. This study employs a time-varying Difference-in-Differences (DID) model, utilizing data from publicly listed enterprises in China over the period from 2010 to 2023, to examine the effects of carbon price level and stability on Total Factor Productivity (TFP). The results suggest that both an increase in carbon price level and stability contribute to improvements in TFP, particularly for heavy-polluting and non-stateowned enterprises. Mechanism analysis reveals that higher carbon prices and stability can stimulate corporate engagement in green innovation, activate the Porter effect, and subsequently enhance TFP. Furthermore, optimizing the system environment proves to be an effective means of strengthening the scheme's impact. The study also finds that allocating initial quotas via payment-based mechanisms offers a more effective design. This research highlights the importance of strengthening the financial attributes of carbon emission allowances and offers practical recommendations for increasing the activity of trading entities and improving market liquidity.

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.

Under the goal of carbon peaking and carbon neutrality, taking environment, social responsibility, and corporate governance (ESG) as the important investment factor has become an action guide and standard for capital market participants. The practice of the ESG concept is not only a new way for enterprises to form new asset advantages and realize green and low-carbon transformation, but also important access for promoting high-quality and sustainable development. Based on Chinese-listed companies within the period of 2009 to 2015, we investigate the impact of ESG responsibility performance on export performance as well as its mechanism. We theorize and find out show that ESG responsibility performance can significantly and stably promote enterprises’ export performance. Mechanism analysis shows that ESG can improve export performance by reducing financing costs and easing financing constraints, and the green technology innovation effect is also an important channel for ESG to affect export performance. Therefore, government should strengthen the supervision and incentive of ESG performance, encourage enterprises to improve their environmental, social and governance performance in order to adapt to the goal of carbon peak and carbon neutrality and promote the high-quality development of export trade. Future research may consider combining ESG accountability with other factors such as supply chain management, intermediate imports, and transnational spillovers to more fully understand its impact on export performance, so as to create more value for society.

It has been widely recognized that firms’ environmental, social, and governance (ESG) performances are crucial for shaping their information environments. Nonetheless, the impact of ESG performances on important analyst report attributes still remains clear. Our study reveals that superior firm. ESG performances significantly enhance the analyst report readability. The mechanism analysis demonstrates that this effect is primarily driven by increased information accessibility (the information acquisition channel) and greater analysts’ research efforts (the analyst effort channel). As expected, this effect is more pronounced in firms operating in highly polluted industries, firms with opaque financial infomration and state-owned enterprises (SOEs). Finally, our findings reveal that the release of analyst reports triggers higher market reactions for firms with superior ESG performances. In overall, our study highlights the criticial role of firm ESG performances in boosting financial analysts’ information production process.

This paper investigates how institutional investors’ site visits affect firm productivity by using a dataset of China’s A-share listed firms. The findings reveal that site visits have a constructive effect on firm productivity. Moreover, mechanism analysis indicates that reducing information asymmetry and improving stock price informativeness are two channels through which site visits influence firm productivity. Heterogeneity analysis demonstrates that the nexus between site visits and firm productivity is more pronounced for non-state-owned firms and firms with intenser product market competition. Overall, this study brings new insights into the benefits of site visits and highlights the importance of investor activism.

This paper examines the impact of green mergers and acquisitions (M&As) on firms’ transition to green exports. We develop a “Technology-Qualification” theoretical framework and conduct the empirical analysis using a matched dataset of Chinese listed manufacturing firms and customs records. The findings show that green M&As significantly promote firms’ green exports, and this effect remains consistent across a series of robustness test. Mechanism analysis reveals that green M&As promote green exports through two key channels: green innovation spillovers and green qualification spillovers. Further heterogeneity analysis indicates that the positive impact of green M&As on green exports is more pronounced among firms with stronger operational performance, weaker green foundations, and those involved in processing trade. In addition, green M&As not only stimulate green exports but also prevent the entry of polluting products and reduce the exit of green product, thereby driving a green-oriented dynamic restructuring of firms’ export structure. This paper offers micro-level insights into how firms can navigate the dual challenges of enhancing green production capabilities and overcoming barriers to green trade during their transition to green exports.

Shill bidding, the use of non-genuine bids to inflate prices, undermines auction market integrity. Exploiting China’s online judicial housing auctions as a laboratory, we identify 2% of participants as suspected shill bidders, affecting 8% of auctions. They raise price premium by 14.3%, causing an annual deadweight loss of ¥570 million for homebuyers. Mechanism analysis reveals they create bidding momentum and intensify competition. We establish causality using a difference-in-differences analysis leveraging a 2017 regulatory intervention and an instrumental variable approach using dishonest judgment debtors. These findings offer actionable insights for policymakers and auction platforms to combat fraud in online high-stake auctions.

We collect the geographical dataset of bank physical branch in China from 2008 to 2023, obtaining the 261,382 branches. Through careful data processing, we calculate the bank branch closure at city-level and merge it with regional entrepreneurship in China. With the panel dataset at city-industry-year level, we find that bank branch closure (BBC) significantly reduces neighbor entrepreneurship, which is proxied by the number of new firm entry. In mechanism analysis, we document that bank branch closure affects entrepreneurship through the financing channel and mobility channel. We also find that commercial bank branch closure plays a crucial role in affecting entrepreneurship. The reduction effect of BBC is more pronounced for those observations located in geographical intersections, coastal lines. Further, we explore the impact of BBC on the direction of entrepreneurship, showing that there is less new firm formation in manufacture industry after the BBC. In addition, we show that BBC may contribute to the entrepreneurship failure as well. Our findings may shed light on the policy makers, bank owners and those who want to form a new firm.