This paper investigates whether increased female representation on corporate boards affects firms’ bond financing costs. Exploiting the 2017 Big Three’s campaigns as a plausibly exogenous shock, we document that firms experiencing larger increases in female board representation, induced by the campaigns, experience significant reductions in bond yield spreads and improvements in credit ratings. We identify reduced leverage and enhanced workplace environment as key mechanisms, and show that the effects are stronger among firms with greater tail risk and information asymmetry. An alternative identification strategy based on California’s SB 826 regulatory mandate yields consistent results. Our findings suggest that board gender diversity enhances governance in ways valued by credit markets.

As digital technologies proliferate, firms increasingly leverage digital transformation strategically, necessitating new orientations attuned to digital technological change. This study investigates how digital orientation (DORI)- the philosophy of harnessing digital technology scope, digital capabilities, digital ecosystem coordination, and digital architecture configuration for competitive advantage – influences firms’ environmental, social, and governance performance (ESG_per). Analysis of Chinese A-share firms from 2010-2019 reveals DORI is associated with superior ESG_per, operating through the mediating mechanism of enhanced digital finance (DIFIN) as a fund-providing facilitator for sustainability initiatives. Additional analysis uncovers important heterogeneities – private firms, centrally owned state-owned enterprises, politically connected, and emerging companies exhibit the strongest DORI - ESG_per linkages. Prominently, the study findings are validated through a battery of robustness tests, including instrumental variable methods, and propensity score matching. Overall, the results underscore the need for firms to purposefully develop multifaceted digital orientation and furnishes novel theoretical insights and practical implications regarding DORI’s role in improving ESG_per.

We examine the relationship between customer concentration and capital structure adjustment speed using a sample of US listed firms from 1977 to 2020. We found that the customer-concentrated firms have a lower speed of leverage adjustment. Customer concentration affects leverage adjustment speed mainly through increased cash flow volatility and asset specificity. The negative association is more pronounced in firms with high relationship-specific investments and low switching costs for their customers. Stock market reacts to leverage deviation strongly for firms with concentrated customers. Our findings highlight the vital role of customers as key stakeholders in capital structure decisions.

This study examines how firm-level exposure to the COVID-19 pandemic affects the speed of leverage adjustment among 3260 US-listed firms from 2019q1 to 2022q1. Using a novel measure of COVID-19 exposure, we find that higher exposure significantly reduces the speed at which firms adjust their leverage towards target levels. This effect is more pronounced for financially constrained firms and those operating in competitive markets. We further show that COVID-19 exposure adversely impacts corporate liquidity, default risk, and financial flexibility. Our findings highlight the role of exogenous shocks in shaping corporate financing decisions.

Local financial development is crucial for advancing regional financial supply side structural reform, enabling local governments to leverage financial instruments to effectively mobilize land resources and foster competitive growth. The introduction of numerous financial products linked to land-related rights and interests has resulted in a pronounced transmission and interconnection of fiscal and financial risks across regions. This study examines the impact of local financial development on land financialization in China using panel data from prefecture-level cities and detailed information on land mortgages. The findings indicate that the establishment of city commercial banks (CCBs) contributes to the progress of land financialization by incentivizing local government financing vehicles to participate in land mortgage financing, increasing the transfer of debt risks to the financial sector. Notably, the impact of CCBs on land financialization is more pronounced in regions with urban agglomeration, high GDP manipulation, inadequate local financial regulation, and robust implicit government guarantees. Further analysis reveals that CCB establishment has negative spillover effects on land financialization in neighboring areas, while expansion strategies such as establishing intercity branches, engaging in cross-regional mergers, and relaxing regulations have mitigated the rise of land financialization at the regional level. This study provides policy recommendations that focus on reducing local governments’ reliance on land financing and enhancing the prevention and management of financial risks.

We demonstrate that personal political preferences of corporate managers influence cor- porate policies. Specifically, Republican managers who are likely to have conservative personal ideologies adopt and maintain more conservative corporate policies. Those firms have lower levels of corporate debt, lower capital and research and development (R&D) expenditures, less risky investments, but higher profitability. Using the 9/11 terrorist attacks and Sept. 2008 Lehman Brothers bankruptcy as natural experiments, we demonstrate that investment policies of Republican managers became more conservative following these ex- ogenous uncertainty-increasing events. Furthermore, around chief executive officer (CEO) turnovers, including CEO deaths, firm leverage policy becomes more conservative when managerial conservatism increases.

This paper investigates the supervisory incentive effects of employee stock ownership plans based on a corporate risk-taking perspective using data from a sample of Chinese A-share listed companies from 2006-2021. The results show that employee stock ownership plans significantly enhance corporate risk-taking. The specific mechanism is that employee stock ownership plans reduce the two-tier agency costs between shareholders and managers and managers and employees, alleviate corporate financing constraints, and thus enhance the level of corporate risk-taking. It is also found that employee stock ownership plan enhances the level of corporate risktaking with high quality, because employee stock ownership plan not only promotes R&D investment which is beneficial to corporate value growth, but also reduces excessive investment and high debt which are detrimental to corporate value, and the corporate risk-taking is of higher quality and more substantial value effect. In addition, differences in the institutional design of employee stock ownership plans have different effects on corporate risk-taking: employee stock ownership plans that are leveraged, highly discounted, with longer lock-up periods and duration, and entrusted to third-party institutions have a stronger effect on corporate risk-taking; employee subscriptions can promote corporate risk-taking more than executive subscriptions; employee stock ownership plans in China do not have the problem of "free-riding There is no "free-rider" problem in China's employee stock ownership plan. The larger the issuance ratio of the employee stock ownership plan, the greater the number of participants, and the larger the scale of capital, the better the implementation effect.

The healthy operation of the stock market relies on sound liquidity. We utilize the semantic information from disclosure texts of listed companies on the China Science and Technology Innovation Board (STAR Market) to construct a daily corporate network. Through empirical tests and performance analyses of machine learning models, we elucidate the relationship between the similarity of company disclosure text contents and the temporal and spatial correlations of stock liquidity. Our liquidity indicators encompass trading costs, market depth, trading speed, and price impact, recognized across four dimensions. Furthermore, we reveal that the information loss caused by employing Minimum Spanning Tree (MST) topology significantly affects the explanatory power of network topology indicators for stock liquidity, with a more pronounced impact observed at the document level. Subsequently, by establishing a neural network model to predict next-day liquidity indicators, we demonstrate the temporal relationship of stock liquidity. We model a liquidity predicting task and train a daily liquidity prediction model incorporating Graph Convolutional Network (GCN) modules to solve it. Compared to models with the same parameter structure containing only fully connected layers, the GCN prediction model, which leverages company network structure information, exhibits stronger performance and faster convergence. We provide new insights for research on company disclosure and capital market liquidity.

This study explores how foreign competition impacts the capital structure of domestic firms. While import competition is associated with a decrease in domestic firms’ leverage, we propose a novel perspective concerning the positive effect of inward foreign direct investment (FDI) on leverage. FDI competition can boost demand for debt via productivity spillover to domestic firms, and also increase supply of debt by inducing lenders to herd toward foreign investors. Using Chinese firm-level data, we find that the positive effects of industry inward FDI on domestic firms’ leverage are more pronounced in high-tech industries and industries where foreign investors exhibit a high degree of herding behavior. Our instrument variable approach, employing industry exchange rates and import tariffs, supports these findings. Additionally, we reveal that the positive effect of FDI on local firms’ leverage is amplified when the firms have stronger absorptive capacities, receive foreign capital, and experience more human capital transfers from foreign rivals.

A lack of sufficient information about potential borrowers is a major obstacle to access to financing from the traditional financial sector. In response to the need for better information to prevent fraud, to increase access to finance and to support balanced sustainable development, countries around the world have moved over the past several decades to develop credit information reporting requirements and systems to improve the coverage and quality of credit information. Until recently, such requirements mainly covered only banks. However, with the process of digital transformation in China and around the world, a range of new credit providers have emerged, in the context of financial technology (FinTech, TechFin and BigTech). Application of advanced data and analytics technologies provides major opportunities for both market participants – both traditional and otherwise – as well as for credit information agencies: by utilizing advanced technologies, participants and credit reporting agencies can collect massive amounts of information from various online and other activities (‘Big Data’), which contributes to the analysis of borrowing behavior and improves the accuracy of creditworthiness assessments, thereby enhancing availability of finance and supporting growth and development while also moderating prudential, behavioral and conduct related concerns at the heart of financial regulation. Reflecting international experience, China has over the past three decades developed a regulatory regime for credit information reporting and business. However, even in the context of traditional banking and credit, it has not come without problems. With the rapid growth and development of FinTech, TechFin and BigTech lenders, however, have come both real opportunities to leverage credit information and data but also real challenges around its regulation. For example, due to fragmented sources of borrower information and the involvement of many players of different types, there are difficulties in clarifying the business scope of credit reporting and also serious problems in relation to customer protection. Moreover, inadequate incentives for credit information and data sharing pose a challenge for regulators to promote competition and innovation in the credit market. Drawing upon the experiences of other jurisdictions, including the United States, United Kingdom, European Union, Singapore and Hong Kong, this paper argues that China should establish a sophisticated licensing regime and setout differentiated requirements for credit reporting agencies in line with the scope and nature of their business, thus addressing potential for regulatory arbitrage. Further, there is a need to formulate specific rules governing the provision of customer information to credit reporting agencies and the resolution of disputes arising from the accuracy and completeness of credit data. An effective information and data sharing scheme should be in place to help lenders make appropriate credit decisions and facilitate access to finance where necessary. The lessons from China’s experience in turn hold key lessons for other jurisdictions as they move from credit information to credit data regulation in their own financial systems.