We study how public credit information affects corporate debt financing. Using the staggered rollout of China's Social Credit System as a quasi-natural experiment, we find that public disclosure of credit information significantly lowers corporate bond yield spreads. The effect is stronger in regions with stricter disclosure requirements and enforcement, and among firms with greater information asymmetry and weaker monitoring. Consistent with reduced informational frictions, the reform is associated with fewer bond covenants, lower secondary-market yields, and improved liquidity. Our findings highlight the role of digital public information in enhancing debt market efficiency.

As an emerging market, China's capital market is still developing, and stock mispricing due to information asymmetry is common. As the primary spokesperson for information disclosure, the Board Secretary plays a pivotal role in mitigating this issue. This study examines the impact of Board Secretary shareholding on stock mispricing using a sample of Chinese A-share listed companies from 2010 to 2020. The findings show that shareholding significantly reduces mispricing. This effect is more pronounced in firms with lower media attention, suggesting it compensates for weak external monitoring. Furthermore, the reduction is primarily achieved by improving the quality of analyst forecasts. This research provides insights into mitigating mispricing and optimizing the governance of Board Secretaries.

This paper develops a theoretical and empirical framework to analyze China's interest rate corridor, focusing on the Standing Lending Facility (SLF). We construct a general equilibrium model featuring an explicit corridor and a novel accessibility cost friction (α), which captures implicit costs during SLF application. The theoretical properties of the model explain key stylized facts associated with the corridor operation. The study highlights several fundamental properties of the corridor as a policy framework: 1) Both the width and the midpoint of the corridor are active policy tools, implying that SLF and Interest on Excess Reserves (IOER) policies should be designed cohesively within the unified corridor framework; 2) The policy's efficiency varies with the level of market liquidity; and 3) The corridor framework allows for a separation between price-based and quantity-based monetary policy instruments. Empirically, we employ the Joint Power Prior (JPP) Bayesian estimation to quantify the α time series, identifying structural breakpoints that align with major policy and market events. This study provides a quantitative tool for monitoring SLF transmission efficiency.

Taking China’s environmental “fee-to-tax” reform as a quasi-natural experiment, this paper employs a difference-in-differences (DID) approach to examine the impact of the green tax reform on firms’ cost of equity on a sample of A-share listed firms from 2012 to 2023. The results show that the implementation of the Environmental Protection Tax Law significantly reduced the cost of equity for heavily polluting firms. This finding remains robust after a series of robustness checks. Analyses of the underlying mechanisms reveal that the green tax reform lowered the cost of equity primarily through the channel of “Porter effect.” Moreover, the effect is more pronounced among firms located in the eastern China, those with stronger internal governance, and those operating in a stricter external monitoring environment.

This paper investigates whether and how independent director-affiliated corporate donations affect stock price crash risk in China. We find a significant positive relationship between affiliated donations and future crash risk. The relationship is more significant for firms with weak internal governance and limited external monitoring, when affiliated directors serve on the audit committee, and in non-state-owned enterprises. Overall, our findings suggest that the social ties built through affiliated donations undermine rather than enhance director monitoring, and that agency theory has more explanatory power than resource dependence theory for understanding the impact of affiliated donations on stock price crash risk.

This article examines the link between foreign institutional holdings and firms’ efficiency in labor investment in the setting of Chinese markets. We find that foreign institutional investors enhance firms’ labor investment outcomes primarily through mitigating asymmetric information and by strengthening internal governance. Specifically, the influence of foreign institutional investors on a firm’s labor investment efficiency is stronger when the firm faces greater labor adjustment frictions. This effect is more evident when foreign institutional investors are originated from countries or areas with stronger cultural connections to China, stronger governance quality, common law traditions, or stronger bargaining power in the firms’ governance. Our paper contributes to the literature in that it documents the monitoring role of foreign institutional investors from the perspective of firms’ labor investment decisions, and adds to the literature on the drivers of firms’ labor investment choices.

Research Question/Issue: This study investigates whether and how political connections affect customer complaints in the Chinese market, using a comprehensive dataset from the country’s largest online complaint platform. Research Findings/Insights: Analyzing 22,644 firm-year observations from 2018 to 2023, we find that politically connected firms experience significantly fewer customer complaints. A one-unit increase in political connection strength is associated with a 9% reduction in complaints relative to the sample mean. This effect operates through two primary mechanisms: a reputation-motivation channel and a financial resource channel. The mitigating effect is more pronounced for firms in highly marketized regions, those with higher advertising expenditures, companies facing greater earnings pressure, and those with lower tangible asset ratios. Theoretical/Academic Implications: Our study contributes to the literature on political connections and corporate governance by demonstrating how political capital translates into tangible consumer experience advantages. It also advances research on the determinants of customer complaints by highlighting the role of internal governance mechanisms, particularly managerial political ties. Our findings support the Corporate Reputation and Financial Resource Hypotheses while challenging alternative explanations based on regulatory shielding or managerial complacency. Practitioner/Policy Implications: For corporate leaders, our results underscore the importance of reputation management and quality investment, particularly when political connections are absent. Policymakers should consider strengthening public monitoring institutions to reinforce reputational incentives across markets. Investors may use customer complaints as an indicator of product quality and operational stability in their investment decisions.

Recent technological advancements have enabled the emergence of business organizations fully managed by algorithms, such as decentralized autonomous organizations (DAOs) or through artificial intelligence (AI), as observed in China’s online food delivery sector. These organizations are collectively referred to as algorithm-managed firms (AMFs). Given machines’ capabilities in data collection and analysis, human directors are increasingly being replaced by algorithms or AI in specific sectors. This article contends that algorithms can effectively take over human directors’ managerial, monitoring, and mediating roles. The diminishing role of human directors raises certain concerns of stakeholder protection. Unlike human directors, algorithm directors or managers would not consider stakeholders’ interests unless clearly instructed to do so. However, the algorithm supplier and the AMFs may lack the incentives to fully consider stakeholders because they do not always internalize the social costs. To address the challenges of AMFs, policymakers need to consider different regulation strategies. First, they must choose between command-and-control regulations and target-based regulations. Command-and-control regulations often do not work well because regulators lack enough information or control over complex algorithms. Instead of setting detailed technical rules, policymakers should adopt target-based regulations that let the algorithm balance various interests and regulate its own operations. Second, policymakers should decide between entity-based and algorithm-based regulations. Algorithm-based regulation is more suitable because it prevents companies from passing costs onto society. The state could consider regulating the composition of the board of directors of the algorithm supplier to ensure that they incorporate the concerns of stakeholders’ interests in the development of the algorithm. Additionally, corporate law doctrines that protect creditors and other stakeholders, such as piercing the corporate veil and limiting liability for corporate torts, must be revisited and modified because their foundational assumptions no longer align with the realities of AMFs.

This study examines the mean-reversion behavior of trading volume in China’s A-share market, with a focus on the speed at which abnormal surges dissipate. We compare two competing hypotheses: the stealth-trading hypothesis, where persistent volume reflects order-splitting by informed traders, and the informational-efficiency hypothesis, which interprets faster reversion as a sign of efficient information absorption. Using the Ornstein–Uhlenbeck (OU) model, we estimate the reversion speed for over 3,000 stocks and link it to firm- and industry-level characteristics. We find that trading volume is strongly mean-reverting, with over 98% of stocks classified as stationary. The OU model forecasts reversion speed with less than 7% error. Faster reversion is associated with larger size, higher analyst coverage, lower volatility, and greater liquidity. Notably, reversion speed increased after the 2006 IFRS reform but declined following Stock Connect, suggesting that stock market policies can influence informational efficiency. Our OU-based methodology offers a simple, observable proxy for monitoring how quickly markets process information. These results position trading volume as a core variable in market microstructure research and policy evaluation.

In emerging markets characterized by signiffcant information asymmetry, mitigat-ing firm-level risk is paramount for market stability. While the governance role ofinstitutional investors is known, the impact of their direct, on-the-ground engagementremains underexplored. This study’s objective is to investigate how institutionalinvestor site visits, a crucial hands-on governance mechanism, affect stock returnvolatility. Using a sample of Chinese-listed A-share firms from 2012 to 2022, wefind that frequent site visits significantly reduce firm-level stock return volatility.This risk-reduction effect is more pronounced for firms with greater agency problems,poorer ESG performance, and higher expropriation risk. Our analysis, robust toendogeneity concerns, indicates this effect is driven by improved external oversight.We conclude that direct institutional engagement is a vital channel for reducinginformation asymmetry, enhancing corporate governance, and ultimately promotingmarket stability by lowering investment risk.