We study the mandated introduction of a supervised auction for the primary bond market in China. The regulatory intervention significantly reduced the cost of debt for Chinese issuers. Most of the benefits flowed from reduced agency conflict between underwriters and issuers. Using unique bidder-level data from a lead underwriter, we develop replicable tools and techniques to identify collusive bidding behavior resulting in artificial (and economically costly) increases in bond yields. Such evidence can benefit global regulators, issuers, and investors currently using unsupervised auction mechanisms, for example, in securities issuance, construction projects, and procurement.

Exploiting the unexpected Central Environmental Inspections (CEI) in China as a quasinaturalexperiment, we find that public firms in polluting industries experience significant gains in both profitability and market valuation after the regulatory shock, relative to firms in nonpolluting industries. The outperformance of public firms can be explained by the retreat of their private competitors, many shut down due to poor environmental performance. Because firms seeking public listing are required to meet high environmental standards, CEI significantly strengthen public firms’ competitive position, leading to increased sales growth and market share. Moreover, the outperformance is more pronounced for firms with more eco-friendly technologies, consistent with strict environmental regulations increasing the marginal benefit of these technologies. We provide novel evidence of the bright side of environmental regulation by highlighting the importance of industry dynamics.

This paper employs a difference-in-differences approach to study whether a Chinese audit firm improves its competencies through organizational learning after one of its audit teams has a client cross-listed in the US. Among a group of companies that are listed only in China, we define those audited by firms that have cross-listed clients as the treatment group, and companies audited by other firms as the control group. We find an improvement in audit quality for the treatment group after their audit firms have cross-listed client experience in the US. A large-scale survey of auditors corroborates these findings and sheds light on specific actions undertaken by audit firms to facilitate learning. Both the empirical and survey results highlight the benefits of auditing crosslisted clients in the US and its positive externality on improving the audit quality of non-US-listed companies.

As the world’s two largest economies, China and the US are currently experiencing political and economic friction. This conflict brings high uncertainty to financial markets. Assessing risk spillover effects in a sector level will help us to characterize international risk contagions. We construct a multilayer network to examine tail risk spillovers between China and the US and find that (1) the value of total connectedness rises amidst tensions but declines during reconciliations; (2) interlayer spillovers mainly manifest as extreme pulses instead of steady outflows, which implies a significant increase in the frequency and magnitude of interlayer spillovers requires vigilant monitoring; and (3) compared with the in-strength, the out-strength is more concentrated, which represents that some sectors may play the role of major interlayer transmitter in tail risk spillovers. Monitoring interlayer spillovers helps policymakers and investors respond to emerging systemic threats.

Using the data of Chinese listed firms from 2003-2020, this study applies a System GMM estimation approach to document that high local government ecological concerns increase a firm’s stock price crash risk. This finding remains consistent after addressing endogeneity issues and undergoing robustness checks. This study also reveals that the implementation of the new environmental protection law in 2015 mitigates the relationship between local government ecological concerns and stock price crash risk. Further analyses indicate that stricter environmental regulation and high subsidies, as well as enhanced corporate social responsibility and governance, can effectively alleviate the adverse effect of local government ecological concerns on stock price crash risk. In addition, we note that the influence of local government ecological concerns on stock price crash risk is more significant in the eastern region, heavily polluting industries, and non-SOEs. Lastly, the research identifies two potential channels through which local government ecological concerns can impact stock price crash risk by reducing the quality of information disclosure and intensifying investor disagreement.

Climate change shocks pose a threat to the stability of the financial system. This study examines the influence of climate risks on systemic risk in the Chinese market by utilizing extreme risk spillover network. Moreover, we construct climate risk indices for physical risks (abnormal temperature), and transition risks (Climate Policy Uncertainty). We demonstrate a significant increase in systemic risk due to climate risks, which can be attributed, in part, to investor sentiment. Furthermore, institutional investors can mitigate the adverse impact of climate risks. Our findings suggest that policymakers and investors need to exercise greater vigilance in addressing climaterelated adverse effects.

In this paper, we present an entropy-based approach to measure the asymmetry of stock returns. By applying this approach, we use the Bootstrap method that our asymmetry measure exhibits a significantly enhanced ability to detect asymmetry compared to skewness. Moreover, our empirical findings reveal that stocks characterized by higher upside asymmetries, as determined by our innovative entropy measure, exhibit lower average returns across a crosssection of stocks. This supports the conclusions drawn by Han et al. (2018). In contrast, when employing the three-moment skewness measure, the relationship between asymmetry and stock returns remains inconclusive within the Chinese market.

This paper addresses the dynamic tail risk in price-limited financial markets. We propose a novel censored autoregressive conditional Fr´echet model with a fiexible evolution scheme for the time-varying parameters, which allows deciphering the impact of historical information on tail risk from the viewpoint of different risk preferences. The proposed model can well accommodate many important empirical characteristics, such as thick-tailness, extreme risk clustering, and price limits. The empirical analysis of the Chinese stock market reveals the effectiveness of our model in interpreting and predicting time-varying tail behaviors in price-limited equity markets, providing a new tool for financial risk management.

As digital transformation strategies have emerged as a primary approach for enterprises to enhance their Total Factor Productivity (TFP), it is crucial to empirically examine the impact of these strategies on TFP. For this purpose, this study considers these transformation strategies as a quasi-natural experiment and employees a propensity score-weighted difference-indifferences methodology on data from Chinese firms listed on the A-share market between 2007 and 2020. The key findings include: (1) digital transformation has a significant positive influence on TFP; (2) Generalized boosted regression trees analysis reinforces this finding after controlling for other TFP determinants; (3) notably, non-state-owned and technology-intensive enterprises exhibit a more distinct enhancement in TFP following digital transformation. These results underscore the need for firms to increase investment in research and development capabilities and digital competencies.

This study examines the influence of ESG report textual similarity on stock price synchronicity within the Chinese A-share market. Using advanced textual analysis methods, including TF-IDF and LDA, we measure the textual similarity of ESG reports among industry peers. Our results reveal a positive association between ESG report textual similarity and stock price synchronicity, suggesting that ESG reports with high textual resemblance may not convey distinct market information. This research underscores the importance of textual distinctiveness in ESG reports and offers a fresh perspective on the role of non-financial information, particularly related to CSR, in stock pricing dynamics. By emphasizing the significance of ESG report textual distinctiveness, we contribute to the broader discourse on ESG disclosure behaviors and their implications for capital market efficiency.