Between high-quality and high-efficiency green innovation, which can truly reduce stock price crash risk? We use data from Chinese listed companies from 2010 to 2022 to study the impact mechanism and effect of radical and incremental green innovation stock price crash risk. Results show that radical green innovation can significantly reduce stock price crash risk, and this effect is more evident than the incremental one. Radical green innovation can improve information efficiency and enhance risk management, thus reducing stock price crash risk. Besides, among companies held by trading institutions and with low analyst coverage, the inhibitory effect is more evident.

ESG is emerging as a new benchmark for measuring a company's sustainable development capabilities and social impact. As a measure of ESG performance, ESG ratings are increasingly receiving attention from companies, the general public, and government institutions, and are becoming an important reference factor influencing their decision-making. This paper investigates the impact of corporate ESG ratings on Total Factor Productivity (TFP) and its mechanisms of action. Focusing on listed companies in China, we find that higher ESG ratings contribute to improving a company's TFP, and this conclusion remains valid after robustness tests and addressing endogeneity issues. Further exploration into the reasons behind this result reveals that ESG ratings can be seen as a signal that a company sends to the outside world, representing its overall performance. Higher ESG ratings enhance a company's TFP by reducing market financing constraints and obtaining government subsidies. Heterogeneity analysis shows that the positive impact of ESG ratings on TFP is more pronounced for companies with higher levels of attention, reputation, and audit quality. Additionally, we explore whether ESG ratings can serve as a predictive indicator for measuring a company's TFP. This hypothesis was tested using machine learning algorithms, and the results indicate that models incorporating ESG rating indicators significantly improve the accuracy of predicting a company's TFP capabilities.

Informal institutions can play a crucial role in fostering corporate and policy innovation, especially when formal institutions are weak. However, their intangible nature makes them difficult to quantify. In this paper, we proxy the strength of kinship-based informal institutions using surname homogeneity among business owners, specifically, the extent to which they share a limited number of surnames within the same county. Our analysis reveals that a one-standard-deviation increase in the strength of informal institutions leads to a 21.1% increase in patent filings and an 18.9% increase in policy innovation. We find that kinship-related informal institutions foster corporate innovation by compensating for weak formal institutions, enhancing protection for intellectual property rights, facilitating access to finance, improving public service delivery, and promoting supply chain cooperation. We also suggest that kinship-related informal institutions encourage local governments to engage in policy experimentation, which relies on the collaboration of business owners. This experimentation process is easier to coordinate and monitor in counties dominated by a few kinship networks. Both informal institutions and policy innovation contribute to economic development and foster entrepreneurial market entries. However, the positive impact of informal institutions declines over time as formal institutions strengthen in China.

We examine the impact of state-owned shareholders on fraud within private firms. Utilizing a sample of A-share private listed firms in China observed from 2008 to 2021. We discover a significant negative association between state-owned shareholders and the likelihood of fraud in private firms. State-owned shareholders primarily act as inhibitors of fraud, and their effect on the probability of fraud being detected is not statistically significant. This finding remains robust even after conducting a series of sensitivity tests to mitigate potential selectivity bias and reverse causality endogeneity issues. In the analysis of heterogeneity, we found that state-owned shareholders play a more active role under conditions of imperfect external institutional development, and they also exert a more significant inhibitory effect on enterprises with lower governance levels and higher business risks. Our mechanism test demonstrates that the inhibitory effect of state-owned shareholders on corporate fraud is achieved by improving corporate governance and alleviating financial distress. This study also examines the impact of state-owned shareholders' local characteristics, external supervision mechanisms, and internal governance mechanisms in unique Chinese enterprises on fraudulent behaviour by private enterprises. Overall, our study provides empirical evidence that state-owned shareholder ownership is associated with reducing fraudulent behaviour within private firms.

Based on the sample of Chinese A-listed firms from 2003 to 2020, this paper investigates the effect of common institutional ownership on labor income share. The result shows that common institutional ownership can significantly increase firms’ labor income share. Mechanism tests indicate that common ownership can: 1) alleviate financial constraints by reducing the debt financing costs and increasing the trade credit financing, thus increasing the labor income share; 2) improve corporate innovation and therefore enhances the demand for highly-skilled labor, which eventually boost labor income share. Competitive hypothesis test represents that common institutional ownership can reduce the monopoly power of enterprises and decrease monopoly rent, so as to increase the proportion of labor in the distribution. Further analyses present that the network formed by the common ownership can effectively exert the financing support role of SOEs and the knowledge spillover effect of innovative-advantage firms, which contributes to the labor income share increasing of other related firms in the network connection. This study not only enriches the economic consequences of common institutional ownership, but also provides policy guidance for the government to further optimize the income-distribution pattern by deepening the reform of the financial market.

We examine whether large language models (LLMs) can extract contextualized representation of Chinese news articles and predict stock returns. The LLMs we examine include BERT, RoBERTa, FinBERT, Baichuan, ChatGLM and their ensemble model. We find that tones and return forecasts extracted by LLMs from news significantly predict future returns. The equal- and value-weighted long minus short portfolios yield annualized returns of 90% and 69% on average for the ensemble model. Given that these news articles are public information, the predictive power lasts about two days. More interestingly, the signals extracted by LLMs contain information about firm fundamentals, and can predict the aggressiveness of future trades. The predictive power is noticeably stronger for firms with less efficient information environment, such as firms with lower market cap, shorting volume, institutional and state ownership. These results suggest that LLMs are helpful in capturing under-processed information in public news, for firms with less efficient information environment, and thus contribute to overall market efficiency.

This study explores the price drivers of Chinese Emissions Allowances (CEAs) in the early stage of China’s national carbon market. Using daily time series data from July 2021 to July 2023, we find limited influence from conventional drivers, including energy prices and economic factors. Instead, national power generation emerges as a significant driver. These are primarily due to the distinct institutional features of China’s national carbon market, notably its rate-based system and sectoral coverage. Moreover, the study uncovers cumulative abnormal volatility in CEA prices ranging from 12% to 20% around the end of the first compliance cycle, reflecting sentiments about the policy design and participants’ limited understanding about carbon trading. Our results extend previous literature regarding carbon pricing determinants by highlighting China’s unique carbon market design, comparing it with the traditional cap-and-trade programs, and offering valuable insights for tailored market-based policies in developing countries.

The economic institutionalist literature often suggests that sub-optimal institutional arrangements impart unique distortions in China, and excessive corporate debt is a symptom of this condition. However, lax monetary policies after the global financial crisis, and specifically, quantitative easing have led to concerns about debt bubbles under a wide range of institutional regimes. This study draws on data from Chinese listed firms, supplemented by numerous macroeconomic control variables, to isolate the effect of international capital flows from other drivers of firm leverage. We conclude that the rise in, and distribution of, Chinese corporate debt can partly be as-cribed to the effects of monetary policy outside of China and that Chinese institutional features amplify these effects. Whilst Chinese firms are affected by developments in the global financial ecosystem, domestic institutional realities and distortions may unevenly add their own particular effects, providing further support for and extending the variegated capitalism literature.

Purpose – This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experimentand investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aimsto provide some policy implications for corporate debt financing and further liberalization of the capital marketin China. Design/methodology/approach – Employing the exogenous event of Shanghai-Shenzhen-Hong Kong StockConnect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturitystructure. To validate the results, this study performed several robustness tests, including the parallel test, theplacebo test, the Heckman two-stage regression and the propensity score matching. Findings – This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on thedebt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit.Channel tests show that capital market liberalization improves firms’ information environment and curbsself-interested management behavior. Originality/value – This research provides empirical evidence for the consequences of capital marketliberalization and enriches the literature on the determinants of corporate debt maturity structure. Further thisstudy makes a reference for regulators and financial institutions to improve corporate financing through thegovernance role of capital market liberalization.

Using comprehensive account-level data and 192 asset pricing anomaly signals, we investigate whether retail investors and institutions trade on anomalies in China. We find that retail investors tend to trade contrary to anomaly prescriptions, suggesting that they have a strong tendency to buy (sell) overvalued (undervalued) stocks. In contrast, institutions trade consistent with anomalies, indicating that they buy (sell) undervalued (overvalued) stocks. Regarding the information content of anomalies, we find that small retail investors trade contrary to trading-based anomalies, whereas institutions trade consistent with both trading- and accounting-based anomalies. Additionally, lottery stock preference and return extrapolation help explain investors’ trading behavior on anomalies.