In the process of green transformation of China's economy, it is of great practical significance to study the impact of green finance in supporting the development of the real economy, especially the impact of green credit on enterprise innovation, in order to promote the green transformation of enterprises, industrial structure upgrading and sustainable economic development. This paper takes green credit as a perspective and introduces it into the analytical framework of the impact of environmental regulation on corporate green innovation, through theoretical mechanism analysis and empirical testing, in order to reveal the impact and mechanism of green credit on corporate green innovation. It is found that green credit can effectively promote green innovation in heavy polluting enterprises, and it is mainly reflected in the increase of green utility model patent applications with a low degree of inventiveness. The promotion effect of green credit on green innovation is more obvious in regions with lower levels of economic development. Further mechanism analysis shows that green credit policy promotes green innovation of heavy polluting enterprises mainly through the incentive effect brought by changing financing environment and the pressure effect brought by increasing market competition. The findings of this paper can provide references for policy-making departments, banks and enterprises.

In recent years, the attempt to curb state-owned enterprises (SOEs) has resulted in dedicated rules in trade agreements. This paper reveals significant paradigm shifts in cross-border SOE regulation by exploring the emerging SOE rules and contrasting them with SOE disciplines in WTO agreements. First, the emerging SOE rules shift the emphasis from regulating trade measures to the competitive behaviour of SOEs. More importantly, the emerging SOE rules are characterized by excessive focus on behaviour analysis and a per se approach. Under a per se approach, a violation of the emerging SOE rules could be established regardless of whether the behaviour of an SOE caused a harmful trade or competition effect. Finally, in light of SOE reform in China, the article contends that the emerging SOE rules’ behaviour analysis deviate cross-border SOE regulation from its primary goal of levelling the playing field.

The effects of skyscraper development on surrounding firms’ innovation in China is assessed in this paper, and empirical results show that skyscraper development significantly promotes the innovation of firms within 1 km of skyscrapers. However, such effect only exists around very tall skyscrapers in large cities. This means that skyscraper development in small cities often is unfit for the economic fundamentals of these cities, which may weaken the positive externalities generated by skyscrapers. The mechanism analysis in this paper shows that increased surrounding population density brought by skyscraper development and knowledge sharing between firms surrounding the skyscrapers and other firms in the same city are the main paths through which skyscrapers affect innovation.

The increasing awareness and adoption of technology, particularly artificial intelligence, are reshaping industries and daily life. This study explores how adopting artificial intelligence (AoAI) influences stock price crash risk for Chinese A-share listed companies between 2010 and 2020. The primary findings emphasize AoAI's significant role in reducing stock price crash likelihood, enhancing financial market performance, and mitigating manager opportunism. Further, the research identifies varied effects of AoAI on crash risk among different enterprise types, notably benefiting non-state-owned and non-foreign businesses. Additionally, the study finding supports the notion that financial analysts enhance transparency, reducing the risk of stock price crashes. These results underscore the Chinese government's role in shaping the digital economy. Overall, the study's findings remain consistent and robust across statistical methods like 2SLS, PSM, SysGMM, and instrumental variable analysis.

This study investigates whether and how the central discipline inspection of the securities regulators affects the information environment and investor valuation in the Chinese capital market. Based on the private equity placement (PEP) events, we find that the self-interested media outlets provide more negative coverage of the passed PEP firms during the inspection period than those passed outside the inspection period, resulting in poorer stock returns. Additionally, we find that the negative effect of the inspection on the PEPs’ market reactions is attenuated in media-connected firms and firms with higher advertising expenditure. However, we do not find significant long-term market performance differences between the passed PEP firms during the inspection period and those passed outside the inspection period. Additional results show that during the inspection period, the securities regulators tend to approve the PEP applicants with better initial announcement returns. Moreover, sophisticated investors pay a higher price for the shares of these passed PEP firms during the inspection period. Collectively, our findings suggest that anti-corruption campaigns have unintended effects that hinder retail investors’ access to objective information.

Widely used volatility forecasting methods are usually based on low frequency time series models. Although some of them employ high frequency observations, these intraday data are often summarized into a point low frequency statistic, e.g., a daily realized measure, before being incorporated into a forecasting model. This paper contributes to the volatility forecasting literature by instead predicting the next-period intraday volatility curve via a functional time series forecasting approach. In contrast with non-functional methods, the proposed functional approach fully exploits the rich intraday information and hence leads to more accurate volatility forecasts. This is further confrmed by extensive comparisons between the proposed functional method and those widely used non-functional methods in out-of-sample volatility forecasting for a number of stocks and equity indices from the Chinese market.

Using data from 123 reverse mergers (RMs) in China, this study investigates the determinants and economic consequences of auditor choice in RMs. We find that the choice of a new auditor instead of the incumbent auditor is not related to auditor competence but to the relative bargaining power of RM firms and publicly listed firms (shell firms), and that the probability of choosing new auditors is higher when RM firms have more bargaining power relative to shell firms. We also find that hiring new auditors in the RM is associated with a higher valuation of injected assets and higher pre-listing income-increasing discretionary accruals in RM firms. Furthermore, post-merger firms exhibit drops in accounting performance and firm value and are more likely to restate their financial reports within 3 years of listing when new auditors are appointed in RMs. Finally, the cross-sectional test shows that this effect mainly exists in the context of RMs where the newly appointed auditor is a non-Big 10 auditor and a non-specialist auditor. Overall, our results emphasize the role of RM firms and shell firms in auditor choice for RMs and highlight the implications of such a joint decision on investor protection.

From the perspective of corporate labor employment, we examine whether debt pressure on local governments prompts them to shift part of their social responsibilities to local firms. We conduct an analysis on Chinese local government debt (LGD) data and find that when LGD is higher, local firms are less likely to cut labor costs when their sales decrease, indicating greater labor cost stickiness. We attribute this to the responsibility-shifting effect, i.e., with heavier debt burdens, local governments intervene more in corporate labor decisions by restricting employee layoffs. Consistent with this argument, we find that the effect of LGD on labor cost stickiness is more pronounced for state-owned and politically connected firms; in regions with lower marketization levels and government fiscal self-sufficient capacities; and when regional unemployment rates, macroeconomic uncertainty, and political risk are higher. We show that through responsibilityshiftingamid high LGD, local governments benefit from a reduction in social expenditures. However, firms with stickier current labor costs will have lower subsequent productivity and market value, despite local governments reciprocating with more subsidies. Overall, LGD not only adversely impacts firm financing through the crowding-out effect but also erodes firm value through the responsibility-shifting effect.

This paper investigates the impact of Chinese firms’ ESG performance on their financial constraint and financing activities. We find a negative association between firms’ ESG performance and their financial constraint driven by the Chinese government’s commitment to tackling climate change. Compared with state-owned enterprises (SOEs), non-SOEs have alleviated their financial constraint through both equity and debt issuance, thanks to the stock price appreciation and green credit. High-pollution firms benefit from both equity and debt issuance, while low-pollution firms mainly finance through equity issuance. Our findings demonstrate the leading role of the Chinese government in its domestic capital markets.

China’s energy stocks are confronted with significant climate-related challenges. This paper aims to measure the daily climate transition risk in China by assessing the intensity of climate policies. The daily climate physical risk encountered by China’s renewable energy stocks is also measured based on the perspective of temperature change. Then, the partial linear function coefficient model is adopted to empirically investigate the non-linear impacts of climate transition risk and climate physical risk on the return and volatility of renewable energy stocks. The nonlinear moderating effect of climate transition risk is also involved. It is found that: (1) Between 2017 and 2022, the climate transition risk in China exhibited a persistent upward trend, while the climate policies during this period particularly emphasized energy conservation, atmospheric improvements, and carbon emissions reduction. Additionally, the climate physical risk level demonstrated a pattern consistent with a normal distribution. (2) There is a U-shaped nonlinear impact of climate physical risk on the return and volatility of renewable energy stocks. High climate physical risk could not only increase the return of renewable energy stocks but also lead to stock market volatility. (3) Climate transition risk exhibits a U-shaped effect on the return of renewable energy stocks, alongside an inverted U-shaped effect on their volatility. Notably, a high level of climate transition risk not only increases the return of renewable energy stocks but also serves to stabilize the renewable energy stock market. Moreover, the heightened risk associated with climate transition enhances the negative impact of oil price volatility on the yield of renewable energy stocks and, concurrently, leads to an increase in volatility.The strength of this moderating effect is directly correlated with the level of climate risk.