The role of Market-incentive environmental regulation (MIER) within the framework of environmental governance is patently evident. While extant literature lauds the advantageous outcomes attributed to the environmental protection tax (EPT) which as a representative of MIER, our empirical inquiry presents a contrasting narrative. By employing the sophisticated Difference-in-Difference-in-Difference (DDD) methodology and utilizing data from A-share listed firms in Shanghai and Shenzhen from 2015-2022, our investigation reveals a significant decrease in firms’ total factor productivity (TFP) following the implementation of EPT. Our core assertion is fortified through the discernment of two plausible mechanisms, namely, the production downsizing effect and the production capital crowding-out effect. Building upon this revelation, we delve into the nuanced pathways through which firms can strategically mitigate the impacts of EPT, encompassing the enhancement of human capital, amplification of research and development (R&D) investments, and fortification of overall firm resilience. Heterogeneity analysis discloses a notably heightened impact of EPT on TFP of state-owned enterprises (SOEs), larger enterprises and enterprises located in eastern regions. Ultimately, an approximately cost-benefit analysis conclusively demonstrates that the benefits derived from EPT far surpass the costs incurred by the concomitant industrial output reduction, which further illustrates the rationale for the implementation of EPT.

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 paper examines the impact of asset bubbles on innovation and long-run economic growth within a semi-endogenous growth framework, incorporating idiosyncratic productivity shocks and endogenous credit constraints in the R&D sector. It demonstrates that pure bubbles tied to intrinsically useless assets and equity bubbles linked to intermediate goods firms can coexist, relaxing credit constraints and boosting entrepreneurs’ total factor productivity (TFP), which stimulates R&D and enhances growth along the transitional path. However, these bubbles generally do not influence the long-run economic growth rate. The model’s mechanisms and predictions are supported by aggregate and firm-level evidence, showing a positive correlation between equity bubbles and R&D investment, with stronger effects during periods of tightened financial constraints.

Developing countries are taking advantage of FinTech tools to provide more people with convenient access to financial market investment through digital wealth management. Using COVID-19 as an uncertainty shock, we examine whether and how digital wealth management affects the resilience of consumption to shocks based on a unique micro dataset provided by a leading Big Tech platform, Alipay in China. We find that digital wealth management mitigates the response of consumption to uncertainty shocks: residents who participate in digital wealth management, especially in risky asset investments, have a lower reduction in consumption. Importantly, digital wealth management helps improve financial inclusion, with a more pronounced mitigation effect among residents with lower-level wealth, living in less developed areas, and those with lower-level conventional finance accessibility. The mitigation effect works through the wealth channel: those who allocate a larger proportion of risky assets in their portfolio and obtain a higher realized return show more resilience of consumption to negative shocks. We also find that digital wealth management substitutes for conventional bank credit but serves as a complement to FinTech credit in smoothing consumption during uncertainty shocks. Digital wealth management provides a crucial way to improve financial inclusion and the resilience of consumption to shocks.

In the wave of digital and intelligent transformation, corporate governance is undergoing profound changes. This paper, from the perspective of green governance and sustainable development, explores the new trends in corporate governance under this background, such as data-driven decision-making and the application of intelligent technologies in supervision; analyzes the new challenges faced, including data security and privacy protection, and the digital divide; and based on relevant theories, combined with practical cases and using data models and other methods, explores new paths, aiming to provide theoretical and practical guidance for enterprises to achieve the coordinated and simultaneous progress of digitalization, intelligentization, greenization, and sustainable development.

Recent research highlights the significant impact of managerial industry tournament incentives on internal firm decisions. However, their potential impact on external stakeholders-in the context of evolving product market relationships-has received scant attention. To address this gap, we examine the effect of customer aspiration, incentivized by CEO industry tournaments (CITIs), on supplier innovation. Utilizing customer-supplier pair-level data from 1992 to 2018, we establish that customer CITIs enhance supplier innovation, both in quantity and quality. Additionally, we identify that CITIs positively impact the relationship-specific innovation and market valuation for suppliers. The effect of CITIs is more pronounced when customers are larger, geographically closer, socially connected, and have long-standing relationships with their suppliers. The results remain robust to alternative specifications and considering potential endogeneity issues. Our study highlights the bright side of executives’ industry tournament incentives, which not only drive innovation within the sector but can also positively influence related sectors within the supply chain.

We develop a model economy with active financial markets in which a policymaker's adoption of a gradualistic approach constitutes a Bayesian Nash equilibrium. In our model, the ex ante policy proposal influences the supply side of the economy, while the ex post policy action affects the demand side and shapes market equilibrium. When choosing policies, the policymaker internalizes the impact of her decisions on the precision of the firm-value signal. Moreover, financial markets provide a price signal that informs the government. The policymaker learns about the productivity shocks not only from firm-value performance signals but also from financial market prices. Access to information through both channels creates strong incentives for the policymaker to adopt a gradualistic approach in a time-consistent manner. Smaller policy steps yield more precise information about the productivity shock. These results hold robustly for both exogenous and endogenous information models.

There is substantial evidence indicating that enterprises are negatively impacted by climate risk, with the most direct effects typically occurring in financial domains. This study examines A-share listed companies from 2007 to 2023, employing text analysis to develop the firm-level climate risk indicator and investigate the influence on corporate financial risk. The results show a significant positive correlation between climate risk and financial risk at the firm level. Mechanism analysis shows that the negative impact of climate risk on corporate financial condition is mainly achieved through three paths: increasing financial constraints, reducing inventory reserves, and increasing the degree of maturity mismatch. To address potential endogeneity, this study applies instrumental variable tests, propensity score matching, and a quasi-natural experiment based on the Paris Agreement. Additional tests indicate that reducing the degree of information asymmetry and improving corporate ESG performance can alleviate the negative impact of climate risk on corporate financial conditions. This relationship is more pronounced in high-carbon emission industries. In conclusion, this research deepens the understanding of the link between climate risk and corporate financial risk, providing a new micro perspective for risk management, proactive governance transformation, and the mitigation of financial challenges faced by enterprises.

We study how financial markets integrate news about pollution abatement costs into firm values. Using China’s automation of pollution monitoring, we find that firms with factories in bad-news cities---cities that used to report much lower pollution than the automated reading---see significant declines in stock prices. This is consistent with the view that investors expect firms in high-pollution cities to pay significant adjustment and abatement costs to become “greener.” However, the efficiency with which such information is incorporated into prices varies widely---while the market reaction is quick in the Hong Kong stock market, it is considerably delayed in the mainland ones, resulting in a drift. The equity markets expect most of these abatement costs to be paid by private firms and not by state-owned enterprises, and by brown firms and not by green firms.

Using bank-county-year level mortgage application data, we document that minority borrowers are systematically evaluated with less soft information compared to White borrowers within the same bank-county branch. Using variation in local sunshine as an instrument and conducting a series of robustness checks, we show that the soft information imbalance significantly increases the denial gap between minority and White applicants. However, this imbalance does not appear to affect pricing disparities. Further analysis shows that internal capital reallocation to under-resourced bank branches can serve as an effective strategy to reduce soft information imbalances and, thus, promote more equitable credit allocation. Our results highlight that soft information imbalance is an overlooked but significant factor driving disparities against minority borrowers.