We develop a signaling game model of investment to explore the effects of ambiguity aversion on corporate equilibrium strategies, investment dynamics, and financing decisions in incomplete markets with asymmetric information. Our analysis shows that volatility ambiguity aversion has a similar but more pronounced effect than asymmetric information, leading to higher financing costs, lower investment probabilities, and a greater likelihood of non-participation in investment. Importantly, volatility ambiguity aversion exhibits an amplifier effect, magnifying financing costs, adverse selection costs, and distortion in investment choices under asymmetric information. This increased ambiguity aversion raises the chances of inefficient separating and pooling equilibria, resulting in notable welfare losses. These findings highlight the significant impact of ambiguity aversion on strategic decision-making and equilibrium outcomes in investment, particularly in settings marked by information asymmetry and incomplete markets.

本文从数字化战略、数字化组织、数字化产品、数字化服务、数字化技术和数字化人才等六个一级指标和二十六个二级指标构建了银行数字化转型指标体系，进一步基于2010-2022年中国上市企业与其贷款银行的配对样本,考察银行数字化转型对企业投融资期限错配的影响。结论如下：银行数字化转型有助于改善企业投融资期限错配。银行数字化转型主要是通过银行数字化战略、数字化组织和数字化技术对企业投融资期限错配产生影响。机制分析表明，银行数字化转型通过 “融资期限结构调整”机制和 “融资约束缓解”机制改善企业投融资期限错配。异质性分析表明，对于高分析师关注、高研报关注，高企业数字化转型程度和低信息披露的企业，银行数字化转型能够更好地改善其投融资期限错配。银行数字化转型通过改善企业投融资期限错配进而提升了其盈利能力和可持续增长能力，同时缓解了企业的财务风险，但对企业经营风险的缓解作用不显著。银行金融科技对投资显。研究为银行数字化转型赋能实体经济提供了新的经验证据,为政策制定者、银行和企业提供了有益的参考和启示。

This paper, based on data from Chinese A-share listed companies between 2009 and 2019, employs the implementation of the "Shanghai-Hong Kong Stock Connect" as a landmark event of capital market liberalization, utilizing a difference-in-differences model to empirically examine the impact of market openness on firms' cross-region investment behavior and its underlying mechanisms. The findings indicate that: (1) the launch of the "Shanghai-Hong Kong Stock Connect" has significantly promoted the establishment of cross-provincial and cross-border subsidiaries by the companies involved; (2) capital market liberalization influences firms' cross-region investment through three dimensions: finance, governance, and stakeholders. In terms of finance, the openness alleviated financing constraints and improved stock liquidity; in governance, it pressured companies to adopt more digitalized and transparent governance structures to accommodate cross-regional expansion; in the stakeholder dimension, it attracted the attention of external investors, accelerating their understanding of firms and alleviating the trust issues associated with cross-region expansion. (3) The effect of capital market liberalization on promoting cross-border investments by private enterprises is particularly pronounced, and this effect is further strengthened as the quality of corporate information disclosure improves. Firms with higher levels of product diversification benefit more from market liberalization, accelerating their overseas expansion. (4) Capital market liberalization has elevated the level of cross-region investment, thereby significantly fostering innovation and improving investment efficiency. The conclusions of this study provide fresh empirical evidence for understanding the microeconomic effects of China's capital market liberalization, the intrinsic mechanisms of corporate cross-region investments, and their economic consequences.

This paper investigates the high-frequency dynamics of macroeconomic expectations and disagreement among professional forecasters. We propose a novel mixed-frequency estimation approach that integrates daily asset returns with quarterly expectation data from the Survey of Professional Forecasters. Our findings indicate that consensus forecasts are updated efficiently according to Bayes' rule, independent of prior forecasts. By employing "representative forecasters" as proxies for real-world agents, we derive a simple yet intuitive evolution equation for disagreement, revealing that changes in disagreement are primarily driven by different interpretations of new information. Furthermore, we reconstruct daily series of expectations and disagreement concerning macroeconomic growth, achieving impressive R2 values of 93.3% and 84.5% against the true quarterly series.

Climate change and the escalation of extreme weather events jeopardize every corner of the globe. This paper investigates the impact of extreme high temperatures on the spread of newly issued municipal corporate bonds (MCBs) in China, which serves as a crucial instrument for local governments to meet the financial demands. We find that relative to the reference temperature range of 16 ◦C–20 ◦C, the issuing spread of MCBs increases by 2.48 basis points for each extra day where the mean temperature surpasses 32 ◦C. The findings highlight the risk-increasing effects of extreme temperatures in financial markets.

We examine whether large language models (LLMs) can extract contextualized representation of Chinese public news articles to predict stock returns. Based on representativeness and influences, we consider seven LLMs: BERT, RoBERTa, FinBERT, Baichuan, ChatGLM, InternLM, and their ensemble model. We show that news tones and return forecasts extracted by LLMs from Chinese news significantly predict future returns. The value-weighted long-minus-short portfolios yield annualized returns between 35% and 67%, depending on the model. Building on the return predictive power of LLM signals, we further investigate its implications for information efficiency. The LLM signals contain firm fundamental information, and it takes two days for LLM signals to be incorporated into stock prices. The predictive power of the LLM signals is stronger for firms with more information frictions, more retail holdings and for more complex news. Interestingly, many investors trade in opposite directions of LLM signals upon news releases, and can benefit from the LLM signals. These findings suggest LLMs can be helpful in processing public news, and thus contribute to overall market efficiency.

This paper investigates the supervisory incentive effects of employee stock ownership plans based on a corporate risk-taking perspective using data from a sample of Chinese A-share listed companies from 2006-2021. The results show that employee stock ownership plans significantly enhance corporate risk-taking. The specific mechanism is that employee stock ownership plans reduce the two-tier agency costs between shareholders and managers and managers and employees, alleviate corporate financing constraints, and thus enhance the level of corporate risk-taking. It is also found that employee stock ownership plan enhances the level of corporate risktaking with high quality, because employee stock ownership plan not only promotes R&D investment which is beneficial to corporate value growth, but also reduces excessive investment and high debt which are detrimental to corporate value, and the corporate risk-taking is of higher quality and more substantial value effect. In addition, differences in the institutional design of employee stock ownership plans have different effects on corporate risk-taking: employee stock ownership plans that are leveraged, highly discounted, with longer lock-up periods and duration, and entrusted to third-party institutions have a stronger effect on corporate risk-taking; employee subscriptions can promote corporate risk-taking more than executive subscriptions; employee stock ownership plans in China do not have the problem of "free-riding There is no "free-rider" problem in China's employee stock ownership plan. The larger the issuance ratio of the employee stock ownership plan, the greater the number of participants, and the larger the scale of capital, the better the implementation effect.

Comprehensive evaluation and identification of the critical regulatory determinants of carbon emission efficiency (CEE) are very important for China’s low-carbon transition. Accordingly, this paper first employs an undesirable global super-hybrid measure approach to calculate the CEE of China’s iron and steel industry (ISI). We then further use spatial error and threshold regression models to examine the spatial and non-linear effects of heterogeneous environmental regulations on CEE, respectively. Our empirical results show that (1) CEE varies significantly across China’s regions, with the eastern region having the highest CEE score, followed by the western and central regions, with the northeast region ranking the lowest; (2) command-and-control and market-incentive regulations both promote CEE, whereas the public participation approach does not significantly contribute to performance gains; (3) all three types of environmental regulations exhibit a non-linear threshold effect on CEE; (4) openness level, technological progress, and industrial concentration enhance efficiency gains, while urbanization level exerts a negative impact on CEE. Our findings have important implications for the design of environmental regulations.

近年来，随着气候风险的不断累积，中国极端气候灾害事件发生的频率和强度持续上升，对企业正常的生产经营造成了十分严重的影响。本文手工整理了应急管理部自然灾害数据，构建了考虑企业子公司数量及所在地的气候灾害冲击加权平均指标，基于2007—2022年中国A股上市公司数据，实证研究了气候灾害冲击对企业债务融资成本的影响及作用机制。结果表明，气候灾害冲击显著提高了企业的债务融资成本，冲击造成企业营业收入下降和固定资产减值与折旧增加是其中的影响机制。异质性考察发现，气候灾害冲击提高债务融资成本的效应在受到“信贷歧视”更严重的民营企业和规模较小企业中更加显著，且在受气候灾害影响程度较大的行业和金融业市场化水平较低地区的企业中更加显著。进一步研究表明，企业能够通过使用商业信用融资、提高风险感知水平和改善ESG表现缓解气候灾害冲击造成的融资贵问题。本文为气候灾害这一因素对企业融资贵问题带来的重要影响提供了更为直接的证据，对企业防范和化解气候灾害冲击带来的负面影响具有积极的现实意义。

旨在推动实现生态环境根本好转的质量型环境治理政策在多大程度上能够协同降碳，如何进一步提质增效，是推进“双碳”战略过程中亟需解答的关键问题。特别地，签署《巴黎协定》以来，中国在减污降碳协同增效面临着不同于以往的新形势和新任务。然而，受限于数据可得性，现有研究尚未提供这一时间段内的定量分析直接证据。本文使用新近的企业层面较为精细的碳排放数据，基于《打赢蓝天保卫战三年行动计划》（国发〔2018〕22号）的研究场景，系统分析了“双碳”背景下空气质量目标政策的微观降碳效果与增效机制。研究表明，蓝天保卫战能够协同降低企业碳排放强度，平均降幅约为15%，单个企业年均降碳量约为1.2万吨。这一效果主要由碳排放总量下降驱动，而非以生产活动收缩为代价，也未引起区域间和产业链上的碳泄漏问题。并且，与现有研究强调行业结构调整不同，本文发现高碳排放企业也实现了显著的减排效应。增效机制方面，蓝天保卫战主要通过促进企业绿色低碳投资发挥作用，而人力结构优化、绿色研发创新等机制尚未明显起效，同时缓解融资约束有助于提升协同降碳效果。本文的研究表明，进一步完善现有大气污染防治制度体系，辅以大规模节能降碳设备更新、优化生产要素配置以及绿色金融等组合措施，能够有效兼顾环境、气候和经济效益，助推减污降碳协同增效。