随着全球经济的发展以及环境容量资源有限性之间的矛盾升级、无实际控制人现象在上市公司中逐渐增多。无实际控制人企业引发的内外部治理结构对碳排放强度会产生何种影响呢？本文基于代理理论，以2007-2022年沪深A股上市公司为研究对象，检验无实际控制人对碳排放强度的影响。研究发现，无实际控制人企业的碳排放强度更高。内部治理结构如股权制衡、管理层持股有助于显著降低无实际控制人企业的碳排放强度，外部治理机制如建立环保法庭和实施低碳城市的试验政策，使得碳排放强度显著降低。本文的研究结论为改善无实际控制人企业的碳排放强度提供了经验证据，拓展了代理理论的适用范围，基于无实际控制人视角丰富了碳排放管理的相关研究。

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统筹金融开放和安全是构建高水平开放型金融新体制的基本要求。本文以美国货币政策为切入点，先从实证角度分析美国加息对我国产出的影响，然后构建包含跨境金融关联的两国DSGE模型，定量分析美国货币政策的溢出效应及应对之策。研究发现，美国加息1个百分点使中国产出下降约0.4个百分点，其中贸易渠道和金融渠道分别使中国产出下降0.2个百分点。分析作用机制发现，UIP偏离机制使金融中介净值波动和汇率波动相互强化，外部融资溢价机制使金融中介净值波动和企业净值波动相互强化，正是这两个机制放大了美国货币政策的外溢效应。进一步研究发现，金融开放度越高和汇率越缺乏弹性，美国加息冲击对我国变量的传导效应越显著。基于不同的福利函数特征，本文构建了统一的政策评估框架，对宏观审慎政策和双支柱调控应对美国加息冲击的有效性作出了精准评估。结果表明，无论是针对国内金融机构信贷监管的宏观审慎政策还是针对跨境资本流动和外汇相关的宏观审慎政策，均能降低美国加息的溢出效应，且宏观审慎政策有效性与汇率制度无关。在联合最优政策组合下，货币政策无需对名义汇率作出反应，外汇市场要强化价格调控淡化数量干预。在货币政策和宏观审慎政策相互协调搭配下，双支柱调控通过维护经济金融稳定具有显著的社会福利增进效应。本文为构建高水平开放型金融新体制，以金融高质量发展加快推进中国式现代化提供了政策启示。

This study investigates whether corruption differentially affects contracting through auctions and negotiations. Using data on Chinese land-market transactions, where corruption is known to be present, we first show that, on average, it exerts similar effects on transactions carried out via auctions and negotiation. However, this finding masks important heterogeneity – auctions featuring healthy competition are less affected by corruption, and significantly less so than negotiation. We then develop a simple model of bidding under the possibility of corruption that rationalizes our findings.

Based on high-frequency data of China's commodity market from 2017 to 2022, this article examines the intraday momentum effect. The results indicate that China's commodity futures and options have significant intraday reversal effects, and the overnight opening factor and opening to last half hour factor are more significant. These effects are driven, in part, by liquidity factors. This trend aligns with market makers' behavior, passively accepting orders during low liquidity and actively closing positions amid high liquidity. Furthermore, our examination of cross-predictive ability shows strong futures-to-options predictability, while the reverse is weaker. We posit options traders' Vega hedging as a key factor in this phenomenon, our study finds futures volatility changes can predict options’ return.

The Chinese government has actively traded in the stock market through governmentsponsored institutions, the National Team, since the 2015 market crash. I adopt Koijen and Yogo’s (2019) demand system approach in China’s stock market to understand the impact of government participation. Estimation results indicate the government tilts towards large, less risky, and SOE stocks. During the crash, government participation indeed stabilized the market: the large-scale purchases reduced the cross-sectional market volatility of annual return by 1.8% and raised the market price by 11%. When the market ffuctuation returns to normal, the government acts more like an active investor; its price impact remains high but does not contribute to the cross-sectional volatility. Based on the theoretical framework of Brunnermeier et al. (2020), I investigate the interaction between the Nation Team and retail investors to reveal the government trading strategy. No evidence shows that government participation signiffcantly distorts market information efficiency.

Emissions data collection and management are crucial to operationalizing an emissions trading scheme (ETS). Regulators need high-quality data to allocate emissions allowances and monitor compliance. However, collecting such data can be costly, challenging various actors. Emitters may misreport data, weighing the cost against their interest, while governments may struggle with limited resources in managing compliance. Third-party verification is a solution but tends to be ineffectual and causes new problems unless with sufficient oversight and support. This quality-cost dilemma becomes even more complex in multi-level ETSs, as in China’s national ETS (NETS). Despite increased regulatory efforts to address data challenges, there remains a lack of in-depth legal analysis on the relationship between data quality and cost. This Article establishes a three-element analytical framework—data quality, cost concerns, and intergovernmental relations in data management—to shed light on the nuances of data regulation. Using China’s NETS as a case study, we gain a deeper understanding of the three elements in a specific jurisdiction and the legal institutions, practices, and challenges involved. Governments, emitters, and third-party verifiers each have unique roles and limitations in this process. We suggest legal and regulatory strategies for finding solutions. Our actor-centered analytical model and practical recommendations for the NETS can serve as a valuable guide for jurisdictions facing similar data challenges.

Using the staggered intercity but within-province deregulation of local banks in China as exogenous variations, we evaluate the effect of banking integration across geographical segmentation on capital misallocation. Based on an administrative data set comprehensively covering Chinese manufacturing firms, we find that for firms with initially high marginal revenue products of capital (MRPK), the integration increases physical capital by 19.3%, and reduces MRPK by 33.1% relative to low MRPK ffrms. Our findings are more pronounced for non-statedowned firms and firms with higher exposure to integrated banks. Integration also significantly increases the responsiveness of firms’ investments to deposit shock on other cities within the same province.

如何合理评价基金业绩是满足培育一流投资机构这一国家重大需求的重要议题。现有的基于传统资产定价方法所构造的因子无法满足大数据时代高维特征决定基金业绩的市场环境。本文创新性地运用前沿的工具主成分分析法，从28个与基金业绩有关的特征中提取出隐性定价因子。本文发现，五因子隐性模型对基金和基金组合业绩的整体解释力度在样本内分别达到了81.85%和99.82%，这一整体解释力度在样本外分别为79.53%和99.74%。本模型对基金和基金组合的解释力从整体、时序、截面和相对误差每个角度都优于传统的显性因子模型。在识别隐性因子过程中，基金持仓股票的市值、换手率、营业利润、过往表现和基金过往业绩发挥了最重要的作用，但同时，隐性因子部分的定价能力同通货膨胀率、国债利率、宏观杠杆率、股债市场流动性和工业生产不确定性等常见的宏观周期波动有关。最后，基于以上发现，本文认为应当利用大数据多元化基金业绩度量体系，以优化散户投资者基金资产配置效率。