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。

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

This paper represents the first attempt to show how heterogeneous shock experiences help explain the enduring scars on household future behaviors. Using a large-scale household survey with 15,652 observations combined with geospatial transportation big data, we identify a novel belief-updating mechanism through which crises may exert prolonged impacts on household asset allocation and consumption patterns. An increase in the duration of previous lockdown experience is associated with a 10.52% escalation in enhanced anxiety for future precautionary saving motivations. This experience-based learning perspective supports the resolution of long-lasting overreactions to negative shocks via belief revisions and extends to households’ consumption behaviors. The lingering effects continue to skew households' beliefs even when conditions improve. Additionally, households with different individual-based shock experiences may exhibit varying perceptions of external shocks, resulting in disparate belief revision processes.

影子银行监管政策旨在防范和化解系统性风险，推动金融强国建设和经济高质量发展。本文构建了一个同时面临流动性约束和影子银行监管的商业银行资产负债管理分析框架，在此基础上以《资管新规》的实施作为准自然实验，以2014-2022年中国A股非金融非房地产类上市公司年度数据为样本，基于银行理财产品视角探究影子银行监管对企业信贷可得性的影响。本文基于上市公司贷款数据识别企业与银行之间的信贷关联，并结合银行理财产品发行数据构建企业对银行理财产品的敞口指数。研究发现：《资管新规》实施前对银行理财产品敞口较高的企业在此后的信贷可得性明显降低，且该效应在信用风险较高的企业、无四大国有银行贷款的企业、与银行信贷关联较为单一的企业、所在地区市场化水平较低的企业中表现更加突出；机制分析表明，《资管新规》实施前对理财产品依赖程度较高的银行在此后的非流动性资产持有比例显著降低，资产端流动性囤积水平明显上升，该效应通过银企信贷关联传导至企业并导致其信贷可得性降低。本文厘清了影子银行监管政策影响企业信贷融资的内在机制，为金融强监管政策的制定和优化提供了理论依据。

This study examines the effects of the robotic subsidy policy in China’s manufacturing sector. The demand-side subsidy policy aims at encouraging manufacturing firms to invest in robotics by lowering the cost of purchase. Our difference-in-difference analysis reveals distributional impacts of municipality-level robot subsidies on manufacturing firms of different scales. Although the subsidy brings a 14.2% increase in the application of robot patents, the facilitated access to robotics has not transformed into new firm entries. Strikingly, new firm entry decreases by 23.5% after the policy implementation. On the other hand, robot subsidies have increased the revenue, total asset, and employment of larger manufacturing firms by 9.8%, 6.9%, and 6.7%, respectively. To interpret the mechanism, we develop a simplified framework incorporating financial frictions into a task-based model. The model reveals that idiosyncratic borrowing costs lead to an inefficient equilibrium by generally depressing automation adoption and creating automation dispersion across firms. Such ex-ante distortion results in a uniform subsidy disproportionately benefiting firms with better capital access, thus creating a trade-off in terms of efficiency: while the subsidy can enhance overall automation, it simultaneously exacerbates automation dispersion. To quantify the efficiency implications, we embed this simplified model into a dynamic heterogeneous-agent framework, calibrated to the 2010 productivity distribution, financial frictions, and robot density in the industrial sector in China. Our dynamic model reveals that a 20% robot subsidy narrows the gap between mean and optimal automation level by 22% percentage points, while raises automation dispersion by 49%. This results in a 1.23% increase in aggregate output at the cost of a 2.40% decline in TFP. This dynamic model proposes a novel mechanism that automation exacerbates capital misallocation by enlarging asset accumulation dispersion between workers and entrepreneurs. Controlling for this dynamic feedback could enhance the subsidy-induced output gain by an additional 26%

贸易摩擦作为近年来世界经济格局最显著的风险因素之一，不仅阻碍了多边主义包容发展的整体进程，也对我国以广大中小企业为代表的经营主体产生了直接且深远的影响。本研究以2018年中美贸易战为准自然实验，聚焦某一线城市高新技术企业的全量样本，运用强度双重差分法系统探究贸易摩擦对中小企业创新产出的影响及其作用机制。基准回归结果表明，相较于对照组，受出口冲击企业的创新总产出和实质性创新均呈现显著增长。异质性分析进一步揭示，国有产权、低外资投资比例以及位于自贸区外的企业更能强化贸易摩擦对创新的促进效应。机制分析则指出，加大政策扶持力度、优化人力资本结构和增加企业内源研究是提升企业创新产出的关键渠道。本文的研究揭示了在面对关税冲击时，中小企业应当迅速调整内部决策以促进自主创新，同时也强调了政府在提供适度支持和引导方面的重要性，这些发现为理解贸易摩擦背景下中小企业的创新策略及政策制定提供了重要启示。

In recent decades, over 40% of dollar-denominated corporate bonds have been issued by non-US firms. Strikingly, these foreign issuers face an extra discount of 20 bps than their US counterparts. While standard risks fail to account for the discount, the Economic Policy Uncertainty index from Baker, Bloom, and Davis (2016) can explain a substantial portion of this discrepancy, consistent with uncertainty-based model calibrations. Moreover, such foreign discount (USA effect) dominates the dollar safety premium (USD effect). My findings highlight the foreign discount effect in interna- tional corporate bonds, particularly amidst escalating global economic instability and uncertainty.

中国式现代化建设科技创新是关键，科技金融为促进科技创新高质量发展提供了有力支撑。本文基于2013—2022年省级面板数据，构建科技金融、科技创新高质量发展综合指标体系，检验科技金融对科技创新高质量发展的影响。实证结果表明，科技金融能通过实质性创新、可持续性创新以及协同性创新三个维度，显著促进科技创新高质量发展，且该促进作用表现出地区及投入异质性。一方面，科技金融对东、西部地区科技创新高质量发展作用明显；另一方面，来自科技资本市场、企业的科技金融投入对科技创新高质量发展有更为显著推动作用。利用不同稳健性检验方法、科技和金融结合试点政策等内生性检验方法的回归结果仍然支持该结论。

How does information sharing affect consumers' usage of FinTech credit? Using a unique dataset of ``Buy Now, Pay Later (BNPL)" users from a large digital platform and exploiting a credit reporting policy change, we document that consumers significantly reduce their usage of BNPL credit when the BNPL lender becomes subject to credit reporting regulation. This reduction is more pronounced among borrowers with previous default records, who also become more disciplined in repayment behaviors, than those without such records. The decrease in BNPL usage also leads to a reduction in online consumption, supporting the financial constraint hypothesis. Our results suggest that information sharing can help alleviate overborrowing and overspending, with stronger effects observed among younger borrowers, those who previously consumed more, or those with credit cards. We also highlight the synergies between BNPL lending and Big Tech platforms' ecosystems, which imperfectly substitute for formal enforcement institutions.

This study empirically investigates the impact of dialect diversity on corporate investment efficiency under different levels of economic policy uncertainty. Our findings reveal that local dialect diversity enhances investment efficiency during stable periods, but this advantage significantly diminishes under high economic policy uncertainty. This reduction primarily arises from underinvestment and overly cautious decision-making by fragmented management during periods of turmoil. Further analysis reveals that this reduction is exacerbated by stronger internal governance, which emphasizes checks and balances, and mitigated by stronger external governance, which focuses on supervisory power. Our results remain robust when using alternative measures of main variables and employing topography as an instrumental variable.