We leverage machine learning to introduce belief dispersion measures to distinguish different opinion (DO) and information asymmetry (IA). Our measures align with the human-based measure and relate to economic outcomes in a manner consistent with theoretical prediction: DO positively relates to trading volume and negatively linked to bid-ask spread, whereas IA shows the opposite effects. Moreover, IA negatively predicts the cross-section of stock returns, while DO positively predicts returns for underpriced stocks and negatively for overpriced ones. Our findings reconcile conflicting disagree-return relations in the literature and are consistent with Atmaz and Basak (2018)’s model. We also show that the return predictability of DO and IA stems from their unique economic rationales, underscoring that components of disagreement can influence market equilibrium via distinct mechanisms.

中共二十届三中全会强调要健全高质量充分就业促进机制，就业是最大的民生，如何扩大就业对社会稳定和经济发展意义重大。本文基于投入产出表数据构建企业宏观层面的数字化转型指标，并基于中国31个省份代表性报纸构建中国省级行政区经济政策不确定性指数，考察企业数字化转型对经济政策不确定性与劳动力就业规模关系的影响。研究发现，经济政策不确定性对劳动力就业存在破坏效应，数字化转型能够有效缓解经济政策不确定性对劳动力就业的不利影响。机制检验发现，数字化主要通过减弱企业对经济政策不确定性的感知度、缓解企业融资压力和减弱企业金融化动机的途径缓解经济政策不确定性对劳动力就业的破坏效应。异质性分析表明，这一缓解作用在东部地区、知识产权保护强地区和国有属性企业效果更强。此外，数字化转型对第三产业和中高技能劳动力就业规模的缓解效果更强，有助于提升就业质量。本文基于企业数字化角度为高效减轻经济政策不确定对劳动力就业的破坏效应提供了新的经验证据。

通货膨胀如何影响资产价格？经典的“债务-通胀”渠道认为，通胀将降低债务的实际价值并将财富由银行转移至企业。而本研究发现，不同监管环境下通胀会引起银行和企业间非单调的价值转移。理论分析结果表明，在债券违约率更高、回收率更低的松监管环境下，通胀使得回收率上升，实际价值从企业向银行转移；在违约率较低、回收率较高的严监管环境下，通胀使得名义债务贬值，实际价值从银行向企业转移。本文利用1994-2025年的A股数据，提供了支持分析的经验证据：08金融危机引发对银行监管的关注和巴塞尔Ⅲ导致了银行价值对通胀的暴露由正转至长期为负，而影子银行的发展又重新降低了银行对通胀的负向暴露。基于DSGE的量化模型中，货币政策与通胀冲击会产生符合分析的价值转移结果。本文为通胀对资产价格和实体经济的影响提供了一个新的研究视角，为货币政策制定与银行监管提供了重要的关注对象和货币非中性的证据。

We examine how mutual funds form stock market expectations and the implications of these beliefs for asset returns, using a novel text-based measure extracted from Chinese fund reports. Funds extrapolate from recent stock market and fund returns when forming expectations, with more recent returns receiving greater weight. This recency tendency is weaker among more experienced managers. At the aggregate level, consensus expectations positively predict short-term future market returns, both in and out of sample. At the fund level, expectations are positively related to subsequent fund performance in the time series. In the cross-section, however, superior performance arises only when funds accurately forecast market direction and adjust their portfolios accordingly. This effect is stronger for optimistic forecasts and among funds with greater exposure to liquid stocks. Our findings highlight the conditional nature of belief-driven performance, shaped jointly by forecasting skill and the ability to implement views in the presence of execution frictions such as short-selling and liquidity constraints.

With fintech growth and smartphone adoption, e-wallets, which enable instant transactions while offering cash management products with financial returns, have become increasingly prevalent. Using a unique dataset from Alipay, the world’s largest e-wallet provider, we find that holdings in Yu’EBao—an investment product usable for payments—are less affected by interest rate changes than similar assets without payment functions. This effect is stronger for users who depend on Yu’EBao for daily spending, during peak payment periods, or among less experienced investors. Our findings show that Yu’EBao reduces retail fund flow to riskier assets by 7.7% for every one-percentage-point interest rate cut, dampening monetary policy transmission through the portfolio rebalancing channel.

随着互联网经济的发展,互联网评论渗透在人们生活的方方面面。为了研究Twitter上关于新能 源汽车的大量评论情绪是否是TESLA的股价波动产生的原因, 本论文假设从Twitter收集到的用户情绪 数据与TESLA股票市场价格相关。并采取CS新能车指数399976和Twitter上的关于新能源汽车的评论情 绪数据与CS新能源车指数的股价数据进行格兰杰因果检验。研究结果表明中国投资者情绪是指数价格 变化的主要原因,且投资者对新能源汽车指数的正面冲击是短期的,长期来看情绪对股票价格的影响将 会消失。

就业是最基本的民生，也是实现高质量发展的重要目标。实施包括地方政府债务置换在内的“逆周期”财政调节政策对促进企业劳动力雇佣、实现“稳就业”目标具有重大意义。本文从产业关联度视角出发，基于2010-2016年全国税收调查数据，采用广义双重差分法实证检验了债务置换政策对企业劳动雇佣的影响。研究发现，债务置换具有“稳就业”效应，并且与政府关联度更高的基建行业受到债务置换影响更为显著，机制分析结果表明，债务置换通过缓解企业融资约束，促进欠款偿还缓解企业流动性约束，改善企业预期等机制促进企业劳动力雇佣。本文的研究对准确评估2024年开始的新一轮债务置换政策效果，优化“逆周期”财政政策设计、实现“稳就业”目标具有重要的意义。

本文以2011—2023年A股市场存续的全部股票型ETF基金为样本，基于多期双重差分法（DID）识别流动性服务业务引入对ETF跟踪误差的影响效应。研究发现，引入流动性服务机制可显著降低ETF的跟踪误差，该结论在通过了一系列稳健性检验。机制检验表明，流动性服务商激励改善与市场交易条件优化是跟踪误差降低的主要传导路径，机构投资者比例提升进一步强化流动性服务的政策效应。异质性分析显示，优化复制策略、宽基指数ETF与中小规模产品受益更为显著。进一步研究发现，该机制显著改善了流动性基础薄弱ETF的跟踪误差，缓解了市场“马太效应”。本文从制度演变的视角系统揭示了ETF市场流动性服务机制的微观传导与结构性影响，为提升ETF基金运行质量与健全ETF市场功能提供了实证支持与政策启示。

This study shows how price limit rules, intended to stabilize markets, inadvertently distort price dynamics by fostering strategic speculation. Through a dynamic rational expectations model, we demonstrate that price limits induce post limit-up price jumps by impeding full information incorporation, enabling speculators to artificially push prices to upper bounds and exploit uninformed traders. The model predicts two distinct patterns: (1) stocks closing at price limits exhibit positive overnight returns followed by long-term reversals, and (2) stocks retreating from upper bounds suffer sharp reversals with partial recovery. Empirical analysis confirms these predictions. A natural experiment from China’s 2020 GEM reform —- which widened the price limit -— further provides causal evidence that relaxed limits mitigate speculative distortions.

随着中国经济转型与绿色发展的深入，绿色全要素生产率逐渐成为衡量区域绿色发展与经济效率的重要指标。本文基于2006—2022年中国279个地级市的面板数据，通过双重差分模型实证分析了科技金融对绿色全要素生产率与绿色全要素生产率区域差距的影响。研究发现：（1）科技金融显著提高了绿色全要素生产率并缩小了绿色全要素生产率区域差距。（2）科技金融可通过提升财政投资力度与绿色基金规模助力绿色全要素生产率提升与绿色全要素生产率区域差距的缩小。（3）科技金融对绿色全要素生产率与绿色全要素生产率区域差距存在城市规模、城市特征与地理区域的异质性影响。（4）科技金融对绿色全要素生产率存在显著的正向空间溢出效应，对绿色全要素生产率区域差距存在显著的负向空间溢出效应。研究不仅从绿色全要素生产率与绿色全要素生产率区域差距的角度深化了科技金融影响的研究，也为理解科技金融对区域协调发展的作用提供了理论依据。