在防范化解重大金融风险、强化科技监管能力的战略背景下，如何有效运用监管科技手段维护资本市场稳定成为关键议题。本文聚焦交易所企业画像系统对企业股价崩盘风险的抑制效应，基于2015-2018年沪深A股上市公司数据，采用双重差分模型实证检验监管科技的创新应用对资本市场稳定的影响。研究发现，交易所企业画像系统的实施显著降低了企业股价崩盘风险。机制分析表明，一方面，企业画像系统有助于交易所增加监管问询的频率和强度，并促使企业及时高效回复，从而有效减少企业坏消息隐匿，降低股价崩盘风险；另一方面，画像系统通过有效抑制企业管理层隐匿坏消息的动机，减少坏消息的生成概率，从而减少坏消息囤积，抑制股价崩盘风险。异质性分析表明，企业画像系统抑制股价崩盘风险的效应在坏消息隐匿动机更强、信息环境更差以及对监管预期感知更强的企业中更为显著。进一步分析表明，画像系统对企业信息隐匿的抑制，不仅会引发不同市场参与者的关注调整，还有利于市场对企业形成乐观一致预期。本文的研究对于深入理解交易所企业画像系统在资本市场监管治理中的效能及其降低股价崩盘风险的机制，具有重要的理论和现实意义。

当今社会最大矛盾是国家法定数字货币供给不足，社会分工无法通过足够的数字货币进行交换，导致有产品卖不出，有需要却没钱支付的怪圈。解决这个问题可以通过给居民按身份证发放法定数字贷币，让社会分工通过数字货币交换，而不是原始的物物交换。发放数字货币不是不劳而获，因为数字货币本身不能吃不能用，要得到需要的东西就需要有付出或对等服务去交换，数字货币底层逻辑是交换的载体并不代表财富，只有满足公平交换的规则，社会才能激发创造力和分工协作，有了交易交换才能带动就业和税收，社会才能稳健有序发展。

本文基于间接融资体系抵押品本位，构建涵盖银行信贷与REITs资产的全口径抵押财富测度框架，利用跨国与城市面板数据开展实证检验。结果显示，抵押品减值对金融风险存在9.7%与24.8%两道临界门槛，跨门槛后冲击强度阶梯式抬升，且呈显著非对称特征，价格止跌不足以推动资产负债表回归稳态。纳入市场摩擦与货币稀释双重约束后，全国层面稳态修复的最低估值缺口约为10.6%-12.1%，三四线城市所需修复幅度明显更高。总量货币、财政与柔性监管三类常规工具仅在短期缓释风险，商用不动产证券化可在同等跌幅下将系统性风险降低24%-27%，但无法完全替代抵押品估值修复。本文为四部门资产负债表修复与不动产证券化制度设计提供了量化参考。

本文针对王国刚等（2024）提出的“双层存款乘数”理论进行了系统的批判。该理论试图通过构建中央银行与商业银行之间同样存在存款派生过程的“新框架”，以挽救传统货币乘数理论，但其底层逻辑与央行资产负债表的会计操作差距很大。本文从三个层面展开反驳：第一，澄清基础货币创造的本质是央行资产端扩张驱动负债端同步扩张，不存在所谓的“本币资产”科目，也不存在央行吸收存款后再进行派生的“乘数”过程；第二，剖析量化宽松期间货币乘数下降的真实原因，对方将美联储资产购买误解为“央行存款乘数”的循环过程，但实际上，联储购买证券时直接增加商业银行准备金，这是一次性操作；若联储继续购买，属于新增的基础货币投放，而非同一笔资金的反复派生；第三，揭示“资金观”谬误，对方将微观主体的资金约束错误地移植到中央银行身上，误以为提高法定存款准备金率能增加央行“可用资金”并用于购汇，实际上资产业务扩张不以负债增加为前提是中央银行的特有权力。本文由此认为，在充裕准备金框架和利率调控主导的现代货币政策体系下，对货币乘数的补救已失去意义，学术研究应转向央行资产负债表操作逻辑与内生信用创造机制。

2015年MLF常态化运作后，我国基础货币投放转向抵押品本位框架，十年期国债利率出现"加息灵敏联动、降息单边钝化"的非对称阻滞特征。本文构建四部门DSGE模型，匹配2006—2024年宏观月度面板与银企微观面板，综合运用NARDL、Bootstrap链式中介、内生门限回归等方法开展实证检验，并引入美、德、法、日四国构建跨国安慰剂对照。研究发现：不动产抵押框架通过存量M2锁定与银行负债淤积两条渠道推高M1-M2剪刀差，货币分层是降息传导受阻的核心中介闸门；2015年制度切换引发传导结构永久性塑性跳变，短端利率始终维持对称。微观面板验证了银行信贷配置倾斜与企业活期调整两类底层行为，跨国安慰剂检验证实长端钝化并非间接融资体系共性特征，而是不动产抵押货币制度的独有摩擦。本文据此提出短期逆周期调控与中长期多元抵押锚建设分层方案。

This study examines the role of financial derivatives in managing operational and financial risks within China's chemical manufacturing sector. While prior research has primarily focused on financial determinants of hedging decisions, we highlight the significant influence of operational metrics—particularly inventory levels and turnover rates—in shaping firms’ engagement in derivatives markets. Drawing from a sample of 289 publicly listed chemical firms from 2016 to 2022, we employ probit regression and K-means clustering to explore how operational and financial factors jointly determine derivatives adoption. Our empirical results reveal that operational metrics have a non-negligible impact on hedging decisions. Specifically, inventory and turnover rates emerge as primary determinants of firms' initiatives, while pre-tax operating profit remains significant from a financial perspective. The moderation analysis of cash flow reveals that financially constrained firms prioritize derivatives for operational risk mitigation, while resource-abundant firms employ them selectively for strategic optimization. Furthermore, our robustness tests, which control for geographical distinctions and the COVID-19 effect, confirm that firm-specific operational characteristics consistently dominate firms' hedging decisions despite regional heterogeneity. Finally, clustering analysis underscores the interplay between operational efficiency and capital robustness, showing that firms exhibiting superior operational efficiency and capital robustness demonstrate higher engagement in derivatives hedging. These findings contribute to the corporate risk management literature by expounding on the primacy of operational considerations in derivatives usage, particularly in asset-intensive industries. The study also provides practical implications for manufacturing firms navigating volatile market conditions, emphasizing that integrating operational and financial strategies is crucial for effective risk management.

This paper investigates the weekly evolution of child skills as measured by unique data from a widely-emulated early childhood home-visiting program developed in Jamaica, adapted to rural China, and applied in different versions worldwide. The design of the study avoids problems of endogeneity of inputs and lack of truly comparable measures of skills across children that plague previous econometric studies of child development. Skills that are nominally classified as the same, in fact, do not appear to share a common unit scale across levels. They are produced by skill-specific, lifecycle-stage-specific technologies. We formulate and estimate a new dynamic stochastic skill production model for multiple skills that is consistent with the evidence. We quantify the dynamics of early life learning. The model explains the “fadeout” of measures of learning by the emergence of new skills not properly measured. We investigate the role of ability in learning. We find important differences in learning patterns between boys and girls.

This paper examines the interactional phenomenon where an institutional complainee initiates a complaint and becomes a co-complainant with their original complainant against a third party that is proposed to have caused grievances to both participants. Institutional complainees initiate their third-party complaints when their complainants repeatedly refuse to affiliate with their attempts to shift responsibility or their proposed solutions. This shift from being the complainee to being a co-complainant is regularly accomplished through practices in which the institutional complainee: 1) produces implicit counter-complaints; 2) partitions complainants and themselves as sharing similar identities; and 3) highlights and upgrades their own grievances. Once complainants affiliate with their complaints, institutional complainees attempt to end the complaint sequences. The interactions end with a sense of solidarity sustained between the participants, even though no satisfying solutions are offered to the original complainants. The findings suggest that institutional actors can make relevant their non-institutional identities and go against what is expected of them as institutional actors to achieve the institutional task of directing blame away from their institutions. Recorded phone conversations between local residents and various institutional actors during COVID-19 lockdowns in China serve as data for this study.

Investors and forecasters often extrapolate from past returns, but whether this reffects behavioral bias or efficient information processing remains unclear. We address this questionby inferring Chinese mutual fund managers’ market expectations from textual analysis oftheir commentaries and linking them to portfolio choices and performance. Extrapola-tion is state-dependent: it is stronger when growth is above trend and idiosyncratic riskis relatively more important. It is associated with weaker market timing and strongerstock picking, leaving overall performance unchanged. Our findings support a rational-inattention model of expectation formation, in which managers shift scarce attentionbetween aggregate and stock-speciffc information as the relative importance of differentrisks change.

Using proprietary data from China’s interbank bond-pledged repo market, we show that the interest-rate risk and credit risk of the pledged bond are key determinants of repo pricing. From a bond-option perspective, we develop arbitrage-free models that anchor the repo yield curve to the pledged-bond yield curve. The fair repo haircut is interpreted as the per-unit price of a call option on the pledged bond. We extend this framework to incorporate bail-in or bail-out potential, which enhances the model’s empirical performance and provides a novel explanation for systematic repo cheapness and existence of negative haircuts.