资金脱离实体经济在金融与债务体系内部空转，制约中国产业转型升级。传统GDP单一口径长期误读费雪1911年原始交易方程的全口径内涵，无法解释"宏观货币宽松、微观产业缺钱"的现实悖论。本文采用T1-T2-T3交易层级三分法框架，基于2000Q1—2024Q4经季节调整的官方季度数据（100个观测值），辅以年度及31省省级面板数据交叉验证（2025年为模拟值，不纳入基准样本），运用门槛回归等计量方法检验实体流动性弹塑性断裂机制。 2000—2025年全域货币流通速度累计增长8.34%，但T1实体交易层仅增长6.81%，T2、T3层分别达13.34%、17.35%；债务流速16.92%为系统性突变门槛，样本期内持续被突破，流动性边际冲击放大3.08倍，实体产业进入不可逆塑性区间；传统T=GDP范式存在8.34%的系统性测算缺口。依托国家统计局收入法GDP、财政部财税官方原始数据，严格遵循白重恩（2006）基准、白重恩与张琼（2014）迭代核算规则重新测算税后实体资本收益率，全样本均值为4.82%，长期低于5%临界安全线。结合姊妹文献M1灭失等结果形成存量-流量两重视证链条，本文构建的量化测算工具具备全流程可复现特征，能够常态化监测资金空转现象，佐证T1-T2-T3框架的科学性与适用性。

同等经济规模的地级市之间，工业发展差距持续拉大，仅依靠经济发展阶段理论无法充分解释这一分化现象。本文搭建资金禀赋与经营意愿的二维分析框架，选取 2016—2025 年国内 289 座地级市平衡面板数据，利用双重门槛模型内生测算得到两组临界数值：资金充裕度分界点为 0.54、0.72，资金流动活跃度分界点为 0.76、0.94，并按照两项指标的组合差异划分出九类城市工业发展形态。实证结果显示，资金储备水平决定区域工业发展的基础底线，企业扩张意愿则影响资金转化为实体产出的实际效率，二者存在显著正向交互效应。基于上述门槛识别结论，本文提出双门槛陷阱假说，配套设计九类型工业发展诊断工具，可用于季度动态监测，为城市制定差异化产业扶持政策提供量化参考。

中国式 “宽货币、紧信用” 结构性悖论，长期缺乏机制闭环、量化统一的 解释框架。研究依托 2015Q1—2025Q4 银行微观时序与宏观匹配数据，构建货 币异化全链条传导体系，实证识别出双重非线性安全边界：银行业活期存款占 比 27.2%（存量阈值）、M2/M1 增速倍率 1.8（增速阈值）。活期占比跌破 27.2% 后，数字金融对货币异化、信贷收缩的负面冲击放大 3.8 倍。27.2% 并 非简单统计均值，而是同时契合净稳定资金比例（NSFR）=100%、银行负债盈亏 平衡、货币乘数由 9.0 骤降至 5.5 的三重机制熔断点。依托标准化系数分解 （规避主观赋值偏差），信贷收缩由供给约束（45%）、需求约束（30%）、结 构挤占（25%）复合驱动，终结供需二元对立争议。2015—2025 年测算显示， 累计失踪 M1 达 18.2 万亿元，形成 32.8 万亿元信贷缺口，货币流通速度下 降 0.14 次，从货币结构梗阻维度，揭示扩大内需面临的深层约束。研究为理 解中国货币结构异化提供可量化阈值体系，也为疏通货币传导、破解内需瓶颈 提供实证锚点。

2014 年我国货币信用体系实现信用创造机制范式转型，正式进入以不动产为核心载体的抵押品经济时代。本文识别出中国不动产抵押品的核心结构参数，将其定义为不动产抵押品非对称乘数（Collateral Asymmetry Multiplier，CAM），其中枢估计值为2.37，95%置信区间为[2.16，2.55]。研究选取2001—2025年宏观数据，构建内嵌时变摩擦的不动产抵押品经济模型，综合采用 Bai-Perron 断点检验、NARDL非对称协整模型与历史地理外生工具变量实证识别。检验结果显示，2014年是信用锚转型的显著结构性断点；不动产抵押品下行收缩效应为上行扩张效应的2.37倍，高市场化区域强度放大至3.02倍；不动产抵押品价值波动通过资产负债表渠道抑制居民可选消费与企业投资，动产融资体系缺失持续放大非对称冲击。基于 CAM 参数的识别，提出差异化区域化宏观审慎方案，为信用周期调控提供量化依据。

实体经济盈利承压与虚实经济失衡的矛盾持续凸显，本文将产能约束与金融化 冲击纳入统一分析框架，依托 2010—2025 年中国省级工业面板与制造业上市公司 微观数据，运用面板门槛模型、多期连续双重差分模型与工具变量法，系统检验两 类结构性因素对工业利润的非线性冲击及盈利缓冲机制。研究表明，中国工业盈利 呈现显著的双阈值突变特征：金融化指数非线性临界阈值为 0.22，突破后利润挤出 效应呈非线性放大；产能利用率约束临界阈值为 0.75，低于该值后利润压制效应显 著增强，且金融化冲击强度显著高于产能约束。0.22 阈值对应企业财务费用占利润 总额的 22%，是付息能力的生死临界点，契合民间融资 2 分息极限、利息保障倍数 安全线与监管红色预警线。机制检验发现，阈值突破后金融化通过挤占实业投资、 抬升融资成本形成非效率分配冲击，传统产业升级、出口与逆周期政策的缓冲效应 全面失效。异质性分析显示，民营企业、传统制造业与中西部地区更易突破金融化 临界阈值，盈利受冲击程度更深。本文为划定金融化监管临界值、防范脱实向虚、 提振制造业盈利提供了量化依据与经验支撑。

This paper illustrates how firms with publicly disclosed political connections use subsidiaries to obtain preferential treatment in land markets. While the headquarters of politically connected listed firms pay land prices comparable to those paid by other firms, their subsidiaries receive discounts of 12.1%–13.2%. These discounts are more pronounced when land is acquired through less transparent methods, in regions with weaker institutional environments, and among private firms. The anti-corruption campaign launched in 2012 effectively mitigates corruption-related discounts, with the magnitude of the discounts negatively associated with campaign intensity. Additionally, larger discounts for subsidiaries are observed following greater charitable donations, suggesting a reciprocal relationship between firms and officials. Overall, the findings contribute to a broader understanding of how firms with publicly disclosed political ties use complex corporate structures to engage in rent-seeking behavior.

We use nearly a decade’s worth of panel data from European Union Chamber of Commerce in China business confidence surveys to analyse the deteriorating outlooks of EU firms in China from 2017 to 2025. All firms in China currently face challenges including slow profit growth and deflation. These circumstances have contributed to a rare drop of foreign direct investment into China over the last two years. However, certain challenges are particularly acute for foreign firms, including those from the EU. According to survey results, business sentiment among EU firms operating in China has never been bleaker. Respondents view their profitability, growth opportunities and competitiveness negatively, while fewer respondents than ever plan to expand their Chinese operations. Moreover, significant shares of respondents report recent increases in political pressure from the Chinese state and media, while nearly a third of respondents say they are siloing their Chinese operations, meaning separating them from other global activities. Disaggregated by size, sector, and years of operation in China, insightful differences emerge between the business strategies of EU firms. We broadly classify these into four categories: doubling-down, hedging, hibernating and ready to exit. EU policymakers should consider how to address the challenges EU firms in China face, such as asset-heavy sectors being ‘stuck’ in China and smaller firms lacking the capacity to operate at a loss in China’s market. The EU might need to facilitate transitions for these companies, helping them to reduce exposure to China and diversify into other emerging markets.

This study documents a novel, culturally embedded calendar anomaly in the Shanghai Composite Index (SSE Composite) derived from the Nayin (纳音) Five Elements system—a traditional Chinese sexagenary calendrical framework. Utilizing daily data from 1990 to 2025, the analysis reveals a significant correlation between elemental two-year periods and market performance. Key findings include: Earth-Element Dominance: Earth periods exhibit a 100% positive return rate (4/4) with a mean return of +123.4%. The effect size is substantial (Cohen’s d=1.50) compared to non-Earth periods. Metal-Element Declines: Metal periods universally display a structural peak-and-decline morphology, with an average −30.4% late-cycle decline. Water-Element Momentum: Water periods systematically mirror the directional momentum of their predecessors with 100% accuracy (3/3). These patterns fail to replicate in the S&P 500, suggesting a unique cultural-behavioral channel where traditional metaphysical cycles modulate investor sentiment in the Chinese market. This research provides the first empirical validation of Nayin-based cyclicality in financial asset pricing, offering a predictive framework for institutional and individual investors focused on the China-specific market. Keywords: Calendar anomaly, Chinese traditional calendar, Nayin Five Elements, Shanghai Composite Index, Cultural behavioral finance, Sexagenary Cycle, Market Sentiment Declaration of Interest The author declares no conflict of interest. To ensure the objectivity of this research, the author further declares that he holds no active personal trading positions in the securities discussed. The author's personal trading account has been inactive with zero transactions over the past five years.

We propose the AI Narrative Gap as a novel firm characteristic—the systematic divergence between a firm’s AI strategic narrative intensity and its subsequent AI capital expenditure commitment—and document its capital market consequences. Using Chinese A-share listed firms from 2015 to 2022, we show that firms with a wider AI Narrative Gap attract significantly more optimistic and less accurate analyst earnings forecasts. These distorted expectations, in turn, predict lower subsequent stock returns, lower industry-adjusted abnormal returns, and weaker future accounting performance. A double-sort portfolio placing firms simultaneously in the highest tercile of the AI Narrative Gap and highest tercile of analyst optimism earns a mean return 22.8 percentage points below that of the lowest tercile on both dimensions (t = −5.10). The return reduction in the AI Narrative Gap coefficient is attenuated but not eliminated after controlling for optimism, consistent with a partial expectation-distortion channel. Collectively, these results establish the AI Narrative Gap as a cross-sectionally informative firm characteristic that captures the credibility of a firm’s AI strategic identity, with systematic implications for analyst expectations and asset prices.

We posit and demonstrate that, in China’s retail-dominated market, quantitative trading over-relies on non-fundamental signals, thereby crowding out fundamental information from stock prices and increasing crash risk. Using trading data from quantitative mutual funds and Chinese A-share firms during 2009-2023, we find that greater exposure to quantitative trading is associated with higher future crash risk. Mediation analysis further reveals that reduced information efficiency constitutes a key channel through which quantitative trading elevates crash risk. The effect is stronger for stocks with more retail investors, consistent with our proposed mechanism. Overall, we identify a novel potential risk of quantitative trading in underdeveloped emerging markets.