In view of the divergence of existing research results on the relationship between ESG and investment returns, this paper constructs an S-score metric, which comprehensively measures corporate sustainability performance. It further tests the applicability of a sustainability-based investment strategy using this metric in China's A-share market. Using Shanghai and Shenzhen A-shares from May 2016 to April 2024 as the research sample, the S-score is constructed across five dimensions: Profitability, Growth Opportunities, Investment Efficiency, Risk Mitigation, and ESG Performance. The S-score is calculated using Z-score standardization and entropy weighted. Strategy effectiveness was tested through univariate grouping, bivariate grouping, and Fama-Macbeth regression, further examining strategy performance under varying market conditions, holding periods, and information environments. The study finds that the S-score demonstrates significant discriminative power for cross-sectional stock returns. The hedge portfolio based on this metric achieved an annualized excess return of 7.943% after adjusting for the China three-factor (CH-3) model. Its predictive power remains robust after controlling for variables such as market capitalization and book-to-market ratio, delivering significant positive returns across bull and bear markets, extreme pandemic conditions, and holding periods of up to eight years. From a behavioral finance perspective, this paper reveals that explanations such as the gradual diffusion of information and investors' limited attention span help elucidate the profitability of the S-score strategy. The findings demonstrate the effectiveness of Sustainable Investing strategies in China's A-share market, indicating that ESG-integrated factor investing can optimize resource allocation. This research contributes empirical evidence on Sustainable Investing in emerging markets, providing insights for policy formulation and practical implementation while supporting the virtuous cycle between Sustainable Investing and long-termism.

在“小院高墙”政策冲击与全球价值链重构的背景下，出口企业如何在外部约束上升时调整出口渠道并配置能力投资，是理解产业链供应链韧性的重要问题。本文构建了包含直接出口、第三国转运、海外生产和退出选择的异质性企业贸易模型，并结合海关贸易流与上市公司经营信息进行结构估计。研究发现，地缘风险上升会提高直接出口生存门槛，推动部分存活企业转向非直接渠道；相对于冲击后被迫留在原渠道的反事实，渠道重置能够显著降低出口损失，能力投资通过降低转运风险和组织调整成本进一步增强这一作用。模拟矩估计结果显示，基准情形下直接出口损失约为 9.06%；若禁止渠道切换，损失上升至 14.86%；若关闭能力投资，损失上升至 10.63%。稳健性和异质性检验表明，冲击前具有海外经营经验、研发投入强度较高的企业更可能完成渠道调整。本文为解释地缘经济冲击下出口企业的渠道应对和能力建设提供了微观证据，也为完善企业出海支持和供应链韧性政策提供了参考。

资金脱离实体经济在金融与债务体系内部空转，是当前中国产业转型升级面 临的核心金融障碍。传统范式基于单一 GDP 口径的货币进行测算，无法有效解 释 “宏观货币宽松与微观产业缺钱” 的现实悖论。本文回归欧文・费雪 1911 年 原始交易定义，构建实体经济 — 金融体系 — 债务存续三层底盘分析框架，采 用纯数理恒等推演方法，经口径修正与验证，对 2021-2025 年中国资金脱实向 虚的规模、流速与产业传导逻辑进行量化诊断。 研究表明，2021-2025 年全域货币流通速度累计增长14.25%。但实体经济 流速仅增长 11.18%，显著低于全域增速；更值得重视的是金融与债务部分流速 分别增长 16.88% 和 35.88%，成为全域流速增长的核心构成，也是资金脱实向 虚的量化证据。传统 T=GDP 范式存在14.25个百分点的系统性缺口，本质是遗 漏金融与债务交易，这部分资金长期在体系内空转，并未参与实体经济与产业资 本循环。本文构建了可复制、可验证的资金脱实向虚量化诊断工具，测算出三层底盘 的资金分流比例与产业传导弹性，突破了现有产业金融化研究缺乏统一量化工具 的瓶颈。

中国工业发展的空间分化态势持续加剧，资金供给能力与企业经营 决策的异质性是驱动区域非均衡发展的核心变量。本文基于 2016—2025 年 290 座地级市平衡面板数据，统一规上工业统计口径，引入综合能耗、税收总 额与出口交货值作为传导变量，构建双重面板门槛模型识别资金能力与经营意 愿的临界阈值，搭建全域城市工业发展九类型诊断工具。研究表明：规上工业 存贷比存在 0.54、0.72 两道结构性门槛，资金流动活跃度存在 0.76、0.94 两道行为性门槛，共同界定工业承压、平稳运行与效益跃升三个发展区间；以 投资强度、营业利润率为双被解释变量的模型拟合优度分别达 0.829、0.831， 核心变量均通过 1% 显著性检验。剔除 25.45% 估算样本后，核心门槛值波动 小于 0.02，结论保持稳健。依托资金 — 意愿二维组合划分的九类城市，其人 均 GDP、一般公共预算收入与规上工业税收呈现严格逐档递增特征，同一资金 档位内经营意愿每提升一档，城市 GDP 全国排名平均前移 15—25 位，且存在 显著的空间俱乐部趋同现象。内生性、空间溢出与安慰剂检验均支持因果推 断。本文构建的标准化诊断工具可为国土空间产业布局优化与区域协同发展提 供量化决策依据。

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。

宏观经济学长期面临主流模型测算自然利率与实体真实回报显著背离的 " 利率鸿沟" 困境，传统 HLW 滤波、DSGE 等方法在 2020 年代低增长、高债务 环境中已普遍失效。基于无套利均衡原理，构建包含家庭、企业、金融中介的 三部门一般均衡模型，推导出自然利率白箱测算公式，提出 "自然利率即实体 经济长期盈利盈亏平衡线" 核心命题，构建与 BIS、IMF 等国际标准全面衔接 的五维债务健康度评价体系。经多轮参数校准与 2017Q1-2026Q1 中美日德韩跨 国面板数据实证检验，中国自然利率中枢稳定在 4.8%-6.1% 区间，显著高于传 统测算值；该指标对固定资产投资具有显著预测力，比 HLW 滤波平均提前 2-3 个季度预警经济波动。研究表明，中国债务核心指标处于发达国家合理区间， 产业利润可稳定覆盖利息支出，不存在系统性风险。以持续付息保障新质生产 力培育时间窗口的发展逻辑，可为宏观调控提供可落地的实操工具。

研究识别出中国抵押品经济核心非对称杠杆乘数为 2.37，95% 置信区间 [2.16，2.55]。2014 年前后，我国货币信用体系完成范式转型，进入以房地产 为核心载体的抵押品经济时代，资产成为联结信用创造与民生福祉的关键纽 带。依托 2001—2024 年宏观月度数据、粤港澳大湾区面板数据，结合佛山市 供应链企业一手调研资料，构建内嵌时变摩擦的抵押品经济模型。实证环节规 避主观断点设定与双向因果争议，采用 Bai-Perron 数据驱动检验、NARDL 非 对称协整模型，搭配历史地理外生工具变量。结果显示，2014 年 1 月为信用 锚转型唯一显著结构性断点；全样本下，抵押品下行收缩效应为上行扩张效应 的 2.37 倍，珠三角区域非对称效应放大至 3.02 倍；抵押品价值波动通过资 产负债表渠道抑制居民可选消费，供应链动产融资体系缺失进一步放大冲击强 度。研究回应审稿对非对称机制与区域异质性的核心质疑，为区域差异化宏观 审慎管理提供量化依据

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.