Economic policy uncertainty is a key determinant of exchange rate stability. This study investigates the impact of China's categorical economic policy uncertainties on the long-term correlation between onshore (CNY) and offshore (CNH) Renminbi (RMB) exchange rates. We find that fiscal policy uncertainty (FPU), monetary policy uncertainty (MPU), and exchange rate and capital account uncertainty (EXRPU) have a significant negative effect on this correlation, while trade policy uncertainty (TPU) has no significant impact. Furthermore, CNY and CNH do not effectively diversify risks and provide only limited hedging benefits.

This paper investigates how the Global Supply Chain Pressure Index (GSCPI) affects long-term stock–bond correlations in China, employing mixed-frequency data from April 2005 to June 2025 in a DCC-MIDAS-X framework. Results show that higher GSCPI significantly reduces long-term stock–bond correlations, thereby enhancing the hedging property of bonds. This effect is both state-dependent and asymmetric, remaining significant in low-volatility regimes and following negative shocks, while becoming largely muted during high-volatility periods or after positive shocks. However, the impact of GSCPI weakens substantially after China’s 2014 financial liberalization, as global financial factors increasingly drive cross-asset dynamics. Moreover, GSCPI provides incremental information that enhances portfolio diversification and hedging performance.

Against the backdrop of recurrent global crises, economic uncertainty, and mounting environmental and social pressures, corporate resilience—defined as a firm’s capability to withstand external systemic shocks—has emerged as a critical determinant of long-term sustainability. This study empirically exames the effect of ESG (Environmental, Social, and Governance) performance on corporate resilience in China’s A-share market, using the COVID-19 pandemic as a natural experiment to identify causal effects. The sample comprises 651 A-share listed firms, excluding financial institutions, real estate firms, and ST/*ST companies, over the period from January 20, 2020, when the pandemic was officially announced in China, to June 30, 2024. ESG performance is measured as the average of 2018–2019 ratings issued by three major domestic agencies, thereby capturing firms’ pre-shock conditions and mitigating concerns of reverse causality. Corporate resilience is evaluated along two dimensions: resistance, measured by the severity of losses in net income, revenue, and stock price, and recovery, measured by the time required for ROA, EBIT, stock price, and Tobin’s Q to return to pre-shock levels. To ensure the robustness of the findings, this study employs linear regression models with industry-clustered robust standard errors, an instrumental-variable approach using R&D intensity and analyst coverage as instruments, and a Cox accelerated failure time model to estimate recovery duration. The empirical results indicate that stronger pre-shock ESG performance significantly enhances corporate resistance and shortens recovery time. Mechanism analyses further reveal that ESG strengthens corporate resilience by improving total factor productivity, alleviating financing constraints, and enhancing corporate reputation. These findings remain robust to multicollinearity diagnostics and a range of additional robustness tests. Overall, this study provides empirical evidence of the value of ESG in strengthening corporate resilience and offers important implications for firms, policymakers, and investors.

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，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。

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。

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。