This paper studies whether and how policies that promote a currency’s use in international invoicing can also strengthen its role as an anchor currency in other economies’ exchange rate baskets. We exploit the establishment of swap lines by the People’s Bank of China as a natural setting to examine this mechanism. First, we estimate countries’ implicit currency baskets and the weights assigned to the RMB. We then use a staggered difference-in-differences design to assess the effect of initiating swap line agreements on the RMB’s weights in these baskets. Our results indicate that RMB weights increase by approximately 5% about nine months after a swap line is introduced and remain persistently higher thereafter. Finally, we develop a three-country DSGE model to interpret these findings, showing that by promoting RMB invoicing, swap lines reinforce the RMB’s role as an anchor currency for exchange rate stabilization.

Financial crises rarely erupt without warning; they are preceded by long periods of hidden fragility. Yet traditional market indicators such as the VIX capture only realized volatility, offering little foresight. This paper introduces the Stability Gap Model (SGM), developed iteratively from a simple intuition: fragility arises when risk-taking diverges from fundamentals and systemic buffers are insufficient. We trace the evolution of the model from its original formulation, through corrections and extensions, to its present form. The Classic SGM captures instantaneous imbalance, while the Beta SGM incorporates memory of past shocks. Empirical analysis demonstrates that the SGM provided clear early warnings ahead of the 2008 Global Financial Crisis, the 2011 Eurozone debt episode, the 2015 China/oil slowdown, and the 2018 tightening cycle, while also trending upward in 2019 before the COVID-19 crash. Furthermore, the paper demonstrates the model's utility in assessing fragility in hedge funds and proposes its application as a universal framework for stability analysis across diverse systems, from corporate finance to supply chains.

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。

中国经济增速自 2012 年起持续下行，学界对其潜在增速的判断长期存在分歧。本文基于2005Q1—2025Q4中国31个省级行政区季度面板数据，构建“双场景 + 双红利 + 双约束”统一分析框架，系统检验不同经济循环模式下的增长约束机制。对比多种计量方法的稳健性后，采用工具变量法、多期 DID、中介效应、滚动窗口门槛回归、反事实模拟及异质性企业 DSGE 模型开展实证分析，得到三项核心结论。第一，中国经济增长呈现清晰的四阶段演化特征，外需主导期与内需主导期的约束机制存在本质差异；仅在外需主导阶段，美元M2增速与GDP增速存在显著倒 U 型关系，7%—10%为最优黄金区间。第二，3.30% 实际融资利率与零边际利润率双重约束严格锁定内需主导期增长，一旦进入“越投越亏”区间，GDP增速将出现断崖式回落。第三，现有研究关于潜在增速的分歧，本质是无条件收敛假说与有条件收敛假说的视角差异。本文拓展了开放条件下的经济收敛理论，构建的双场景双约束分析框架，为理解中国经济增速换挡提供了新的理论视角与实证支撑。

货币结构研究长期存在一个核心困惑：1999-2019 年M1/QM存量比始终稳定在 1:2，2020 年后却出现持续性失锚。现有研究大多聚焦M1/M2增速剪刀差的短期周期特征，普遍忽视存量资金收支的底层约束，同时资本收益率与融资成本的核算口径混乱，导致不同研究结论缺乏可比性。本文构建居民-商业银行-实体企业三部门时变参数 DSGE 模型，采用白重恩（2006）国民核算法范式，采用MPK与全实体WACC对偶口径，提炼得到M1,tre,t=QMtrd,t这一收益等价核心恒等式。依托1999Q1-2026Q1跨国时序、全国年度、中国31省份季度面板三层数据，综合多套识别策略，分国别测算资本收益倍数Kt的破裂临界值：中国 1.801、日本 1.785、德国1.922，混合样本临界值1.803可作为类似制度特征工业化经济体的参考基准。当Kt跌破临界阈值时，存量货币持续从经营性活期向定期沉淀。纠正“单纯依靠放宽银行信贷供给就能改善货币结构、降息万能、紧盯历史比值调控”的政策误区。量化测算结果显示，累计新增 11.23 万亿元实体利润可修复收益闭环，经济体将自发形成适配现行制度的全新货币均衡比例。

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。

In emerging markets characterized by signiffcant information asymmetry, mitigat-ing firm-level risk is paramount for market stability. While the governance role ofinstitutional investors is known, the impact of their direct, on-the-ground engagementremains underexplored. This study’s objective is to investigate how institutionalinvestor site visits, a crucial hands-on governance mechanism, affect stock returnvolatility. Using a sample of Chinese-listed A-share firms from 2012 to 2022, wefind that frequent site visits significantly reduce firm-level stock return volatility.This risk-reduction effect is more pronounced for firms with greater agency problems,poorer ESG performance, and higher expropriation risk. Our analysis, robust toendogeneity concerns, indicates this effect is driven by improved external oversight.We conclude that direct institutional engagement is a vital channel for reducinginformation asymmetry, enhancing corporate governance, and ultimately promotingmarket stability by lowering investment risk.

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.

This study examines how global turbulence factors shape volatility spillovers among emerging stock markets through the lens of risk cycles. We find that emerging market connectedness exhibits clear regime heterogeneity across risk cycles, while also preserving several persistent structural patterns. Specifically, trade policy uncertainty (TPU) and economic policy uncertainty (EPU) serve the dominant drivers during risk outbreak and risk accumulation periods, respectively. Meanwhile, sustainability uncertainty (ESGUI) consistently plays a leading driver role in both regimes, while physical climate risk plays a comparatively limited role. Furthermore, the effects of these core turbulence factors are nonlinear and threshold-dependent, highlighting the importance of accounting for risk cycle heterogeneity and nonlinear dynamics when assessing emerging market risk transmission.