North American Journal of Economics and Finance最新文献_第4页

The spillover effect of customer extreme climate risk: Evidence from supplier trade credit 顾客极端气候风险的溢出效应：来自供应商贸易信用的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-12 DOI: 10.1016/j.najef.2025.102553

Zhen Huang, Tianyu Dou

This study examines the spillover effect of customer extreme climate risk on suppliers’ trade credit provision to their customers, and the moderating effects of customer climate sensitivity and customer green investment. We find that suppliers decrease trade credit provision as customer extreme climate risk increases. This adverse impact is stronger when firms have higher customer climate sensitivity and lower customer green investment. The negative effect continues to hold under several robustness tests, such as instrumental variable regression and propensity score matching. We further find that the influencing mechanism through which customer extreme climate risk impacts supplier trade credit is to increase the likelihood of customer credit risk. Additionally, the effect of customer extreme climate risk on suppliers’ trade credit provision is more significant when customers are non-state-owned or have a low market position. Our findings highlight the importance of customer extreme climate risk and offer valuable insights for suppliers to refine their business strategies in the context of supply chain risk spillover.

本研究考察了客户极端气候风险对供应商向其客户提供贸易信贷的溢出效应，以及客户气候敏感性和客户绿色投资的调节效应。我们发现，随着客户极端气候风险的增加，供应商减少了贸易信贷供应。当企业具有较高的客户气候敏感性和较低的客户绿色投资时，这种不利影响更强。在几个稳健性测试下，如工具变量回归和倾向得分匹配，负面影响继续保持。进一步发现客户极端气候风险影响供应商贸易信用的影响机制是增加客户信用风险的可能性。此外，当客户是非国有企业或市场地位较低时，客户极端气候风险对供应商贸易信贷提供的影响更为显著。我们的研究结果强调了客户极端气候风险的重要性，并为供应商在供应链风险溢出的背景下完善其业务策略提供了有价值的见解。

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引用次数: 0

Does climate policy uncertainty affect expected shortfall (and Value-at-Risk) in the Chinese sector? Evidence from the mixed-frequency dynamic semi-parametric approach 气候政策的不确定性是否会影响中国行业的预期缺口（和风险价值）？来自混合频率动态半参数方法的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-12 DOI: 10.1016/j.najef.2025.102555

Kunliang Jiang , Pengfei Luo , Wenxiao Gan , Jiashan Song , Yuejing Wang

Climate policy uncertainty (CPU) increases risks across sectors by affecting the economic environment, stock price volatility, corporate transformations, and investor confidence. However, incorporating such low-frequency information into sector risk assessments remains insufficiently addressed. This study combines the GARCH-MIDAS model with the Fissler–Ziegel (FZ) loss function to jointly model Value-at-Risk (VaR) and expected shortfall (ES), and explores the heterogeneous impact of CPU on risk measures across eleven sectors from 1 January 2008 to 31 December 2022 in China. Our findings indicate that CPU positively affects the VaR and ES in five sectors: energy, material, industry, consumer discretionary, and utility, while negatively impacting six sectors: consumer staple, healthcare, information technology, telecommunication service, real estate, and finance. The effect of CPU on the VaR and ES in the energy and material sectors demonstrates strong long memory, whereas the impact on telecommunication service is the opposite. Incorporating CPU into the model significantly improves the accuracy of sector risk measures across various risk levels, while the FZ loss function method provides effective risk measurement results primarily under extreme risk conditions.

气候政策的不确定性（CPU）通过影响经济环境、股价波动、企业转型和投资者信心，增加了各行业的风险。然而，将这种低频率信息纳入部门风险评估的问题仍然没有得到充分解决。本研究结合GARCH-MIDAS模型和Fissler-Ziegel （FZ）损失函数对风险价值（VaR）和预期缺口（ES）进行联合建模，并探讨了2008年1月1日至2022年12月31日期间中国11个行业的CPU对风险措施的异质性影响。研究结果表明，CPU对能源、材料、工业、非必需消费品和公用事业五个行业的VaR和ES有正向影响，而对主要消费品、医疗保健、信息技术、电信服务、房地产和金融六个行业的VaR和ES有负向影响。CPU对能源和材料行业VaR和ES的影响表现出较强的长记忆性，而对电信服务的影响则相反。将CPU纳入模型显著提高了各行业风险度量的准确性，而FZ损失函数法主要在极端风险条件下提供有效的风险度量结果。

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引用次数: 0

Quantile-frequency dependence between U.S. sector stock indices and macro-financial indicators: A quantile coherence approach 美国行业股票指数和宏观金融指标之间的分位数频率依赖性：分位数一致性方法

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-07 DOI: 10.1016/j.najef.2025.102552

Halilibrahim Gökgöz , Aamir Aijaz Syed , Catalin Gheorghe , Ahmed Jeribi

This study explores the quantile–frequency linkages between U.S. sectoral stock indices and four macro-financial indicators: market volatility (VIX), geopolitical risk (GPR), inflation expectations (T5YIE), and the yield curve (T10Y3M), using the Quantile Coherence (QC) framework. The method captures nonlinear and asymmetric interactions across quantiles and horizons. The dataset covers daily observations from January 2016 to July 2025, encompassing episodes such as Brexit, the China–U.S. trade war, and recent geopolitical conflicts. Results reveal strong sectoral heterogeneity: dependence on VIX is predominantly negative in the short term during bullish phases, with reversals at longer horizons; the influence of GPR is asymmetric and forward-looking; inflation expectations, captured by T5YIE, show a stable long-run positive association with all sectors; while the yield curve (T10Y3M) generates systematic long-term co-movements, with leadership alternating between financial indicators and sector indices across regimes. These findings demonstrate uneven sectoral responses to macro-financial drivers and provide guidance for risk management and portfolio design in uncertain environments.

本研究利用分位数一致性（QC）框架，探讨了美国行业股票指数与四个宏观金融指标：市场波动率（VIX）、地缘政治风险（GPR）、通胀预期（t5ie）和收益率曲线（T10Y3M）之间的分位数-频率联系。该方法捕获了跨分位数和视界的非线性和非对称相互作用。该数据集涵盖了从2016年1月到2025年7月的每日观测数据，包括英国脱欧、中美关系和气候变化等事件。贸易战和最近的地缘政治冲突。结果显示了很强的行业异质性：在看涨阶段，对VIX的依赖在短期内主要为负，在较长时间内出现逆转；探地雷达的影响是非对称的、前瞻性的；t5ye反映的通胀预期显示，通胀预期与所有行业都存在稳定的长期正相关关系；而收益率曲线（T10Y3M）则产生系统性的长期协同运动，在不同体制的金融指标和行业指数之间交替领导。这些发现表明，行业对宏观金融驱动因素的反应不均衡，并为不确定环境下的风险管理和投资组合设计提供指导。

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引用次数: 0

Asymmetric drivers of inflation: new evidence from machine learning and quantile method 通货膨胀的不对称驱动因素：来自机器学习和分位数方法的新证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-11-07 DOI: 10.1016/j.najef.2025.102551

Kingsley Imandojemu , Adetutu Omotola Habib , Omozele Lynda Showunmi , Loveth Oribhabor Agboola

This paper investigates the complex, nonlinear forces behind price movements in Nigeria by applying quantile econometric techniques. Using monthly data from December 2012 to August 2024, the analysis applies Elastic Net Regression for variable selection and employs Quantile-on-Quantile Kernel Regularized Least Squares (QQKRLS) alongside Quantile-on-Quantile Granger Causality (QQGC) tests. The results show that while money supply consistently drives inflation, the effects of other variables are regime-dependent; for instance, private sector credit fuels inflation in moderate-to-high periods, while bank reserves can dampen it in moderate ones. Furthermore, the analysis confirms a directional causality from these variables of interest to inflation, with the strength of the relationship varying significantly across quantiles. The results reveal that uniform policies are inadequate. Policymakers should, therefore, adopt quantile-specific and context-sensitive fiscal and monetary strategies to ensure durable price stability in Nigeria.

本文通过应用分位数计量经济学技术调查了尼日利亚价格变动背后的复杂非线性力量。利用2012年12月至2024年8月的月度数据，采用弹性网络回归进行变量选择，并采用分位数对核正则化最小二乘（QQKRLS）和分位数对格兰杰因果关系（QQGC）检验。结果表明，虽然货币供应量持续推动通胀，但其他变量的影响是依赖于制度的；例如，在中高时期，私人部门信贷会推动通胀，而在中高时期，银行准备金则会抑制通胀。此外，分析证实了这些感兴趣的变量与通货膨胀之间的方向性因果关系，这种关系的强度在分位数之间存在显著差异。结果表明，统一的政策是不够的。因此，政策制定者应采取具体分位数和对环境敏感的财政和货币战略，以确保尼日利亚的持久价格稳定。

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引用次数: 0

Does innovation-driven policy optimize urban energy consumption? Evidence from China’s innovation-driven city pilot policies 创新驱动政策是否能优化城市能源消费？中国创新驱动型城市试点政策的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-10-28 DOI: 10.1016/j.najef.2025.102548

Yingnan Cong , Yufei Hou , Yuan Ji , Xiaojing Cai

Restructuring energy consumption is essential for promoting green, low-carbon economic and societal development. Innovation-driven policies, particularly those implemented in pilot cities, play a crucial role in this transformation. This study conducts a theoretical analysis to examine how such policies influence urban energy-consumption structures. Using a multitime-point difference-in-differences model, it treats China’s national innovation-driven city pilot policies as a quasi-natural experiment. The results indicate that these policies significantly improve urban energy structures. Mechanism analyses reveal that the improvements occur mainly through green innovation and industrial upgrading. Heterogeneity analysis further indicates that the effects are more pronounced in cities with lower administrative tiers, more challenging geographical conditions, and stronger environmental priorities. These findings provide valuable policy insights for refining innovation-driven strategies, enhancing urban energy-consumption structures, and promoting sustainable economic development in China.

调整能源结构是推动经济社会绿色低碳发展的必然要求。创新驱动型政策，特别是在试点城市实施的政策，在这一转型中发挥着至关重要的作用。本研究从理论上分析了这些政策对城市能源消费结构的影响。采用多时间点差异模型，将中国国家创新驱动型城市试点政策视为准自然实验。结果表明，这些政策显著改善了城市能源结构。机制分析表明，绿色创新和产业升级是提高产业竞争力的主要途径。异质性分析进一步表明，在行政级别较低、地理条件更具挑战性、环境优先性更强的城市，这种影响更为明显。研究结果为完善创新驱动战略、优化城市能源消费结构、促进中国经济可持续发展提供了有价值的政策见解。

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引用次数: 0

Credit information sharing and corporate debt maturity structure: Evidence from a quasi-natural experiment in China 信用信息共享与企业债务期限结构：来自中国准自然实验的证据

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-10-28 DOI: 10.1016/j.najef.2025.102549

Zhiliang Zhu , Wuqi Song

Credit information sharing allows creditors to access borrowers’ credit histories, serving as an effective tool to monitor and discipline firms. Using China’s Social Credit System (CSCS) as an exogenous shock to credit information sharing, this study employs a difference-in-difference analysis and demonstrates that such sharing extends corporate debt maturity. This increase in debt maturity is attributable to improved information transparency and lowered debt agency costs. We further find that the effect is more pronounced among firms with state ownership and firms with higher leverage ratio. Additional tests show that shared credit files help alleviate firms’ investment and financing maturity mismatch issues. Collectively, this study provides new insights into the economic consequences of credit information sharing through the lens of debt maturity structure.

信用信息共享使债权人能够获得借款人的信用记录，成为监督和约束企业的有效工具。本研究将中国社会信用体系（CSCS）作为信用信息共享的外生冲击，采用异中异分析，证明了这种共享延长了企业债务期限。债务期限的增加是由于信息透明度的提高和债务代理成本的降低。我们进一步发现，这种效应在国有企业和杠杆率较高的企业中更为明显。另外的测试表明，共享信用档案有助于缓解企业投资和融资期限错配问题。总的来说，本研究通过债务期限结构的视角为信用信息共享的经济后果提供了新的见解。

引用次数: 0

Financial and business cycles in the US: A non-parametric time–frequency investigation 美国的金融和商业周期：一项非参数时频调查

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-10-26 DOI: 10.1016/j.najef.2025.102547

Marco Gallegati

In this study, we contrast U.S. financial and business cycles using turning point and wavelet analysis. These non-parametric methods enable us to identify the key characteristics of financial cycles and assess their relationship with business cycles without imposing assumptions about their cyclical or secular components. Contrary to the conventional view in the literature, we find that financial and business cycles are more similar than generally assumed. Wavelet analysis reveals that: i) since the 1990s, the dominant frequency range of both cycles has shifted towards lower frequencies; and ii) the observed increase in their average length is linked to a change in the relationship between financial and business cycles − from shorter business cycle frequencies (4–8 years) to higher medium-term frequencies (8–16 years). Focusing on the post-1990s period and using a measure of the financial cycle that includes equity prices, we find that the average lengths of business and financial cycles have become more aligned, at approximately 9 and 10 years, respectively. From a policy perspective, these findings cast doubt on the need for macroprudential policy as a distinct tool separate from traditional macroeconomic stabilization policy.

在本研究中，我们使用拐点和小波分析对比了美国的金融和商业周期。这些非参数方法使我们能够识别金融周期的关键特征，并评估它们与商业周期的关系，而无需对其周期性或长期成分施加假设。与文献中的传统观点相反，我们发现金融周期和商业周期比通常认为的更相似。小波分析表明：1)20世纪90年代以来，两个周期的主导频率范围都向低频偏移；ii)观察到的平均长度的增加与金融周期和商业周期之间关系的变化有关——从较短的商业周期频率（4-8年）到较高的中期频率（8-16年）。关注上世纪90年代后的时期，并使用包括股价在内的金融周期衡量标准，我们发现商业和金融周期的平均长度变得更加一致，分别约为9年和10年。从政策的角度来看，这些发现对宏观审慎政策作为一种有别于传统宏观经济稳定政策的独特工具的必要性提出了质疑。

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引用次数: 0

Dynamic interrelations and the potential of global industrial sectors to function as a refuge for the global transition towards a low-carbon economy 动态的相互关系和全球工业部门作为全球向低碳经济过渡的避难所的潜力

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-10-25 DOI: 10.1016/j.najef.2025.102545

Murad A. Bein

The article analyzes the interconnections among ten global industrial sectors and the returns associated with low-carbon investments across a spectrum of investment horizons. The findings derived from a time-varying parameter and quantile connectedness reveal that volatility primarily stems from transient economic and financial events rather than lasting structural changes within the market. The global low-carbon returns exhibit a remarkable resilience against the volatility inherent in the global industrial sectors across diverse market conditions and within various temporal frameworks. The findings from cross-quantilograms indicate that during periods of reduced low-carbon emissions, the utilities, consumer staples, energy, materials, financial, and communication sectors act to hedge against losses, thus providing potential stability to investors seeking refuge during economic downturns. Additionally, the estimation results reveal a significant influence of monetary policy and bitcoin valuation on connectedness. A tightening monetary policy is inversely linked, and this effect is more pronounced in a declining market. Similarly, the increase in bitcoin valuations diminishes interconnectedness, indicating that cryptocurrencies may serve as alternative investment vehicles during episodes characterized by market turbulence. Overall, the outcome highlights the importance of integrating financial strategies that align with environmental sustainability.

本文分析了全球十大工业部门之间的相互联系，以及在投资范围内与低碳投资相关的回报。从时变参数和分位数连通性得出的结果表明，波动性主要源于短暂的经济和金融事件，而不是市场内持久的结构变化。全球低碳回报在不同市场条件和不同时间框架下，对全球工业部门固有的波动性表现出非凡的弹性。交叉量化图的研究结果表明，在低碳排放减少期间，公用事业、主要消费品、能源、材料、金融和通信部门采取行动对冲损失，从而为在经济衰退期间寻求庇护的投资者提供了潜在的稳定性。此外，估计结果显示货币政策和比特币估值对连通性有显著影响。紧缩的货币政策是反向关联的，这种效应在下跌的市场中更为明显。同样，比特币估值的上升削弱了互联性，表明加密货币可能在市场动荡时期作为另类投资工具。总体而言，结果突出了将与环境可持续性相一致的财务战略整合起来的重要性。

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引用次数: 0

Enhancing stock market predictions with multivariate signal decomposition and dynamic feature optimization 用多元信号分解和动态特征优化增强股市预测

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-10-24 DOI: 10.1016/j.najef.2025.102546

Xiaorui Xue , Shaofang Li , Xiaonan Wang , Tingting Ren

Predicting stock trends is vital in financial systems, providing insights for strategies aimed at generating excess returns. The market’s intrinsically chaotic, nonlinear, and multivariate characteristics hinder the efficacy of traditional deep learning models, especially in recognizing dynamic interdependencies and temporal non-stationarity. This study introduces an innovative hybrid framework (MVMD-NT-TiF) that integrates multivariate signal decomposition, non-stationary sequence modeling, and dual-attention-based feature selection into a cohesive architecture. By concurrently tackling noise, temporal adaptability, and feature redundancy, the approach facilitates precise and resilient forecasting in intricate financial contexts. Empirical findings regarding key stock indices illustrate its enhanced accuracy and universality relative to leading baselines, underscoring its use in real-world scenarios such as quantitative investing, risk management, and trend analysis.

预测股票走势在金融系统中至关重要，它为旨在产生超额回报的策略提供洞见。市场固有的混沌、非线性和多元特征阻碍了传统深度学习模型的有效性，特别是在识别动态相互依赖性和时间非平稳性方面。本研究引入了一种创新的混合框架（MVMD-NT-TiF），该框架将多元信号分解、非平稳序列建模和基于双注意力的特征选择集成到一个内聚架构中。通过同时处理噪声、时间适应性和特征冗余，该方法有助于在复杂的金融环境中进行精确和有弹性的预测。关于主要股票指数的实证研究结果表明，相对于领先基线，它具有更高的准确性和普遍性，强调了它在量化投资、风险管理和趋势分析等现实场景中的应用。

引用次数: 0

Examining climate risk attention in stock markets: insights from quantile-on-quantile regression 考察股市对气候风险的关注：来自分位数对分位数回归的见解

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance

Pub Date : 2025-09-28 DOI: 10.1016/j.najef.2025.102544

Lili Zhao , Yutong Lin , Zhenhao Liu , Guozheng Yang

Climate change has profound effects on society and the global economy. This study investigates the impact of climate risk attention (CRA) on China’s overall and sectoral stock markets by constructing a CRA index and applying the Quantile-on-Quantile regression approach. We find asymmetric and heterogeneous effects of CRA on the overall stock market, with the strongest positive effects concentrated in the upper quantiles. The results also reveal a saturation point beyond which further increases in CRA exert diminishing influence. At the sectoral level, high CRA is positively associated with non-distressed market states in Public Utilities, Information Technology, Optional Consumption, Materials, and Industrials. By contrast, its significant effects appear only during extremely prosperous conditions in Real Estate and Source Energy. Both low and high CRA are positively linked to upside volatility in the Medical Care and Daily Consumption sectors. The Financials sector responds mainly on the downside, with reduced CRA showing a positive association. Our findings underscore the importance of integrating climate risk considerations into financial strategies to support sustainable market development.

气候变化对社会和全球经济产生深远影响。本文通过构建气候风险关注（CRA）指数，采用分位数对分位数回归方法，探讨了气候风险关注对中国整体和行业股票市场的影响。我们发现CRA对整个股票市场的影响是不对称的和异质性的，其中最强烈的积极影响集中在高分位数。结果还揭示了一个饱和点，超过这个饱和点，CRA进一步增加的影响就会减弱。在行业层面上，高CRA与公用事业、信息技术、可选消费、材料和工业领域的非困境市场状态呈正相关。相比之下，它的显著影响只出现在房地产和能源极其繁荣的条件下。CRA的高低都与医疗保健和日常消费板块的上行波动呈正相关。金融板块的反应主要是下行，CRA的降低显示出正相关。我们的研究结果强调了将气候风险因素纳入金融战略以支持可持续市场发展的重要性。

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引用次数: 0