Research in International Business and Finance最新文献

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Climate risk, informal lending default, and financial risk spillovers: A dual perspective of physical and transition risks 气候风险、非正式贷款违约和金融风险溢出：物理风险和转型风险的双重视角

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-08 DOI: 10.1016/j.ribaf.2025.103249

Genhao Li , Xiaojiao Ye , Chaochao Li , Chao Long

Informal lending has long operated outside formal financial regulation, emerging as a key source of risk in the financial system. However, its role as a potential transmission channel for climate risks has rarely been explored in existing literature. Based on a dual perspective of physical and transition risks, this study systematically examines the impact of climate risks on informal lending default and their spillover effects on the formal financial system. The results show that climate risks exhibit significant heterogeneity in their impact on informal lending default: physical risk significantly increases default risk, serving as the primary climate threat faced by informal lending; transition risk, by contrast, presents a nonlinear impact characterized by short-term inhibition and long-term promotion, which is associated with its short-term boosting effect on return on capital (ROC). The core transmission mechanism is as follows: climate risks erode ROC, exacerbate operational risks, and drive a shift in financing channels toward informal lending, thereby increasing default risk. Heterogeneity analysis reveals that the aforementioned impacts are more pronounced among individual borrowers, in eastern China, and in scenarios affected by extreme low temperatures and heavy rainfall shocks. Furthermore, this study confirms that climate risks can be transmitted to the formal financial system via the informal lending channel, exhibiting significant cross-market spillover effects. This study expands the research scope of climate risks to the informal financial sector, offering new insights into the critical function of informal lending in climate risk transmission.

长期以来，非正规贷款一直在正规金融监管之外运作，成为金融体系风险的主要来源。然而，现有文献很少探讨其作为气候风险潜在传递渠道的作用。基于物理风险和过渡风险的双重视角，本研究系统地考察了气候风险对非正式借贷违约的影响及其对正式金融体系的溢出效应。结果表明，气候风险对非正式借贷违约的影响具有显著的异质性：物理风险显著增加违约风险，是非正式借贷面临的主要气候威胁；而转型风险则表现为短期抑制、长期促进的非线性影响，并与其对资本收益率（ROC）的短期提升效应相关。核心传导机制为：气候风险侵蚀ROC，加剧操作风险，推动融资渠道向非正规借贷转移，从而增加违约风险。异质性分析显示，上述影响在个人借款人、中国东部地区以及受极端低温和强降雨冲击影响的情景中更为明显。此外，本研究证实，气候风险可以通过非正式贷款渠道传递到正式金融体系，并表现出显著的跨市场溢出效应。本研究将气候风险的研究范围扩大到非正式金融部门，为非正式贷款在气候风险传导中的关键作用提供了新的见解。

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引用次数: 0

How do extreme climate risks affect banking active risk-taking? Empirical evidence from 107 countries 极端气候风险如何影响银行业主动承担风险？来自107个国家的经验证据

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-06 DOI: 10.1016/j.ribaf.2025.103247

Qirui Tang , Yi Fang

Leveraging banking data from 107 countries between 2001 and 2020, this study explores the influence of extreme natural disasters on the banking industry's active risk-taking. The results reveal that the occurrence of extreme natural disasters leads to a reduction in active risk-taking and the magnitude of impacts caused by different types of disasters varies. Mechanism analysis shows that disasters reduce banks' active risk-taking levels by affecting the profitability of the demand side of funds. Heterogeneity analysis demonstrates that the impact of natural disasters on banking sectors' active risk-taking varies with national industrial structure. Banks in net energy-importing countries are more susceptible to the effects of natural disasters on active risk-taking. Furthermore, using machine learning methods, we demonstrate that natural disaster indicators are important predictors of financial crises and should be incorporated into early warning systems.

本研究利用2001年至2020年107个国家的银行数据，探讨了极端自然灾害对银行业主动承担风险的影响。结果表明，极端自然灾害的发生会导致主动冒险行为的减少，不同类型灾害造成的影响程度不同。机制分析表明，灾害通过影响资金需求方的盈利能力来降低银行的主动风险承担水平。异质性分析表明，自然灾害对银行业主动风险承担的影响随国家产业结构的不同而不同。能源净进口国的银行更容易受到自然灾害对积极冒险行为的影响。此外，使用机器学习方法，我们证明了自然灾害指标是金融危机的重要预测指标，应该纳入预警系统。

引用次数: 0

Financial sector development in East Africa: Determinants, trend, and regional progress 东非金融部门发展：决定因素、趋势和区域进展

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-05 DOI: 10.1016/j.ribaf.2025.103251

Abdissa Demise Damasa

This study examines the determinants, trends, and regional progress of financial sector development in seven East African countries from 1990 to 2023. Grounded in financial development theory, a composite index of financial development (FSDI) is constructed using Principal Component Analysis (PCA) to capture multidimensional aspects of financial access, depth, efficiency, stability, and liberalization. The study employs dynamic heterogeneous panel estimators, including mean group, pooled mean group, dynamic fixed effect, fully modified ordinary least square, canonical co-integration regression, feasible generalized least square, along with augmented mean group and common correlate effect mean group estimators to analyze both short-run and long-run relationships with economic and institutional factors. Results reveal significant disparities, with Kenya recording the highest index (0.72) and Sudan the lowest (0.22); followed by Burundi (0.66), while Rwanda, Ethiopia, Uganda, and Tanzania exhibit moderate development (0.49–0.30). In the long run, financial development is positively influenced by government consumption, bank deposits, gross domestic savings, corruption control, and remittances, whereas high lending interest rates constrain growth. In the short run, economic growth and bank deposits remain key contributors. Methodologically, the study contributes by integrating PCA-based index construction with dynamic heterogeneous panel estimation, providing robust insights into country-specific and regional dynamics. Policy recommendations include promoting domestic savings and investment, strengthening governance and anti-corruption measures, improving formal financial inclusion, managing interest rates prudently, and harnessing remittance flows to foster a more inclusive, resilient, and sustainable financial sector across East Africa.

本研究考察了1990年至2023年七个东非国家金融部门发展的决定因素、趋势和区域进展。在金融发展理论的基础上，利用主成分分析（PCA）构建金融发展综合指数（FSDI），以捕捉金融准入、深度、效率、稳定性和自由化的多维方面。本研究采用动态异质性面板估计量，包括均值组、混合均值组、动态固定效应、完全修正普通最小二乘、典型协整回归、可行广义最小二乘，以及增广均值组和共相关效应均值组估计量，分析经济和制度因素之间的短期和长期关系。结果显示了显著的差异，肯尼亚的指数最高（0.72），苏丹最低（0.22）；其次是布隆迪（0.66），而卢旺达、埃塞俄比亚、乌干达和坦桑尼亚则表现出中等发展（0.49-0.30）。从长期来看，金融发展受到政府消费、银行存款、国内储蓄总额、腐败控制和汇款的积极影响，而高贷款利率则制约增长。短期来看，经济增长和银行存款仍是主要因素。在方法上，该研究将基于pca的指数构建与动态异质性面板估计相结合，为具体国家和地区的动态提供了强有力的见解。政策建议包括促进国内储蓄和投资，加强治理和反腐败措施，改善正式的普惠金融，审慎管理利率，利用汇款流动，在东非建立更具包容性、弹性和可持续性的金融部门。

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引用次数: 0

A dual lens examination of peer effects on OFDI: Learning and competition perspectives 外商直接投资同伴效应的双重视角：学习与竞争视角

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-05 DOI: 10.1016/j.ribaf.2025.103250

Zhongyuan Li , Shuo Chen , Ruike Ye , Wenzhi Chen

The motivation for outward foreign direct investment (OFDI) has consistently been a focal point in international business research. Using data from listed Chinese firms, this study examined whether peer effects drive OFDI. We meticulously identified peer effect-driven OFDI as an enterprise engaging in OFDI in a country where other firms from the same city and industry have already invested. Our findings revealed that peer firms’ OFDI activities significantly influence focal firms’ OFDI behavior, and learning and competition mechanisms drive these peer effects. The peer effects are more pronounced among firms that are larger, older, more profitable, or state-owned. Furthermore, under the learning mechanism, firms exhibit rational OFDI behavior, favoring geographically or culturally proximate countries. In contrast, under the competition mechanism, firms exhibit irrational OFDI behavior, preferring to invest in geographically or culturally distant countries. These results offer valuable insights for policymakers seeking to guide firms toward rational OFDI.

对外直接投资的动机一直是国际商业研究的焦点。本文利用中国上市公司的数据，考察了同行效应对OFDI的驱动作用。我们仔细地将同行效应驱动型对外直接投资定义为在一个国家从事对外直接投资的企业，而同一城市和行业的其他公司已经在这个国家进行了投资。研究发现，同行企业的对外直接投资活动显著影响焦点企业的对外直接投资行为，而学习机制和竞争机制驱动了这种效应。同行效应在规模更大、历史更悠久、盈利能力更强或国有的公司中更为明显。此外，在学习机制下，企业表现出理性的对外直接投资行为，倾向于地理或文化上接近的国家。相反，在竞争机制下，企业表现出非理性的对外直接投资行为，倾向于在地理或文化上遥远的国家进行投资。这些结果为寻求引导企业理性对外直接投资的政策制定者提供了有价值的见解。

引用次数: 0

The impact of co-movements in international commodity idiosyncratic volatility on China’s financial market risk 国际大宗商品异质波动对中国金融市场风险的影响

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-05 DOI: 10.1016/j.ribaf.2025.103248

Shuping Li , Xiaoyang Yao , Jianfeng Li

This study applies the generalized dynamic factor model (GDFM), TVP-VAR-DY framework, and pattern causality to investigate spillover effect from international commodity idiosyncratic volatility co-movements to China’s financial market risk, as well as the impact of a series of macroeconomic factors on such spillover effect. The empirical results indicate that the idiosyncratic volatility co-movements of energy, industrial metals, precious metals, soft commodities, and agricultural products all have significant spillover effects on China’s financial market risk. The influence of commodity idiosyncratic co-movements on China’s financial market risk is relatively stable under normal economic conditions but intensifies significantly during periods of deteriorating economic fundamentals. Macroeconomic factors such as international capital flows, investor sentiment, geopolitical risks, economic conditions, and international freight rates predominantly exhibit a positive causal effect on the dynamic spillover effect.

本文运用广义动态因素模型（GDFM）、TVP-VAR-DY框架和模式因果关系，研究国际商品异质波动协同运动对中国金融市场风险的溢出效应，以及一系列宏观经济因素对这种溢出效应的影响。实证结果表明，能源、工业金属、贵金属、软商品和农产品的异质波动协同运动对中国金融市场风险具有显著的溢出效应。在正常经济条件下，大宗商品异质波动对中国金融市场风险的影响相对稳定，但在经济基本面恶化期间，影响显著增强。国际资本流动、投资者情绪、地缘政治风险、经济状况和国际运价等宏观经济因素对动态溢出效应主要表现为正因果关系。

引用次数: 0

Interdependence and portfolio scheme of emerging industry of Metaverse 元汇新兴产业的相互依赖与投资组合方案

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-03 DOI: 10.1016/j.ribaf.2025.103222

Liukai Wang , Yuqing Li , Larisa Yarovaya

The Metaverse industry has attracted global attention and holds significant potential for investment, yet its investment environment and portfolio strategies remain underexplored, particularly in China. This study analyzes the industry’s structure and interdependencies using returns from 110 listed Metaverse firms. Employing a Kendall-based network, we identify leaders and peripheral enterprises within the industry. From a micro-perspective, we propose a hybrid Kendall-based investment scheme, showing that portfolios of peripheral firms consistently outperform those of leaders and the overall market. The scheme also proves robust across different network scales, investor preferences, and market conditions. Overall, this research advances understanding of the Metaverse industry by combining a macro view of its industrial environment with a micro focus on portfolio design, offering practical insights for regulators, managers, and investors.

Metaverse行业吸引了全球的关注，具有巨大的投资潜力，但其投资环境和投资组合策略仍未得到充分开发，尤其是在中国。本研究利用110家Metaverse上市公司的收益分析了该行业的结构和相互依赖性。利用kendall为基础的网络，我们确定行业内的领导者和外围企业。从微观角度来看，我们提出了一个基于肯德尔的混合投资方案，表明外围公司的投资组合始终优于领导者和整体市场的投资组合。该方案还证明了在不同网络规模、投资者偏好和市场条件下的稳健性。总体而言，本研究通过将宏观的产业环境与微观的投资组合设计相结合，推进了对虚拟现实行业的理解，为监管者、管理者和投资者提供了实用的见解。

引用次数: 0

Funding liquidity regulation, ultra-expansionary monetary policy and European banks’ profitability 资金流动性监管、超扩张性货币政策和欧洲银行的盈利能力

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-01 DOI: 10.1016/j.ribaf.2025.103246

Erika Bragaglia , Domenico Curcio , Giuseppe Galloppo , Roberto Guida

By reducing the asset-liability maturity mismatch, the Basel III Net Stable Funding Ratio (NSFR) might have a tremendous impact on banks’ ability to make profits. We show that the joint effect of the adoption of ultra-expansionary measures of monetary policy and this liquidity requirement can seriously threaten banks’ profitability in terms of their net interest margins. Based on a panel dataset of European banks observed over the 2011–2018 years, we find that the level and the dynamics of interest rates affect the relationship between NSFR and banks’ profits. The impact of the NSFR is null during the years 2011–2012, when market rates firstly raise and then decline, which suggests that, when rates show a certain volatility, the decrease in the funding cost due to a lower exposure to funding liquidity risk more than offsets the drawback of lower interest earnings. This result does not hold for the years 2013–2018, when interest rates stay close to the zero level and, finally, become negative, but with a much more stable trend. We argue that the higher level of interest rates in the years 2011–2012 gives banks the room to negotiate more profitable conditions with the clientele following the changes in market rates observed during those years. The proximity to the zero level of the interest rates and their stability remove or significantly limit that possibility and can explain the negative impact of the NSFR on banks’ net interest margins.

通过减少资产负债期限错配，巴塞尔协议III净稳定资金比率（NSFR）可能会对银行的盈利能力产生巨大影响。我们表明，采用超扩张性货币政策措施和这种流动性要求的共同效应可能严重威胁银行的净息差盈利能力。基于2011-2018年观察到的欧洲银行面板数据集，我们发现利率水平和动态会影响非净存款准备金率与银行利润之间的关系。在市场利率先升后降的2011-2012年期间，NSFR的影响为零，这表明，当利率表现出一定的波动性时，由于资金流动性风险暴露较低而导致的资金成本下降远远抵消了较低利息收益的缺点。这一结果并不适用于2013-2018年，当时利率保持在接近零的水平，并最终变为负值，但趋势要稳定得多。我们认为，2011-2012年较高的利率水平使银行有空间在这些年观察到的市场利率变化之后与客户谈判更有利可图的条件。接近于零的利率水平及其稳定性消除或显著限制了这种可能性，并可以解释NSFR对银行净息差的负面影响。

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引用次数: 0

Disruptive innovation or systemic resilience? Investigating the impact of artificial intelligence on banking stability 颠覆性创新还是系统弹性？调查人工智能对银行业稳定性的影响

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-12-01 DOI: 10.1016/j.ribaf.2025.103245

Abu Bakkar Siddik , Noor ul Amin

This study examines the impact of artificial intelligence (AI) on banking stability in 37 OECD countries from 2010 to 2022, guided by Neo-Schumpeterian innovation theory which frames AI as both a stabilizing and disruptive force. AI is operationalized using annual venture capital funding directed toward AI-focused startups, covering domains such as machine learning, generative AI, natural language processing, and predictive analytics—data sourced from Crunchbase. We further validate this using an alternative proxy: the number of AI startups. Banking stability is measured by the Z-score, capturing the risk of insolvency. Using Panel-Corrected Standard Errors (PCSE) for baseline estimation, and two-step System Generalized Method of Moments (GMM) as the core identification strategy to address endogeneity, along with Heckman selection models to correct sample selection bias, the findings reveal that increased AI funding significantly enhances banking stability—particularly in technologically advanced and well-regulated OECD economies. Furthermore, mechanism analysis confirms the partial role of financial development in this relationship, while government effectiveness shows no significant mediation. Cross-country heterogeneity analysis reveals stronger effects in Western Europe and countries with advanced financial infrastructure. By integrating AI investment dynamics with institutional and technological contexts, this study provides actionable insights for designing responsible AI strategies that promote banking resilience while managing systemic risks.

本研究在新熊彼特创新理论的指导下，考察了2010年至2022年37个经合组织国家人工智能（AI）对银行业稳定性的影响，该理论将人工智能视为稳定和破坏力量。人工智能的运营使用年度风险投资资金，这些资金直接投向以人工智能为重点的初创公司，涵盖机器学习、生成式人工智能、自然语言处理和预测分析等领域——数据来自Crunchbase。我们使用另一个代理来进一步验证这一点：人工智能初创公司的数量。银行稳定性是通过Z-score来衡量的，它捕捉到了破产的风险。使用面板校正标准误差（PCSE）进行基线估计，使用两步系统广义矩量法（GMM）作为解决内质性的核心识别策略，以及Heckman选择模型来纠正样本选择偏差，研究结果表明，人工智能资金的增加显著提高了银行业的稳定性，特别是在技术先进且监管良好的经合组织经济体中。此外，机制分析证实了金融发展在这一关系中的部分作用，而政府有效性在这一关系中没有显著的中介作用。跨国异质性分析显示，西欧和金融基础设施发达的国家的影响更大。通过将人工智能投资动态与制度和技术背景相结合，本研究为设计负责任的人工智能战略提供了可行的见解，从而在管理系统性风险的同时提高银行业的抵御能力。

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引用次数: 0

Forecasting returns using image-based convolutional neural networks: Evidence from Korea 使用基于图像的卷积神经网络预测回报：来自韩国的证据

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-11-30 DOI: 10.1016/j.ribaf.2025.103231

Jin-Gyu Jeong , Suk-Joon Byun , Donghoon Kim

This study employs a chart image-based convolutional neural network (CNN) to predict stock returns in the Korean stock market, following Jiang et al. (2023). We transform historical price and volume data into chart images and utilize CNN to extract predictive patterns. Our findings demonstrate that the CNN-based models outperform traditional benchmarks, particularly for short-term return forecasts. Additional double-sort and panel logistic regression analyses with firm characteristic variables, buy-sell imbalance analysis of investor groups, and subsample tests confirm the robustness of CNN-based predictors. This study represents the first application of a chart image-based deep learning model to the Korean stock market, providing new insights into the potential of deep learning models for stock return forecasting in emerging markets.

本研究采用基于图表图像的卷积神经网络（CNN）来预测韩国股市的股票收益，借鉴Jiang et al.（2023）。我们将历史价格和成交量数据转换为图表图像，并利用CNN提取预测模式。我们的研究结果表明，基于cnn的模型优于传统基准，特别是在短期回报预测方面。额外的双排序和面板逻辑回归分析与公司特征变量，投资者群体的买卖不平衡分析，和子样本检验证实了cnn基于预测的稳健性。该研究首次将基于图表图像的深度学习模型应用于韩国股票市场，为深度学习模型在新兴市场股票收益预测中的潜力提供了新的见解。

引用次数: 0

Family involvement in the board and green innovation of family firms: The moderating effect of family-based naming 家族参与董事会与家族企业绿色创新：家族命名的调节作用

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Research in International Business and Finance

Pub Date : 2025-11-27 DOI: 10.1016/j.ribaf.2025.103241

Qingmei Tan , Yuge Wang , Tianqi Cheng , Zhenhua Li

Drawing on the perspective of socioemotional wealth (SEW), this paper explores the effect of family involvement in the board (FIB) on green innovation of family firms and the moderating role of family-based naming. By analyzing a sample of Chinese A-share listed family firms from 2008 to 2022, this paper finds that increased FIB can significantly inhibit green innovation of family firms, and family-based naming weakens the negative relationship. The channel test shows that increased FIB weakens the risk-taking level, aggravates managerial myopia and type II agency costs, thereby affecting the family firm’s green innovation. The heterogeneity analysis indicates that the negative impact of FIB on green innovation is more pronounced in family firms with higher analyst coverage and facing stronger industrial competition.

本文利用社会情感财富（SEW）的视角，探讨家族参与董事会（FIB）对家族企业绿色创新的影响以及家族命名的调节作用。本文通过对2008 - 2022年中国a股上市家族企业样本的分析发现，FIB的增加显著抑制了家族企业的绿色创新，家族命名削弱了这种负相关关系。渠道检验表明，FIB的增加削弱了家族企业的风险承担水平，加剧了管理短视和II型代理成本，从而影响了家族企业的绿色创新。异质性分析表明，在分析师覆盖率高、行业竞争激烈的家族企业中，FIB对绿色创新的负面影响更为显著。

引用次数: 0

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