Pub Date : 2025-11-26DOI: 10.1016/j.ribaf.2025.103226
Luoxi Lin , Peiyuan Wang , Yilin Huang
By utilizing the geographic data of institutional investors from 2012 to 2023, this study investigates how the geographic concentration of institutional investors (GCII) affects firms’ stock price idiosyncratic volatility (IVOL). The findings indicate that the GCII significantly mitigates corporate information asymmetry and enhances internal governance quality, consequently reducing firms’ IVOL. Additional analysis reveals that the negative impact of the GCII on IVOL is pronounced for firms located in provinces with underdeveloped transport infrastructure and firms with lower analyst coverage.
{"title":"How does the geographic concentration of institutional investors affect corporate risk? Evidence from China","authors":"Luoxi Lin , Peiyuan Wang , Yilin Huang","doi":"10.1016/j.ribaf.2025.103226","DOIUrl":"10.1016/j.ribaf.2025.103226","url":null,"abstract":"<div><div>By utilizing the geographic data of institutional investors from 2012 to 2023, this study investigates how the geographic concentration of institutional investors (GCII) affects firms’ stock price idiosyncratic volatility (IVOL). The findings indicate that the GCII significantly mitigates corporate information asymmetry and enhances internal governance quality, consequently reducing firms’ IVOL. Additional analysis reveals that the negative impact of the GCII on IVOL is pronounced for firms located in provinces with underdeveloped transport infrastructure and firms with lower analyst coverage.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103226"},"PeriodicalIF":6.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1016/j.ribaf.2025.103233
Tomasz Kaczmarek , Ender Demir , Wael Rouatbi , Adam Zaremba
We examine sovereign bond market reactions to the U.S. ”reciprocal” tariff announcement on April 2, 2025, using daily returns from 61 countries. Government bond prices rose following the announcement, consistent with a flight-to-safety response amid heightened global uncertainty. Cross-country variation reflects three main drivers: tariff exposure, fiscal fundamentals, and export orientation. Bonds from countries facing higher tariffs experience stronger gains, but this effect weakens for sovereigns with poor credit quality or high unemployment. Moreover, bonds issued by net exporters underperform, suggesting that investor concerns center on structural vulnerabilities rather than general trade openness. Overall, the results highlight the selective nature of the flight-to-safety dynamic during episodes of rising protectionism.
{"title":"Protectionism and safe-haven demand: Sovereign bond reactions to the 2025 U.S. tariff announcement","authors":"Tomasz Kaczmarek , Ender Demir , Wael Rouatbi , Adam Zaremba","doi":"10.1016/j.ribaf.2025.103233","DOIUrl":"10.1016/j.ribaf.2025.103233","url":null,"abstract":"<div><div>We examine sovereign bond market reactions to the U.S. ”reciprocal” tariff announcement on April 2, 2025, using daily returns from 61 countries. Government bond prices rose following the announcement, consistent with a flight-to-safety response amid heightened global uncertainty. Cross-country variation reflects three main drivers: tariff exposure, fiscal fundamentals, and export orientation. Bonds from countries facing higher tariffs experience stronger gains, but this effect weakens for sovereigns with poor credit quality or high unemployment. Moreover, bonds issued by net exporters underperform, suggesting that investor concerns center on structural vulnerabilities rather than general trade openness. Overall, the results highlight the selective nature of the flight-to-safety dynamic during episodes of rising protectionism.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103233"},"PeriodicalIF":6.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1016/j.ribaf.2025.103232
Dexiang Mei , Xiaotao Li
Against the backdrop of economic globalization, the outbreak of numerous transnational emergencies (such as geopolitical wars, trade frictions, and political conflicts) has affected the Chinese financial market and introduced significant uncertainties (e.g., monetary policy, political risk, and geopolitical risk). In addition, the stock market is a complex, nonlinear, and dynamic system. Therefore, the least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA) techniques are used to construct a comprehensive uncertainty index for the Chinese stock market. Neural networks (a gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short-term memory (BiLSTM)) are embedded into a generalized autoaggressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model to construct an integrated model. The empirical results show that the newly constructed uncertainty factor provided effective information for predicting Chinese stock market volatility, and that the model's predictive ability integrated model's predictive ability is significantly better than that of the traditional model both statistical and economical. A robustness test confirms these conclusions. Therefore, understanding the volatility rules and structural characteristics of the financial market plays a vital role in accurately predicting volatility and preventing financial risk.
{"title":"Forecasting of Chinese stock price using a hybrid neural network model","authors":"Dexiang Mei , Xiaotao Li","doi":"10.1016/j.ribaf.2025.103232","DOIUrl":"10.1016/j.ribaf.2025.103232","url":null,"abstract":"<div><div>Against the backdrop of economic globalization, the outbreak of numerous transnational emergencies (such as geopolitical wars, trade frictions, and political conflicts) has affected the Chinese financial market and introduced significant uncertainties (e.g., monetary policy, political risk, and geopolitical risk). In addition, the stock market is a complex, nonlinear, and dynamic system. Therefore, the least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA) techniques are used to construct a comprehensive uncertainty index for the Chinese stock market. Neural networks (a gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short-term memory (BiLSTM)) are embedded into a generalized autoaggressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model to construct an integrated model. The empirical results show that the newly constructed uncertainty factor provided effective information for predicting Chinese stock market volatility, and that the model's predictive ability integrated model's predictive ability is significantly better than that of the traditional model both statistical and economical. A robustness test confirms these conclusions. Therefore, understanding the volatility rules and structural characteristics of the financial market plays a vital role in accurately predicting volatility and preventing financial risk.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103232"},"PeriodicalIF":6.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum to “Carbon pricing and sovereign credit risk: A threshold analysis of policy design and economic structure for climate-fiscal resilience” [Res. Int. Bus. Financ. 81 (2025) 103197]","authors":"Chabi Marcellin Daki Dominique , Yixiang Tian , Huiling Huang , Haroon ur Rashid Khan","doi":"10.1016/j.ribaf.2025.103216","DOIUrl":"10.1016/j.ribaf.2025.103216","url":null,"abstract":"","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"81 ","pages":"Article 103216"},"PeriodicalIF":6.9,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-25DOI: 10.1016/j.ribaf.2025.103230
Zhen Wang
This study refines the economics of privacy and explores the impact of personal privacy protection on the sustainable development of enterprises. The findings provide a valuable reference for governments to optimize existing personal privacy policies, and provide guidance for enterprises to manage data property rationally and improve firm value. This study introduces a novel approach by creating a dynamic model involving incomplete information, which includes businesses, consumers, and the government, to theoretically elucidate how establishing a personal data protection system can enhance the market value of enterprises. Additionally, this study seeks to determine the minimum government-imposed fines and likelihood of inspections necessary to reduce the incentive for enterprises to falsify data when they do not protect them. The subsequent empirical analysis uses data from 2011 to 2020 to verify the theoretical hypothesis. Further analysis explores the driving effects that not only originate from the independent intrinsic value of establishing a personal data protection system, but also rely on social trust enhancement, market share expansion, and institutional investor preference mechanisms. Moreover, the market value enhancement effects resulting from enterprises' privacy protection measures are more pronounced in enterprises characterized by data insensitivity, industry chain upstream, and competitive industries. The government's data governance, including public data openness and digital government construction, generates multiplier effects.
{"title":"Can the establishment of a personal data protection system promote firm value? An exploration of the economics of privacy","authors":"Zhen Wang","doi":"10.1016/j.ribaf.2025.103230","DOIUrl":"10.1016/j.ribaf.2025.103230","url":null,"abstract":"<div><div>This study refines the economics of privacy and explores the impact of personal privacy protection on the sustainable development of enterprises. The findings provide a valuable reference for governments to optimize existing personal privacy policies, and provide guidance for enterprises to manage data property rationally and improve firm value. This study introduces a novel approach by creating a dynamic model involving incomplete information, which includes businesses, consumers, and the government, to theoretically elucidate how establishing a personal data protection system can enhance the market value of enterprises. Additionally, this study seeks to determine the minimum government-imposed fines and likelihood of inspections necessary to reduce the incentive for enterprises to falsify data when they do not protect them. The subsequent empirical analysis uses data from 2011 to 2020 to verify the theoretical hypothesis. Further analysis explores the driving effects that not only originate from the independent intrinsic value of establishing a personal data protection system, but also rely on social trust enhancement, market share expansion, and institutional investor preference mechanisms. Moreover, the market value enhancement effects resulting from enterprises' privacy protection measures are more pronounced in enterprises characterized by data insensitivity, industry chain upstream, and competitive industries. The government's data governance, including public data openness and digital government construction, generates multiplier effects.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103230"},"PeriodicalIF":6.9,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper constructs a dynamic stochastic equilibrium model for climate policies. We allow for three types of economic damages from climate warming. On one hand, rising temperatures damage output and capital stock of both green sector and brown sector. On the other hand, rising temperatures will damage the carbon storage of natural carbon sinks. Given damages, this paper compares two climate policies to mitigate economic damages from climate change. One is the Nordhaus carbon abatement policy which is from the perspective of carbon sources, and we derive the optimal carbon price path under dynamic carbon sinks. The other is the CCS (Carbon Capture and Storage) artificial carbon sink policy, and we address the problem of the optimal CCS investment path in the future. We recommend that future investment in CCS should follow a trend that first increases and then decreases over time. Green investment is projected to overtake brown investment around 2050 and completely substitute it by 2100 driven by the implementation of climate policies. Moreover, we reveal that there is a reverse optimal relationship between the two climate policies and the implementation of carbon sink policies contributes to the stability of the carbon pricing market. In addition, scenario analysis shows that high CCS investment crowds out green investment and leads to partial economic losses compared to lower or no CCS investment.
{"title":"Optimal carbon capture and storage investments under global warming","authors":"Renzhong Li , Chen Fei , Xiaodong Ding , Weiyin Fei","doi":"10.1016/j.ribaf.2025.103229","DOIUrl":"10.1016/j.ribaf.2025.103229","url":null,"abstract":"<div><div>This paper constructs a dynamic stochastic equilibrium model for climate policies. We allow for three types of economic damages from climate warming. On one hand, rising temperatures damage output and capital stock of both green sector and brown sector. On the other hand, rising temperatures will damage the carbon storage of natural carbon sinks. Given damages, this paper compares two climate policies to mitigate economic damages from climate change. One is the Nordhaus carbon abatement policy which is from the perspective of carbon sources, and we derive the optimal carbon price path under dynamic carbon sinks. The other is the CCS (Carbon Capture and Storage) artificial carbon sink policy, and we address the problem of the optimal CCS investment path in the future. We recommend that future investment in CCS should follow a trend that first increases and then decreases over time. Green investment is projected to overtake brown investment around 2050 and completely substitute it by 2100 driven by the implementation of climate policies. Moreover, we reveal that there is a reverse optimal relationship between the two climate policies and the implementation of carbon sink policies contributes to the stability of the carbon pricing market. In addition, scenario analysis shows that high CCS investment crowds out green investment and leads to partial economic losses compared to lower or no CCS investment.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103229"},"PeriodicalIF":6.9,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-24DOI: 10.1016/j.ribaf.2025.103227
Lihong Cao , Xuanning Zhu , Yi Li
This paper examines how firm digitalization influences bank loans and debt maturity using data from Chinese-listed firms from 2009 to 2021. By employing machine learning and large language models to measure digitalization, we find that digitalization significantly increases both the scale of bank loans and the proportion of long-term loans. The effect of digitalization is stronger for credit and guaranteed loans than for collateral loans, indicating that digitalization reduces the collateral requirements in lending. Mechanism analysis reveals that digitalization enhances firms’ access to bank lending by improving information transparency, financial stability and corporate reputation. The positive effect is stronger for firms without credit ratings, highlighting digitalization’s role in reducing information asymmetry. Additionally, the effects are more pronounced in regions with advanced banking systems and marketization, for firms in traditional industries and firms under competitive pressure. Our findings highlight digitalization’s critical role in improving firms’ credit market competitiveness and advocate for government policies to facilitate firm digitalization. It offers actionable insights for firms in bank-dominated economies globally to alleviate financial constraints through technological development.
{"title":"Firm digitalization and bank lending: Evidence from China","authors":"Lihong Cao , Xuanning Zhu , Yi Li","doi":"10.1016/j.ribaf.2025.103227","DOIUrl":"10.1016/j.ribaf.2025.103227","url":null,"abstract":"<div><div>This paper examines how firm digitalization influences bank loans and debt maturity using data from Chinese-listed firms from 2009 to 2021. By employing machine learning and large language models to measure digitalization, we find that digitalization significantly increases both the scale of bank loans and the proportion of long-term loans. The effect of digitalization is stronger for credit and guaranteed loans than for collateral loans, indicating that digitalization reduces the collateral requirements in lending. Mechanism analysis reveals that digitalization enhances firms’ access to bank lending by improving information transparency, financial stability and corporate reputation. The positive effect is stronger for firms without credit ratings, highlighting digitalization’s role in reducing information asymmetry. Additionally, the effects are more pronounced in regions with advanced banking systems and marketization, for firms in traditional industries and firms under competitive pressure. Our findings highlight digitalization’s critical role in improving firms’ credit market competitiveness and advocate for government policies to facilitate firm digitalization. It offers actionable insights for firms in bank-dominated economies globally to alleviate financial constraints through technological development.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103227"},"PeriodicalIF":6.9,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-24DOI: 10.1016/j.ribaf.2025.103228
Nhan Huynh , Hoa Phan , Kyle Paquette , Phuong Thi Thu Vu
This study examines how changes in sovereign credit ratings influence corporate investment decisions, with a particular emphasis on the moderating role of public debt burdens. Using a panel of 2213 rated firms across 52 countries from 1995 to 2021, we document an asymmetric effect: sovereign downgrades lead to a significant 20.5 % reduction in total investment, primarily driven by sharp declines in long-term capital expenditures and a reallocation toward short-term investments. By contrast, rating upgrades have no meaningful effect on investment, highlighting that rating shocks are more disruptive in the downward direction. Our results suggest that rising borrowing costs and heightened financial constraints are key channels through which sovereign risk spills over to firms, with the adverse effects of downgrades further amplified in high-debt countries. Our results are robust across alternative investment proxies, subsample analyses, and endogeneity controls, and are reinforced by additional sectoral and institutional heterogeneity tests, highlighting both the pervasiveness of the downgrade effect and the capacity of strong governance environments to mitigate its impact.
{"title":"Sovereign credit ratings, fiscal burden and corporate investment policies: An international evidence","authors":"Nhan Huynh , Hoa Phan , Kyle Paquette , Phuong Thi Thu Vu","doi":"10.1016/j.ribaf.2025.103228","DOIUrl":"10.1016/j.ribaf.2025.103228","url":null,"abstract":"<div><div>This study examines how changes in sovereign credit ratings influence corporate investment decisions, with a particular emphasis on the moderating role of public debt burdens. Using a panel of 2213 rated firms across 52 countries from 1995 to 2021, we document an asymmetric effect: sovereign downgrades lead to a significant 20.5 % reduction in total investment, primarily driven by sharp declines in long-term capital expenditures and a reallocation toward short-term investments. By contrast, rating upgrades have no meaningful effect on investment, highlighting that rating shocks are more disruptive in the downward direction. Our results suggest that rising borrowing costs and heightened financial constraints are key channels through which sovereign risk spills over to firms, with the adverse effects of downgrades further amplified in high-debt countries. Our results are robust across alternative investment proxies, subsample analyses, and endogeneity controls, and are reinforced by additional sectoral and institutional heterogeneity tests, highlighting both the pervasiveness of the downgrade effect and the capacity of strong governance environments to mitigate its impact.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103228"},"PeriodicalIF":6.9,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-21DOI: 10.1016/j.ribaf.2025.103221
Sam Hakim , Simon Neaime
This study investigates whether and to what extent financial markets in MENA countries exhibit structural decoupling from global financial trends in response to geopolitical shocks. Specifically, we test the hypothesis that heightened geopolitical uncertainty accelerates financial differentiation in MENA markets. Using a GARCH-VAR model on monthly data from 2014 to 2024, we identify evolving volatility transmission patterns between MENA and global markets, particularly during key geopolitical episodes. Our results suggest a regionally specific shift toward financial insularity, shaped by both economic and strategic realignments. We note a clear decoupling from historical correlations in the MENA region’s equity markets, with leading countries of that region either completely or partially decoupled. The empirical results indicate that countries in the region are rejecting pressures to take sides, and seeking a new direction by strengthening ties with emerging markets.
{"title":"MENA stock markets decoupling: Winners and losers from the wars in Ukraine and Middle East","authors":"Sam Hakim , Simon Neaime","doi":"10.1016/j.ribaf.2025.103221","DOIUrl":"10.1016/j.ribaf.2025.103221","url":null,"abstract":"<div><div>This study investigates whether and to what extent financial markets in MENA countries exhibit structural decoupling from global financial trends in response to geopolitical shocks. Specifically, we test the hypothesis that heightened geopolitical uncertainty accelerates financial differentiation in MENA markets. Using a GARCH-VAR model on monthly data from 2014 to 2024, we identify evolving volatility transmission patterns between MENA and global markets, particularly during key geopolitical episodes. Our results suggest a regionally specific shift toward financial insularity, shaped by both economic and strategic realignments. We note a clear decoupling from historical correlations in the MENA region’s equity markets, with leading countries of that region either completely or partially decoupled. The empirical results indicate that countries in the region are rejecting pressures to take sides, and seeking a new direction by strengthening ties with emerging markets.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103221"},"PeriodicalIF":6.9,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-21DOI: 10.1016/j.ribaf.2025.103225
Zheng Li , Haitong Li , Pengyi Dai
The rapid development of artificial intelligence (AI) is reshaping corporate practices, making its unintended implications for firms’ governance a topic worth exploring. This study examines the association between AI innovation and financial information quality from a governance perspective. Based on patent-level textual data, we construct an AI keyword dictionary using machine learning and measure firm-level AI innovation using text analysis method. Our empirical results indicate that AI innovation is positively associated with firm’s financial information quality. The mechanisms include improvements in internal control and increased external market attention. In cross-sectional analyses, our main finding is more pronounced in firms with poor corporate governance, high-tech certifications, and strong government digital initiatives. We further find the dual role of AI innovation in enhancing governance by reducing two types of agency costs. Our study provides new insights into the role of AI innovation in improving corporate governance and financial information quality.
{"title":"Artificial intelligence innovation and financial information quality: Evidence from firm patent data","authors":"Zheng Li , Haitong Li , Pengyi Dai","doi":"10.1016/j.ribaf.2025.103225","DOIUrl":"10.1016/j.ribaf.2025.103225","url":null,"abstract":"<div><div>The rapid development of artificial intelligence (AI) is reshaping corporate practices, making its unintended implications for firms’ governance a topic worth exploring. This study examines the association between AI innovation and financial information quality from a governance perspective. Based on patent-level textual data, we construct an AI keyword dictionary using machine learning and measure firm-level AI innovation using text analysis method. Our empirical results indicate that AI innovation is positively associated with firm’s financial information quality. The mechanisms include improvements in internal control and increased external market attention. In cross-sectional analyses, our main finding is more pronounced in firms with poor corporate governance, high-tech certifications, and strong government digital initiatives. We further find the dual role of AI innovation in enhancing governance by reducing two types of agency costs. Our study provides new insights into the role of AI innovation in improving corporate governance and financial information quality.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103225"},"PeriodicalIF":6.9,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145584544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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