Pub Date : 2025-03-17DOI: 10.1016/j.ribaf.2025.102872
Jie Dou , Nawazish Mirza , Muhammad Umar , Alexandra Horobet
This study investigates the impact of financed emissions and ESG controversies on the valuation of banking firms within the European Union. As climate-related risks become increasingly critical to financial markets, banks face pressures to manage their contributions to climate change and adhere to evolving Environmental, Social, and Governance (ESG) standards. Using panel data between 2018 and 2021 of banks across twenty-seven countries, we assess the influence of financed emissions and ESG controversy scores on two key valuation metrics of residual income and price-to-book ratios. Our findings reveal that banks with lower ESG controversies tend to achieve higher market valuations. Regarding climate change, the banks with higher financed emissions face declining valuations. Our results highlight banks' strategic importance in minimizing their carbon footprint and mitigating ESG-related risks to safeguard long-term value. The research has significant actionable implications. We contribute to the ongoing dialogue on sustainable finance, offering insights for banks, regulators, and investors seeking to navigate the challenges of a transitioning financial sector.
{"title":"ESG uncertainties and valuation implications: Evidence from the EU banking sector","authors":"Jie Dou , Nawazish Mirza , Muhammad Umar , Alexandra Horobet","doi":"10.1016/j.ribaf.2025.102872","DOIUrl":"10.1016/j.ribaf.2025.102872","url":null,"abstract":"<div><div>This study investigates the impact of financed emissions and ESG controversies on the valuation of banking firms within the European Union. As climate-related risks become increasingly critical to financial markets, banks face pressures to manage their contributions to climate change and adhere to evolving Environmental, Social, and Governance (ESG) standards. Using panel data between 2018 and 2021 of banks across twenty-seven countries, we assess the influence of financed emissions and ESG controversy scores on two key valuation metrics of residual income and price-to-book ratios. Our findings reveal that banks with lower ESG controversies tend to achieve higher market valuations. Regarding climate change, the banks with higher financed emissions face declining valuations. Our results highlight banks' strategic importance in minimizing their carbon footprint and mitigating ESG-related risks to safeguard long-term value. The research has significant actionable implications. We contribute to the ongoing dialogue on sustainable finance, offering insights for banks, regulators, and investors seeking to navigate the challenges of a transitioning financial sector.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102872"},"PeriodicalIF":6.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642556","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 : 2025-03-13DOI: 10.1016/j.ribaf.2025.102863
Gaoxiu Qiao , Yunrun Wang , Wenwen Liu
This paper examines the predictive capacity of higher-order moments (skewness and kurtosis) of the Chinese stock index and futures market for the realized volatility of the stock market. Owing to the model uncertainty caused by structural changes, we propose the use of data-driven combination forecasting, namely, the LASSO-weighted average windows method over forecasts of long short-term memory network (LSTM), support vector regression (SVR), or the ordinary least squares (OLS) method. Empirical findings indicate that the LSTM method outperforms both SVR and OLS. The LASSO-weighted forecasts across these three methods significantly enhance the predictive ability of individual methods. The realized higher-order moments of both markets can effectively increase the prediction accuracy of stock market volatility, with the higher-order moments in the stock market contributing more than those in index futures.
{"title":"Prediction of Chinese stock volatility: Harnessing higher-order moments information of stock and futures markets","authors":"Gaoxiu Qiao , Yunrun Wang , Wenwen Liu","doi":"10.1016/j.ribaf.2025.102863","DOIUrl":"10.1016/j.ribaf.2025.102863","url":null,"abstract":"<div><div>This paper examines the predictive capacity of higher-order moments (skewness and kurtosis) of the Chinese stock index and futures market for the realized volatility of the stock market. Owing to the model uncertainty caused by structural changes, we propose the use of data-driven combination forecasting, namely, the LASSO-weighted average windows method over forecasts of long short-term memory network (LSTM), support vector regression (SVR), or the ordinary least squares (OLS) method. Empirical findings indicate that the LSTM method outperforms both SVR and OLS. The LASSO-weighted forecasts across these three methods significantly enhance the predictive ability of individual methods. The realized higher-order moments of both markets can effectively increase the prediction accuracy of stock market volatility, with the higher-order moments in the stock market contributing more than those in index futures.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102863"},"PeriodicalIF":6.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636282","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 : 2025-03-13DOI: 10.1016/j.ribaf.2025.102870
Zhenqing Su , Jiankun Li , Qiwei Pang , Miao Su
As globalization increases, the volatility of China's financial market is gradually affecting world trade and economic development. However, few studies have quantified the impact of China's commodity futures market on the global container shipping market outlook. Therefore, this study collects 45,966 points of daily data from January 4, 2016, to January 1, 2023, and mines the price prediction function of Chinese commodity futures market indicators on the Shanghai Container Freight Index (SCFI). Specifically, a deep learning integrated model is constructed by combining a convolutional neural network (CNN), a bi-directional long and short-term memory network (BILSTM), and an attentional mechanism (AM). The results show that the CNN-BILSTM-AM model can accurately identify nonlinear features in SCFI data using Chinese commodity futures market indicators. In addition, the model effectively captures the long-term dependence of SCFI changes with Chinese commodity futures. Finally, this study concludes that the integrated model outperforms the single CNN, LSTM, and BILSTM machine learning models and the combined CNN-LSTM and CNN-BILSTM models (R²= 94.8 %). We also observe that when using Shapley's additive interpretation (SHAP) framework to predict SCFI, Power Coal Futures (ZCF) and CSI 300 Index Futures (IFI) significantly influence the CNN-BILSTM-AM model. In summary, this study enriches the understanding of the interaction between the Chinese commodity futures market and the global container shipping industry. This study also highlights the price mining potential of Chinese futures market indicators in forecasting world shipping economic indices, thus opening new paths in the field of forecasting and management of world shipping economic indicators. The results provide a powerful decisional support and risk management tool for financial institutions, shipping companies, individual investors, and government policymakers.
{"title":"China futures market and world container shipping economy: An exploratory analysis based on deep learning","authors":"Zhenqing Su , Jiankun Li , Qiwei Pang , Miao Su","doi":"10.1016/j.ribaf.2025.102870","DOIUrl":"10.1016/j.ribaf.2025.102870","url":null,"abstract":"<div><div>As globalization increases, the volatility of China's financial market is gradually affecting world trade and economic development. However, few studies have quantified the impact of China's commodity futures market on the global container shipping market outlook. Therefore, this study collects 45,966 points of daily data from January 4, 2016, to January 1, 2023, and mines the price prediction function of Chinese commodity futures market indicators on the Shanghai Container Freight Index (SCFI). Specifically, a deep learning integrated model is constructed by combining a convolutional neural network (CNN), a bi-directional long and short-term memory network (BILSTM), and an attentional mechanism (AM). The results show that the CNN-BILSTM-AM model can accurately identify nonlinear features in SCFI data using Chinese commodity futures market indicators. In addition, the model effectively captures the long-term dependence of SCFI changes with Chinese commodity futures. Finally, this study concludes that the integrated model outperforms the single CNN, LSTM, and BILSTM machine learning models and the combined CNN-LSTM and CNN-BILSTM models (R²= 94.8 %). We also observe that when using Shapley's additive interpretation (SHAP) framework to predict SCFI, Power Coal Futures (ZCF) and CSI 300 Index Futures (IFI) significantly influence the CNN-BILSTM-AM model. In summary, this study enriches the understanding of the interaction between the Chinese commodity futures market and the global container shipping industry. This study also highlights the price mining potential of Chinese futures market indicators in forecasting world shipping economic indices, thus opening new paths in the field of forecasting and management of world shipping economic indicators. The results provide a powerful decisional support and risk management tool for financial institutions, shipping companies, individual investors, and government policymakers.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102870"},"PeriodicalIF":6.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637667","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 : 2025-03-13DOI: 10.1016/j.ribaf.2025.102862
Xin Gao , Weidong Xu , Donghui Li
Employing a large sample of 26,819 firms over a 20-year period, our study investigates the correlation between media coverage and investment-to-price sensitivity through OLS regression. The findings reveal a noteworthy positive impact of media coverage on investment-to-price sensitivity, remaining robust even after controlling for various factors. Mechanism analysis demonstrates that the positive influence of media coverage on managerial investment learning operates through channels related to information asymmetry and corporate governance. We also find that retail investor attention can strengthen the positive relationship between media coverage and investment-to-price sensitivity. Moreover, our analysis of news sources and content highlights the significant role of internationally renowned sources, business channels, positive sentiment, and stock-related coverage in enhancing investment-to-price sensitivity. These insights provide valuable guidance for firms to optimize their use of media for decision-making, offer investors a means to identify opportunities through media-disseminated information, and call for policy-makers to support the healthy development of media in the capital market while addressing potential negative impacts.
{"title":"Media coverage and managerial investment learning from stock markets: International evidence","authors":"Xin Gao , Weidong Xu , Donghui Li","doi":"10.1016/j.ribaf.2025.102862","DOIUrl":"10.1016/j.ribaf.2025.102862","url":null,"abstract":"<div><div>Employing a large sample of 26,819 firms over a 20-year period, our study investigates the correlation between media coverage and investment-to-price sensitivity through OLS regression. The findings reveal a noteworthy positive impact of media coverage on investment-to-price sensitivity, remaining robust even after controlling for various factors. Mechanism analysis demonstrates that the positive influence of media coverage on managerial investment learning operates through channels related to information asymmetry and corporate governance. We also find that retail investor attention can strengthen the positive relationship between media coverage and investment-to-price sensitivity. Moreover, our analysis of news sources and content highlights the significant role of internationally renowned sources, business channels, positive sentiment, and stock-related coverage in enhancing investment-to-price sensitivity. These insights provide valuable guidance for firms to optimize their use of media for decision-making, offer investors a means to identify opportunities through media-disseminated information, and call for policy-makers to support the healthy development of media in the capital market while addressing potential negative impacts.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102862"},"PeriodicalIF":6.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642558","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 : 2025-03-13DOI: 10.1016/j.ribaf.2025.102868
Mahmoud Hassan , Ji-Yong Lee , Luc Rouge , Marc Kouzez
This article investigates the impact of green public finance and green taxes on total, environmental, and non-environmental innovation in developed economies from 1994 to 2019. The findings reveal that in the short run, these variables do not significantly influence any of the three types of innovation. However, over the long run, green taxes are found to enhance both environmental and non-environmental innovation, whereas green public finance only promotes environmental innovation. Additionally, the Granger non-causality test indicates that past values of green taxes can predict future values across all three categories of innovation. The policy implications of this research are significant: increasing allocations toward green public finance and implementing green taxes can accelerate the development of various technologies, thereby contributing to the achievement of carbon neutrality in developed economies. Nonetheless, policymakers should justify the adoption of these measures by focusing on their positive long-term impacts on innovation.
{"title":"The impact of green public finance and green taxes on environmental and non-environmental innovation","authors":"Mahmoud Hassan , Ji-Yong Lee , Luc Rouge , Marc Kouzez","doi":"10.1016/j.ribaf.2025.102868","DOIUrl":"10.1016/j.ribaf.2025.102868","url":null,"abstract":"<div><div>This article investigates the impact of green public finance and green taxes on total, environmental, and non-environmental innovation in developed economies from 1994 to 2019. The findings reveal that in the short run, these variables do not significantly influence any of the three types of innovation. However, over the long run, green taxes are found to enhance both environmental and non-environmental innovation, whereas green public finance only promotes environmental innovation. Additionally, the Granger non-causality test indicates that past values of green taxes can predict future values across all three categories of innovation. The policy implications of this research are significant: increasing allocations toward green public finance and implementing green taxes can accelerate the development of various technologies, thereby contributing to the achievement of carbon neutrality in developed economies. Nonetheless, policymakers should justify the adoption of these measures by focusing on their positive long-term impacts on innovation.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102868"},"PeriodicalIF":6.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642559","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 : 2025-03-13DOI: 10.1016/j.ribaf.2025.102865
Jie Yang , Yanfang Niu , Wenlei Shi , Kanghuan Zhu
This study employs a machine learning approach to explore the relationship between board secretaries' (BS') characteristics and the quality of Environmental, Social, and Governance (ESG) disclosure in enterprises. The results indicate that BS' competence characteristics are the primary drivers of ESG disclosure quality, with salary, functional experience, age, and tenure as key predictive features. BS' salary and functional experience show an upward trend with ESG disclosure quality. BS' age has a nonlinear predictive effect on ESG disclosure quality, exhibiting an approximately positive "U"-shaped relationship. BS' tenure also demonstrates a nonlinear predictive effect. Robustness checks confirm that BS' characteristics remain crucial factors even after controlling for CEO characteristics. Interaction effect analysis reveals that the impact of BS' salary, functional experience, and tenure on ESG disclosure quality is more significant among middle-aged board secretaries. Heterogeneity tests based on ownership type, institutional environment, and media attention show that the importance of BS' characteristics varies across different contexts. This study provides a new perspective and empirical evidence for predicting ESG disclosure quality, offering guidance for improving the appointment process and incentive mechanisms for board secretaries.
{"title":"Predicting ESG disclosure quality through board secretaries' characteristics: A machine learning approach","authors":"Jie Yang , Yanfang Niu , Wenlei Shi , Kanghuan Zhu","doi":"10.1016/j.ribaf.2025.102865","DOIUrl":"10.1016/j.ribaf.2025.102865","url":null,"abstract":"<div><div>This study employs a machine learning approach to explore the relationship between board secretaries' (BS') characteristics and the quality of Environmental, Social, and Governance (ESG) disclosure in enterprises. The results indicate that BS' competence characteristics are the primary drivers of ESG disclosure quality, with salary, functional experience, age, and tenure as key predictive features. BS' salary and functional experience show an upward trend with ESG disclosure quality. BS' age has a nonlinear predictive effect on ESG disclosure quality, exhibiting an approximately positive \"U\"-shaped relationship. BS' tenure also demonstrates a nonlinear predictive effect. Robustness checks confirm that BS' characteristics remain crucial factors even after controlling for CEO characteristics. Interaction effect analysis reveals that the impact of BS' salary, functional experience, and tenure on ESG disclosure quality is more significant among middle-aged board secretaries. Heterogeneity tests based on ownership type, institutional environment, and media attention show that the importance of BS' characteristics varies across different contexts. This study provides a new perspective and empirical evidence for predicting ESG disclosure quality, offering guidance for improving the appointment process and incentive mechanisms for board secretaries.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102865"},"PeriodicalIF":6.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642557","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 : 2025-03-12DOI: 10.1016/j.ribaf.2025.102860
Mosab I. Tabash
The article examines the relationship between economic policy uncertainty (EPU) and institutional quality (INQ) and how both factors affect FDI inflow into South Asia between 2000 and 2019. The relationship between the variables was analyzed using the FMOLS and DOLS models while the robustness of analysis was performed by employing GMM model. Demonstrated by the strong negative correlation between FDI inflows and EPU, the findings suggest that policy instability discourages investments essential for sustainable development. In contrast, INQ posits a direct relationship with FDI inflow. Notably, INQ also mitigates the negative effects of policy uncertainty on investment by moderating the relationship between EPU and FDI. These findings have significant policy implications, indicating that an investment climate conducive to sustainable FDI can be established by prioritizing institutional improvement, policy stability, and financial development. This study offers a way to integrate FDI policy with sustainable development goals by examining the moderating effect of INQ on the EPU-FDI nexus. It also contributes to the existing body of literature on environmental transition, opening new research avenues for further exploration.
{"title":"Economic policy uncertainty and foreign direct investment inflow: The role of institutional quality in South Asia region","authors":"Mosab I. Tabash","doi":"10.1016/j.ribaf.2025.102860","DOIUrl":"10.1016/j.ribaf.2025.102860","url":null,"abstract":"<div><div>The article examines the relationship between economic policy uncertainty (EPU) and institutional quality (INQ) and how both factors affect FDI inflow into South Asia between 2000 and 2019. The relationship between the variables was analyzed using the FMOLS and DOLS models while the robustness of analysis was performed by employing GMM model. Demonstrated by the strong negative correlation between FDI inflows and EPU, the findings suggest that policy instability discourages investments essential for sustainable development. In contrast, INQ posits a direct relationship with FDI inflow. Notably, INQ also mitigates the negative effects of policy uncertainty on investment by moderating the relationship between EPU and FDI. These findings have significant policy implications, indicating that an investment climate conducive to sustainable FDI can be established by prioritizing institutional improvement, policy stability, and financial development. This study offers a way to integrate FDI policy with sustainable development goals by examining the moderating effect of INQ on the EPU-FDI nexus. It also contributes to the existing body of literature on environmental transition, opening new research avenues for further exploration.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102860"},"PeriodicalIF":6.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609256","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 : 2025-03-12DOI: 10.1016/j.ribaf.2025.102861
Jiacai Xiong , Zelin Yang , Qing Sophie Wang
This study examines the impact of non-punitive regulations on corporate greenwashing. We employ a word embedding model to quantify greenwashing levels in Chinese A-share listed companies from 2015 to 2021. Using comment letters issued by stock exchanges as a proxy for non-punitive intervention, our finding reveals their effectiveness in deterring greenwashing behavior. The results remain robust after a battery of sensitivity tests. We posit three potential mechanisms underlying this effect: enhanced information transparency, increased media scrutiny, and mitigated agency problems within firms. The impact of comment letters is particularly pronounced in firms with a higher propensity for greenwashing, including private and smaller companies, those with limited analyst coverage, firms operating in polluting or highly competitive industries, and regions with lower environmental transparency or market development. Overall, this study contributes to the understanding of non-punitive regulation's role in shaping corporate environmental practices and provides valuable insights for mitigating greenwashing.
{"title":"Can non-punitive regulation curb corporate greenwashing?Evidence from a word embedding model","authors":"Jiacai Xiong , Zelin Yang , Qing Sophie Wang","doi":"10.1016/j.ribaf.2025.102861","DOIUrl":"10.1016/j.ribaf.2025.102861","url":null,"abstract":"<div><div>This study examines the impact of non-punitive regulations on corporate greenwashing. We employ a word embedding model to quantify greenwashing levels in Chinese A-share listed companies from 2015 to 2021. Using comment letters issued by stock exchanges as a proxy for non-punitive intervention, our finding reveals their effectiveness in deterring greenwashing behavior. The results remain robust after a battery of sensitivity tests. We posit three potential mechanisms underlying this effect: enhanced information transparency, increased media scrutiny, and mitigated agency problems within firms. The impact of comment letters is particularly pronounced in firms with a higher propensity for greenwashing, including private and smaller companies, those with limited analyst coverage, firms operating in polluting or highly competitive industries, and regions with lower environmental transparency or market development. Overall, this study contributes to the understanding of non-punitive regulation's role in shaping corporate environmental practices and provides valuable insights for mitigating greenwashing.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102861"},"PeriodicalIF":6.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-08DOI: 10.1016/j.ribaf.2025.102856
Sultan Sikandar Mirza , Ninglu Xu , Shaen Corbet , Frank Scrimgeour
This study examines the effect of idiosyncratic risk on the green innovation of A-share listed companies in China from 2010 to 2021, using idiosyncratic risk as a proxy for financial risk. Results indicate that idiosyncratic risk adversely affects a firm’s green innovation, which is negatively mod- erated by heightened economic policy uncertainty (EPU), highlighting that firms tend to defer or halt green innovation investments under high EPU, appreciating the ’real option’ value of a deci- sion to ‘wait-and-see’. Further, policy determinant analysis reveals that the negative moderation originates from trade-related policy uncertainties. Heterogeneity analysis reveals that the primary findings are more pronounced in non-SOEs and those companies determined to be larger, older, and more leveraged firms with elevated ESG performance. Findings are found to be robust across several various econometric approaches. This research contributes to the literature on corporate green innovation by analysing the moderating role of EPU and providing insights for managers, investors, and policymakers.
{"title":"Green innovation under financial and policy uncertainty: Evidence from China","authors":"Sultan Sikandar Mirza , Ninglu Xu , Shaen Corbet , Frank Scrimgeour","doi":"10.1016/j.ribaf.2025.102856","DOIUrl":"10.1016/j.ribaf.2025.102856","url":null,"abstract":"<div><div>This study examines the effect of idiosyncratic risk on the green innovation of A-share listed companies in China from 2010 to 2021, using idiosyncratic risk as a proxy for financial risk. Results indicate that idiosyncratic risk adversely affects a firm’s green innovation, which is negatively mod- erated by heightened economic policy uncertainty (EPU), highlighting that firms tend to defer or halt green innovation investments under high EPU, appreciating the ’real option’ value of a deci- sion to ‘wait-and-see’. Further, policy determinant analysis reveals that the negative moderation originates from trade-related policy uncertainties. Heterogeneity analysis reveals that the primary findings are more pronounced in non-SOEs and those companies determined to be larger, older, and more leveraged firms with elevated ESG performance. Findings are found to be robust across several various econometric approaches. This research contributes to the literature on corporate green innovation by analysing the moderating role of EPU and providing insights for managers, investors, and policymakers.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102856"},"PeriodicalIF":6.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-08DOI: 10.1016/j.ribaf.2025.102859
Bohui Wen , Wei You , Ming Yuan
In recent years, the rise of ESG concepts has gradually had an impact on economic entities, and commercial banks are also facing changes in their risk-taking behavior while practicing ESG concepts. This paper takes data of 42 A-share listed commercial banks in China from 2009Q1 to 2023Q3 to analyze the impact of ESG performance on commercial banks by distinguishing between proactive and passive risk-taking. The findings reveal that strong ESG performance promotes proactive risk-taking while suppressing passive risk-taking, ultimately reducing overall passive risk-taking. This helps improve asset quality, mitigate the risk of asset deterioration, and enhance financing functions of commercial banks. Mechanism tests show that ESG performance fosters proactive risk-taking by accumulating reputational capital, while curbing passive risk-taking through optimizing credit structures and alleviating information asymmetry. Regulatory effect analysis indicates that expanding the MPA (Macroprudential Assessment) to the green sector can moderate the positive impact of ESG performance on proactive risk-taking, preventing excessive risk-taking. This study provides recommendations for the banking industry to balance ESG practices with financial stability under the "dual carbon" goals.
{"title":"The Impact of commercial banks' ESG performance: Difference between provocative and passive risk-taking – Evidence from China","authors":"Bohui Wen , Wei You , Ming Yuan","doi":"10.1016/j.ribaf.2025.102859","DOIUrl":"10.1016/j.ribaf.2025.102859","url":null,"abstract":"<div><div>In recent years, the rise of ESG concepts has gradually had an impact on economic entities, and commercial banks are also facing changes in their risk-taking behavior while practicing ESG concepts. This paper takes data of 42 A-share listed commercial banks in China from 2009Q1 to 2023Q3 to analyze the impact of ESG performance on commercial banks by distinguishing between proactive and passive risk-taking. The findings reveal that strong ESG performance promotes proactive risk-taking while suppressing passive risk-taking, ultimately reducing overall passive risk-taking. This helps improve asset quality, mitigate the risk of asset deterioration, and enhance financing functions of commercial banks. Mechanism tests show that ESG performance fosters proactive risk-taking by accumulating reputational capital, while curbing passive risk-taking through optimizing credit structures and alleviating information asymmetry. Regulatory effect analysis indicates that expanding the MPA (Macroprudential Assessment) to the green sector can moderate the positive impact of ESG performance on proactive risk-taking, preventing excessive risk-taking. This study provides recommendations for the banking industry to balance ESG practices with financial stability under the \"dual carbon\" goals.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"76 ","pages":"Article 102859"},"PeriodicalIF":6.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609257","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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