Pub Date : 2025-06-11DOI: 10.1016/j.jcorpfin.2025.102834
Nihad Aliyev , Fariz Huseynov , Khaladdin Rzayev
We investigate how firm managers’ learning from share prices is influenced by two different types of algorithmic trading (AT) activities in their shares. We find that liquidity-supplying AT enhances managers’ ability to learn from share prices by encouraging information acquisition in markets, leading to increased investment sensitivity to share prices. However, liquidity-demanding AT impairs this learning process by discouraging information acquisition. Firm operating performance correspondingly improves with liquidity-supplying AT and deteriorates with liquidity-demanding AT. To establish causality, we use NYSE’s Autoquote implementation as a source of exogenous variation in AT. Our findings demonstrate AT’s significant impact on real economic outcomes.
{"title":"The good and evil of algos: Investment-to-price sensitivity and the learning hypothesis","authors":"Nihad Aliyev , Fariz Huseynov , Khaladdin Rzayev","doi":"10.1016/j.jcorpfin.2025.102834","DOIUrl":"10.1016/j.jcorpfin.2025.102834","url":null,"abstract":"<div><div>We investigate how firm managers’ learning from share prices is influenced by two different types of algorithmic trading (AT) activities in their shares. We find that liquidity-supplying AT enhances managers’ ability to learn from share prices by encouraging information acquisition in markets, leading to increased investment sensitivity to share prices. However, liquidity-demanding AT impairs this learning process by discouraging information acquisition. Firm operating performance correspondingly improves with liquidity-supplying AT and deteriorates with liquidity-demanding AT. To establish causality, we use NYSE’s Autoquote implementation as a source of exogenous variation in AT. Our findings demonstrate AT’s significant impact on real economic outcomes.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102834"},"PeriodicalIF":7.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-11DOI: 10.1016/j.jcorpfin.2025.102836
Heng Geng , Harald Hau , Roni Michaely , Binh Hoang Nguyen
The large increase in common institutional ownership has raised legitimate antitrust concerns. While the exact channel by which common institutional shareholders might influence firm policy remains unclear, a prominent potential mechanism is corporate board representation. Using hand-collected data on shareholders' board representation, we show that instances of institutional investors simultaneously holding board positions in rival companies are exceedingly rare and do not account for the positive correlation between common institutional ownership and firm-pair profitability. Our findings suggest that board representation by institutional investors is unlikely to represent an empirically potent channel of influence on corporate policy.
{"title":"Common institutional investors and board representation in rival firms","authors":"Heng Geng , Harald Hau , Roni Michaely , Binh Hoang Nguyen","doi":"10.1016/j.jcorpfin.2025.102836","DOIUrl":"10.1016/j.jcorpfin.2025.102836","url":null,"abstract":"<div><div>The large increase in common institutional ownership has raised legitimate antitrust concerns. While the exact channel by which common institutional shareholders might influence firm policy remains unclear, a prominent potential mechanism is corporate board representation. Using hand-collected data on shareholders' board representation, we show that instances of institutional investors simultaneously holding board positions in rival companies are exceedingly rare and do <em>not</em> account for the positive correlation between common institutional ownership and firm-pair profitability. Our findings suggest that board representation by institutional investors is unlikely to represent an empirically potent channel of influence on corporate policy.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102836"},"PeriodicalIF":7.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper contributes to the growing body of research on private firms, particularly private firm accounting. We explore the economic factors that drive improvements in the default prediction of unlisted private firms using peers’ market-based information. Specifically, we examine how the market-based default probability of a peer firm can provide valuable insights into the often noisy accounting data of private firms. Our analysis delves deeply into these economic issues to uncover essential insights. To address our research question, we utilize a granular proprietary dataset of 10,136 Italian micro-, small-, and mid-sized enterprises (MSMEs) that are required to disclose their financial statements publicly. We propose a novel public–private firm mapping approach to investigate whether incorporating peers’ market-based information improves the accuracy of default predictions for private unlisted firms. Our mapping approach matches the market information of listed firms with private firms through a data-driven clustering technique using Neural Network Autoencoder. This method enables us to link the Merton Probability of Default (PD) of public peers to the corresponding private firms within the same cluster. We then apply five statistical techniques – linear models, multivariate adaptive regression splines, support vector machines, k-nearest neighbours and random forests – to predict corporate default among private firms, comparing model performance with and without the inclusion of Merton’s PD estimated using peers’ market-based information. To assess the contribution of each predictor, we employ Shapley values. Our results demonstrate a significant improvement in default prediction for unlisted private firms when incorporating peers’ market-based information, confirming that the noisy accounting data of private firms alone hinders accurate default prediction. Furthermore, our findings highlight the importance for banks to broaden the scope of information used in credit risk assessments of private firms. These results have important policy implications for financial institutions and policymakers, providing a tool to mitigate the challenges posed by the noisy information disclosure of MSMEs while ensuring more accurate credit risk assessments.
{"title":"Machine Learning for the Unlisted: Enhancing MSME Default Prediction with Public Market Signals","authors":"Alessandro Bitetto , Stefano Filomeni , Michele Modina","doi":"10.1016/j.jcorpfin.2025.102830","DOIUrl":"10.1016/j.jcorpfin.2025.102830","url":null,"abstract":"<div><div>This paper contributes to the growing body of research on private firms, particularly private firm accounting. We explore the economic factors that drive improvements in the default prediction of unlisted private firms using peers’ market-based information. Specifically, we examine how the market-based default probability of a peer firm can provide valuable insights into the often noisy accounting data of private firms. Our analysis delves deeply into these economic issues to uncover essential insights. To address our research question, we utilize a granular proprietary dataset of 10,136 Italian micro-, small-, and mid-sized enterprises (MSMEs) that are required to disclose their financial statements publicly. We propose a novel public–private firm mapping approach to investigate whether incorporating peers’ market-based information improves the accuracy of default predictions for private unlisted firms. Our mapping approach matches the market information of listed firms with private firms through a data-driven clustering technique using Neural Network Autoencoder. This method enables us to link the Merton Probability of Default (PD) of public peers to the corresponding private firms within the same cluster. We then apply five statistical techniques – linear models, multivariate adaptive regression splines, support vector machines, k-nearest neighbours and random forests – to predict corporate default among private firms, comparing model performance with and without the inclusion of Merton’s PD estimated using peers’ market-based information. To assess the contribution of each predictor, we employ Shapley values. Our results demonstrate a significant improvement in default prediction for unlisted private firms when incorporating peers’ market-based information, confirming that the noisy accounting data of private firms alone hinders accurate default prediction. Furthermore, our findings highlight the importance for banks to broaden the scope of information used in credit risk assessments of private firms. These results have important policy implications for financial institutions and policymakers, providing a tool to mitigate the challenges posed by the noisy information disclosure of MSMEs while ensuring more accurate credit risk assessments.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102830"},"PeriodicalIF":7.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-11DOI: 10.1016/j.jcorpfin.2025.102800
Lin William Cong , Liam Fox , Siguang Li , Luofeng Zhou
Oracle nodes enable smart contracts to access off-chain and cross-chain data, thus bridging information among digital networks and with the real economy. However, reliance on external input creates security and reliability risks in information aggregation and transfer. We describe the general oracle problem, introduce the Oracle Trilemma – highlighting the trade-offs between scalability, decentralization, and truthfulness – and discuss relevant economic issues concerning the role of oracles in applications such as DeFi, supply chain management, gaming, and prediction markets. In particular, we survey off-chain reporting, off-equilibrium alerting, and dynamic incentive design as promising approaches to resolving the trilemma. We further list oracle vulnerabilities and evaluate oracle sustainability through staking and tokenomics programs. Finally, we highlight empirical studies on how oracle integration affects DeFi adoption, token valuation, liquidity, and system risks. We conclude by presenting emerging trends and suggesting open research questions.
{"title":"A primer on oracle economics","authors":"Lin William Cong , Liam Fox , Siguang Li , Luofeng Zhou","doi":"10.1016/j.jcorpfin.2025.102800","DOIUrl":"10.1016/j.jcorpfin.2025.102800","url":null,"abstract":"<div><div>Oracle nodes enable smart contracts to access off-chain and cross-chain data, thus bridging information among digital networks and with the real economy. However, reliance on external input creates security and reliability risks in information aggregation and transfer. We describe the general oracle problem, introduce the Oracle Trilemma – highlighting the trade-offs between scalability, decentralization, and truthfulness – and discuss relevant economic issues concerning the role of oracles in applications such as DeFi, supply chain management, gaming, and prediction markets. In particular, we survey off-chain reporting, off-equilibrium alerting, and dynamic incentive design as promising approaches to resolving the trilemma. We further list oracle vulnerabilities and evaluate oracle sustainability through staking and tokenomics programs. Finally, we highlight empirical studies on how oracle integration affects DeFi adoption, token valuation, liquidity, and system risks. We conclude by presenting emerging trends and suggesting open research questions.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102800"},"PeriodicalIF":7.2,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine the differences in the options implied left-tail risk and volatility of government-owned and private banks in India. We show that left-tail risk and the cost of insurance for protection against it are high for private banks as compared to government-owned banks, despite their superior asset quality. The COVID-19 crisis, an exogenous shock to systematic risk, increased the left-tail risk more for private banks. Furthermore, the effect of government ownership on left-tail risk is more significant for smaller banks compared to larger banks. Contrary to our left-tail risk result, we find that government-owned banks have higher near-the-money options implied volatility than private banks. Our findings suggest that while government ownership mitigates expected downside risk, it also leads to higher expected volatility due to riskier lending policies and uncertainties about capital infusions.
{"title":"Does government ownership differently impact expected left-tail and volatility risk of bank stock? Evidence from options market","authors":"Pranjal Srivastava , Sumit Saurav , Abinash Mishra","doi":"10.1016/j.jcorpfin.2025.102832","DOIUrl":"10.1016/j.jcorpfin.2025.102832","url":null,"abstract":"<div><div>We examine the differences in the options implied left-tail risk and volatility of government-owned and private banks in India. We show that left-tail risk and the cost of insurance for protection against it are high for private banks as compared to government-owned banks, despite their superior asset quality. The COVID-19 crisis, an exogenous shock to systematic risk, increased the left-tail risk more for private banks. Furthermore, the effect of government ownership on left-tail risk is more significant for smaller banks compared to larger banks. Contrary to our left-tail risk result, we find that government-owned banks have higher near-the-money options implied volatility than private banks. Our findings suggest that while government ownership mitigates expected downside risk, it also leads to higher expected volatility due to riskier lending policies and uncertainties about capital infusions.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102832"},"PeriodicalIF":7.2,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-07DOI: 10.1016/j.jcorpfin.2025.102828
Barıs Ince , Cansu Iskenderoglu
This paper documents that industrial robots enhance firms’ ability to reduce operating costs, especially during periods of declining sales. Building on this, we propose a firm-level measure of automation cost flexibility (ACF), which quantifies a firm’s capacity to reduce operating costs through automation. Using this measure, we find that firms with greater ACF exhibit higher firm values. To address endogeneity concerns and strengthen the interpretation of our results, we employ: (i) a difference-in-differences specification with a matching algorithm, and (ii) exploit the 2011 Thailand hard drive crisis as an exogenous shock. The paper further reveals that the positive impact of ACF is more pronounced for firms in highly competitive industries, those facing significant competitive threats, industries with high strategic interactions, and smaller firms. This suggests that cost flexibility encompasses a strategic dimension.
{"title":"Automation cost flexibility and firm value","authors":"Barıs Ince , Cansu Iskenderoglu","doi":"10.1016/j.jcorpfin.2025.102828","DOIUrl":"10.1016/j.jcorpfin.2025.102828","url":null,"abstract":"<div><div>This paper documents that industrial robots enhance firms’ ability to reduce operating costs, especially during periods of declining sales. Building on this, we propose a firm-level measure of automation cost flexibility (ACF), which quantifies a firm’s capacity to reduce operating costs through automation. Using this measure, we find that firms with greater ACF exhibit higher firm values. To address endogeneity concerns and strengthen the interpretation of our results, we employ: (i) a difference-in-differences specification with a matching algorithm, and (ii) exploit the 2011 Thailand hard drive crisis as an exogenous shock. The paper further reveals that the positive impact of ACF is more pronounced for firms in highly competitive industries, those facing significant competitive threats, industries with high strategic interactions, and smaller firms. This suggests that cost flexibility encompasses a strategic dimension.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102828"},"PeriodicalIF":7.2,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-06DOI: 10.1016/j.jcorpfin.2025.102837
Kose John , Jingrui Li
In this paper, we study the determinants of Bitcoin volatility. We estimate and decompose Bitcoin's realized volatility into jump volatility and continuous volatility components. We find that innovations in Robinhood retail trading are positively related to the continuous component of Bitcoin's volatility. Specifically, the innovations in Robinhood retail trading predict an increase in future ten-day continuous volatility. The innovations in the (anonymous) trading volume of Monero are also positively related to the jump component in Bitcoin's volatility. Specifically, the innovations in Monero trading volume predict an increase in average jump volatility over the next five days. Our results suggest that retail trading positively influences the continuous component of Bitcoin volatility, while the preference for transaction anonymity positively affects the jump component of Bitcoin volatility.
{"title":"Bitcoin price volatility: Effects of retail traders, illegal users, and sentiment","authors":"Kose John , Jingrui Li","doi":"10.1016/j.jcorpfin.2025.102837","DOIUrl":"10.1016/j.jcorpfin.2025.102837","url":null,"abstract":"<div><div>In this paper, we study the determinants of Bitcoin volatility. We estimate and decompose Bitcoin's realized volatility into jump volatility and continuous volatility components. We find that innovations in Robinhood retail trading are positively related to the continuous component of Bitcoin's volatility. Specifically, the innovations in Robinhood retail trading predict an increase in future ten-day continuous volatility. The innovations in the (anonymous) trading volume of Monero are also positively related to the jump component in Bitcoin's volatility. Specifically, the innovations in Monero trading volume predict an increase in average jump volatility over the next five days. Our results suggest that retail trading positively influences the continuous component of Bitcoin volatility, while the preference for transaction anonymity positively affects the jump component of Bitcoin volatility.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102837"},"PeriodicalIF":7.2,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-06DOI: 10.1016/j.jcorpfin.2025.102812
Buhui Qiu , Teng Wang
This paper examines corporate mergers and acquisitions (M&A) outcomes under lender scrutiny. Using the unique shocks of U.S. supervisory stress testing, we find that firms under increased lender scrutiny after their relationship banks fail stress tests engage in fewer but higher-quality M&A deals. Evidence from comprehensive supervisory data reveals improved credit quality for newly originated M&A-related loans under enhanced lender scrutiny. This improvement is further evident in positive stock return reactions to M&A deals financed by loans subject to enhanced lender scrutiny. As companies engage in fewer but higher-quality deals, they also experience higher returns on assets. Our findings highlight the importance of lender scrutiny in corporate M&A activities.
{"title":"Corporate mergers and acquisitions under lender scrutiny","authors":"Buhui Qiu , Teng Wang","doi":"10.1016/j.jcorpfin.2025.102812","DOIUrl":"10.1016/j.jcorpfin.2025.102812","url":null,"abstract":"<div><div>This paper examines corporate mergers and acquisitions (M&A) outcomes under lender scrutiny. Using the unique shocks of U.S. supervisory stress testing, we find that firms under increased lender scrutiny after their relationship banks fail stress tests engage in <em>fewer</em> but <em>higher-quality</em> M&A deals. Evidence from comprehensive supervisory data reveals improved credit quality for newly originated M&A-related loans under enhanced lender scrutiny. This improvement is further evident in positive stock return reactions to M&A deals financed by loans subject to enhanced lender scrutiny. As companies engage in fewer but higher-quality deals, they also experience higher returns on assets. Our findings highlight the importance of lender scrutiny in corporate M&A activities.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102812"},"PeriodicalIF":7.2,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-02DOI: 10.1016/j.jcorpfin.2025.102835
Denis Schweizer , Xinjie Wang , Ge Wu , Aoran Zhang
This paper examines how political connections shape media bias and contribute to regulatory noncompliance in China's capital markets. Using a large sample of news articles on publicly listed non-state-owned enterprises (non-SOEs), we find that politically connected firms receive significantly more favorable media coverage than their unconnected peers. A difference-in-differences analysis exploiting a regulatory shock—China's Rule 18 anti-corruption regulation—that forced politically connected directors to resign confirms the link between political ties and biased reporting. Around corporate scandals, politically connected firms face softer media scrutiny, weakening reputational penalties. Critically, we show that this media shielding effect increases the likelihood of repeated regulatory violations. These findings highlight the social costs of the “scandal-covering” role of political connections, which not only distort the information environment but also undermine regulatory deterrence and market discipline.
{"title":"Political connections and media bias: Evidence from China","authors":"Denis Schweizer , Xinjie Wang , Ge Wu , Aoran Zhang","doi":"10.1016/j.jcorpfin.2025.102835","DOIUrl":"10.1016/j.jcorpfin.2025.102835","url":null,"abstract":"<div><div>This paper examines how political connections shape media bias and contribute to regulatory noncompliance in China's capital markets. Using a large sample of news articles on publicly listed non-state-owned enterprises (non-SOEs), we find that politically connected firms receive significantly more favorable media coverage than their unconnected peers. A difference-in-differences analysis exploiting a regulatory shock—China's Rule 18 anti-corruption regulation—that forced politically connected directors to resign confirms the link between political ties and biased reporting. Around corporate scandals, politically connected firms face softer media scrutiny, weakening reputational penalties. Critically, we show that this media shielding effect increases the likelihood of repeated regulatory violations. These findings highlight the social costs of the “scandal-covering” role of political connections, which not only distort the information environment but also undermine regulatory deterrence and market discipline.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102835"},"PeriodicalIF":7.2,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144222652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-31DOI: 10.1016/j.jcorpfin.2025.102833
Kenuo Li , Lijuan Zhang
This paper explores the impact of share pledging on workplace safety. Using establishment-level data on workplace safety, we find that firms with executive share pledging exhibit higher workplace injuries/illnesses. Our channel analyses suggest that the higher injury/illness cases in pledging firms are associated with increased employee workloads and poor corporate safety cultures. Further analysis shows that the documented association between share pledging and workplace safety is weaker for firms that have more analyst coverage, face higher levels of pressure from labor unions, and operate in counties that have higher levels of social capital. Conversely, the association is more pronounced when firms meet or just beat analyst earnings forecasts and when CEOs are approaching retirement age. The results are robust to using injury rate as an alternative measure for workplace safety, controlling for accrual-based earnings management and financial constraints, and using firm-level analyses. Overall, our findings suggest a positive association between share pledging and compromised workplace safety, potentially driven by efforts to support short-term stock performance.
{"title":"Does share pledging affect workplace safety?","authors":"Kenuo Li , Lijuan Zhang","doi":"10.1016/j.jcorpfin.2025.102833","DOIUrl":"10.1016/j.jcorpfin.2025.102833","url":null,"abstract":"<div><div>This paper explores the impact of share pledging on workplace safety. Using establishment-level data on workplace safety, we find that firms with executive share pledging exhibit higher workplace injuries/illnesses. Our channel analyses suggest that the higher injury/illness cases in pledging firms are associated with increased employee workloads and poor corporate safety cultures. Further analysis shows that the documented association between share pledging and workplace safety is weaker for firms that have more analyst coverage, face higher levels of pressure from labor unions, and operate in counties that have higher levels of social capital. Conversely, the association is more pronounced when firms meet or just beat analyst earnings forecasts and when CEOs are approaching retirement age. The results are robust to using injury rate as an alternative measure for workplace safety, controlling for accrual-based earnings management and financial constraints, and using firm-level analyses. Overall, our findings suggest a positive association between share pledging and compromised workplace safety, potentially driven by efforts to support short-term stock performance.</div></div>","PeriodicalId":15525,"journal":{"name":"Journal of Corporate Finance","volume":"94 ","pages":"Article 102833"},"PeriodicalIF":7.2,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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