Pub Date : 2025-10-16DOI: 10.1016/j.jfineco.2025.104171
Mark Jansen , Fabian Nagel , Constantine Yannelis , Anthony Lee Zhang
We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This increases total social welfare and transfers surplus across borrower types. We show that under certain assumptions the magnitudes of these welfare changes can be estimated using only quantity and price data. Applying our methodology to bankruptcy flag removal, we find that in a counterfactual world where bankruptcy flags are never removed from credit reports, previously-bankrupt borrowers’ surplus decreases substantially, whereas efficiency increases only modestly.
{"title":"Data and welfare in credit markets","authors":"Mark Jansen , Fabian Nagel , Constantine Yannelis , Anthony Lee Zhang","doi":"10.1016/j.jfineco.2025.104171","DOIUrl":"10.1016/j.jfineco.2025.104171","url":null,"abstract":"<div><div>We show how to measure the welfare effects arising from increased data availability. When lenders have more data on prospective borrower costs, they can charge prices that are more aligned with these costs. This increases total social welfare and transfers surplus across borrower types. We show that under certain assumptions the magnitudes of these welfare changes can be estimated using only quantity and price data. Applying our methodology to bankruptcy flag removal, we find that in a counterfactual world where bankruptcy flags are never removed from credit reports, previously-bankrupt borrowers’ surplus decreases substantially, whereas efficiency increases only modestly.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104171"},"PeriodicalIF":10.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321993","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 : 2025-10-16DOI: 10.1016/j.jfineco.2025.104186
Jean-Edouard Colliard , Co-Pierre Georg
We propose a framework to study regulatory complexity, based on concepts from computer science. We distinguish different dimensions of complexity, classify existing measures, develop new ones, compute them on three examples — Basel I, the Dodd–Frank Act, and the European Banking Authority’s reporting rules — and test them using experiments and a survey on compliance costs. We highlight two measures that capture complexity beyond the length of a regulation. We propose a quantitative approach to the policy trade-off between regulatory complexity and precision.
{"title":"Measuring regulatory complexity","authors":"Jean-Edouard Colliard , Co-Pierre Georg","doi":"10.1016/j.jfineco.2025.104186","DOIUrl":"10.1016/j.jfineco.2025.104186","url":null,"abstract":"<div><div>We propose a framework to study regulatory complexity, based on concepts from computer science. We distinguish different dimensions of complexity, classify existing measures, develop new ones, compute them on three examples — Basel I, the Dodd–Frank Act, and the European Banking Authority’s reporting rules — and test them using experiments and a survey on compliance costs. We highlight two measures that capture complexity beyond the length of a regulation. We propose a quantitative approach to the policy trade-off between regulatory complexity and precision.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104186"},"PeriodicalIF":10.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321992","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 : 2025-10-15DOI: 10.1016/j.jfineco.2025.104185
Batchimeg Sambalaibat
This paper studies a search-based model of OTC markets in which clients with heterogeneous trading needs direct their trades to one of ex-ante identical dealers. The main insight of the paper is that the way clients sort across dealers shapes dealer-to-dealer trading patterns and, in turn, generates a core–periphery interdealer network structure. Dealers in the model become heterogeneous because they attract different clients in equilibrium. Some dealers attract clients who trade frequently (e.g., index funds); others attract clients with infrequent trading needs (e.g., pension funds). Dealers attracting clients with frequent trading needs receive a larger volume of client orders, trade more with other dealers, and, as a result, form the core of the interdealer network. Conversely, dealers specializing in clients with infrequent trading needs form the periphery. I also show that accounting for client heterogeneity across dealers (a) challenges standard measurements and interpretations of bid–ask spreads and (b) generates predictions on bid–ask spreads and dealer centrality consistent with the empirical literature.
{"title":"Heterogeneous clienteles and dealer networks","authors":"Batchimeg Sambalaibat","doi":"10.1016/j.jfineco.2025.104185","DOIUrl":"10.1016/j.jfineco.2025.104185","url":null,"abstract":"<div><div>This paper studies a search-based model of OTC markets in which clients with heterogeneous trading needs direct their trades to one of ex-ante identical dealers. The main insight of the paper is that the way clients sort across dealers shapes dealer-to-dealer trading patterns and, in turn, generates a core–periphery interdealer network structure. Dealers in the model become heterogeneous because they attract different clients in equilibrium. Some dealers attract clients who trade frequently (e.g., index funds); others attract clients with infrequent trading needs (e.g., pension funds). Dealers attracting clients with frequent trading needs receive a larger volume of client orders, trade more with other dealers, and, as a result, form the core of the interdealer network. Conversely, dealers specializing in clients with infrequent trading needs form the periphery. I also show that accounting for client heterogeneity across dealers (a) challenges standard measurements and interpretations of bid–ask spreads and (b) generates predictions on bid–ask spreads and dealer centrality consistent with the empirical literature.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104185"},"PeriodicalIF":10.4,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321995","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 : 2025-10-14DOI: 10.1016/j.jfineco.2025.104184
Riccardo Colacito , Yan Qian , Andreas Stathopoulos
We document that the currency denomination of the debt of large firms in developed countries is strongly associated with the geographical distribution of their sales. Furthermore, those firms exhibit significant home currency bias and international currency bias in borrowing: controlling for the geography of sales, they borrow more in their home currency and the two most traded currencies, the US dollar and the euro. We also show that the firms’ debt currency denomination choices are associated with export invoicing currency patterns in a way consistent with a currency hedging mechanism. In particular, firms domiciled in countries that invoice a larger share of their exports in either their home currency or in a vehicle currency exhibit a weaker connection between the currency denomination of their debt and the geography of their sales. Moreover, firms in countries that invoice more of their exports in an international currency are characterized by stronger international currency bias in debt issuance.
{"title":"Global sales, international currencies, and the currency denomination of debt","authors":"Riccardo Colacito , Yan Qian , Andreas Stathopoulos","doi":"10.1016/j.jfineco.2025.104184","DOIUrl":"10.1016/j.jfineco.2025.104184","url":null,"abstract":"<div><div>We document that the currency denomination of the debt of large firms in developed countries is strongly associated with the geographical distribution of their sales. Furthermore, those firms exhibit significant home currency bias and international currency bias in borrowing: controlling for the geography of sales, they borrow more in their home currency and the two most traded currencies, the US dollar and the euro. We also show that the firms’ debt currency denomination choices are associated with export invoicing currency patterns in a way consistent with a currency hedging mechanism. In particular, firms domiciled in countries that invoice a larger share of their exports in either their home currency or in a vehicle currency exhibit a weaker connection between the currency denomination of their debt and the geography of their sales. Moreover, firms in countries that invoice more of their exports in an international currency are characterized by stronger international currency bias in debt issuance.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104184"},"PeriodicalIF":10.4,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145322264","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 : 2025-10-11DOI: 10.1016/j.jfineco.2025.104183
Efraim Benmelech , Michał Zator
Using cross-country and German administrative data on robotization, we show that the impact of robots on firms and labor markets is limited. First, investment in robots is small and highly concentrated in a few industries, representing less than 0.3% of aggregate expenditures on equipment. Second, robotization does not grow as rapidly as Information Technology did in the past, and current growth is driven by gains in developing countries. Third, firms invest in robots when they face difficulties in finding workers and subsequently increase employment after the investment. The total employment effect in exposed industries and regions is negative but modest in magnitude. We discuss why the effects of robots are limited and demonstrate that other digital technologies have more potential for large economic impact.
{"title":"Robots and firm investment","authors":"Efraim Benmelech , Michał Zator","doi":"10.1016/j.jfineco.2025.104183","DOIUrl":"10.1016/j.jfineco.2025.104183","url":null,"abstract":"<div><div>Using cross-country and German administrative data on robotization, we show that the impact of robots on firms and labor markets is limited. First, investment in robots is small and highly concentrated in a few industries, representing less than 0.3% of aggregate expenditures on equipment. Second, robotization does not grow as rapidly as Information Technology did in the past, and current growth is driven by gains in developing countries. Third, firms invest in robots when they face difficulties in finding workers and subsequently increase employment after the investment. The total employment effect in exposed industries and regions is negative but modest in magnitude. We discuss why the effects of robots are limited and demonstrate that other digital technologies have more potential for large economic impact.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104183"},"PeriodicalIF":10.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270408","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 : 2025-10-08DOI: 10.1016/j.jfineco.2025.104173
Lubos Pastor , Robert F. Stambaugh , Lucian A. Taylor
We estimate financial institutions’ portfolio tilts related to U.S. stocks’ environmental, social, and governance (ESG) characteristics. From 2012 to 2023, ESG-related tilts consistently total about 6% of the investment industry’s assets and rise from 17% to 27% of institutions’ total portfolio tilts. Significant ESG tilts arise from the choice of stocks held and, especially, the weights on stocks held. The largest institutions tilt increasingly toward green stocks, while other institutions and households tilt increasingly brown. Divestment from brown stocks is typically partial rather than full, even for individual mutual funds. UNPRI signatories and European institutions tilt greener; banks tilt browner.
{"title":"Green tilts","authors":"Lubos Pastor , Robert F. Stambaugh , Lucian A. Taylor","doi":"10.1016/j.jfineco.2025.104173","DOIUrl":"10.1016/j.jfineco.2025.104173","url":null,"abstract":"<div><div>We estimate financial institutions’ portfolio tilts related to U.S. stocks’ environmental, social, and governance (ESG) characteristics. From 2012 to 2023, ESG-related tilts consistently total about 6% of the investment industry’s assets and rise from 17% to 27% of institutions’ total portfolio tilts. Significant ESG tilts arise from the choice of stocks held and, especially, the weights on stocks held. The largest institutions tilt increasingly toward green stocks, while other institutions and households tilt increasingly brown. Divestment from brown stocks is typically partial rather than full, even for individual mutual funds. UNPRI signatories and European institutions tilt greener; banks tilt browner.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104173"},"PeriodicalIF":10.4,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270410","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 : 2025-10-07DOI: 10.1016/j.jfineco.2025.104170
Colleen Honigsberg , Edwin Hu , Robert J. Jackson Jr.
The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Prior empirical literature on financial advisors has largely focused on a single subset of financial advisors, but we create a database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC or state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator. This overlap has implications for labor allocation and market discipline. For example, of the individuals who exit FINRA’s broker regime, 79% were jointly registered in insurance upon exiting FINRA’s regime. This could be efficient if it reflects bad actors who transition to lower risk work, but our evidence shows that these advisors continue to engage in financial planning after they move to the insurance side, as over 90% maintain licenses to sell annuities. Moreover, those who committed misconduct when regulated by FINRA continue to have heightened levels of misconduct in insurance. Our findings have additional implications for regulatory discipline. In 2018 and 2019, FINRA proposed rules designed to nudge “bad” brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services—98% are currently registered with state regulators as insurance producers.
{"title":"Regulatory leakage among financial advisors: Evidence from FINRA regulation of “bad” brokers","authors":"Colleen Honigsberg , Edwin Hu , Robert J. Jackson Jr.","doi":"10.1016/j.jfineco.2025.104170","DOIUrl":"10.1016/j.jfineco.2025.104170","url":null,"abstract":"<div><div>The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Prior empirical literature on financial advisors has largely focused on a single subset of financial advisors, but we create a database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC or state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator. This overlap has implications for labor allocation and market discipline. For example, of the individuals who exit FINRA’s broker regime, 79% were jointly registered in insurance upon exiting FINRA’s regime. This could be efficient if it reflects bad actors who transition to lower risk work, but our evidence shows that these advisors continue to engage in financial planning after they move to the insurance side, as over 90% maintain licenses to sell annuities. Moreover, those who committed misconduct when regulated by FINRA continue to have heightened levels of misconduct in insurance. Our findings have additional implications for regulatory discipline. In 2018 and 2019, FINRA proposed rules designed to nudge “bad” brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services—98% are currently registered with state regulators as insurance producers.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104170"},"PeriodicalIF":10.4,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270409","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 : 2025-10-01DOI: 10.1016/j.jfineco.2025.104168
Adlai Fisher , Jiří Knesl , Ryan C.Y. Lee
This article investigates predictors and benefits of corporate adaptation to crisis, adding a new dimension to studies of flexibility and resilience based on ex ante characteristics. We produce a unique sample of work-from-home announcements scraped from company websites during Covid-19. The announcers’ valuations increased by 3%–5% and risk declined versus matches, consistent with real-options theory under asymmetric information. We estimate characteristics, including subtle textual topics from 10-Ks, that predicted adaptation, show faster price response following Bloomberg coverage, and real advantages in subsequent operating performance. Corporate adaptation to crisis adds value and reduces risk, beyond information in firm characteristics.
{"title":"How valuable is corporate adaptation to crisis? Estimates from Covid-19 work-from-home announcements","authors":"Adlai Fisher , Jiří Knesl , Ryan C.Y. Lee","doi":"10.1016/j.jfineco.2025.104168","DOIUrl":"10.1016/j.jfineco.2025.104168","url":null,"abstract":"<div><div>This article investigates predictors and benefits of corporate adaptation to crisis, adding a new dimension to studies of flexibility and resilience based on <em>ex ante</em> characteristics. We produce a unique sample of work-from-home announcements scraped from company websites during Covid-19. The announcers’ valuations increased by 3%–5% and risk declined versus matches, consistent with real-options theory under asymmetric information. We estimate characteristics, including subtle textual topics from 10-Ks, that predicted adaptation, show faster price response following Bloomberg coverage, and real advantages in subsequent operating performance. Corporate adaptation to crisis adds value and reduces risk, beyond information in firm characteristics.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"174 ","pages":"Article 104168"},"PeriodicalIF":10.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195802","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 : 2025-09-25DOI: 10.1016/j.jfineco.2025.104169
Yann Decressin , Steven N. Kaplan , Morten Sorensen
Using more than 4900 personality assessments, we study changes in the characteristics of CEOs and top executives since 2001. The same four factors explain roughly half of the variation in executive characteristics in this larger sample of assessments as in Kaplan and Sorensen (2021). In later years, CEO candidates have shown declining general ability, are increasingly execution-oriented, less interpersonal, less charismatic, and less creative-strategic, and many of these differences persist for hired CEOs. We find no evidence of increasing prevalence or importance of interpersonal and softer skills. Executives assessed for the same company have positively correlated abilities, suggesting that high-ability executives complement each other. Finally, we consider corporate objectives and CEO characteristics.
{"title":"Have CEOs changed?","authors":"Yann Decressin , Steven N. Kaplan , Morten Sorensen","doi":"10.1016/j.jfineco.2025.104169","DOIUrl":"10.1016/j.jfineco.2025.104169","url":null,"abstract":"<div><div>Using more than 4900 personality assessments, we study changes in the characteristics of CEOs and top executives since 2001. The same four factors explain roughly half of the variation in executive characteristics in this larger sample of assessments as in Kaplan and Sorensen (2021). In later years, CEO candidates have shown declining general ability, are increasingly execution-oriented, less interpersonal, less charismatic, and less creative-strategic, and many of these differences persist for hired CEOs. We find no evidence of increasing prevalence or importance of interpersonal and softer skills. Executives assessed for the same company have positively correlated abilities, suggesting that high-ability executives complement each other. Finally, we consider corporate objectives and CEO characteristics.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"173 ","pages":"Article 104169"},"PeriodicalIF":10.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158178","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 : 2025-09-22DOI: 10.1016/j.jfineco.2025.104158
R. David McLean , Jeffrey Pontiff , Christopher Reilly
We assess how nine different categories of market participants trade relative to a comprehensive forecasted-return variable based on 193 predictors. Firms and short sellers tend to be the smart money—both sell stocks with low-forecasted returns, and their trades predict returns in the intended direction. Retail investors trade against forecasted returns. Retail investors’ and institutions’ trades predict returns opposite to the intended direction. This poor trading performance is driven by trades in stocks with either high- or low-forecasted returns. The forecasted-return variable predicts returns more strongly in stocks with more intense retail trading, consistent with retail investors exacerbating mispricing.
{"title":"Taking sides on return predictability","authors":"R. David McLean , Jeffrey Pontiff , Christopher Reilly","doi":"10.1016/j.jfineco.2025.104158","DOIUrl":"10.1016/j.jfineco.2025.104158","url":null,"abstract":"<div><div>We assess how nine different categories of market participants trade relative to a comprehensive forecasted-return variable based on 193 predictors. Firms and short sellers tend to be the smart money—both sell stocks with low-forecasted returns, and their trades predict returns in the intended direction. Retail investors trade against forecasted returns. Retail investors’ and institutions’ trades predict returns opposite to the intended direction. This poor trading performance is driven by trades in stocks with either high- or low-forecasted returns. The forecasted-return variable predicts returns more strongly in stocks with more intense retail trading, consistent with retail investors exacerbating mispricing.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"173 ","pages":"Article 104158"},"PeriodicalIF":10.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103962","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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