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Mandatory Portfolio Disclosure, Stock Liquidity, and Mutual Fund Performance

Vikas Agarwal; Kevin Mullally; Yuehua Tang; Baozhong Yang
Journal of Finance 2015 70(6), 2733-2776
We examine the impact of mandatory portfolio disclosure by mutual funds on stock liquidity and fund performance. We develop a model of informed trading with disclosure and test its predictions using the May 2004 SEC regulation requiring more frequent disclosure. Stocks with higher fund ownership, especially those held by more informed funds or subject to greater information asymmetry, experience larger increases in liquidity after the regulation change. More informed funds, especially those holding stocks with greater information asymmetry, experience greater performance deterioration after the regulation change. Overall, mandatory disclosure improves stock liquidity but imposes costs on informed investors.

Organized Labor and Inventory Stockpiling

Sophia Hamm; Boochun Jung; Woo-Jong Lee; Daniel Yang
The Accounting Review 2022 97(2), 241-266
We document that managers stockpile excess inventory to mitigate the operational risk posed by labor unions and to maintain bargaining power in labor negotiations. Inventory levels are higher for union firms and are incrementally higher preceding the renegotiation of collective bargaining agreements with unions. Inventory stockpiling at union firms is more salient when capital market pressure for transparency or information spillover from peers constrains managers from using disclosure strategies. We further show that managers weigh the costs and benefits of inventory stockpiling, as holding excess inventory due to the presence of a union is negatively associated with future profitability, but provides the benefits of avoiding a stockout and mitigating negative outcomes from a strike. Our findings highlight the importance of a major stakeholder, i.e., labor, in managers' investment decision making. Data Availability: All data are available from the public/private sources cited in the text.

What If Borrowers Were Informed about Credit Reporting? Two Natural Field Experiments

Li Liao; Xiumin Martin; Ni Wang; Zhengwei Wang; Jun Yang
The Accounting Review 2023 98(3), 397-425
Using two natural field experiments, we examine how warning individual retail borrowers that their loan performance will be reported to a public credit registry before and after the loan take-up affects their borrowing behavior. We show that credit warnings reduce default rates by 3.7 to 7 percentage points and increase loan take-up rates by 4.1 percentage points, which suggests that credit warnings benefit both lenders and borrowers. The main drivers appear to be borrowers’ anticipation of a reduction in lenders’ informational rents and improved repayment incentives. Moreover, the reduction in default rates is comparable for borrowers who receive the credit warning before and after the loan take-up. As credit warnings received before but not after a loan take-up can affect the borrower pool, and thus the overall credit risk of the pool, the results suggest that credit warnings have little net effect on the pool’s credit risk due to selection.

Earnings Performance Targets in Annual Incentive Plans and Management Earnings Guidance

Xiumin Martin; Hojun Seo; Jun Yang; Daniel Sungyeon Kim; Jordan Martel
The Accounting Review 2023 98(4), 289-319
We study how corporate boards set earnings performance targets in CEOs’ annual incentive plans (AIPs) and the implications for strategic management earning guidance. We find that corporate boards rely on management and analyst information in setting the earnings performance targets, and the weight placed on each signal increases with its precision. We also find that management earnings guidance issued before compensation committee meetings (“event-window management forecast (MF)”) is more pessimistic than that issued by the same firm at other times. The pessimism in the event-window MF is more pronounced when the expected managerial benefits of having lower performance targets are greater. Ex post, the event-window MF pessimism is associated with higher bonus payouts to CEOs. We use a theoretical framework to illustrate how the use of earnings performance targets might drive our findings. This study highlights boards’ tradeoffs in designing executive compensation and the resulting managerial strategic disclosure.

Do Credit Ratings Reflect Private Information about SEC Investigations?

Samuel B. Bonsall; John Donovan; Eric Holzman; Xue Wang; Daniel Yang
The Accounting Review 2025 100(2), 21-44
Despite private access to managers, issuer-paid credit rating agencies (CRAs) are often criticized for failing to promptly reflect material negative private information in their ratings and being ineffective corporate watchdogs. We utilize a novel dataset of private SEC investigations to examine the timeliness and informativeness of CRAs’ rating adjustments in response to material negative private information. Our evidence suggests that CRAs adjust ratings downward within a quarter following the opening of an SEC investigation. Moreover, these adjustments are over three times larger for those investigations that ultimately yield an enforcement action than for those that do not, suggesting that CRAs quickly form sophisticated expectations about the materiality of the private information. Additionally, rating downgrades during the investigations are more informative to the stock market than other rating downgrades. Overall, our evidence suggests that CRAs reduce information asymmetry in the capital markets by timely incorporating material private information in their ratings. Data Availability: All data are available from the sources cited in the text.

Curriculum and Ideology

Davide Cantoni; Yuyu Chen; David Y. Yang; Noam Yuchtman; Y. Jane Zhang
Journal of Political Economy 2017 125(2), 338-392 open access
We study the causal effect of school curricula on students? political attitudes, exploiting a major textbook reform in China between 2004 and 2010. The sharp, staggered introduction of the new curriculum across provinces allows us to identify its causal effects. We examine government documents articulating desired consequences of the reform and identify changes in textbooks reflecting these aims. A survey we conducted reveals that the reform was often successful in shaping attitudes, while evidence on behavior is mixed. Studying the new curriculum led to more positive views of China?s governance, changed views on democracy, and increased skepticism toward free markets.

What Is the Active Prevalence of COVID-19?

Mu-Jeung Yang; Marinho Bertanha; Nathan Seegert; Maclean Gaulin; Adam Looney; Brian Orleans; Andrew T. Pavia; Kristina Stratford; Matthew H. Samore; Steven Alder
The Review of Economics and Statistics 2025 107(1), 279-288
We provide a method to track the active prevalence of COVID-19 in real time, correcting for time-varying sample selection in symptom-based testing data and incomplete tracking of recovered cases and fatalities. Our method only requires publicly available data on positive testing rates in combination with one parameter, which we estimate based on a representative randomized sample of nearly 10,000 individuals tested in Utah in May and June 2020. We validate our method using external studies in Indiana in April 2020 and two counties in Utah in March 2021. In all three locations and times, our estimates of latent prevalence are within the 95 percent confidence intervals of prevalence estimates from randomized testing. Applying our method to all 50 states, we show that true prevalence is 2–3 times higher than publicly reported.

Nonstandard Errors

Albert J. Menkveld; Anna Dreber; Felix Holzmeister; Jürgen Huber; Magnus Johannesson; Michael Kirchler; SEBASTIAN NEUSÜß; Michael Razen; Utz Weitzel; DAVID ABAD-DÍAZ; Menachem Abudy; Tobias Adrian; Yacine Aït-Sahalia; Olivier Akmansoy; Jamie Alcock; Vitali Alexeev; Arash Aloosh; LIVIA AMATO; Diego Amaya; James J. Angel; ALEJANDRO T. AVETIKIAN; AMADEUS BACH; EDWIN BAIDOO; GAETAN BAKALLI; LI BAO; Andrea Barbon; OKSANA BASHCHENKO; Parampreet Christopher Bindra; Geir Høidal Bjønnes; Jeffrey R. Black; Bernard S. Black; DIMITAR BOGOEV; SANTIAGO BOHORQUEZ CORREA; Oleg Bondarenko; CHARLES S. BOS; Ciril Bosch-Rosa; ELIE BOURI; Christian T. Brownlees; ANNA CALAMIA; Viet Nga Cao; Gunther Capelle-Blancard; LAURA M. CAPERA ROMERO; Massimiliano Caporin; Allen Carrion; TOLGA CASKURLU; Bidisha Chakrabarty; Jian Chen; Mikhail Chernov; WILLIAM CHEUNG; LUDWIG B. CHINCARINI; Tarun Chordia; SHEUNG-CHI CHOW; BENJAMIN CLAPHAM; Jean-Edouard Colliard; Carole Comerton-Forde; EDWARD CURRAN; THONG DAO; WALE DARE; Ryan J. Davies; RICCARDO DE BLASIS; GIANLUCA F. DE NARD; Fany Declerck; OLEG DEEV; Hans Degryse; SOLOMON Y. DEKU; CHRISTOPHE DESAGRE; Mathijs A. van Dijk; Chukwuma Dim; Thomas Dimpfl; YUN JIANG DONG; PHILIP A. DRUMMOND; Tom L. Dudda; TEODOR DUEVSKI; Ariadna Dumitrescu; Teodor Dyakov; Anne Haubo Dyhrberg; Michał Dzieliński; ASLI EKSI; Izidin El Kalak; Saskia ter Ellen; Nicolas Eugster; Martin D. D. Evans; Michael Farrell; ESTER FELEZ-VINAS; Gerardo Ferrara; EL MEHDI FERROUHI; Andrea Flori; JONATHAN T. FLUHARTY-JAIDEE; Sean Foley; Kingsley Y. L. Fong; Thierry Foucault; TATIANA FRANUS; Francesco A. Franzoni; Bart Frijns; MICHAEL FRÖMMEL; SERVANNA M. FU; Sascha Füllbrunn; BAOQING GAN; GE GAO; Thomas Gehrig; ROLAND GEMAYEL; DIRK GERRITSEN; Javier Gil-Bazo; Dudley Gilder; Lawrence R. Glosten; THOMAS GOMEZ; Arseny Gorbenko; Joachim Grammig; Vincent Grégoire; Ufuk Güçbilmez; Björn Hagströmer; JULIEN HAMBUCKERS; ERIK HAPNES; Jeffrey H. Harris; Lawrence Harris; SIMON HARTMANN; JEAN-BAPTISTE HASSE; Nikolaus Hautsch; XUE-ZHONG (TONY) HE; Davidson Heath; SIMON HEDIGER; Terrence Hendershott; Ann Marie Hibbert; Erik Hjalmarsson; Seth A. Hoelscher; Peter Hoffmann; Craig W. Holden; Alex R. Horenstein; Wenqian Huang; DA HUANG; Christophe Hurlin; KONRAD ILCZUK; ALEXEY IVASHCHENKO; Subramanian R. Iyer; Hossein Jahanshahloo; NAJI JALKH; Charles M. Jones; SIMON JURKATIS; Petri Jylhä; ANDREAS T. KAECK; GABRIEL KAISER; ARZÉ KARAM; Egle Karmaziene; BERNHARD KASSNER; Markku Kaustia; EKATERINA KAZAK; Fearghal Kearney; Vincent van Kervel; SAAD A. KHAN; MARTA K. KHOMYN; Tony Klein; OLGA KLEIN; Alexander Klos; Michael Koetter; Aleksey Kolokolov; Robert A. Korajczyk; Roman Kozhan; Jan P. Krahnen; PAUL KUHLE; Amy Kwan; QUENTIN LAJAUNIE; F. Y. Eric C. Lam; Marie Lambert; Hugues Langlois; JENS LAUSEN; Tobias Lauter; Markus Leippold; VLADIMIR LEVIN; YIJIE LI; HUI LI; CHEE YOONG LIEW; THOMAS LINDNER; Oliver Linton; JIACHENG LIU; Anqi Liu; Guillermo Llorente; Matthijs Lof; ARIEL LOHR; FRANCIS LONGSTAFF; Alejandro Lopez-Lira; Shawn Mankad; NICOLA MANO; ALEXIS MARCHAL; Charles Martineau; Francesco Mazzola; Debrah Meloso; MICHAEL G. MI; Roxana Mihet; Vijay Mohan; Sophie Moinas; DAVID MOORE; Liangyi Mu; Dmitriy Muravyev; Dermot Murphy; GABOR NESZVEDA; CHRISTIAN NEUMEIER; Ulf Nielsson; Mahendrarajah Nimalendran; Sven Nolte; LARS L. NORDEN; Peter O’Neill; Khaled Obaid; BERNT A. ØDEGAARD; Per Östberg; EMILIANO PAGNOTTA; Marcus Painter; Stefan Palan; IMON J. PALIT; Andreas Park; Roberto Pascual; Paolo Pasquariello; Ľuboš Pástor; VINAY PA℡; Andrew J. Patton; Neil D. Pearson; Loriana Pelizzon; MICHELE PELLI; Matthias Pelster; Christophe Pérignon; CAMERON PFIFFER; Richard Philip; TOMÁŠ PLÍHAL; PUNEET PRAKASH; OLIVER-ALEXANDER PRESS; TINA PRODROMOU; Marcel Prokopczuk; Talis Putnins; YA QIAN; GAURAV RAIZADA; David Rakowski; Angelo Ranaldo; Luca Regis; Stefan Reitz; Thomas Renault; REX W. RENJIE; Roberto Renò; Steven J. Riddiough; Kalle Rinne; PAUL RINTAMÄKI; Ryan Riordan; THOMAS RITTMANNSBERGER; IÑAKI RODRÍGUEZ LONGARELA; Dominik Roesch; LAVINIA ROGNONE; Brian Roseman; Ioanid Roşu; Saurabh Roy; NICOLAS RUDOLF; STEPHEN R. RUSH; Khaladdin Rzayev; ALEKSANDRA A. RZEŹNIK; Anthony Sanford; Harikumar Sankaran; Asani Sarkar; Lucio Sarno; Olivier Scaillet; STEFAN SCHARNOWSKI; KLAUS R. SCHENK-HOPPÉ; ANDREA SCHERTLER; MICHAEL SCHNEIDER; FLORIAN SCHROEDER; Norman Schürhoff; Philipp Schuster; MARCO A. SCHWARZ; Mark S. Seasholes; Norman J. Seeger; Or Shachar; Andriy Shkilko; JESSICA SHUI; MARIO SIKIC; Giorgia Simion; Lee A. Smales; Paul Söderlind; Elvira Sojli; Konstantin Sokolov; JANTJE SÖNKSEN; Laima Spokeviciute; Denitsa Stefanova; Marti G. Subrahmanyam; BARNABAS SZASZI; Oleksandr Talavera; Yuehua Tang; Nick Taylor; Wing Wah Tham; Erik Theissen; Julian Thimme; Ian Tonks; Hai Tran; Luca Trapin; Anders B. Trolle; M. ANDREEA VADUVA; Giorgio Valente; Robert A. Van Ness; Aurelio Vasquez; Thanos Verousis; Patrick Verwijmeren; ANDERS VILHELMSSON; Grigory Vilkov; Vladimir Vladimirov; SEBASTIAN VOGEL; Stefan Voigt; Wolf Wagner; THOMAS WALTHER; Patrick Weiss; Michel van der Wel; Ingrid M. Werner; P. Joakim Westerholm; Christian Westheide; HANS C. WIKA; Evert Wipplinger; Michael Wolf; Christian C. P. Wolff; LEONARD WOLK; WING-KEUNG WONG; Jan Wrampelmeyer; Zhen-Xing Wu; Shuo Xia; Dacheng Xiu; KE XU; CAIHONG XU; Pradeep K. Yadav; JOSÉ YAGÜE; Cheng Yan; Antti Yang; Woongsun Yoo; WENJIA YU; YIHE YU; Shihao Yu; Bart Z. Yueshen; Darya Yuferova; MARCIN ZAMOJSKI; Abalfazl Zareei; STEFAN M. ZEISBERGER; LU ZHANG; S. Sarah Zhang; Xiaoyu Zhang; LU ZHAO; Zhuo Zhong; Z. IVY ZHOU; CHEN ZHOU; XINGYU S. ZHU; Marius Zoican; REMCO ZWINKELS
Journal of Finance 2024 79(3), 2339-2390 open access
In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.