The Journal of Finance

The Allocation of Capital Between Residential and Nonresidential Uses: Taxes, Inflation and Capital Market Constraints

Published: 6/1983,  Volume: 38,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1983.tb02502.x  |  Cited by: 13

PATRIC H. HENDERSHOTT, SHENG CHENG HU

We have constructed a simple two‐sector model of the demand for housing and corporate capital. Economic growth and an increase in the inflation rate were then simulated with a number of model variants. The model and simulation experiments illustrate both the tax bias in favor of housing and the manner in which the increase in inflation between 1965 and 1978 magnified it. The existence of capital‐market constraints offsets the bias against corporate capital, but it introduces a sharp, inefficient reallocation of housing from less wealthy, constrained households to wealthy households who do not have gains on mortgages and are not financially constrained.

Exploiting the Conditional Density in Estimating the Term Structure: An Application to the Cox, Ingersoll, and Ross Model

Published: 9/1994,  Volume: 49,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1994.tb02454.x  |  Cited by: 304

NEIL D. PEARSON, TONG‐SHENG SUN

We propose an empirical method that utilizes the conditional density of the state variables to estimate and test a term structure model with known price formulae, using data on both discount and coupon bonds. The method is applied to an extension of a two‐factor model due to Cox, Ingersoll, and Ross (1985; CIR). Our results show that estimates based on only bills imply unreasonably large price errors for longer maturities. We reject the original CIR model using a likelihood ratio test, and conclude that the extended CIR model also fails to provide a good description of the Treasury market.

FUNCTIONAL FORM AND THE DIVIDEND EFFECT IN THE ELECTRIC UTILITY INDUSTRY

Published: 12/1976,  Volume: 31,  Issue: 5  |  DOI: 10.1111/j.1540-6261.1976.tb03226.x  |  Cited by: 15

Cheng F. Lee

A NOTE ON THE PROGRESSIVE CONSUMPTION TAX

Published: 9/1953,  Volume: 8,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1953.tb01173.x  |  Cited by: 0

Pao Lun Cheng

ERRORS‐IN‐VARIABLES ESTIMATION PROCEDURES WITH APPLICATIONS TO A CAPITAL ASSET PRICING MODEL*

Published: 9/1974,  Volume: 29,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1974.tb03114.x  |  Cited by: 0

Cheng‐few Lee

DURABILITY OF CONSUMER GOODS AND BUSINESS INSTABILITY*

Published: 12/1956,  Volume: 11,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1956.tb04089.x  |  Cited by: 0

Fao Lun Cheng

Persuading Investors: A Video‐Based Study

Published: 8/14/2025,  Volume: 80,  Issue: 5  |  DOI: 10.1111/jofi.13471  |  Cited by: 31

ALLEN HU, SONG MA

Persuasive communication functions through not only content but also delivery—facial expression, tone of voice, and diction. This paper examines the persuasiveness of delivery in startup pitches. Using machine learning algorithms to process full pitch videos, we quantify persuasion in visual, vocal, and verbal dimensions. We find that positive (i.e., passionate, warm) pitches increase funding probability. However, conditional on funding, startups with higher levels of pitch positivity underperform. Women are more heavily judged on delivery when evaluated in single‐gender teams, but they are neglected when copitching in mixed‐gender teams. Using an experiment, we show that persuasion delivery works mainly through leading investors to form inaccurate beliefs.

A Theory of Zombie Lending

Published: 4/26/2021,  Volume: 76,  Issue: 4  |  DOI: 10.1111/jofi.13022  |  Cited by: 91

YUNZHI HU, FELIPE VARAS

An entrepreneur borrows from a relationship bank or the market. The bank has a higher cost of capital but produces private information over time. While the entrepreneur accumulates reputation as the lending relationship continues, asymmetric information is also developed between the bank/entrepreneur and the market. In this setting, zombie lending is inevitable: Once the entrepreneur becomes sufficiently reputable, the bank will roll over loans even after learning bad news, for the prospect of future market financing. Zombie lending is mitigated when the entrepreneur faces financial constraints. Finally, the bank stops producing information too early if information production is costly.

AN INTER‐TEMPROAL APPROACH TO THE OPTIMIZATION OF DIVIDEND POLICY WITH PRE‐DETERMINED INVESTMENT: A FURTHER COMMENT

Published: 9/1977,  Volume: 32,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1977.tb03336.x  |  Cited by: 0

Cheng F. Lee, Manak Gupta

REPLY

Published: 3/1976,  Volume: 31,  Issue: 1  |  DOI: 10.1111/j.1540-6261.1976.tb03208.x  |  Cited by: 0

Pao L. Cheng, M. King Deets

BLOCK RECURSIVE SYSTEMS IN ASSET PRICING MODELS: AN EXTENSION

Published: 5/1978,  Volume: 33,  Issue: 2  |  DOI: 10.1111/j.1540-6261.1978.tb04874.x  |  Cited by: 1

Cheng F. Lee, William P. Lloyd

Expectations, Tobin's q, and Investment: A Note

Published: 3/1982,  Volume: 37,  Issue: 1  |  DOI: 10.1111/j.1540-6261.1982.tb01106.x  |  Cited by: 14

HENRY W. CHAPPELL, DAVID C. CHENG

A CONTRIBUTION TO THE THEORY OF CAPITAL BUDGETING—THE MULTI‐INVESTMENT CASE*

Published: 12/1963,  Volume: 18,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1963.tb01636.x  |  Cited by: 0

Pao L. Cheng, John P. Shelton

BLOCK RECURSIVE SYSTEMS IN ASSET PRICING MODELS

Published: 9/1976,  Volume: 31,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1976.tb01962.x  |  Cited by: 7

William P. Lloyd, Cheng F. Lee

TEST OF PORTFOLIO BUILDING RULES: COMMENT

Published: 9/1971,  Volume: 26,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1971.tb00935.x  |  Cited by: 1

Pao L. Cheng, M. King Deets

REPLY

Published: 12/1964,  Volume: 19,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1964.tb02894.x  |  Cited by: 1

Pao L. Cheng, John P. Shelton

REPLY

Published: 6/1973,  Volume: 28,  Issue: 3  |  DOI: 10.1111/j.1540-6261.1973.tb01394.x  |  Cited by: 1

Pao L. Cheng, M. King Deets

PORTFOLIO RETURNS AND THE RANDOM WALK THEORY

Published: 3/1971,  Volume: 26,  Issue: 1  |  DOI: 10.1111/j.1540-6261.1971.tb00585.x  |  Cited by: 26

Pao L. Cheng, M. King Deets

Continuous Maturity Diversification of Default‐Free Bond Portfolios and a Generalization of Efficient Diversification

Published: 9/1984,  Volume: 39,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1984.tb03895.x  |  Cited by: 5

W. JOHN HEANEY, PAO L. CHENG

This paper presents a method for solving the mean‐variance portfolio selection problem that is applicable to the case where the number of securities is nondenumerably infinite. Necessary conditions for the existence of an optimal portfolio density are obtained and an expression for the efficient frontier is derived. The conditions for the existence of an optimal portfolio of continuously maturing bonds when their covariance matrix is singular are used to derive an arbitrage‐free bond pricing equation. A method for estimating the covariance matrix and the associated efficient frontier is presented.

A Re‐Examination of the Market Reaction to Failed Mergers

Published: 9/1989,  Volume: 44,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1989.tb02640.x  |  Cited by: 35

WALLACE N. DAVIDSON, DIPA DUTIA, LOUIS CHENG

This study examines the revaluation of shares surrounding the cancellation of mergers over the years 1976–1985. The results are first categorized according to the party cancelling the merger and then by subsequent merger activity. The results are as expected: target firms that become involved in merger activity, subsequent to the cancellation, experience positive cumulative prediction errors (CPEs). Targets that do not become involved in subsequent merger activity have CPEs that return to pre‐merger announcement levels. These results do not vary when bidders or targets cancel the merger.

The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks

Published: 3/2/2005,  Volume: 60,  Issue: 2  |  DOI: 10.1111/j.1540-6261.2005.00742.x  |  Cited by: 580

JOHN H. BOYD, JIAN HU, RAVI JAGANNATHAN

We find that on average, an announcement of rising unemployment is good news for stocks during economic expansions and bad news during economic contractions. Unemployment news bundles three types of primitive information relevant for valuing stocks: information about future interest rates, the equity risk premium, and corporate earnings and dividends. The nature of the information bundle, and hence the relative importance of the three effects, changes over time depending on the state of the economy. For stocks as a group, information about interest rates dominates during expansions and information about future corporate dividends dominates during contractions.

Noise as Information for Illiquidity

Published: 11/12/2013,  Volume: 68,  Issue: 6  |  DOI: 10.1111/jofi.12083  |  Cited by: 412

GRACE XING HU, JUN PAN, JIANG WANG

We propose a market‐wide liquidity measure by exploiting the connection between the amount of arbitrage capital in the market and observed “noise” in U.S. Treasury bonds—the shortage of arbitrage capital allows yields to deviate more freely from the curve, resulting in more noise in prices. Our noise measure captures episodes of liquidity crises of different origins across the financial market, providing information beyond existing liquidity proxies. Moreover, as a priced risk factor, it helps to explain cross‐sectional returns on hedge funds and currency carry trades, both known to be sensitive to the general liquidity conditions of the market.

FinTech Credit and Entrepreneurial Growth

Published: 8/30/2024,  Volume: 79,  Issue: 5  |  DOI: 10.1111/jofi.13384  |  Cited by: 74

HARALD HAU, YI HUANG, CHEN LIN, HONGZHE SHAN, ZIXIA SHENG, LAI WEI

Based on automated credit lines to vendors trading on Alibaba's online retail platform and a discontinuity in the credit decision algorithm, we document that a vendor's access to FinTech credit boosts its sales growth, transaction growth, and the level of customer satisfaction gauged by product, service, and consignment ratings. These effects are more pronounced for vendors characterized by greater information asymmetry about their credit risk and less collateral, which reveals the information advantage of FinTech credit over traditional credit technology.

Short‐Sales Constraints and Price Discovery: Evidence from the Hong Kong Market

Published: 9/4/2007,  Volume: 62,  Issue: 5  |  DOI: 10.1111/j.1540-6261.2007.01270.x  |  Cited by: 373

ERIC C. CHANG, JOSEPH W. CHENG, YINGHUI YU

Short‐sales practices in the Hong Kong stock market are unique in that only stocks on a list of designated securities can be sold short. By analyzing the price effects following the addition of individual stocks to the list, we find that short‐sales constraints tend to cause stock overvaluation and that the overvaluation effect is more dramatic for individual stocks for which wider dispersion of investor opinions exists. These findings are consistent with Miller's (1977) intuition and other optimism models. We also document higher volatility and less positive skewness of individual stock returns when short sales are allowed.

Yesterday's Heroes: Compensation and Risk at Financial Firms

Published: 3/12/2015,  Volume: 70,  Issue: 2  |  DOI: 10.1111/jofi.12225  |  Cited by: 235

ING‐HAW CHENG, HARRISON HONG, JOSÉ A. SCHEINKMAN

Many believe that compensation, misaligned from shareholders’ value due to managerial entrenchment, caused financial firms to take risks before the financial crisis of 2008. We argue that, even in a classical principal‐agent setting without entrenchment and with exogenous firm risk, riskier firms may offer higher total pay as compensation for the extra risk in equity stakes borne by risk‐averse managers. Using long lags of stock price risk to capture exogenous firm risk, we confirm our conjecture and show that riskier firms are also more productive and more likely to be held by institutional investors, who are most able to influence compensation.

Integrating Factor Models

Published: 4/4/2023,  Volume: 78,  Issue: 3  |  DOI: 10.1111/jofi.13226  |  Cited by: 35

DORON AVRAMOV, SI CHENG, LIOR METZKER, STEFAN VOIGT

This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on a composite model that integrates over competing factor models weighted by posterior probabilities. Evidence shows that unconditional models record near‐zero probabilities, while postearnings announcement drift, quality‐minus‐junk, and intermediary capital are potent factors in conditional asset pricing. Out‐of‐sample, the integrated model performs well, tilting away from subsequently underperforming factors. Model uncertainty makes equities appear considerably riskier, while model disagreement about expected returns spikes during crash episodes. Disagreement spans all return components involving mispricing, factor loadings, and risk premia.

Pledgeability, Industry Liquidity, and Financing Cycles

Published: 7/26/2019,  Volume: 75,  Issue: 1  |  DOI: 10.1111/jofi.12831  |  Cited by: 34

DOUGLAS W. DIAMOND, YUNZHI HU, RAGHURAM G. RAJAN

Why do firms choose high debt when they anticipate high valuations, and underperform subsequently? We propose a theory of financing cycles where the importance of creditors’ control rights over cash flows (“pledgeability”) varies with industry liquidity. The market allows firms take on more debt when they anticipate higher future liquidity. However, both high anticipated liquidity and the resulting high debt limit their incentives to enhance pledgeability. This has prolonged adverse effects in a downturn. Because these effects are hard to contract upon, higher anticipated liquidity can also reduce a firm's current access to finance.

Testing Disagreement Models

Published: 6/8/2022,  Volume: 77,  Issue: 4  |  DOI: 10.1111/jofi.13137  |  Cited by: 105

YEN‐CHENG CHANG, PEI‐JIE HSIAO, ALEXANDER LJUNGQVIST, KEVIN TSENG

We provide plausibly identified evidence for the role of investor disagreement in asset pricing. Our natural experiment exploits the staggered implementation of the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system, which induces a reduction in investor disagreement. Consistent with models of investor disagreement, EDGAR inclusion helps resolve disagreement around information events, leading to stock price corrections. The reduction in disagreement following EDGAR inclusion also reduces stock price crash risk, especially among stocks with binding short‐sale constraints and high investor optimism.

Nonstandard Errors

Published: 4/17/2024,  Volume: 79,  Issue: 3  |  DOI: 10.1111/jofi.13337  |  Cited by: 112

ALBERT J. MENKVELD, ANNA DREBER, FELIX HOLZMEISTER, JUERGEN HUBER, MAGNUS JOHANNESSON, MICHAEL KIRCHLER, SEBASTIAN NEUSÜß, MICHAEL RAZEN, UTZ WEITZEL, DAVID ABAD‐DÍAZ, MENACHEM (MENI) ABUDY, TOBIAS ADRIAN, YACINE AIT‐SAHALIA, OLIVIER AKMANSOY, JAMIE T. 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 C. BINDRA, GEIR H. BJØNNES, JEFFREY R. BLACK, BERNARD S. BLACK, DIMITAR BOGOEV, SANTIAGO BOHORQUEZ CORREA, OLEG BONDARENKO, CHARLES S. BOS, CIRIL BOSCH‐ROSA, ELIE BOURI, CHRISTIAN 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 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 D. V. FOLEY, KINGSLEY Y. L. FONG, THIERRY FOUCAULT, TATIANA FRANUS, FRANCESCO FRANZONI, BART FRIJNS, MICHAEL FRÖMMEL, SERVANNA M. FU, SASCHA C. FÜLLBRUNN, BAOQING GAN, GE GAO, THOMAS P. 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, LUBOS PASTOR, VINAY PATEL, 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 RENO, 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

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.