Nonstandard Errors

MENKVELD, AJ DREBER, A HOLZMEISTER, F HUBER, J JOHANNESSON, M KIRCHLER, M NEUSÜß, S RAZEN, M WEITZEL, U ABAD‐DÍAZ, D ABUDY, M MANO, N MARCHAL, A MARTINEAU, C MAZZOLA, F MELOSO, D MI, MG MIHET, R MOHAN, V MOINAS, S ANGEL, JJ GEMAYEL, R MOORE, D MU, L MURAVYEV, D MURPHY, D NESZVEDA, G NEUMEIER, C NIELSSON, U NIMALENDRAN, M NOLTE, S NORDEN, LL GERRITSEN, D AVETIKIAN, AT O'NEILL, P OBAID, K ØDEGAARD, BA ÖSTBERG, P PAGNOTTA, E PAINTER, M PALAN, S PALIT, IJ PARK, A GIL‐BAZO, J PASCUAL, R BACH, A PASQUARIELLO, P PASTOR, L PATEL, V PATTON, AJ PEARSON, ND PELIZZON, L PELLI, M PELSTER, M GILDER, D PÉRIGNON, C PFIFFER, C BAIDOO, E PHILIP, R PLÍHAL, T PRAKASH, P PRESS, O PRODROMOU, T PROKOPCZUK, M PUTNINS, T GLOSTEN, LR QIAN, Y RAIZADA, G RAKOWSKI, D BAKALLI, G RANALDO, A REGIS, L REITZ, S RENAULT, T RENJIE, RW RENO, R GOMEZ, T RIDDIOUGH, SJ RINNE, K RINTAMÄKI, P RIORDAN, R BAO, L RITTMANNSBERGER, T LONGARELA, IR ROESCH, D ROGNONE, L ROSEMAN, B GORBENKO, A ROŞU, I ROY, S RUDOLF, N RUSH, SR RZAYEV, K BARBON, A RZEŹNIK, AA SANFORD, A SANKARAN, H SARKAR, A GRAMMIG, J SARNO, L SCAILLET, O SCHARNOWSKI, S SCHENK‐HOPPÉ, KR SCHERTLER, A SCHNEIDER, M BASHCHENKO, O SCHROEDER, F SCHÜRHOFF, N SCHUSTER, P GRÉGOIRE, V SCHWARZ, MA SEASHOLES, MS SEEGER, NJ SHACHAR, O SHKILKO, A SHUI, J SIKIC, M BINDRA, PC SIMION, G SMALES, LA GÜÇBILMEZ, U SÖDERLIND, P SOJLI, E SOKOLOV, K SÖNKSEN, J SPOKEVICIUTE, L STEFANOVA, D SUBRAHMANYAM, MG SZASZI, B BJØNNES, GH TALAVERA, O ADRIAN, T TANG, Y TAYLOR, N THAM, W THEISSEN, E THIMME, J TONKS, I TRAN, H TRAPIN, L TROLLE, AB BLACK, JR HAGSTRÖMER, B VADUVA, MA VALENTE, G VAN NESS, RA VASQUEZ, A VEROUSIS, T VERWIJMEREN, P VILHELMSSON, A VILKOV, G VLADIMIROV, V VOGEL, S HAMBUCKERS, J BLACK, BS VOIGT, S WAGNER, W WALTHER, T WEISS, P VAN DER WEL, M WERNER, IM WESTERHOLM, PJ WESTHEIDE, C WIKA, HC HAPNES, E WIPPLINGER, E BOGOEV, D WOLF, M WOLFF, CCP WOLK, L WONG, W WRAMPELMEYER, J WU, Z XIA, S XIU, D HARRIS, JH XU, K XU, C CORREA, SB YADAV, PK YAGÜE, J YAN, C YANG, A YOO, W YU, W YU, Y HARRIS, L YU, S YUESHEN, BZ YUFEROVA, D BONDARENKO, O ZAMOJSKI, M ZAREEI, A ZEISBERGER, SM ZHANG, L ZHANG, SS ZHANG, X HARTMANN, S ZHAO, L ZHONG, Z ZHOU, ZI ZHOU, C BOS, CS ZHU, XS ZOICAN, M ZWINKELS, R BOSCH‐ROSA, C BOURI, E HASSE, J BROWNLEES, C CALAMIA, A CAO, VN CAPELLE‐BLANCARD, G ROMERO, LMC CAPORIN, M CARRION, A CASKURLU, T CHAKRABARTY, B CHEN, J HAUTSCH, N CHERNOV, M CHEUNG, W CHINCARINI, LB CHORDIA, T CHOW, S CLAPHAM, B COLLIARD, J COMERTON‐FORDE, C CURRAN, E DAO, T HE, X DARE, W DAVIES, RJ DE BLASIS, R DE NARD, GF DECLERCK, F DEEV, O DEGRYSE, H DEKU, SY DESAGRE, C VAN DIJK, MA HEATH, D DIM, C DIMPFL, T DONG, YJ DRUMMOND, PA DUDDA, T DUEVSKI, T DUMITRESCU, A DYAKOV, T DYHRBERG, AH DZIELIŃSKI, M AIT‐SAHALIA, Y EKSI, A KALAK, IE ELLEN, ST EUGSTER, N EVANS, MDD FARRELL, M FELEZ‐VINAS, E FERRARA, G FERROUHI, EM FLORI, A HEDIGER, S FLUHARTY‐JAIDEE, JT FOLEY, SDV FONG, KYL FOUCAULT, T FRANUS, T FRANZONI, F FRIJNS, B FRÖMMEL, M FU, SM FÜLLBRUNN, SC HENDERSHOTT, T GAN, B GAO, G GEHRIG, TP HIBBERT, AM HJALMARSSON, E HOELSCHER, SA HOFFMANN, P HOLDEN, CW HORENSTEIN, AR HUANG, W HUANG, D AKMANSOY, O HURLIN, C ILCZUK, K IVASHCHENKO, A IYER, SR JAHANSHAHLOO, H JALKH, N JONES, CM JURKATIS, S JYLHÄ, P KAECK, AT ALCOCK, JT KAISER, G KARAM, A KARMAZIENE, E KASSNER, B KAUSTIA, M KAZAK, E KEARNEY, F VAN KERVEL, V KHAN, SA KHOMYN, MK ALEXEEV, V KLEIN, T KLEIN, O KLOS, A KOETTER, M KOLOKOLOV, A KORAJCZYK, RA KOZHAN, R KRAHNEN, JP KUHLE, P KWAN, A ALOOSH, A LAJAUNIE, Q LAM, FYEC LAMBERT, M LANGLOIS, H LAUSEN, J LAUTER, T LEIPPOLD, M LEVIN, V LI, Y LI, H AMATO, L LIEW, CY LINDNER, T LINTON, O LIU, J LIU, A LLORENTE, G LOF, M LOHR, A LONGSTAFF, F LOPEZ‐LIRA, A AMAYA, D MANKAD, S
Publisher:
Wiley
Publication Type:
Journal Article
Citation:
The Journal of Finance, 2024, 79, (3), pp. 2339-2390
Issue Date:
2024-06
Full metadata record
ABSTRACTIn 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.
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