Nonstandard Errors
Copyright policy )10.1111/jofi.13337 , 10.2139/ssrn.3961574 , 10.17863/cam.93928 , 10.5445/ir/1000170594 , 10.26181/27041872.v1 , 10.5282/ubm/epub.94706
10230/70639 , 10045/142686 , 10486/719919 , 20.500.14342/5320 , https://repository.ubn.ru.nl/handle/2066/240328 , 10398/77ca5a90-df1a-450a-af4a-ed53c3307363 , 10398/7ba45f84-f517-4089-b4dd-711979b4e41d , 11245.1/d182d208-f5b3-4490-bf1b-9c7198890bfc , 1871.1/18d396ba-7200-46e4-9edd-5a6c36adbac5 , 2066/240328 , 2268/267437 , 10419/247267 , 10419/250153 , 10419/248998 , 10419/247663 , 10419/248784 , 11250/3180679 , 11562/1136448 , 10278/5061226 , 11577/3516584 , 11385/253204 , 11585/997683 , 1854/LU-01J1Q29832WBKEPDW15RQN9DXW , 10037/36386 , 2318/1934370 , 11343/351421
10.1111/jofi.13337 , 10.2139/ssrn.3961574 , 10.17863/cam.93928 , 10.5445/ir/1000170594 , 10.26181/27041872.v1 , 10.5282/ubm/epub.94706
10230/70639 , 10045/142686 , 10486/719919 , 20.500.14342/5320 , https://repository.ubn.ru.nl/handle/2066/240328 , 10398/77ca5a90-df1a-450a-af4a-ed53c3307363 , 10398/7ba45f84-f517-4089-b4dd-711979b4e41d , 11245.1/d182d208-f5b3-4490-bf1b-9c7198890bfc , 1871.1/18d396ba-7200-46e4-9edd-5a6c36adbac5 , 2066/240328 , 2268/267437 , 10419/247267 , 10419/250153 , 10419/248998 , 10419/247663 , 10419/248784 , 11250/3180679 , 11562/1136448 , 10278/5061226 , 11577/3516584 , 11385/253204 , 11585/997683 , 1854/LU-01J1Q29832WBKEPDW15RQN9DXW , 10037/36386 , 2318/1934370 , 11343/351421
Nonstandard Errors
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.
- London School of Economics and Political Science United Kingdom
- University of Gothenburg Sweden
- UNIVERSITE D'AIX MARSEILLE France
- University of Oxford United Kingdom
- Norges Bank Norway
502009 Corporate finance, Special economic topics (health, labor, transportation...), Economics, multi-analyst approach, 38 Economics, Applied economics, Social Sciences, Non-standard errors, 3801 Applied economics, Management Sciences and Quantitative Methods, CROSS-SECTION; ANALYSTS; RISK, økonomi, Domaines particuliers de l’économie (santé, travail, transport...), 502009 Finanzwirtschaft, 3801 Applied Economics, Business & Economics, 03 Salud y bienestar, G10, Statistischer Fehler, uncertainty, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Probability Theory and Statistics, B- ECONOMIE ET FINANCE, Sciences économiques & de gestion, C12, RISK, info:eu-repo/classification/ddc/330, experiment, ddc:330, Big Data Project, C18, G14, Finance, replication, non-standard errors, Statistics, 1502 Banking, Finance and Investment, Wirtschaftswissenschaften, research design, nonstandard errors, multi-analyst study, liquidity, [QFIN] Quantitative Finance [q-fin], Reproducibility, Evidence-generating process, Research design, Liquidity, Streuungsmaß, Open science, Institute for Management Research, CROSS-SECTION, Theorie, Economics and Econometrics, Wissenschaftler, 330, statistikk, Non-standard, Estadística, Banking, finance and investment, Economía, Business and Economics, VDP::Samfunnsvitenskap: 200::Økonomi: 210, Investigació -- Metodologia, Accounting, G1, Incertesa, FOS: Mathematics, errors, 3502 Banking, finance and investment, 502014 Innovationsforschung, Wissenschaftliche Methode, Business & economic sciences, liquidity, Finance and Financial Management, Nonstandard errors, nonstandard, errors, evidence-generating process, Business, Finance, Multi-analyst approach, FiWi, 502014 Innovation research, Probabilitats, 03 Good Health and Well-being, B26, ANALYSTS, non-standard errors, Data-generating process, Finance, jel: jel:C12, jel: jel:G14, jel: jel:G1, ddc: ddc:330
502009 Corporate finance, Special economic topics (health, labor, transportation...), Economics, multi-analyst approach, 38 Economics, Applied economics, Social Sciences, Non-standard errors, 3801 Applied economics, Management Sciences and Quantitative Methods, CROSS-SECTION; ANALYSTS; RISK, økonomi, Domaines particuliers de l’économie (santé, travail, transport...), 502009 Finanzwirtschaft, 3801 Applied Economics, Business & Economics, 03 Salud y bienestar, G10, Statistischer Fehler, uncertainty, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Probability Theory and Statistics, B- ECONOMIE ET FINANCE, Sciences économiques & de gestion, C12, RISK, info:eu-repo/classification/ddc/330, experiment, ddc:330, Big Data Project, C18, G14, Finance, replication, non-standard errors, Statistics, 1502 Banking, Finance and Investment, Wirtschaftswissenschaften, research design, nonstandard errors, multi-analyst study, liquidity, [QFIN] Quantitative Finance [q-fin], Reproducibility, Evidence-generating process, Research design, Liquidity, Streuungsmaß, Open science, Institute for Management Research, CROSS-SECTION, Theorie, Economics and Econometrics, Wissenschaftler, 330, statistikk, Non-standard, Estadística, Banking, finance and investment, Economía, Business and Economics, VDP::Samfunnsvitenskap: 200::Økonomi: 210, Investigació -- Metodologia, Accounting, G1, Incertesa, FOS: Mathematics, errors, 3502 Banking, finance and investment, 502014 Innovationsforschung, Wissenschaftliche Methode, Business & economic sciences, liquidity, Finance and Financial Management, Nonstandard errors, nonstandard, errors, evidence-generating process, Business, Finance, Multi-analyst approach, FiWi, 502014 Innovation research, Probabilitats, 03 Good Health and Well-being, B26, ANALYSTS, non-standard errors, Data-generating process, Finance, jel: jel:C12, jel: jel:G14, jel: jel:G1, ddc: ddc:330
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).75 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
Citations provided by BIP!Popularity provided by BIP!