The Power of Bias in Economics Research
John P. A. Ioannidis,
T. D. Stanley and
Chris Doucouliagos ()
Economic Journal, 2017, vol. 127, issue 605, F236-F265
We investigate two critical dimensions of the credibility of empirical economics research: statistical power and bias. We survey 159 empirical economics literatures that draw upon 64,076 estimates of economic parameters reported in more than 6,700 empirical studies. Half of the research areas have nearly 90% of their results underâ€ powered. The median statistical power is 18%, or less. A simple weighted average of those reported results that are adequately powered (powerÂ â‰¥Â 80%) reveals that nearly 80% of the reported effects in these empirical economics literatures are exaggerated; typically, by a factor of two and with oneâ€ third inflated by a factor of four or more.
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:wly:econjl:v:127:y:2017:i:605:p:f236-f265
Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1468-0297
Access Statistics for this article
Economic Journal is currently edited by Estelle Cantillon, Martin Cripps, Andrea Galeotti, Morten Ravn, Kjell G. Salvanes, Frederic Vermeulen, Hans-Joachim Voth and Rachel Kranton
More articles in Economic Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().