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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

Abstract: 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 under†powered. The median statistical power is 18%, or less. A simple weighted average of those reported results that are adequately powered (power ≥ 80%) reveals that nearly 80% of the reported effects in these empirical economics literatures are exaggerated; typically, by a factor of two and with one†third inflated by a factor of four or more.

Date: 2017
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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

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