The cult of statistical significance. What economists should and should not do to make their data talk
This article takes issue with a recent book by Ziliak and McCloskey (2008) of the same title. Ziliak and McCloskey argue that statistical significance testing is a barrier rather than a booster for empirical research in economics and should therefore be abandoned altogether. The present article argues that this is good advice in some research areas but not in others. Taking all issues which have appeared so far of the German Economic Review and a recent epidemiological meta-analysis as examples, it shows that there has indeed been a lot of misleading work in the context of significance testing, and that at the same time many promising avenues for fruitfully employing statistical significance tests, disregarded by Ziliak and McCloskey, have not been used.
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"Sectoral Transformation, Turbulence and Labor Market Dynamics in Germany,"
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- Krämer Walter & Arminger Gerhard, 2011. "“True Believers” or Numerical Terrorism at the Nuclear Power Plant," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 608-620, October.
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- McCloskey, Donald N, 1985. "The Loss Function Has Been Mislaid: The Rhetoric of Significance Tests," American Economic Review, American Economic Association, vol. 75(2), pages 201-205, May.
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- Bettina Becker & Silke Uebelmesser, 2010. "Health Insurance Competition in Germany - The Role of Advertising," Discussion Paper Series 2010_05, Department of Economics, Loughborough University, revised Mar 2010.
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