Statistical Significance in the New Tom and the Old Tom: A Reply to Thomas Mayer
Deirdre N. McCloskey and
Stephen Ziliak
Econ Journal Watch, 2012, vol. 9, issue 3, 298-308
Abstract:
Econometricians have been claiming proudly since World War II that significance testing is the empirical side of economics. In fact today most young economists think that the word “empirical” simply means “collect enough data to do a significance test”. Tjalling Koopmans’s influential book of 1957, Three Essays on the State of Economic Science, solidified the claim. A century of evidence after Student’s t-test points strongly to the opposite conclusion. Against conventional econometrics we argue that statistical significance is neither necessary nor sufficient for proving commercial, human, or scientific importance. A recent comment by Thomas Mayer, though in parts insightful, does nothing to alter conclusions about the logic and evidence which we and others have assembled against significance testing. Let’s bury it, and get on to empirical work that actually changes minds.
Keywords: Significance test; economic significance; t test; oomph (search for similar items in EconPapers)
JEL-codes: B4 C12 (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://econjwatch.org/File+download/589/McCloskey ... 012.pdf?mimetype=pdf (application/pdf)
https://econjwatch.org/820 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ejw:journl:v:9:y:2012:i:3:p:298-308
Access Statistics for this article
Econ Journal Watch is currently edited by Daniel Klein
More articles in Econ Journal Watch from Econ Journal Watch Contact information at EDIRC.
Bibliographic data for series maintained by Jason Briggeman (jason@briggeman.org).