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We Agree That Statistical Significance Proves Essentially Nothing: A Rejoinder to Thomas Mayer

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  • Stephen T. Ziliak
  • Deirdre N. McCloskey

Abstract

In several dozen journal reviews and in many other comments we have received—from, for example, four Nobel laureates, the statistician Dennis Lindley (2012), the statistician Arnold Zellner (2004), the mathematician Olle Häggström (2010), the sociologist Steve Fuller (2008), and the historian Theodore Porter (2008)—no one has ever tried to defend null hypothesis significance testing and its numerous errors. Recent articles by Thomas Mayer (2012, 2013), commenting on our book The Cult of Statistical Significance, are no exception. Of the five major claims we make in our book about the theory and practice of significance testing in economics, Mayer strongly agrees with four. On the fifth claim our disagreement is a matter of degree, not of kind, with no substantive change in results. Overall, Mayer agrees with us and with the new and growing consensus that statistical significance proves essentially nothing and has to change.

Suggested Citation

  • Stephen T. Ziliak & Deirdre N. McCloskey, 2013. "We Agree That Statistical Significance Proves Essentially Nothing: A Rejoinder to Thomas Mayer," Econ Journal Watch, Econ Journal Watch, vol. 10(1), pages 97-107, January.
    • Handle: RePEc:ejw:journl:v:10:y:2013:i:1:p:97-107
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    References listed on IDEAS

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    1. Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
    2. Stephen T. Ziliak & Deirdre N. McCloskey, 2004. "Size Matters: The Standard Error of Regressions in the American Economic Review," Econ Journal Watch, Econ Journal Watch, vol. 1(2), pages 331-358, August.
    3. Elliott, Graham & Granger, Clive W.J., 2004. "Evaluating significance: comments on "size matters"," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 547-550, November.
    4. Kevin Hoover & Mark Siegler, 2008. "Sound and fury: McCloskey and significance testing in economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 15(1), pages 1-37.
    5. Zellner, Arnold, 2004. "To test or not to test and if so, how?: Comments on "size matters"," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 581-586, November.
    6. 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.
    7. Walter Krämer, 2011. "The Cult of Statistical Significance – What Economists Should and Should Not Do to Make their Data Talk," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 131(3), pages 455-468.
    8. Thomas Mayer, 2013. "Reply to Deirdre McCloskey and Stephen Ziliak on Statistical Significance," Econ Journal Watch, Econ Journal Watch, vol. 10(1), pages 87-96, January.
    9. Deirdre McCloskey & Stephen Ziliak, 2008. "Signifying nothing: reply to Hoover and Siegler," Journal of Economic Methodology, Taylor & Francis Journals, vol. 15(1), pages 39-55.
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    More about this item

    Keywords

    Significance test; economic significance; Student’s t; oomph; Gosset; Fisher;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology

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