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Star Wars: The Empirics Strike Back

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Author Info

  • Brodeur, Abel

    ()
    (Paris School of Economics)

  • Lé, Mathias

    ()
    (Paris School of Economics)

  • Sangnier, Marc

    ()
    (University of Aix-Marseille II)

  • Zylberberg, Yanos

    ()
    (CREI and Universitat Pompeu Fabra)

Abstract

Journals favor rejection of the null hypothesis. This selection upon tests may distort the behavior of researchers. Using 50,000 tests published between 2005 and 2011 in the AER, JPE, and QJE, we identify a residual in the distribution of tests that cannot be explained by selection. The distribution of p-values exhibits a camel shape with abundant p-values above 0.25, a valley between 0.25 and 0.10 and a bump slightly below 0.05. The missing tests (with p-values between 0.25 and 0.10) can be retrieved just after the 0.05 threshold and represent 10% to 20% of marginally rejected tests. Our interpretation is that researchers might be tempted to inflate the value of those almost-rejected tests by choosing a "significant" specification. We propose a method to measure inflation and decompose it along articles' and authors' characteristics.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7268.

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Length: 61 pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:iza:izadps:dp7268

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Related research

Keywords: hypothesis testing; distorting incentives; selection bias; research in economics;

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References

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  7. J. Bradford De Long & Kevin Lang, . "Are All Economic Hypotheses False?," J. Bradford De Long's Working Papers _117, University of California at Berkeley, Economics Department.
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  12. Katrin Auspurg & Thomas Hinz, 2011. "What Fuels Publication Bias? Theoretical and Empirical Analyses of Risk Factors Using the Caliper Test," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 231(5-6), pages 636-660, November.
  13. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, 04.
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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Star Wars
    by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-04-17 20:49:00
  2. Test statistics and the publication game
    by Economic Logician in Economic Logic on 2013-04-11 15:00:00
  3. Assorted Academia Links
    by RB in The Lumpy Economist on 2013-04-15 00:00:01
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:
  1. Stephan B. Bruns, 2013. "Identifying Genuine Effects in Observational Research by Means of Meta-Regressions," Jena Economic Research Papers 2013-040, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  2. Møen, Jarle & Thorsen, Helge Sandvig, 2013. "Publication bias in the returns to R&D literature," Discussion Papers 2013/12, Department of Business and Management Science, Norwegian School of Economics.
  3. Thomas Mayer, 2012. "Ziliak and McCloskey's Criticisms of Significance Tests: An Assessment," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 256-297, September.
  4. Lant Pritchett, Justin Sandefur, 2013. "Context Matters for Size: Why External Validity Claims and Development Practice Don't Mix-Working Paper 336," Working Papers 336, Center for Global Development.

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