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Star wars: The empirics strike back

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  • Abel Brodeur

    (PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - École des Hautes Études en Sciences Sociales (EHESS) - École des Ponts ParisTech (ENPC) - École normale supérieure [ENS] - Paris - Institut national de la recherche agronomique (INRA), EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Mathias Lé

    (PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - École des Hautes Études en Sciences Sociales (EHESS) - École des Ponts ParisTech (ENPC) - École normale supérieure [ENS] - Paris - Institut national de la recherche agronomique (INRA), EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Marc Sangnier

    (PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - École des Hautes Études en Sciences Sociales (EHESS) - École des Ponts ParisTech (ENPC) - École normale supérieure [ENS] - Paris - Institut national de la recherche agronomique (INRA), EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris, IEP Paris - Sciences Po Paris - Institut d'études politiques de Paris - Institut d'Études Politiques [IEP] - Paris - PRES Sorbonne Paris Cité - Fondation Nationale des Sciences Politiques [FNSP])

  • Yanos Zylberberg

    (CREI - Centre de Recerca en Economia Internacional - Universitat Pompeu Fabra)

Abstract

Journals favor rejections of the null hypothesis. This selection upon results 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 :25, a valley between :25 and :10 and a bump slightly under :05. Missing tests are those which would have been accepted but close to being rejected (p-values between :25 and :10). We show that this pattern corresponds to a shift in the distribution of p-values: between 10% and 20% of marginally rejected tests are misallocated. Our interpretation is that researchers might be tempted to inflate the value of their tests by choosing the specification that provides the highest statistics. Note that Inflation is larger in articles where stars are used in order to highlight statistical significance and lower in articles with theoretical models.

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Bibliographic Info

Paper provided by HAL in its series Working Papers with number halshs-00710122.

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Date of creation: Jun 2012
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Handle: RePEc:hal:wpaper:halshs-00710122

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00710122
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Related research

Keywords: Hypothesis testing ; Distorting incentives ; Selection bias ; Research in economics;

References

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  1. Orley Ashenfelter & Colm Harmon & Hessel Oosterbeek, 2000. "A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias," NBER Working Papers 7457, National Bureau of Economic Research, Inc.
  2. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
  3. Card, David & Krueger, Alan B, 1995. "Time-Series Minimum-Wage Studies: A Meta-analysis," American Economic Review, American Economic Association, vol. 85(2), pages 238-43, May.
  4. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
  5. 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.
  6. David Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Series Working Papers 2004-W17, University of Oxford, Department of Economics.
  7. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-17, May.
  8. 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.
  9. Hristos Doucouliagos & T.D. Stanley & Margaret Giles, 2011. "Are Estimates of the Value of a Statistical Life Exaggerated?," Economics Series 2011_2, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  10. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," American Economic Review, American Economic Association, vol. 94(2), pages 454-460, May.
  11. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-27, February.
  12. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
  13. Emeric Henry, 2009. "Strategic Disclosure of Research Results: The Cost of Proving Your Honesty," Economic Journal, Royal Economic Society, vol. 119(539), pages 1036-1064, 07.
  14. 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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Cited by:
  1. 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.

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