IDEAS home Printed from https://ideas.repec.org/a/aea/aejapp/v8y2016i1p1-32.html
   My bibliography  Save this article

Star Wars: The Empirics Strike Back

Author

Listed:
  • Abel Brodeur
  • Mathias Lé
  • Marc Sangnier
  • Yanos Zylberberg

Abstract

Using 50,000 tests published in the AER, JPE, and QJE, we identify a residual in the distribution of tests that cannot be explained solely by journals favoring rejection of the null hypothesis. We observe a two-humped camel shape with missing p-values between 0.25 and 0.10 that can be retrieved just after the 0.05 threshold and represent 10-20 percent of marginally rejected tests. Our interpretation is that researchers inflate the value of just-rejected tests by choosing "significant" specifications. We propose a method to measure this residual and describe how it varies by article and author characteristics. (JEL A11, C13)

Suggested Citation

  • Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
  • Handle: RePEc:aea:aejapp:v:8:y:2016:i:1:p:1-32
    Note: DOI: 10.1257/app.20150044
    as

    Download full text from publisher

    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/app.20150044
    Download Restriction: no

    File URL: http://www.aeaweb.org/aej/app/app/0801/2015-0044_app.pdf
    Download Restriction: no

    File URL: http://www.aeaweb.org/aej/app/data/0801/2015-0044_data.zip
    Download Restriction: no

    File URL: http://www.aeaweb.org/aej/app/data/0801/2015-0044_data.zip
    Download Restriction: no

    File URL: http://www.aeaweb.org/aej/app/ds/0801/2015-0044_ds.zip
    Download Restriction: no

    File URL: http://www.aeaweb.org/aej/app/app/0801/2015-0044_app.pdf
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    3. B.D. McCullough & Kerry Anne McGeary & Teresa D. Harrison, 2008. "Do economics journal archives promote replicable research?," Canadian Journal of Economics, Canadian Economics Association, vol. 41(4), pages 1406-1420, November.
    4. Gerber, Alan & Malhotra, Neil, 2008. "Do Statistical Reporting Standards Affect What Is Published? Publication Bias in Two Leading Political Science Journals," Quarterly Journal of Political Science, now publishers, vol. 3(3), pages 313-326, October.
    5. 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.
    6. Emeric Henry, 2009. "Disclosure of research results: the cost of proving your honesty," Post-Print hal-01023670, HAL.
    7. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    8. Ashenfelter, Orley & Harmon, Colm & Oosterbeek, Hessel, 1999. "A review of estimates of the schooling/earnings relationship, with tests for publication bias," Labour Economics, Elsevier, vol. 6(4), pages 453-470, November.
    9. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," Working Papers 858, Princeton University, Department of Economics, Industrial Relations Section..
    10. Eric Luis Uhlmann & Anthony Bastardi & Lee Ross, 2011. "Wishful Thinking: Belief, Desire, and the Motivated Evaluation of Scientific Evidence," Post-Print hal-00609541, HAL.
    11. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
    12. Weiß Bernd & Wagner Michael, 2011. "The Identification and Prevention of Publication Bias in the Social Sciences and Economics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 661-684, October.
    13. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    14. Card, David & Krueger, Alan B, 1995. "Time-Series Minimum-Wage Studies: A Meta-analysis," American Economic Review, American Economic Association, vol. 85(2), pages 238-243, May.
    15. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    16. repec:pri:cepsud:97ashenfelter is not listed on IDEAS
    17. Martin Dufwenberg & Peter Martinsson, 2014. "Keeping Researchers Honest: The Case for Sealed-Envelope-Submissions," Working Papers 533, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    18. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-1272, December.
    19. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, July.
    20. 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, July.
    21. Doucouliagos, Chris & Stanley, T.D. & Giles, Margaret, 2012. "Are estimates of the value of a statistical life exaggerated?," Journal of Health Economics, Elsevier, vol. 31(1), pages 197-206.
    22. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    23. 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.
    24. David Card & Stefano DellaVigna, 2013. "Nine Facts about Top Journals in Economics," Journal of Economic Literature, American Economic Association, vol. 51(1), pages 144-161, March.
    25. David F. Hendry & Hans‐Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    26. 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 306-317, May.
    27. Tomáš Havránek, 2015. "Measuring Intertemporal Substitution: The Importance Of Method Choices And Selective Reporting," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1180-1204, December.
    28. repec:fth:prinin:425 is not listed on IDEAS
    29. David Card & Stefano DellaVigna, 2014. "Page Limits on Economics Articles: Evidence from Two Journals," Journal of Economic Perspectives, American Economic Association, vol. 28(3), pages 149-168, Summer.
    30. Auspurg Katrin & Hinz Thomas, 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), De Gruyter, vol. 231(5-6), pages 636-660, October.
    31. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    32. 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, April.
    33. Orley Ashenfelter & Colm Harmon & Hessel Oosterbeek, 1999. "A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias," Working Papers 804, Princeton University, Department of Economics, Industrial Relations Section..
    34. Benjamin A. Olken, 2015. "Promises and Perils of Pre-analysis Plans," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 61-80, Summer.
    35. Daniele Fanelli, 2009. "How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-11, May.
    36. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristina Blanco-Perez & Abel Brodeur, 2020. "Publication Bias and Editorial Statement on Negative Findings," Economic Journal, Royal Economic Society, vol. 130(629), pages 1226-1247.
    2. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    3. Christensen, Garret & Miguel, Edward & Sturdy, Jennifer, 2017. "Transparency, Reproducibility, and the Credibility of Economics Research," MetaArXiv 9a3rw, Center for Open Science.
    4. Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, vol. 110(11), pages 3634-3660, November.
    5. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    6. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    7. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    8. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2018. "Methods Matter: P-Hacking and Causal Inference in Economics," IZA Discussion Papers 11796, Institute of Labor Economics (IZA).
    9. 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.
    10. Tomas Havranek & Anna Sokolova, 2020. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 144 Studies Say 'Probably Not'," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 97-122, January.
    11. Roman Horvath & Ali Elminejad & Tomas Havranek, 2020. "Publication and Identification Biases in Measuring the Intertemporal Substitution of Labor Supply," Working Papers IES 2020/32, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    12. Stephan B. Bruns, 2016. "The Fragility of Meta-Regression Models in Observational Research," MAGKS Papers on Economics 201603, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    13. Hippolyte W. Balima & Eric G. Kilama & Rene Tapsoba, 2017. "Settling the Inflation Targeting Debate: Lights from a Meta-Regression Analysis," IMF Working Papers 2017/213, International Monetary Fund.
    14. Christopher Snyder & Ran Zhuo, 2018. "Sniff Tests as a Screen in the Publication Process: Throwing out the Wheat with the Chaff," NBER Working Papers 25058, National Bureau of Economic Research, Inc.
    15. Havranek, Tomas & Rusnak, Marek & Sokolova, Anna, 2017. "Habit formation in consumption: A meta-analysis," European Economic Review, Elsevier, vol. 95(C), pages 142-167.
    16. Polák, Petr, 2017. "The productivity paradox: A meta-analysis," Information Economics and Policy, Elsevier, vol. 38(C), pages 38-54.
    17. Tomáš Havránek, 2015. "Measuring Intertemporal Substitution: The Importance Of Method Choices And Selective Reporting," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1180-1204, December.
    18. Jerome Geyer-Klingeberg & Markus Hang & Matthias Walter & Andreas Rathgeber, 2018. "Do stock markets react to soccer games? A meta-regression analysis," Applied Economics, Taylor & Francis Journals, vol. 50(19), pages 2171-2189, April.
    19. Opoku-Agyemang, Kweku A., 2017. "A Human-Computer Interaction Approach for Integrity in Economics," SocArXiv ra3cs, Center for Open Science.
    20. Stephan B. Bruns, 2017. "Meta-Regression Models and Observational Research," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 637-653, October.

    More about this item

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Meta-Analysis in Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aejapp:v:8:y:2016:i:1:p:1-32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael P. Albert). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.