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Meta-Regression Approximations to Reduce Publication Selection Bias

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  • T.D. Stanley

    ()

  • Hristos Doucouliagos

    ()

Abstract

Publication selection bias represents a serious challenge to the integrity of all empirical sciences. We develop meta-regression approximations that are shown to reduce this bias and outperform conventional meta-analytic methods. Our approach is derived from Taylor polynomial approximations to the conditional mean of a truncated distribution. Monte Carlo simulations demonstrate how a new hybrid estimator provides a practical solution. These meta-regression methods are applied to several policy-relevant areas of research including: antidepressant effectiveness, the value of a statistical life and the employment effect of minimum wages and alter what we think we know.

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File URL: http://www.deakin.edu.au/buslaw/aef/workingpapers/papers/2011_4.pdf
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Bibliographic Info

Paper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Economics Series with number 2011_4.

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Date of creation: 25 May 2011
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Handle: RePEc:dkn:econwp:eco_2011_4

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Related research

Keywords: meta-regression; publication selection bias; systematic reviews; truncation;

This paper has been announced in the following NEP Reports:

References

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  1. Havranek, Tomas, 2009. "Rose Effect and the Euro: Is the Magic Gone?," MPRA Paper 18479, University Library of Munich, Germany, revised 07 Nov 2009.
  2. Joan Costa‐Font & Marin Gemmill & Gloria Rubert, 2011. "Biases in the healthcare luxury good hypothesis?: a meta‐regression analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 95-107, January.
  3. T. D. Stanley & Stephen B. Jarrell, 2005. "Meta-Regression Analysis: A Quantitative Method of Literature Surveys," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 299-308, 07.
  4. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-72, December.
  5. Hristos Doucouliagos & T.D. Stanley, 2008. "Publication Selection Bias in Minimum-Wage Research? A Meta-Regression Analysis," Economics Series 2008_14, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  6. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, 07.
  7. François Bellavance & Georges Dionne & Martin Lebeau, 2006. "The Value of a Statistical Life: a Meta-Analysis with a Mixed Effects Regression Model," Cahiers de recherche 0646, CIRPEE.
  8. Lars P. Feld & Jost Henrich Heckemeyer, 2009. "FDI and Taxation: A Meta-Study," CESifo Working Paper Series 2540, CESifo Group Munich.
  9. T. D. Stanley, 2008. "Meta-Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 103-127, 02.
  10. Mandel, Micha & Rinott, Yosef, 2009. "A Selection Bias Conflict and Frequentist versus Bayesian Viewpoints," The American Statistician, American Statistical Association, vol. 63(3), pages 211-217.
  11. T.D Stanley & Hristos Doucouliagos, 2007. "Identifying and Correcting Publication Selection Bias in the Efficiency-Wage Literature: Heckman Meta-Regression," Economics Series 2007_11, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  12. Bowland, Brad J. & Beghin, John C., 2001. "Robust Estimates of Value of a Statistical Life for Developing Economies," Staff General Research Papers 5196, Iowa State University, Department of Economics.
  13. T.D. Stanley & Stephen B. Jarrell & Hristos Doucouliagos, 2009. "Could It Be Better to Discard 90% of the Data? A Statistical Paradox," Economics Series 2009_13, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.
  14. Marin C. Gemmill & Joan Costa-Font & Alistair McGuire, 2007. "In search of a corrected prescription drug Elasticity estimate: a meta-regression approach," Health Economics, John Wiley & Sons, Ltd., vol. 16(6), pages 627-643.
  15. Eric Krassoi Peach & T. Stanley, 2009. "Efficiency Wages, Productivity and Simultaneity: A Meta-Regression Analysis," Journal of Labor Research, Springer, vol. 30(3), pages 262-268, September.
  16. T. D. Stanley, 2001. "Wheat from Chaff: Meta-analysis as Quantitative Literature Review," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 131-150, Summer.
  17. T.D. Stanley & Hristos Doucouliagos, 2010. "Picture This: A Simple Graph That Reveals Much Ado About Research," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 170-191, 02.
  18. Viscusi, W Kip, 1993. "The Value of Risks to Life and Health," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1912-46, December.
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Citations

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Cited by:
  1. Bruns, Stephan B. & Gross, Christian & Stern, David I., 2013. "Is There Really Granger Causality Between Energy Use and Output?," FCN Working Papers 11/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  2. Havranek, Tomas & Irsova, Zuzana & Janda, Karel, 2011. "Demand for gasoline is more price-inelastic than commonly thought," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt0m94j50t, Department of Agricultural & Resource Economics, UC Berkeley.
  3. Bruno, Randolph Luca & Campos, Nauro F, 2013. "Reexamining the Conditional Effect of Foreign Direct Investment," IZA Discussion Papers 7458, Institute for the Study of Labor (IZA).
  4. 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.
  5. T.D. Stanley & Hristos Doucouliagos, 2013. "Better than Random: Weighted Least Squares Meta-Regression Analysis," Economics Series 2013_2, Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance.

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