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A Monte Carlo analysis of alternative meta-analysis estimators in the presence of publication bias

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  • Reed, W. Robert
  • Florax, Raymond J. G. M.
  • Poot, Jacques

Abstract

This study uses Monte Carlo analysis to investigate the performances of five different meta-analysis (MA) estimators: the Fixed Effects (FE) estimator, the Weighted Least Squares (WLS) estimator, the Random Effects (RE) estimator, the Precision Effect Test (PET) estimator, and the Precision Effect Estimate with Standard Errors (PEESE) estimator. The authors consider two types of publication bias: publication bias directed against statistically insignificant estimates, and publication bias directed against wrong-signed estimates. Finally, the authors consider three cases concerning the distribution of the "true effect": the Fixed Effects case, where there is only one estimate per study, and all studies have the same true effect; the Random Effects case, where there is only one estimate per study, and there is heterogeneity in true effects across studies; and the Panel Random Effects case, where studies have multiple estimates, and true effects are random both across and within studies. The simulations produce a number of findings that challenge results from previous research.

Suggested Citation

  • Reed, W. Robert & Florax, Raymond J. G. M. & Poot, Jacques, 2015. "A Monte Carlo analysis of alternative meta-analysis estimators in the presence of publication bias," Economics Discussion Papers 2015-9, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwedp:20159
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    6. Hristos Doucouliagos & Martin Paldam, 2013. "The Robust Result in Meta-analysis of Aid Effectiveness: A Response to Mekasha and Tarp," Journal of Development Studies, Taylor & Francis Journals, vol. 49(4), pages 584-587, April.
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    9. 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.
    10. Hristos Doucouliagos & T. D. Stanley, 2009. "Publication Selection Bias in Minimum‐Wage Research? A Meta‐Regression Analysis," British Journal of Industrial Relations, London School of Economics, vol. 47(2), pages 406-428, June.
    11. 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, February.
    12. Tseday Jemaneh Mekasha & Finn Tarp, 2013. "Aid and Growth: What Meta-Analysis Reveals," Journal of Development Studies, Taylor & Francis Journals, vol. 49(4), pages 564-583, April.
    13. Mark Koetse & Raymond Florax & Henri Groot, 2010. "Consequences of effect size heterogeneity for meta-analysis: a Monte Carlo study," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(2), pages 217-236, June.
    14. Nelson, Jon P., 2014. "Estimating the price elasticity of beer: Meta-analysis of data with heterogeneity, dependence, and publication bias," Journal of Health Economics, Elsevier, vol. 33(C), pages 180-187.
    15. 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.
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    Citations

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    Cited by:

    1. Nazila Alinaghi & W. Robert Reed, 2016. "Meta-Analysis and Publication Bias: How Well Does the FAT-PET-PEESE Procedure Work?," Working Papers in Economics 16/26, University of Canterbury, Department of Economics and Finance.
    2. Paldam, Martin, 2015. "Meta-analysis in a nutshell: Techniques and general findings," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-14.
    3. Jianhua Duan & Kuntal K. Das & Laura Meriluoto & W. Robert Reed, 2020. "Estimating the effect of spillovers on exports: a meta-analysis," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(2), pages 219-249, May.
    4. Sanghyun Hong & W. Robert Reed, 2020. "Using Monte Carlo Experiments to Select Meta-Analytic Estimators," Working Papers in Economics 20/10, University of Canterbury, Department of Economics and Finance.
    5. Nazila Alinaghi & W. Robert Reed, 2021. "Taxes and Economic Growth in OECD Countries: A Meta-analysis," Public Finance Review, , vol. 49(1), pages 3-40, January.
    6. Nazila Alinaghi & W. Robert Reed, 2016. "Meta-Analysis and Publication Bias: How Well Does the FAT-PET-PEESE Procedure Work?," Working Papers in Economics 16/26, University of Canterbury, Department of Economics and Finance.
    7. Diana Zigraiova & Tomas Havranek, 2016. "Bank Competition And Financial Stability: Much Ado About Nothing?," Journal of Economic Surveys, Wiley Blackwell, vol. 30(5), pages 944-981, December.
    8. Jianhua Duan & Kuntal K. Das & Laura Meriluoto & W. Robert Reed, 2019. "Spillovers and Exports: A Meta-Analysis," Working Papers in Economics 19/03, University of Canterbury, Department of Economics and Finance.
    9. Xue, Xindong & Reed, W. Robert & Menclova, Andrea, 2020. "Social capital and health: a meta-analysis," Journal of Health Economics, Elsevier, vol. 72(C).
    10. Nelson, Jon Paul, 2020. "Fixed-effect versus random-effects meta-analysis in economics: A study of pass-through rates for alcohol beverage excise taxes," Economics Discussion Papers 2020-1, Kiel Institute for the World Economy (IfW Kiel).
    11. Jurkat, Anne & Klump, Rainer & Schneider, Florian, 2023. "Robots and Wages: A Meta-Analysis," EconStor Preprints 274156, ZBW - Leibniz Information Centre for Economics.
    12. Hippolyte W. BALIMA & Eric Gabin KILAMA & René TAPSOBA, 2017. "Settling the Inflation Targeting Debate: Lights from a Meta-Regression Analysis," Working Papers 4080, FERDI.
    13. Martin Paldam, 2016. "Simulating an empirical paper by the rational economist," Empirical Economics, Springer, vol. 50(4), pages 1383-1407, June.
    14. Gunby, Philip & Jin, Yinghua & Robert Reed, W., 2017. "Did FDI Really Cause Chinese Economic Growth? A Meta-Analysis," World Development, Elsevier, vol. 90(C), pages 242-255.
    15. Sanghyun Hong & W. Robert Reed, 2019. "Towards an Experimental Framework for Assessing Meta-Analysis Methods, with a Focus on Andrews-Kasy Estimators," Working Papers in Economics 19/13, University of Canterbury, Department of Economics and Finance.
    16. Balima, Hippolyte W. & Kilama, Eric G. & Tapsoba, René, 2020. "Inflation targeting: Genuine effects or publication selection bias?," European Economic Review, Elsevier, vol. 128(C).
    17. Randolph Luca Bruno & Maria Cipollina, 2018. "A meta†analysis of the indirect impact of foreign direct investment in old and new EU member states: Understanding productivity spillovers," The World Economy, Wiley Blackwell, vol. 41(5), pages 1342-1377, May.
    18. Petr Polak & Nikol Polakova & Anna Tlusta, 2020. "How Bad Are Trade Wars? Evidence from Tariffs," Working Papers 2020/15, Czech National Bank.
    19. Sanghyun Hong & W. Robert Reed, 2019. "A Performance Analysis of Some New Meta-Analysis Estimators Designed to Correct Publication Bias," Working Papers in Economics 19/04, University of Canterbury, Department of Economics and Finance.
    20. Robbie C M van Aert & Jelte M Wicherts & Marcel A L M van Assen, 2019. "Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-32, April.

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    More about this item

    Keywords

    meta-analysis; random effects; fixed effects; publication bias; Monte Carlo; simulations;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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