IDEAS home Printed from https://ideas.repec.org/p/zbw/ifwedp/20153.html
   My bibliography  Save this paper

Meta-analysis in a nutshell: Techniques and general findings

Author

Listed:
  • Paldam, Martin

Abstract

The purpose of this note is to introduce the technique and main findings of meta-analysis to the reader, who is unfamiliar with the field and has the usual objections. A meta-analysis is a quantitative survey of a literature reporting estimates of the same parameter. The funnel showing the distribution of the results is normally amazingly wide given their t-ratios. Little of the variation can be explained by the quality of the journal or by the estimator used. The funnel has often asymmetries consistent with the most likely priors of the researchers, giving a publication bias.

Suggested Citation

  • Paldam, Martin, 2015. "Meta-analysis in a nutshell: Techniques and general findings," Economics Discussion Papers 2015-3, Kiel Institute for the World Economy (IfW).
  • Handle: RePEc:zbw:ifwedp:20153
    as

    Download full text from publisher

    File URL: http://www.economics-ejournal.org/economics/discussionpapers/2015-3
    Download Restriction: no

    File URL: https://www.econstor.eu/bitstream/10419/106261/1/815775474.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Reed, W. Robert, 2015. "A Monte Carlo analysis of alternative meta-analysis estimators in the presence of publication bias," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 9, pages 1-40.
    3. 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.
    4. Chris Doucouliagos, 1995. "Worker Participation and Productivity in Labor-Managed and Participatory Capitalist Firms: A Meta-Analysis," ILR Review, Cornell University, ILR School, vol. 49(1), pages 58-77, October.
    5. 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.
    6. 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, pages 103-127.
    7. Martin Paldam & Laurent Callot, 2010. "Natural funnel asymmetries. A simulation analysis of the three basic tools of meta analysis," Economics Working Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    8. Summers, Lawrence H, 1991. " The Scientific Illusion in Empirical Macroeconomics," Scandinavian Journal of Economics, Wiley Blackwell, vol. 93(2), pages 129-148.
    9. 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.
    10. Martin Paldam, 2013. "Regression Costs Fall, Mining Ratios Rise, Publication Bias Looms, and Techniques Get Fancier: Reflections on Some Trends in Empirical Macroeconomics," Econ Journal Watch, Econ Journal Watch, vol. 10(2), pages 136-156, May.
    11. 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, pages 584-587.
    12. Stephen B. Jarrell & T. D. Stanley, 1990. "A Meta-Analysis of the Union-Nonunion Wage Gap," ILR Review, Cornell University, ILR School, vol. 44(1), pages 54-67, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thomas R. Dyckman, 2016. "Significance Testing: We Can Do Better," Abacus, Accounting Foundation, University of Sydney, vol. 52(2), pages 319-342, June.

    More about this item

    Keywords

    meta-analysis; selection of regressions; publication bias;

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    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:zbw:ifwedp:20153. 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: (ZBW - German National Library of Economics). General contact details of provider: http://edirc.repec.org/data/iwkiede.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.