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Correcting for Primary Study Misspecifications in Meta-Analysis

Author

Listed:
  • Mark J. Koetse

    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

  • Raymond J.G.M. Florax

    (Vrije Universiteit, and Purdue University)

  • Henri L.F. de Groot

    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

Abstract

In non-experimental sciences the errors associated with model misspecifications in primarystudies carry over to meta-analysis. We use Monte Carlo simulations to analyse the effects ofthese misspecifications on results of a meta-analysis using a meta-estimator that calculates asimple average effect and a meta-estimator that includes dummy variables to control forprimary study misspecification. The results show that using the dummy variable model goes along way in mitigating the negative effects of error propagation on the bias and mean squarederror of the meta-estimator, and the size and the power of statistical tests. Although primarystudy misspecifications can usually be observed and controlled for in a meta-analysis, themore complex interactions between these observed characteristics are far more difficult tocontrol for in practice. Our results show that these interactions may, however, substantiallyaffect the outcomes of a meta-analysis. When meta-analysis is used to look for a ‘true’ effectrather than for analysing variation in outcomes, our results provide an argument for studyselection on model quality to avoid the impact of error propagation in meta-analysis.

Suggested Citation

  • Mark J. Koetse & Raymond J.G.M. Florax & Henri L.F. de Groot, 2005. "Correcting for Primary Study Misspecifications in Meta-Analysis," Tinbergen Institute Discussion Papers 05-029/3, Tinbergen Institute, revised 31 Jan 2013.
    • Handle: RePEc:tin:wpaper:20050029
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    References listed on IDEAS

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    Cited by:

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    2. Entorf, Horst & Hou, Jia, 2018. "Financial Education for the Disadvantaged? A Review," IZA Discussion Papers 11515, Institute of Labor Economics (IZA).
    3. Randall S. Rosenberger & Robert J. Johnston, 2009. "Selection Effects in Meta-Analysis and Benefit Transfer: Avoiding Unintended Consequences," Land Economics, University of Wisconsin Press, vol. 85(3), pages 410-428.
    4. Jon Nelson & Peter Kennedy, 2009. "The Use (and Abuse) of Meta-Analysis in Environmental and Natural Resource Economics: An Assessment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 345-377, March.

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    More about this item

    Keywords

    Meta-analysis; Monte Carlo simulation; Omitted variable bias; Elasticities; Model Misspecification;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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