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Spurious Precision in Meta-Analysis

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  • Irsova, Zuzana
  • Bom, Pedro R. D.
  • Havranek, Tomas
  • Rachinger, Heiko

Abstract

Meta-analysis upweights studies reporting lower standard errors and hence more precision. But in empirical practice, notably in observational research, precision is not given to the researcher. Precision must be estimated, and thus can be p-hacked to achieve statistical significance. Simulations show that a modest dose of spurious precision creates a formidable problem for inverse-variance weighting and bias-correction methods based on the funnel plot. Selection models fail to solve the problem, and the simple mean can beat sophisticated estimators. Cures to publication bias may become worse than the disease. We introduce an approach that surmounts spuriousness: the Meta-Analysis Instrumental Variable Estimator (MAIVE), which employs inverse sample size as an instrument for reported variance.

Suggested Citation

  • Irsova, Zuzana & Bom, Pedro R. D. & Havranek, Tomas & Rachinger, Heiko, 2023. "Spurious Precision in Meta-Analysis," EconStor Preprints 268683, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:268683
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    9. Tersoo David Iorngurum, 2023. "Method Versus Cross-Country Heterogeneity in the Exchange Rate Pass-Through," Working Papers IES 2023/16, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2023.

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    More about this item

    Keywords

    Publication bias; p-hacking; selection models; meta-regression; funnel plot; inverse-variance weighting;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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