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DTSTART;TZID=Europe/Berlin:20240611T153000
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DTSTAMP:20240529T111949Z
CREATED:20240508T085431Z
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UID:10000065-1718119800-1718125200@whatworksclimate.solutions
SUMMARY:Accounting for Sample Overlap in Economics Meta-Analyses: The Generalized-Weights Method in Practice
DESCRIPTION:Meta-analyses in economics frequently exhibit considerable overlap among primary samples. If not addressed\, sample overlap leads to efficiency losses and inflated rates of false positives at\nthe meta-analytical level. Bom and Rachinger (2020) propose a generalized-weights approach to handle sample overlap. This approach effectively approximates the correlation structure between primary estimates using information on sample sizes and overlap degrees in the primary studies. This paper demonstrates the application of the generalized-weights method to economics\nmeta-analyses\, addressing practical challenges that are likely to be encountered. We account for variations in data aggregation levels\, estimation methods\, and effect size metrics\, among other\nissues. We derive explicit covariance formulas for different scenarios\, evaluate the accuracy of the approximations\, and employ Monte Carlo simulations to demonstrate how the method enhances efficiency and restores the false positive rate to its nominal level.
URL:https://whatworksclimate.solutions/presentation/accounting-for-sample-overlap-in-economics-meta-analyses-the-generalized-weights-method-in-practice/
LOCATION:H 0104 (Elinor Ostrom Hall)
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