Скачать с ютуб Spurious Precision in Meta-Analysis - Tomas Havranek в хорошем качестве

Spurious Precision in Meta-Analysis - Tomas Havranek

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 dominate sophisticated estimators. Cures to publication bias can become worse than the disease. We introduce an approach that surmounts spuriousness: the Meta-Analysis Instrumental Variable Estimator (MAIVE). Bio: Tomas Havranek is Professor of Economics at Charles University, Prague, and Research Affiliate at the Centre for Economic Policy Research, London. Between 2016 and 2019 he was Advisor to the Board at the Czech National Bank, where he used meta-analysis in central bank policymaking. He currently focuses on weights in meta-analysis and the interaction between publication and attenuation biases. He has published more than 30 meta-analyses in journals including the Review of Economics and Statistics, Journal of the European Economic Association, and Journal of International Economics. According to the RePEc database he is currently the most cited Czech economist.