- A-Z
- Jena Economic Resea...
- Volume 7
- Identifying Genuine...
- Abgebildete Person
- Erschienen
- 8. Oktober 2012
- Nummer des Discussion-Papers
-
2013-040
- Schlagwort(e)
-
data mining
meta-analysis
Meta-regression
Monte Carlo simulation
publication bias
- Zusammenfsg.
-
Meta-regression models are increasingly utilized to integrate empirical results across studies while controlling for the potential threats of data-mining and publication bias. We propose extended meta-regression models and evaluate their performance in identifying genuine empirical effects by means of a comprehensive simulation study for various scenarios that are prevalent in empirical economics. We can show that the meta-regression models here proposed systematically outperform the prior gold standard of meta-regression analysis of regression coefficients. Most meta-regression models are robust to the presence of publication bias, but data-mining bias leads to seriously inflated type I errors and has to be addressed explicitly.
- article pub. typess JER
- Research article
- article languages JER
- Englisch
- JEL-Classification for JER
- C12 - Hypothesis Testing ; C15 - Simulation Methods ; C40 - General