Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/107140
Authors: 
Reed, W. Robert
Florax, Raymond J. G. M.
Poot, Jacques
Year of Publication: 
2015
Series/Report no.: 
Economics Discussion Papers 2015-9
Abstract: 
This study uses Monte Carlo analysis to investigate the performances of five different meta-analysis (MA) estimators: the Fixed Effects (FE) estimator, the Weighted Least Squares (WLS) estimator, the Random Effects (RE) estimator, the Precision Effect Test (PET) estimator, and the Precision Effect Estimate with Standard Errors (PEESE) estimator. The authors consider two types of publication bias: publication bias directed against statistically insignificant estimates, and publication bias directed against wrong-signed estimates. Finally, the authors consider three cases concerning the distribution of the "true effect": the Fixed Effects case, where there is only one estimate per study, and all studies have the same true effect; the Random Effects case, where there is only one estimate per study, and there is heterogeneity in true effects across studies; and the Panel Random Effects case, where studies have multiple estimates, and true effects are random both across and within studies. The simulations produce a number of findings that challenge results from previous research.
Subjects: 
meta-analysis
random effects
fixed effects
publication bias
Monte Carlo
simulations
JEL: 
B41
C15
C18
Creative Commons License: 
http://creativecommons.org/licenses/by/3.0/
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.