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COMPARISON OF MODEL AVERAGING TECHNIQUES: ASSESSING GROWTH DETERMINANTS
Author(s) -
Amini Shahram M.,
Parmeter Christopher F.
Publication year - 2012
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2288
Subject(s) - replicate , estimator , bayesian probability , econometrics , computer science , sign (mathematics) , bayesian inference , statistics , artificial intelligence , mathematics , mathematical analysis
SUMMARY This paper investigates the replicability of three important studies on growth theory uncertainty that employed Bayesian model averaging tools. We compare these results with estimates obtained using alternative, recently developed model averaging techniques. Overall, we successfully replicate all three studies, find that the sign and magnitude of these new estimates are reasonably close to those produced via traditional Bayesian methods and deploy a novel strategy to implement one of the new averaging estimators. Copyright © 2012 John Wiley & Sons, Ltd.