Social and Behavioral Sciences Commons^™

Comparisons Of Model Averaging Techniques: Assessing Growth Determinants, Shahram Amini, Christopher Parmeter

Christopher F. Parmeter

This paper replicates three important studies on growth theory uncertainty that employed Bayesian model averaging tools. We compare these results with estimates obtained using recently developed frequentist and alternative Bayesian model averaging techniques. Overall, we successfully replicate all three studies using freely available software in the statistical environment R, provide an easily implementable algorithm to operationalize the frequentist model averaging methods and find that the sign and magnitude of these new estimates are reasonably close to those produced via traditional Bayesian methods.