How to Prioritize Policies for Pro-Poor Growth: Applying Bayesian Model Averaging to Vietnam
CentER Discussion Paper Series No. 2006-117
37 Pages Posted: 18 May 2006
Date Written: November 2006
Pro-Poor Growth (PPG) is the vision of combining high growth rates with poverty reduction. Due to the myriad of possible determinants of growth and poverty a unique theoretical model for guiding empirical work on PPG is absent, though. Bayesian Model Averaging is a statistically robust framework for this purpose. It addresses the existent parameter and model uncertainty by not choosing a single model but averaging over all possible ones. Using data for the 61 Vietnamese provinces we are able to ascertain a prioritization of all used determinants of poverty, growth and of PPG of our large set of explanatory variables.
Keywords: Poverty determinants, growth determinants, pro-poor growth, model uncertainty, Vietnam
JEL Classification: C11, C52, R11
Suggested Citation: Suggested Citation