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

See all articles by Patricia Prufer

Patricia Prufer

CentERdata; Tilburg University

Rainer Klump

University of Frankfurt - Economics and Business Administration Area

Date Written: November 2006

Abstract

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

Prufer, Patricia and Klump, Rainer, How to Prioritize Policies for Pro-Poor Growth: Applying Bayesian Model Averaging to Vietnam (November 2006). CentER Discussion Paper Series No. 2006-117, Available at SSRN: https://ssrn.com/abstract=902931 or http://dx.doi.org/10.2139/ssrn.902931

Patricia Prufer (Contact Author)

CentERdata ( email )

PO Box 90153
Tilburg, NL 5000 LE
Netherlands

Tilburg University ( email )

Department of Economics
CentER
Tilburg, 5032 RE
Netherlands

HOME PAGE: http://center.uvt.nl/phd_stud/prufer/

Rainer Klump

University of Frankfurt - Economics and Business Administration Area ( email )

Schumannstrasse 60
D-60325 Frankfurt am Main
Germany
+49 69 798-22288 (Phone)
+49 69 798-28121 (Fax)

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