Prioritizing Policies for Pro-Poor Growth: Applying Bayesian Model Averaging to Vietnam

R. Klump, P. Prüfer

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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.
Original languageEnglish
Place of PublicationTilburg
PublisherMacroeconomics
Number of pages38
Volume2006-117
Publication statusPublished - 2006

Publication series

NameCentER Discussion Paper
Volume2006-117

Keywords

  • poverty determinants
  • growth determinants
  • pro-poor growth
  • model uncertainty
  • Vietnam

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    Klump, R., & Prüfer, P. (2006). Prioritizing Policies for Pro-Poor Growth: Applying Bayesian Model Averaging to Vietnam. (CentER Discussion Paper; Vol. 2006-117). Macroeconomics.