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

R. Klump, P. Prüfer

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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
Number of pages38
Publication statusPublished - 2006

Publication series

NameCentER Discussion Paper


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


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