Prioritizing Policies for Pro-Poor Growth

Applying Bayesian Model Averaging to Vietnam

R. Klump, P. Prüfer

Research output: Working paperDiscussion paperOther research output

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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

Fingerprint

Bayesian model averaging
Pro-poor growth
Poverty
Parameter uncertainty
Model uncertainty
Prioritization
Poverty reduction
Model averaging

Keywords

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

Cite this

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

Prioritizing Policies for Pro-Poor Growth : Applying Bayesian Model Averaging to Vietnam. / Klump, R.; Prüfer, P.

Tilburg : Macroeconomics, 2006. (CentER Discussion Paper; Vol. 2006-117).

Research output: Working paperDiscussion paperOther research output

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T1 - Prioritizing Policies for Pro-Poor Growth

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N2 - 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.

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KW - growth determinants

KW - pro-poor growth

KW - model uncertainty

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