المستودع الأكاديمي جامعة المدينة

How to prioritise policies for poverty reduction: Applying Bayesian Model Averaging to Vietnam

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dc.creator Klump, Rainer
dc.creator Prüfer, Patricia
dc.date 2005
dc.date.accessioned 2013-10-16T07:06:56Z
dc.date.available 2013-10-16T07:06:56Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/19820
dc.identifier ppn:500764816
dc.identifier RePEc:zbw:gdec05:3500
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/19820
dc.description The UN Millennium Development Goals have recognized poverty reduction as the main goal of global development policy. A comprehensive framework to evaluate the effectiveness of single policy measures and policy packages with respect to poverty reduction is still lacking, though. Policy evaluation is exposed to manifold uncertainties given the dependency of the preferred outcomes on a chosen policy, available information, and policy makers' preferences. We show that Bayesian Model Averaging (BMA) is most valuable in this context as it addresses the parameter and model uncertainty inherent in development policies. Using data for the 61 Vietnamese provinces we are able to ascertain the most important determinants of poverty from a large number of potential explanatory variables.
dc.language eng
dc.publisher
dc.relation Proceedings of the German Development Economics Conference, Kiel 2005 / Verein für Socialpolitik, Research Committee Development Economics 27
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject R11
dc.subject C11
dc.subject C52
dc.subject O18
dc.subject O53
dc.subject ddc:330
dc.subject Poverty determinants
dc.subject Vietnam
dc.subject model uncertainty
dc.subject Bayesian Model Averaging (BMA)
dc.title How to prioritise policies for poverty reduction: Applying Bayesian Model Averaging to Vietnam
dc.type doc-type:conferenceObject


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