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ESR 5 Universal health coverage in West Africa

Reference No.:
ESR 5

Objectives:
One of the Targets of SDG 3 for 2030 is to achieve universal health coverage, including financial risk protection, access to quality essential health-care services and to safe, effective and affordable essential medicines and vaccines for all. Knowing if social protection saves lives and prevents from poverty (avoiding catastrophic expenditure) and inequalities is crucial in a context of increased inequalities. The value for money of universal health coverage programmes (versus other social programmes) will be given a particular attention. The research will focus on selected African countries. Data from the introduction of new social programmes and universal health programmes will be collected in order to make comparative analysis and identify factors increasing the value for money of such programs in terms of poverty reduction or of protecting the poor and the vulnerable.

Recruiting University:
Centre National de Recherche Scientifique, University Paris 1 Panthéon Sorbonne (UP1), France

Partner University:
Erasmus University Rotterdam (EUR), Netherlands

Research Directors:
Prof. Dr. Josselin Thuilliez (Centre d’Economie de la Sorbonne UP1),
Prof. Dr. Arjun Bedi (International Institute of Social Studies, EUR)

Secondments:
The project involves a strong collaboration between the Centre d’Economie de la Sorbonne at UP1 and the International Institute of Social Studies of EUR and therefore includes mandatory research stays of the ESR in The Hague for six months in total.
A six-month secondment for field research is planned and supervised by the University for Development Studies (Ghana).

Specific selection criteria for this ESR position:
The successful candidate has completed an internationally recognised Masters’ programme in economics with above-average GPA and excellent marks in econometrics. Specialisations in development economics and health/population economics during the Masters’ would be an advantage. The candidate should have solid knowledge in econometrics software (Stata or R). Knowledge in geo-localized data and software (QGIS) would be an additional plus.


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