Multidimensional Poverty in Cameroon: Determinants and Spatial Distribution

dc.contributor.authorNingaye, Paul
dc.contributor.authorNdjanyou, Laurent
dc.contributor.authorSaakou, Guy Marcel
dc.date.accessioned2019-02-25T10:35:06Z
dc.date.available2019-02-25T10:35:06Z
dc.date.issued2011-01
dc.descriptionHC 995 . Z9 P655 2011en_US
dc.description.abstractThe aim of this study was to target poverty following a multidimensional approach. The main contribution of this approach is that its study of poverty coversmonetary indicators, that is, welfare indicators which cannot be acquired easily through people’s incomes, or the acquisition of which hinges on the existence of certain types of infrastructure. This makes it possible to take into account the population’s welfare while formulating development policies. The results of the present study show that with regard to the spatial dimension of poverty, Cameroon’s regions can be divided into three: a space of extreme multipoverty, a space of non-multipoverty, and a space in between. With regard to socio-economic characteristics, the residential area variable was found to be an absolute determinant because the passage from the urban area to the semi-urban and from the urban area to the rural one increases the risk of multipoverty by about five and 76 times respectively. Monetary poverty is obviously considerable in this distribution, and so are existence poverty, infrastructural poverty and human poverty. Policies aimed at fighting poverty must target the areas of extreme multipoverty and rural areas on the basis of shortages of capabilities in all these dimensions.en_US
dc.description.sponsorshipAERCen_US
dc.identifier.isbn9966-778-81-0
dc.identifier.urihttps://publication.aercafricalibrary.org/123456789/221
dc.publisherAERCen_US
dc.relation.ispartofseries;RESEARCH PAPER 211
dc.subjectPoverty - cameroon - Econometric Modelsen_US
dc.subjectPoor - Cameroon- Econometric Modelsen_US
dc.subjectIncome distribution - Cameroon - Econometric Modelsen_US
dc.titleMultidimensional Poverty in Cameroon: Determinants and Spatial Distributionen_US
dc.typeArticleen_US
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