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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/8317

Title: Spatial analysis of poverty among women in Ghana
Authors: Abdul-Karim, Haruna
Issue Date: 22-Feb-2016
Abstract: In Ghana, although women constitute more than half of the total population, they are grossly disadvantaged in the sharing of political power, wealth, in uence, employments etc. In some parts of the country, the well-being of women is highly affected by these inequities. This study used spatial econometric techniques to investigate the spatial distribution of poverty among women and explored the main factors that determine the incidence of women poverty in Ghana.This study draws on the 2008 GDHS household's women data with their wealth factor scores (economic status) as the response variable. PCA technique was employed to obtain 13 components from an initial 27 socio-economic, demographic and geographic variables. These were the regression variables in GeoDa. The results show a highly positive significant Moran's I (I= 0.396; p=0.001), indicating that neighboring areas have similar poverty status; that is poverty is a geographical phenomenon. Also, the poverty maps identifed the three northern regions as the most endemic women poverty areas. The regression analysis further indicated that SLM [R2 = 79:2%;Log.L=-234;AIC=498;SC=558] fit the data better than the SEM [R2 = 79:0%;Log.L=-242;AIC=511;SC=568] and OLS [R2 = 74:0% ;Log.L=-270;AIC=569;SC=630] models. The selection of SLM indicates that the rate of poverty of one area affects the poverty rates of its neighbors. The major significant determinants of women poverty in 2008 were the education related variables, parity, some occupational related variables and marital status (married). The variables that had no significant relationships with poverty are female headed household and couple married without living together.
Description: A thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of Master of Philosophy in Mathematical Statistics, 2015
URI: http://hdl.handle.net/123456789/8317
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