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A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of household living standard

FO Akinyemi, F Bigirimana

Abstract


This study examines the poverty pattern occurring in Kigali through the use of spatial analysis techniques. It seeks to further decipher the underlying factors contributing to the emerging pattern of poverty. These kinds of information are useful to the Kigali administration as input into devising appropriate poverty reduction strategy for the city. Household living standard is examined using data from the Integrated Living Condition survey (EICV: Enquête Intégrale sur les Conditions de vie des ménages) conducted by the National Institute of Statistics of Rwanda in 2000-2001. It was meant to measure household expenditures, consumption and income, as well as demographic and socioeconomic characteristics of the population. Four poverty dimensions were employed in the analysis of urban poverty in Kigali, namely: expenditure, health, education, and services. The influence exerted by each dimension on the overall poverty level is examined. Several indices were computed such as the poverty headcount, poverty gap and a composite household living standard index. Looking at the example of the poverty headcount index, three distinct regions of poverty incident can be deciphered. In the first region with the highest poverty incident, the number of poor is between 32-78%. These are the extreme southern and north-western part of Kigali comprising of south Kicukiro, south Gikondo and south Butamwa districts and the north-western part of Gisozi District. The second region of medium poverty incident has between 12-32% of its population poor. These are the north of Gisozi, eastern part of Kanombe, northern portions of Kicukiro, Gikondo and Butamwa districts. The third region of low poverty incident has between 4-12% of its population poor. This region consists mainly of Kacyiru, Kanombe, Nyarugenge, the northern parts of Nyamirambo and Gikondo districts, and the south of Gisozi district. The poverty pattern shows a clear urban and rural dichotomy.



http://dx.doi.org/10.4314/rj.v26i1.1
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