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Poverty continues to be one of the major concerns of economies of the day. Developing countries in particular have found it very key in their development agenda as it affects economic growth and development. The conclusion of the Millennium Development Goals has seen a shift from eradication of extreme poverty and hunger (MDG1) to the Sustainable Development Goal of ending poverty in all its forms everywhere (SDG1) by 2030. In Kenya, poverty continues to be a challenge with an average of 45.9 per cent poverty rate reported in 2005 and has faced a significance increase in the last seven years to an average of 47.8 per cent (Kenya Food Security Steering Group 2012). This study was set to identify the spatial determinants of poverty in Kenya. It investigated the link between poverty incidence and geographical conditions within rural sub-locations (administrative areas that usually contain several communities) in Kenya. As a contribution to existing research work on determinants of poverty, the study seeks to find spatial determinants of poverty in Kenya. OLS regression was used to explore the effects of spatial factors on poverty. The study used the Kenya Integrated Household Budget Survey (KIHBS) data collected in 2015/16 by the Kenya National Bureau of Statistics (KNBS) and the 2009 Kenya Population and Housing Census. The spatial analysis portion of this project used a range of spatially referenced variables describing slope, rainfall,demography and road access, all derived from GIS data layers. Land cover and land use variables were also used and were be derived from remote sensing images. The results show mixed effects of geographic variables at county versus constituency levels. Slope, burn ratio, distance to the nearest road, NDVI, type of land use, demographic and other discussed variables prove to be significant in explaining spatial patterns of poverty. However, differential influence of these and other factors at the sub-location-level shows that Constituencies in Machakos are highly heterogeneous; hence different spatial factors are important in explaining welfare levels in different areas within Constituencies, suggested targeted pro-poor policies are needed. Since the results suggest that different spatial factors are important in different constituency, the design and implementation of any poverty reduction strategies can be Constituency specific. Investments on eradicating poverty should be carried at Constituency level e.g. investment on roads, water, agriculture and in housing and settlement. |
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