Abstract
This paper explores urban poverty and inequality in Kenya. We use the 2009 Kenyan population census data and estimate multidimensional poverty and inequality measures in the capital city and other secondary cities and towns. The results of our analysis show that poverty levels vary considerably across the different hierarchies of cities and towns in the country. The incidence of multidimensional poverty is relatively lower in the capital city, Nairobi (27%), and its satellite towns such as Ruiru (22%) and Thika (27%), while the figure is relatively higher in other large secondary cities such as Mombasa (44%) and Kisumu (46%). However, we also find large disparities in poverty levels within these cities/towns. For instance, location level poverty estimates in Nairobi range from more than 60% in Korogocho and Laini saba locations to less than 5% in Kileleshwa and Kilimani. Consistent with this, location-based horizontal inequality estimates are the highest in Nairobi, followed by Thika town. We also find gender gaps in poverty levels in all urban centers. In particular, individuals living in female-headed households are on average poorer than those who live in male-headed households. Our results suggest that comparing living standards across different urban centers based on average poverty estimates masks significant within-urban-center inequalities. Understanding these spatial inequalities in multidimensional poverty is crucial to honing the targeting of anti-poverty policy.
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Notes
However, according to the Kenya (2013, p. 195) the highest urban growth rate between 1999 and 2009 was due to the fact that while in 1999 only the “core urban” population was used in the analysis of urbanization, in 2009, both the “core urban” and “peri-urban” populations were used. “Core urban” refers to the central, built-up area of an urban center with intense use of land and high concentrations of services, functions, and activities. The “peri-urban” area is that beyond the central built-up area and forms the transition between urban and rural areas (Kenya 2013, p. 195).
We thank both the Kenyan National Bureau of Statistics and IPUMS for providing us with the data. We are very grateful to Bernard Obasi for helping us to identify major urban centers in the census data.
“An urban centre has been defined as a built-up and compact human settlement with a population of at least 2,000 people defined without regard to the local authority boundaries. Whereas municipal and town councils essentially consist of local urban authorities, they are administrative units whose service provision boundaries may sometimes include the surrounding rural population” (Kenya 2012, p. 13).
Although the dimensions of poverty include other indicators such as employment and income, availability of data within a single source (population census in our case) limits the number of dimensions and indicators used.
However, we have included livestock only because we do not have information on land access.
For example, let us assume we have four indicators/dimensions and four individuals with the number of deprivations for each individual being 0, 2, 4, 1 respectively. Ignoring weights for simplicity, let us assume a poverty cutoff (k) of 2. Accordingly, the second person (deprived in ½ of the indicators) and the third person (deprived in all the indicators) are considered poor. The intensity (A) can be calculated as the average proportion of deprivations that the poor people experienced: presented. A = (0.5 + 1)/2 = 0.75.
Vertical inequality measures inequality between individuals in a given society (country, region, location), while horizontal inequality measures inequality between groups of people (grouped by, e.g., race, gender, location, etc).
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Acknowledgements
This work forms part of the Governing Food Systems to Alleviate Poverty in Secondary Cities in Africa project, funded under the ESRC-DFID Joint Fund for Poverty Alleviation Research (Poverty in urban spaces theme). The support of the Economic and Social Research Council (UK) and the UK Department for International Development is gratefully acknowledged (grant number is ES/L008610/1).
Muna Shifa also acknowledges the National Research Foundation (NRF) for supporting her post-doctoral research. Murray Leibbrandt acknowledges the Research Chairs Initiative of the South African National Research Foundation and the South African Department of Science and Technology for funding his work as the Research Chair in Poverty and Inequality.
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Shifa, M., Leibbrandt, M. Urban Poverty and Inequality in Kenya. Urban Forum 28, 363–385 (2017). https://doi.org/10.1007/s12132-017-9317-0
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DOI: https://doi.org/10.1007/s12132-017-9317-0