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KEY INSIGHTS
Understanding the size and distribution of the households who rent is a key factor in targeting areas that are likely to suffer financial stress during this period of economic uncertainty. Rent is likely to be a household's single largest expense and if renters and it is likely that the measures to combat the spread of Covid-19 will have a significant negative impact on the ability of may households to make their rent payments.
Over one third of the households in Kenya, 38%, rent their accommodation, this is a total of 4.7 million households. This number is likely to be lower than the true figure as many students, who spend the majority of their time living in rented accommodation, would have been staying with family at the time of the census
Households relying on rental accommodation are heavily concentrated in urban areas and in national parks where accommodation is provided for employees
The vast majority of households that rent have private landlords 86% (4.1 million households). Private companies provide accommodation for 6% (278,613 households) of the households that rent and Parastatals, Central and County Governments provide 4.7% (220,202 households)
There are certain sub counties where the renting population appear to be dependent on a single provider of accommodation for example:
In the following Sub Counties more than 40% of the renting households rent from a private company - Laikipia North (Laikipia), Belgut (Kericho), Konoin (Bomet), Tinderet (Nandi), Nandi East (Nandi), Aberdare Forest (Murang'a). This is an area that needs exploring more as this could be indicate a concentration of a business or businesses that provide not just work but accommodation for a significant number of households
You can also see the concentrations of refugee camps with more than 40% of the renting households rent from an FBO/NGO/Church/Temple/Mosque in Turkana West (Turkana), Dadaab (Garissa)
Datasets used in this analysis have been digitised from the Kenya Population and Housing Census, Volume IV: Distribution of Population by Socio-Economic Characteristics. The data can be accessed and downloaded as spreadsheets below:
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