ICT Usage and Ownership
Mobile phone ownership can not only be, or contribute to, a proxy indicator for individual poverty but given that any cash transfer programme is likely to exploit mobile money as a primary means of dispersal it is key in understanding the potential reach of this channel for financial support.
Over 20 million Kenyans, 47% of the population 3 years and older own a mobile phone
A higher % of men own mobile phones, 40% compared to 48% but more women own mobile phones 10.3 million men compared to 10.4 million women
The at Sub County level % ownership varies wildly from 5% in Kibish in Turkana to 75% in Westlands (this is the highest Sub County excluding the forests and national parks)
Some of those most in need may not be able to receive mobile money transfers. According to KIBHS 2016 the 3 counties with the highest % of the population living in poverty are Turkana 70%, Mandera 78% and Samburu 76%. In these 3 poorest counties only 22% of the population own a mobile phone. This leaves a population living in poverty in just the three poorest counties who do not own a mobile phone at over 1.2 million people. Whilst it is likely that the number and % of households that have access to a mobile phone is much higher it is also possible that not all of those who own mobile phones use mobile money.
In the poorest counties there may not be enough agents or liquidity to meet the needs of direct cash transfers. Whilst current county level data on distribution of mobile money agents is not available, we do know from the 2015 FinAccess geospatial mapping that these counties only contained 0.75% of agents for the country. Whilst this number has probably increased in recent years it highlights the fact that the agent network and local economy may not have the liquidity to service the high demand for cash out services that a direct cash transfer programme is likely to create.
The base population for the mobile phone ownership is those aged 3 years and over and whilst this provides a comprehensive overview of ownership it produces % figures that may appear lower than expected.
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 a spreadsheet below: