Baringo County

Exploring Kenya’s Inequality

Published by

Kenya National Bureau of Statistics Society for International Development – East Africa
P.O. Box 30266-00100 Nairobi, Kenya P.O. Box 2404-00100 Nairobi, Kenya
Email: info@knbs.or.ke Website: www.knbs.or.ke Email: sidea@sidint.org | Website: www.sidint.net

© 2013 Kenya National Bureau of Statistics (KNBS) and Society for International Development (SID)

ISBN – 978 - 9966 - 029 - 18 - 8

With funding from DANIDA through Drivers of Accountability Programme

The publication, however, remains the sole responsibility of the Kenya National Bureau of Statistics (KNBS) and the Society
for International Development (SID).

Written by: Eston Ngugi

Data and tables generation: Samuel Kipruto
Paul Samoei

Maps generation: George Matheka Kamula

Technical Input and Editing: Katindi Sivi-Njonjo
Jason Lakin

Copy Editing: Ali Nadim Zaidi

Leonard Wanyama

Design, Print and Publishing: Ascent Limited

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form, or
by any means electronic, mechanical, photocopying, recording or otherwise, without the prior express and written permission
of the publishers. Any part of this publication may be freely reviewed or quoted provided the source is duly acknowledged. It
may not be sold or used for commercial purposes or for profit.

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Table of contents
Table of contents iii

Foreword iv

Acknowledgements v

Striking features on inter-county inequalities in Kenya vi

List of Tables ix

List Annex Tables xi

List of Figures xii

Abbreviations xiii

Introduction 2

Baringo County 9

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Exploring Kenya’s Inequality

Foreword
Kenya, like all African countries, focused on poverty alleviation at independence, perhaps due to the level of
vulnerability of its populations but also as a result of the ‘trickle down’ economic discourses of the time, which
assumed that poverty rather than distribution mattered – in other words, that it was only necessary to concentrate
on economic growth because, as the country grew richer, this wealth would trickle down to benefit the poorest
sections of society. Inequality therefore had a very low profile in political, policy and scholarly discourses. In
recent years though, social dimensions such as levels of access to education, clean water and sanitation are
important in assessing people’s quality of life. Being deprived of these essential services deepens poverty and
reduces people’s well-being. Stark differences in accessing these essential services among different groups
make it difficult to reduce poverty even when economies are growing. According to the Economist (June 1, 2013),
a 1% increase in incomes in the most unequal countries produces a mere 0.6 percent reduction in poverty. In the
most equal countries, the same 1% growth yields a 4.3% reduction in poverty. Poverty and inequality are thus part
of the same problem, and there is a strong case to be made for both economic growth and redistributive policies.
From this perspective, Kenya’s quest in vision 2030 to grow by 10% per annum must also ensure that inequality
is reduced along the way and all people benefit equitably from development initiatives and resources allocated.

Since 2004, the Society for International Development (SID) and Kenya National Bureau of Statistics (KNBS) have
collaborated to spearhead inequality research in Kenya. Through their initial publications such as ‘Pulling Apart:
Facts and Figures on Inequality in Kenya,’ which sought to present simple facts about various manifestations
of inequality in Kenya, the understanding of Kenyans of the subject was deepened and a national debate on
the dynamics, causes and possible responses started. The report ‘Geographic Dimensions of Well-Being in
Kenya: Who and Where are the Poor?’ elevated the poverty and inequality discourse further while the publication
‘Readings on Inequality in Kenya: Sectoral Dynamics and Perspectives’ presented the causality, dynamics and
other technical aspects of inequality.

KNBS and SID in this publication go further to present monetary measures of inequality such as expenditure
patterns of groups and non-money metric measures of inequality in important livelihood parameters like
employment, education, energy, housing, water and sanitation to show the levels of vulnerability and patterns of
unequal access to essential social services at the national, county, constituency and ward levels.
We envisage that this work will be particularly helpful to county leaders who are tasked with the responsibility
of ensuring equitable social and economic development while addressing the needs of marginalized groups
and regions. We also hope that it will help in informing public engagement with the devolution process and
be instrumental in formulating strategies and actions to overcome exclusion of groups or individuals from the
benefits of growth and development in Kenya.

It is therefore our great pleasure to present ‘Exploring Kenya’s inequality: Pulling apart or pooling together?’

Ali Hersi
Society for International Development (SID)
Regional Director

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Acknowledgements
Kenya National Bureau of Statistics (KNBS) and Society for International Development (SID) are grateful
to all the individuals directly involved in the publication of ‘Exploring Kenya’s Inequality: Pulling Apart or
Pulling Together?’ books. Special mention goes to Zachary Mwangi (KNBS, Ag. Director General) and
Ali Hersi (SID, Regional Director) for their institutional leadership; Katindi Sivi-Njonjo (SID, Progrmme
Director) and Paul Samoei (KNBS) for the effective management of the project; Eston Ngugi; Tabitha
Wambui Mwangi; Joshua Musyimi; Samuel Kipruto; George Kamula; Jason Lakin; Ali Zaidi; Leonard
Wanyama; and Irene Omari for the different roles played in the completion of these publications.

KNBS and SID would like to thank Bernadette Wanjala (KIPPRA), Mwende Mwendwa (KIPPRA), Raphael
Munavu (CRA), Moses Sichei (CRA), Calvin Muga (TISA), Chrispine Oduor (IEA), John T. Mukui, Awuor
Ponge (IPAR, Kenya), Othieno Nyanjom, Mary Muyonga (SID), Prof. John Oucho (AMADPOC), Ms. Ada
Mwangola (Vision 2030 Secretariat), Kilian Nyambu (NCIC), Charles Warria (DAP), Wanjiru Gikonyo
(TISA) and Martin Napisa (NTA), for attending the peer review meetings held on 3rd October 2012 and
Thursday, 28th Feb 2013 and for making invaluable comments that went into the initial production and
the finalisation of the books. Special mention goes to Arthur Muliro, Wambui Gathathi, Con Omore,
Andiwo Obondoh, Peter Gunja, Calleb Okoyo, Dennis Mutabazi, Leah Thuku, Jackson Kitololo, Yvonne
Omwodo and Maureen Bwisa for their institutional support and administrative assistance throughout the
project. The support of DANIDA through the Drivers of Accountability Project in Kenya is also gratefully
acknowledged.

Stefano Prato
Managing Director,
SID

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Exploring Kenya’s Inequality

Striking Features on Intra-County Inequality

in Kenya
Inequalities within counties in all the variables are extreme. In many cases, Kenyans living within a
single county have completely different lifestyles and access to services.

Income/expenditure inequalities
1. The five counties with the worst income inequality (measured as a ratio of the top to the bottom
decile) are in Coast. The ratio of expenditure by the wealthiest to the poorest is 20 to one and above
in Lamu, Tana River, Kwale, and Kilifi. This means that those in the top decile have 20 times as much
expenditure as those in the bottom decile. This is compared to an average for the whole country of
nine to one.
2. Another way to look at income inequality is to compare the mean expenditure per adult across
wards within a county. In 44 of the 47 counties, the mean expenditure in the poorest wards is less
than 40 percent the mean expenditure in the wealthiest wards within the county. In both Kilifi and
Kwale, the mean expenditure in the poorest wards (Garashi and Ndavaya, respectively) is less than
13 percent of expenditure in the wealthiest ward in the county.
3. Of the five poorest counties in terms of mean expenditure, four are in the North (Mandera, Wajir,
Turkana and Marsabit) and the last is in Coast (Tana River). However, of the five most unequal
counties, only one (Marsabit County) is in the North (looking at ratio of mean expenditure in richest
to poorest ward). The other four most unequal counties by this measure are: Kilifi, Kwale, Kajiado
and Kitui.
4. If we look at Gini coefficients for the whole county, the most unequal counties are also in Coast:
Tana River (.631), Kwale (.604), and Kilifi (.570).
5. The most equal counties by income measure (ratio of top decile to bottom) are: Narok, West Pokot,
Bomet, Nandi and Nairobi. Using the ratio of average income in top to bottom ward, the five most
equal counties are: Kirinyaga, Samburu, Siaya, Nyandarua, Narok.

Access to Education
6. Major urban areas in Kenya have high education levels but very large disparities. Mombasa, Nairobi
and Kisumu all have gaps between highest and lowest wards of nearly 50 percentage points in
share of residents with secondary school education or higher levels.
7. In the 5 most rural counties (Baringo, Siaya, Pokot, Narok and Tharaka Nithi), education levels
are lower but the gap, while still large, is somewhat lower than that espoused in urban areas. On
average, the gap in these 5 counties between wards with highest share of residents with secondary
school or higher and those with the lowest share is about 26 percentage points.
8. The most extreme difference in secondary school education and above is in Kajiado County where
the top ward (Ongata Rongai) has nearly 59 percent of the population with secondary education
plus, while the bottom ward (Mosiro) has only 2 percent.
9. One way to think about inequality in education is to compare the number of people with no education

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to those with some education. A more unequal county is one that has large numbers of both. Isiolo
is the most unequal county in Kenya by this measure, with 51 percent of the population having
no education, and 49 percent with some. This is followed by West Pokot at 55 percent with no
education and 45 percent with some, and Tana River at 56 percent with no education and 44 with
some.

Access to Improved Sanitation

10. Kajiado County has the highest gap between wards with access to improved sanitation. The best
performing ward (Ongata Rongai) has 89 percent of residents with access to improved sanitation
while the worst performing ward (Mosiro) has 2 percent of residents with access to improved
sanitation, a gap of nearly 87 percentage points.
11. There are 9 counties where the gap in access to improved sanitation between the best and worst
performing wards is over 80 percentage points. These are Baringo, Garissa, Kajiado, Kericho, Kilifi,
Machakos, Marsabit, Nyandarua and West Pokot.

Access to Improved Sources of Water

12. In all of the 47 counties, the highest gap in access to improved water sources between the county
with the best access to improved water sources and the least is over 45 percentage points. The
most severe gaps are in Mandera, Garissa, Marsabit, (over 99 percentage points), Kilifi (over 98
percentage points) and Wajir (over 97 percentage points).

Access to Improved Sources of Lighting

13. The gaps within counties in access to electricity for lighting are also enormous. In most counties
(29 out of 47), the gap between the ward with the most access to electricity and the least access
is more than 40 percentage points. The most severe disparities between wards are in Mombasa
(95 percentage point gap between highest and lowest ward), Garissa (92 percentage points), and
Nakuru (89 percentage points).

Access to Improved Housing

14. The highest extreme in this variable is found in Baringo County where all residents in Silale ward live
in grass huts while no one in Ravine ward in the same county lives in grass huts.

Overall ranking of the variables

15. Overall, the counties with the most income inequalities as measured by the gini coefficient are Tana
River, Kwale, Kilifi, Lamu, Migori and Busia. However, the counties that are consistently mentioned
among the most deprived hence have the lowest access to essential services compared to others
across the following nine variables i.e. poverty, mean household expenditure, education, work for
pay, water, sanitation, cooking fuel, access to electricity and improved housing are Mandera (8
variables), Wajir (8 variables), Turkana (7 variables) and Marsabit (7 variables).

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Abbreviations
AMADPOC African Migration and Development Policy Centre

CRA Commission on Revenue Allocation

DANIDA Danish International Development Agency

DAP Drivers of Accountability Programme

EAs Enumeration Areas

HDI Human Development Index

IBP International Budget Partnership

IEA Institute of Economic Affairs

IPAR Institute of Policy Analysis and Research

KIHBS Kenya Intergraded Household Budget Survey

KIPPRA Kenya Institute for Public Policy Research and Analysis

KNBS Kenya National Bureau of Statistics

LPG Liquefied Petroleum Gas

NCIC National Cohesion and Integration Commission

NTA National Taxpayers Association

PCA Principal Component Analysis

SAEs Small Area Estimation

SID Society for International Development

TISA The Institute for Social Accountability

VIP latrine Ventilated-Improved Pit latrine

VOCs Volatile Organic Carbons

WDR World Development Report

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Introduction
Background
For more than half a century many people in the development sector in Kenya have worked at alleviating
extreme poverty so that the poorest people can access basic goods and services for survival like food,
safe drinking water, sanitation, shelter and education. However when the current national averages are
disaggregated there are individuals and groups that still lag too behind. As a result, the gap between
the rich and the poor, urban and rural areas, among ethnic groups or between genders reveal huge
disparities between those who are well endowed and those who are deprived.

According to the world inequality statistics, Kenya was ranked 103 out of 169 countries making it the
66th most unequal country in the world. Kenya’s Inequality is rooted in its history, politics, economics
and social organization and manifests itself in the lack of access to services, resources, power, voice
and agency. Inequality continues to be driven by various factors such as: social norms, behaviours and
practices that fuel discrimination and obstruct access at the local level and/ or at the larger societal
level; the fact that services are not reaching those who are most in need of them due to intentional or
unintentional barriers; the governance, accountability, policy or legislative issues that do not favor equal
opportunities for the disadvantaged; and economic forces i.e. the unequal control of productive assets
by the different socio-economic groups.

According to the 2005 report on the World Social Situation, sustained poverty reduction cannot be
achieved unless equality of opportunity and access to basic services is ensured. Reducing inequality
must therefore be explicitly incorporated in policies and programmes aimed at poverty reduction. In
addition, specific interventions may be required, such as: affirmative action; targeted public investments
in underserved areas and sectors; access to resources that are not conditional; and a conscious effort
to ensure that policies and programmes implemented have to provide equitable opportunities for all.

This chapter presents the basic concepts on inequality and poverty, methods used for analysis,
justification and choice of variables on inequality. The analysis is based on the 2009 Kenya housing
and population census while the 2006 Kenya integrated household budget survey is combined with
census to estimate poverty and inequality measures from the national to the ward level. Tabulation of
both money metric measures of inequality such as mean expenditure and non-money metric measures
of inequality in important livelihood parameters like, employment, education, energy, housing, water
and sanitation are presented. These variables were selected from the census data and analyzed in
detail and form the core of the inequality reports. Other variables such as migration or health indicators
like mortality, fertility etc. are analyzed and presented in several monographs by Kenya National Bureau
of Statistics and were therefore left out of this report.

Methodology
Gini-coefficient of inequality
This is the most commonly used measure of inequality. The coefficient varies between ‘0’, which reflects
complete equality and ‘1’ which indicates complete inequality. Graphically, the Gini coefficient can be

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easily represented by the area between the Lorenz curve and the line of equality. On the figure below,
the Lorenz curve maps the cumulative income share on the vertical axis against the distribution of the
population on the horizontal axis. The Gini coefficient is calculated as the area (A) divided by the sum
of areas (A and B) i.e. A/(A+B). If A=0 the Gini coefficient becomes 0 which means perfect equality,
whereas if B=0 the Gini coefficient becomes 1 which means complete inequality. Let xi be a point on
the X-axis, and yi a point on the Y-axis, the Gini coefficient formula is:

N
Gini = 1 − ∑ ( xi − xi −1 )( y i + y i −1 ) .
i =1
An Illustration of the Lorenz Curve

LORENZ CURVE
100
90
Cumulative % of Expenditure

80
70
60
50
40
A
30
B
20
10
0
0 10 20 30 40 50 60 70 80 90 100
Cumulative % of Population

Small Area Estimation (SAE)

The small area problem essentially concerns obtaining reliable estimates of quantities of interest —
totals or means of study variables, for example — for geographical regions, when the regional sample
sizes are small in the survey data set. In the context of small area estimation, an area or domain
becomes small when its sample size is too small for direct estimation of adequate precision. If the
regional estimates are to be obtained by the traditional direct survey estimators, based only on the
sample data from the area of interest itself, small sample sizes lead to undesirably large standard errors
for them. For instance, due to their low precision the estimates might not satisfy the generally accepted
publishing criteria in official statistics. It may even happen that there are no sample members at all from
some areas, making the direct estimation impossible. All this gives rise to the need of special small area
estimation methodology.

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Most of KNBS surveys were designed to provide statistically reliable, design-based estimates only at
the national, provincial and district levels such as the Kenya Intergraded Household Budget Survey
of 2005/06 (KIHBS). The sheer practical difficulties and cost of implementing and conducting sample
surveys that would provide reliable estimates at levels finer than the district were generally prohibitive,
both in terms of the increased sample size required and in terms of the added burden on providers of
survey data (respondents). However through SAE and using the census and other survey datasets,
accurate small area poverty estimates for 2009 for all the counties are obtainable.

The sample in the 2005/06 KIHBS, which was a representative subset of the population, collected
detailed information regarding consumption expenditures. The survey gives poverty estimate of urban
and rural poverty at the national level, the provincial level and, albeit with less precision, at the district
level. However, the sample sizes of such household surveys preclude estimation of meaningful poverty
measures for smaller areas such as divisions, locations or wards. Data collected through censuses
are sufficiently large to provide representative measurements below the district level such as divisions,
locations and sub-locations. However, this data does not contain the detailed information on consumption
expenditures required to estimate poverty indicators. In small area estimation methodology, the first step
of the analysis involves exploring the relationship between a set of characteristics of households and
the welfare level of the same households, which has detailed information about household expenditure
and consumption. A regression equation is then estimated to explain daily per capita consumption
and expenditure of a household using a number of socio-economic variables such as household size,
education levels, housing characteristics and access to basic services.

While the census does not contain household expenditure data, it does contain these socio-economic
variables. Therefore, it will be possible to statistically impute household expenditures for the census
households by applying the socio-economic variables from the census data on the estimated
relationship based on the survey data. This will give estimates of the welfare level of all households
in the census, which in turn allows for estimation of the proportion of households that are poor and
other poverty measures for relatively small geographic areas. To determine how many people are
poor in each area, the study would then utilize the 2005/06 monetary poverty lines for rural and urban
households respectively. In terms of actual process, the following steps were undertaken:

Cluster Matching: Matching of the KIHBS clusters, which were created using the 1999 Population and
Housing Census Enumeration Areas (EA) to 2009 Population and Housing Census EAs. The purpose
was to trace the KIBHS 2005/06 clusters to the 2009 Enumeration Areas.

Zero Stage: The first step of the analysis involved finding out comparable variables from the survey
(Kenya Integrated Household Budget 2005/06) and the census (Kenya 2009 Population and Housing
Census). This required the use of the survey and census questionnaires as well as their manuals.

First Stage (Consumption Model): This stage involved the use of regression analysis to explore the
relationship between an agreed set of characteristics in the household and the consumption levels of
the same households from the survey data. The regression equation was then used to estimate and
explain daily per capita consumption and expenditure of households using socio-economic variables

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such as household size, education levels, housing characteristics and access to basic services, and
other auxiliary variables. While the census did not contain household expenditure data, it did contain
these socio-economic variables.

Second Stage (Simulation): Analysis at this stage involved statistical imputation of household
expenditures for the census households, by applying the socio-economic variables from the census
data on the estimated relationship based on the survey data.

Identification of poor households Principal Component Analysis (PCA)

In order to attain the objective of the poverty targeting in this study, the household needed to be
established. There are three principal indicators of welfare; household income; household consumption
expenditures; and household wealth. Household income is the theoretical indicator of choice of welfare/
economic status. However, it is extremely difficult to measure accurately due to the fact that many
people do not remember all the sources of their income or better still would not want to divulge this
information. Measuring consumption expenditures has many drawbacks such as the fact that household
consumption expenditures typically are obtained from recall method usually for a period of not more
than four weeks. In all cases a well planned and large scale survey is needed, which is time consuming
and costly to collect. The estimation of wealth is a difficult concept due to both the quantitative as well
as the qualitative aspects of it. It can also be difficult to compute especially when wealth is looked at as
both tangible and intangible.

Given that the three main indicators of welfare cannot be determined in a shorter time, an alternative
method that is quick is needed. The alternative approach then in measuring welfare is generally through
the asset index. In measuring the asset index, multivariate statistical procedures such the factor analysis,
discriminate analysis, cluster analysis or the principal component analysis methods are used. Principal
components analysis transforms the original set of variables into a smaller set of linear combinations
that account for most of the variance in the original set. The purpose of PCA is to determine factors (i.e.,
principal components) in order to explain as much of the total variation in the data as possible.

In this project the principal component analysis was utilized in order to generate the asset (wealth)
index for each household in the study area. The PCA can be used as an exploratory tool to investigate
patterns in the data; in identify natural groupings of the population for further analysis and; to reduce
several dimensionalities in the number of known dimensions. In generating this index information from
the datasets such as the tenure status of main dwelling units; roof, wall, and floor materials of main
dwelling; main source of water; means of human waste disposal; cooking and lighting fuels; household
items such radio TV, fridge etc was required. The recent available dataset that contains this information
for the project area is the Kenya Population and Housing Census 2009.

There are four main approaches to handling multivariate data for the construction of the asset index
in surveys and censuses. The first three may be regarded as exploratory techniques leading to index
construction. These are graphical procedures and summary measures. The two popular multivariate
procedures - cluster analysis and principal component analysis (PCA) - are two of the key procedures
that have a useful preliminary role to play in index construction and lastly regression modeling approach.

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Exploring Kenya’s Inequality

In the recent past there has been an increasing routine application of PCA to asset data in creating
welfare indices (Gwatkin et al. 2000, Filmer and Pritchett 2001 and McKenzie 2003).

Concepts and definitions

Inequality
Inequality is characterized by the existence of unequal opportunities or life chances and unequal
conditions such as incomes, goods and services. Inequality, usually structured and recurrent, results
into an unfair or unjust gap between individuals, groups or households relative to others within a
population. There are several methods of measuring inequality. In this study, we consider among
other methods, the Gini-coefficient, the difference in expenditure shares and access to important basic
services.

Equality and Equity

Although the two terms are sometimes used interchangeably, they are different concepts. Equality
requires all to have same/ equal resources, while equity requires all to have the same opportunity to
access same resources, survive, develop, and reach their full potential, without discrimination, bias, or
favoritism. Equity also accepts differences that are earned fairly.

Poverty
The poverty line is a threshold below which people are deemed poor. Statistics summarizing the bottom
of the consumption distribution (i.e. those that fall below the poverty line) are therefore provided. In
2005/06, the poverty line was estimated at Ksh1,562 and Ksh2,913 per adult equivalent1 per month
for rural and urban households respectively. Nationally, 45.2 percent of the population lives below the
poverty line (2009 estimates) down from 46 percent in 2005/06.

Spatial Dimensions
The reason poverty can be considered a spatial issue is two-fold. People of a similar socio-economic
background tend to live in the same areas because the amount of money a person makes usually, but
not always, influences their decision as to where to purchase or rent a home. At the same time, the area
in which a person is born or lives can determine the level of access to opportunities like education and
employment because income and education can influence settlement patterns and also be influenced
by settlement patterns. They can therefore be considered causes and effects of spatial inequality and
poverty.

Employment
Access to jobs is essential for overcoming inequality and reducing poverty. People who cannot access
productive work are unable to generate an income sufficient to cover their basic needs and those of
their families, or to accumulate savings to protect their households from the vicissitudes of the economy.
The unemployed are therefore among the most vulnerable in society and are prone to poverty. Levels
1
This is basically the idea that every person needs different levels of consumption because of their age, gender, height,
weight, etc. and therefore we take this into account to create an adult equivalent based on the average needs of the different
populations

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and patterns of employment and wages are also significant in determining degrees of poverty and
inequality. Macroeconomic policy needs to emphasize the need for increasing regular good quality
‘work for pay’ that is covered by basic labour protection. The population and housing census 2009
included questions on labour and employment for the population aged 15-64.

The census, not being a labour survey, only had few categories of occupation which included work
for pay, family business, family agricultural holdings, intern/volunteer, retired/home maker, full time
student, incapacitated and no work. The tabulation was nested with education- for none, primary and
secondary level.

Education
Education is typically seen as a means of improving people’s welfare. Studies indicate that inequality
declines as the average level of educational attainment increases, with secondary education producing
the greatest payoff, especially for women (Cornia and Court, 2001). There is considerable evidence
that even in settings where people are deprived of other essential services like sanitation or clean
water, children of educated mothers have much better prospects of survival than do the children of
uneducated mothers. Education is therefore typically viewed as a powerful factor in leveling the field of
opportunity as it provides individuals with the capacity to obtain a higher income and standard of living.
By learning to read and write and acquiring technical or professional skills, people increase their chances
of obtaining decent, better-paying jobs. Education however can also represent a medium through
which the worst forms of social stratification and segmentation are created. Inequalities in quality and
access to education often translate into differentials in employment, occupation, income, residence and
social class. These disparities are prevalent and tend to be determined by socio-economic and family
background. Because such disparities are typically transmitted from generation to generation, access
to educational and employment opportunities are to a certain degree inherited, with segments of the
population systematically suffering exclusion. The importance of equal access to a well-functioning
education system, particularly in relation to reducing inequalities, cannot be overemphasized.

Water
According to UNICEF (2008), over 1.1 billion people lack access to an improved water source and over
three million people, mostly children, die annually from water-related diseases. Water quality refers
to the basic and physical characteristics of water that determines its suitability for life or for human
uses. The quality of water has tremendous effects on human health both in the short term and in the
long term. As indicated in this report, slightly over half of Kenya’s population has access to improved
sources of water.

Sanitation
Sanitation refers to the principles and practices relating to the collection, removal or disposal of human
excreta, household waste, water and refuse as they impact upon people and the environment. Decent
sanitation includes appropriate hygiene awareness and behavior as well as acceptable, affordable and
sustainable sanitation services which is crucial for the health and wellbeing of people. Lack of access
to safe human waste disposal facilities leads to higher costs to the community through pollution of

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rivers, ground water and higher incidence of air and water borne diseases. Other costs include reduced
incomes as a result of disease and lower educational outcomes.

Nationally, 61 percent of the population has access to improved methods of waste disposal. A sizeable
population i.e. 39 percent of the population is disadvantaged. Investments made in the provision of
safe water supplies need to be commensurate with investments in safe waste disposal and hygiene
promotion to have significant impact.

Housing Conditions (Roof, Wall and Floor)

Housing conditions are an indicator of the degree to which people live in humane conditions. Materials
used in the construction of the floor, roof and wall materials of a dwelling unit are also indicative of the
extent to which they protect occupants from the elements and other environmental hazards. Housing
conditions have implications for provision of other services such as connections to water supply,
electricity, and waste disposal. They also determine the safety, health and well being of the occupants.
Low provision of these essential services leads to higher incidence of diseases, fewer opportunities
for business services and lack of a conducive environment for learning. It is important to note that
availability of materials, costs, weather and cultural conditions have a major influence on the type of
materials used.

Energy fuel for cooking and lighting

Lack of access to clean sources of energy is a major impediment to development through health related
complications such as increased respiratory infections and air pollution. The type of cooking fuel or
lighting fuel used by households is related to the socio-economic status of households. High level
energy sources are cleaner but cost more and are used by households with higher levels of income
compared with primitive sources of fuel like firewood which are mainly used by households with a lower
socio-economic profile. Globally about 2.5 billion people rely on biomass such as fuel-wood, charcoal,
agricultural waste and animal dung to meet their energy needs for cooking.

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Baringo County

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Baringo County

Figure 1.1: Baringo Population Pyramid

Figure 1.1: Baringo Population Pyramid

Baringo
65+
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
20 15 10 5 0 5 10 15 20

Female Male

Population
Baringo County has a child rich population structure where 0-14 year olds constitute 49% of the total population.
This is due to high fertility rates among women as demonstrated by the percentage household size of 4-6 at 38%.

Employment
The 2009 population and housing census covered in brief the labour status as tabulated below. The main variable
of interest for inequality discussed in the text is work for pay by level of education. The other variables, notably
family business, family agricultural holdings, intern/volunteer, retired/homemaker, fulltime student, incapacitated
and no work are tabulated and presented in the annex table 1.3 up to ward level.

Table1: Overall Employment by Education Levels in Baringo County

Family
Work for Family Agricultural Intern/ Retired/ Fulltime Number of
Education Level pay Business Holding Volunteer Homemaker Student Incapacitated No work Individuals

Total 15.1 10.6 35.9 0.9 14.2 14.4 0.5 8.3 263,734

None 4.7 11.6 55.2 0.7 20.2 0.2 1.0 6.5 67,711

Primary 13.6 10.4 34.4 0.9 14.0 17.6 0.4 8.8 117,138

Secondary+ 26.4 10.1 21.8 1.2 9.2 22.0 0.2 9.1 78,885

In Baringo County, 5% with no formal education, 14% with primary education and 26%with a secondary level of
education or above are working for pay. Work for pay is highest in Nairobi at 49%, which is almost twice the level
of work for pay in Baringo for those with a secondary level of education or above.

10 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Gini Coefficient
In this report, the Gini index measures the extent to which the distribution of consumption expenditure among
individuals or households within an economy deviates from a perfectly equal distribution. A Gini index of ‘0’
represents perfect equality, while an index of ‘1’ implies perfect inequality. Baringo County’s Gini index is 0.356
compared with Turkana County, which has the least inequality nationally (0.283).

Figure 1.2: Baringo County-Gini Coefficient by Ward

Education
In Baringo County, 16 percent of residents have a secondary level of education or above. Baringo Central is the
constituency with the highest share of residents with a secondary level of education or above at 27%. This is nine
times Tiaty constituency, which has the lowest share of residents with a secondary level of education or above.
Baringo Central constituency is therefore 11 percentage points above the county average. Kapropita ward has
the highest share of residents with a secondary level of education or above at 34%. This is 34 percentage points
above Silale ward, which has the lowest share of residents with a secondary level of education or above. Kapro-
pita ward is 18percentage points above the county average.

The proportion of Baringo County residents who only have a primary education stands at 48%.Baringo North
constituency has the highest share of residents with a primary education only at 60%. This is four times Tiaty
constituency, which has the lowest share of residents with a primary education. Baringo North constituency is 12
percentage points above the county average. Lembus ward has the highest share of residents with primary ed-
ucation only at 64%. This is 32 times Silale ward, which has the lowest share of residents with primary education
only. Lembus ward is 16 percentage points above the county average.

The share of Baringo County residents with no formal education is at 36%.Tiaty constituency has the highest
share of residents with no formal education at 82%. This is five times the number in Baringo Central constituen-
cy, which has the lowest share of residents with no formal education. Tiaty constituency is 46 percentage points

11
Exploring Kenya’s Inequality

above the county average. Silale ward has the highest percentage of residents with no formal education at 98%.
This is seven times more than Kabartonjo ward, which has the lowest share of residents with no formal education.
Silale ward is therefore 62 percentage points above the county average.

Figure 1.3: Baringo County-Percentage of Population by Education attainment by Ward

Percentage of Population by Education

Attainment - Ward Level - Baringo County

TIRIOKO

KOLLOWA

SILALE
RIBKWO
LOIYAMOROK
BARTABWA

TANGULBEI/KOROSSI
SAIMO/KIPSARAM CHURO/AMAYA
BARWESSA

SAIMO/SOI
MUKUTAN
KABARTONJO ILCHAMUS
KABARNET Location of Baringo
County in Kenya

KAPROPITA

SACHO MARIGAT

MOCHONGOI

TENGES EMINING
KISANANA

Legend LEMBUS KWEN

County Boundary
None
Primary
Secondary and above
Water Bodies
³ LEMBUS

MUMBERES/MAJI MAZURI
RAVINE MOGOTIO
LEMBUS/PERKERRA

KOIBATEK

0 12.5 25 50 Kilometers

Energy
Cooking Fuel
Figure 1.4: Percentage Distribution of Households by Source of Cooking Fuel in Baringo County

Figure 1.4: Percentage Distribution of Households by Source of Cooking Fuel in Baringo County

100.0
86.5

80.0
Percentage

60.0

40.0

20.0
11.4
0.2 1.0 0.5 0.3 0.0 0.1

Electricty Paraffin LPG Biogas Firewood Charcoal Solar Other

12 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Only 1%of residents in Baringo County use liquefied petroleum gas (LPG), and another 1% use paraffin. A full 87%
of the residents use firewood and 11% use charcoal. Firewood is the most common cooking fuel by either gender;
with 86% of male headed households and 88% of female headed households using the resource.

Tiaty constituency has the highest level of firewood use in Baringo County at 97%.This is 21 percentage points
above Eldama Ravine, which has the lowest level of firewood use at 76%. Tiaty constituency is 10 percentage
points above the county average of firewood use. Tirioko and Silale wards have the highest levels of firewood
use in Baringo County at 99% each. This is 56 percentage points above the level of Ravine ward, which has the
lowest share of firewood usage. Tirioko and Silale wards are 12 percentage points above the county average of
firewood use.

Eldama Ravine constituency has the highest level of charcoal use in Baringo County at 21%. This is 11 times
the level of Tiaty constituency, which has the lowest share. Eldama Ravine constituency is 10 percentage points
above the county average. Ravine ward has the highest level of charcoal use in Baringo County at 49%. This is 49
percentage points more than the level in Silale ward, which has the lowest share. Ravine ward is 38 percentage
points above the county average.

Lighting
Figure 1.5: Percentage Distribution of Households by Source of Lighting Fuel in Baringo County

Figure 1.5: Percentage Distribution of Households by Source of Lighting Fuel in Baringo County

50.0

40.0
39.3
Percentage

30.0 27.9

20.1
20.0

10.0 9.3

0.2 0.4 1.7 0.4

0.7

Electricty Pressure Lamp Lantern Tin Lamp Gas Lamp Fuelwood Solar Other

Only 9% of residents in Baringo County use electricity as their main source of lighting. A further 39% use lanterns,
and 20% use tin lamps, while 28% use fuel wood. In terms of gender, electricity use is almost equal with 10% of
male headed households using it as compared with 9% of female headed households.

Baringo Central constituency has the highest level of electricity use at 24%.This is 23 percentage points above
Tiaty constituency, which has the lowest level of electricity use. Baringo Central constituency is 15 percentage
points above the county average. Kapropita ward has the highest level of electricity use at 42%. Kapropita is there-
fore 42 percentage points above Silale, Tangulbei/Korossi and Churo/Amaya wards that have the lowest levels of
electricity use. Kapropita ward is 33 percentage points above the county average.

13
Exploring Kenya’s Inequality

Housing
Flooring
Figure 1.6: Percentage Distribution of Households by Floor Material in Baringo County

Figure 1.6: Percentage Distribution of Households by Floor Material in Baringo County

80.0

73.1
70.0

60.0

50.0
Percentage

40.0

30.0
24.5

20.0

10.0

0.2 0.3 1.7 0.4

Cement Tiles Wood Earth Other

n Baringo County, 25% of the residents have homes with cement floors, while 73% have earth floors. Less than 1%
has tile floors and 2% have wood floors. Baringo Central constituency has the highest share of cement floors at
46%.This is 42 percentage points above Tiaty constituency, which has the lowest share of cement floors. Baringo
Central constituency is 21 percentage points above the county average of people with cement floors. Kapropita
ward has the highest share of cement floors at 63%.This is 63 percentage points above Silale ward, which has
the lowest share of cement floors. Kapropita ward is 38 percentage points above the county average of homes
with cement floors.

Roofing
Figure 1.7: Percentage Distribution of Households by Roof Material in Baringo County

Figure 1.7: Percentage Distribution of Households by Roof Material in Baringo County

70.0

60.0
57.5

50.0

40.0 39.1
Percentage

30.0

20.0

10.0

0.2 1.0 0.1 1.5 0.1 0.1 0.5

0.2

Corrugated Tiles Concrete Asbestos Grass Makuti Tin Mud/Dung Other

Iron sheets Sheets

14 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Baringo County has less than 1% of its residents homes constructed with concrete roofs, while 58% have corru-
gated iron sheet roofing. Grass thatch and makuti roofs constitute 39% of homes, and less than 1% of roofs are
constructed using mud/dung.

Eldama Ravine constituency has the highest share of corrugated iron sheet roofing at 83%.This is 10 times Tiaty
constituency, which has the lowest share of corrugated iron sheet roofs. Eldama Ravine constituency is 25 per-
centage points above the county average of homes with corrugated iron sheet roofs.Ravine ward has the highest
share of corrugated iron sheet roofs at 92%. It is thus 91 percentage points above Silale ward, which has the
lowest share of corrugated iron sheet roofs. Ravine ward is 34 percentage points above the county average of
homes with corrugated iron sheets roofs.

Tiaty constituency has the highest share of grass/makuti roofs at 92%. This is eight times the share of Eldama
Ravine constituency, which has the lowest share of grass/makuti roofs. Tiaty constituency is 53 percentage points
above the county average of grass/makuti roofing. All the roofing in Silale ward is of grass/makuti roofs, a share of
100%. This is 99 percentage points above Ravine ward, which has the lowest share. Silale ward is 60 percentage
points above the county average of grass/makuti roofing.

Walls
Figure 1.8: Percentage Distribution of Households by Wall Material in Baringo County

Figure 1.8:Percentage Distribution of Households by Wall Material in Baringo County

60.0

50.6
50.0

40.0
Percentage

30.0
25.8

20.0

10.0
6.2 6.5
5.1
3.5
0.2 1.6 0.1 0.8

Stone Brick/Block Mud/Wood Mud/Cement Wood only Coorugated Grass/Reeds Tin Other
Ironsheets

Baringo County has 9% of its homes built of either brick or stone walls. Some 57% of homes in the county have
mud/wood or mud/cement walls. Walls made of wood comprise 26% of structures and corrugated iron sheet
walls are 7%, grass/thatched walls are at 2% while 1% are made of tin or other materials.

Baringo Central and Eldama Ravine constituencies are equal in having the highest share of brick/stone walls at
15% each. This is five times Tiaty constituency, which has the lowest share of brick/stone walls. Baringo Central
and Eldama Ravine constituencies are 6 percentage points above the county average of housing constructed
with brick/stone walls. Lembus/Perkerra ward has the highest share of brick/stone walls at 30%. This puts it 29
percentage points above Silale ward, which has the lowest share of brick/stone walls. Lembus/Perkerra ward is
21 percentage points above the county average of housing constructed with brick/stone walls.

Mogotio constituency has the highest share of mud with wood/cement walls at 77%. That puts it 35 percentage
points above Eldama Ravine constituency, which has the lowest share of mud with wood/cement. Mogotio con-
stituency is 20 percentage points above the county average of housing having mud with wood/cement walls.
Churo/Amaya ward has the highest share of mud with wood/cement walls at 97%. This is almost four times the
share of Mumberes/Maji Mazuri ward, which has the lowest share of mud with wood/cement walls. Churo/Amaya
ward is 40 percentage points above the county average of housing having mud with wood/cement walls.

15
Exploring Kenya’s Inequality

Water
Improved sources of water comprise protected spring, protected well, borehole, piped into dwelling, piped and
rainwater collection while unimproved sources include pond, dam, lake, stream/river, unprotected spring, unpro-
tected well, jabia, water vendor and others.

In Baringo County, 24% of residents use improved sources of water, while the rest rely on unimproved sources.
There is no significant gender differential as 24% of male headed households and 23% of female headed house-
holds use improved sources.

Eldama Ravine constituency has the highest share of residents using improved sources of water at 46%. This
is four times Tiaty constituency, which has the lowest share of improved water source usage. Eldama Ravine
constituency is 22 percentage points above the county average of residents using improved sources of water.
Ravine ward has the highest share of residents using improved sources of water at 84%. This is 83 percentage
points more than Silale ward, which has the lowest share of households using improved sources of water, and 60
percentage points above the county average of residents using improved sources of water.

Figure 1.9: Baringo County-Percentage of Households with Improved and Unimproved Sources of
Water by Ward

16 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Sanitation
In Baringo County, 39% of residents use improved sanitation facilities, while the rest use unimproved sanitation
facilities. The use of improved sanitation is slightly higher in male headed households at 40% compared with
female headed households at 38%.

Baringo Central constituency has the highest share of residents using improved sanitation facilities at 69%. This
is 17 times higher than Tiaty constituency, which has the lowest share of households using improved sanitation.
Baringo Central constituency is 30 percentage points above the county average of households using improved
sanitation facilities. Ravine ward has the highest share of residents using improved sanitation at 84%. This is 83
percentage points above Silale ward, which has the lowest share of households using improved sanitation. Ra-
vine ward is 45 percentage points above the county average of households using improved sanitation facilities.

Figure 1.10: Baringo County – Percentage of Households with Improved and Unimproved
Sanitation by Ward

Percentage of Households with Improved and Unimproved

Sanitation - Ward Level - Baringo County

TIRIOKO

KOLLOWA

SILALE
RIBKWO

LOIYAMOROK
BARTABWA

CHURO/AMAYA
BARWESSA

TANGULBEI/KOROSSI

SAIMO/SOI
KABARTONJO MUKUTAN
ILCHAMUS
KABARNET Location of Baringo
County in Kenya

KAPROPITA

SACHO MARIGAT

TENGES
MOCHONGOI

EMINING
KISANANA

LEMBUS LEMBUS/PERKERRA

³
Legend MOGOTIO
LEMBUS KWEN
County Boundary
Improved Sanitation MUMBERES/MAJI MAZURI
RAVINE
Unimproved Sanitation
Water Bodies KOIBATEK

0 12.5 25 50 Kilometers

Baringo County Annex Tables

17
 1. Baringo

18
Table 1.1: Gender, Age group, Demographic Indicators and Households Size by County, Constituency and Ward

County/Constitu- Gender Age group Demographic indicators Proportion of HH Members:

ency/Ward
Total Pop Male Female 0-5 yrs 0-14 yrs 10-18 yrs 15-34 yrs 15-64 yrs 65+ yrs sex Total de- Child de- aged de- 0-3 4-6 7+ total
Ratio pendency pendency pendency
Ratio Ratio ratio
Exploring Kenya’s Inequality

Kenya 37,919,647 18,787,698 19,131,949 7,035,670 16,346,414 8,293,207 13,329,717 20,249,800 1,323,433 0.982 0.873 0.807 0.065 41.5 38.4 20.1 8,493,380

Rural 26,075,195 12,869,034 5,059,515 12,024,773 6,134,730 8,303,007 12,984,788 1,065,634 0.974 1.008 0.926 0.082 33.2 41.3 25.4 5,239,879
13,206,161
Urban 11,844,452 5,918,664 5,925,788 1,976,155 4,321,641 2,158,477 5,026,710 7,265,012 257,799 0.999 0.630 0.595 0.035 54.8 33.7 11.5 3,253,501
Baringo County 548,635 275,536 273,099 109,671 266,607 139,004 177,373 263,734 18,294 1.009 1.080 1.011 0.069 32.1 38.1 29.8 107,133
Tiaty Constituency 132,070 69,078 62,992 29,794 73,696 36,290 40,286 55,908 2,466 1.097 1.362 1.318 0.044 14.6 41.8 43.7 21152

A PUBLICATION OF KNBS AND SID

Tirioko 23,561 12,295 11,266 5,651 13,516 6,270 6,976 9,698 347 1.091 1.429 1.394 0.036 12.4 44.6 43.0 3748
Kollowa 19,364 9,859 9,505 4,229 10,631 5,421 5,965 8,329 404 1.037 1.325 1.276 0.049 13.6 41.8 44.5 3069
Ribkwo 14,433 7,287 7,146 3,231 8,050 3,869 4,162 6,053 330 1.020 1.384 1.330 0.055 21.8 42.9 35.3 2511
Silale 21,804 12,754 9,050 4,768 12,371 6,493 6,994 9,210 223 1.409 1.367 1.343 0.024 7.5 43.2 49.3 3289
Loiyamorok 13,369 6,877 6,492 2,648 7,172 3,893 4,173 5,942 255 1.059 1.250 1.207 0.043 11.8 33.3 54.9 1977

Tangulbei / Korossi 18,352 9,056 9,296 4,628 10,356 4,440 5,305 7,497 499 1.448 1.381 0.067 22.7 46.9 30.4 3376
0.974
Churo/Amaya 21,187 10,950 10,237 4,639 11,600 5,904 6,711 9,179 408 1.070 1.308 1.264 0.044 12.7 35.9 51.4 3182
Baringo North
34.5 18935
Constituency 93,383 46,001 47,382 17,508 43,802 24,601 28,846 45,291 4,290 0.971 1.062 0.967 0.095 38.4 27.1

Barwessa 35.3 4943

23,938 11,818 12,120 4,954 11,689 6,092 7,070 11,163 1,086 0.975 1.144 1.047 0.097 38.5 26.2

Kabartonjo 32.5 3811

19,038 9,535 9,503 3,121 8,316 5,157 6,318 9,839 883 1.003 0.935 0.845 0.090 39.3 28.2

Saimo / Kipsaram 31.8 4154

20,916 10,127 10,789 3,546 9,495 5,769 6,721 10,457 964 0.939 1.000 0.908 0.092 39.6 28.6

Saimo/Soi 39.6 3663

17,668 8,676 8,992 3,487 8,405 4,371 5,239 8,396 867 0.965 1.104 1.001 0.103 35.6 24.8

Bartabwa 33.0 2364

11,823 5,845 5,978 2,400 5,897 3,212 3,498 5,436 490 0.978 1.175 1.085 0.090 38.5 28.5
Baringo Central
78,634 38,142 40,492 13,882 35,142 20,047 26,648 40,395 3,097 0.942 0.947 0.870 0.077 38.5 33.7 27.8 15864
Constituency

Kabarnet 22,370 10,960 11,410 3,800 9,500 5,443 8,034 12,062 808 0.961 0.855 0.788 0.067 47.3 33.5 19.2 5419

Sacho 14,577 7,083 7,494 2,723 6,878 3,863 4,486 7,053 646 0.945 1.067 0.975 0.092 26.6 28.3 45.0 2025
 Tenges 9,524 4,733 4,791 1,730 4,437 2,455 3,015 4,670 417 0.988 1.039 0.950 0.089 36.3 35.6 28.1 1967

Ewalel / Chapchap 16,349 7,956 8,393 2,876 34.5 3245

7,418 4,319 5,226 8,207 724 0.948 0.992 0.904 0.088 34.8 30.7

Kapropita 15,814 7,410 8,404 2,753 36.5 3208

6,909 3,967 5,887 8,403 502 0.882 0.882 0.822 0.060 35.2 28.3
Baringo South
80,229 40,138 40,091 17,618 39,616 19,535 25,728 38,094 2,519 1.001 1.106 1.040 0.066 36.8 37.8 25.4 16823
Constituency
Marigat 27,242 13,561 13,681 5,338 12,429 6,335 8,959 13,708 1,105 0.991 0.987 0.907 0.081 47.4 33.3 19.3 6615
Ilchamus 15,903 7,892 8,011 3,692 8,213 4,168 5,052 7,253 437 0.985 1.193 1.132 0.060 25.0 43.8 31.2 2901
Mochongoi 27,644 13,975 13,669 6,302 13,976 6,594 8,806 12,952 716 1.022 1.134 1.079 0.055 34.9 37.9 27.2 5651
Mukutan 9,440 4,710 4,730 2,286 4,998 2,438 2,911 4,181 261 0.996 1.258 1.195 0.062 22.1 44.5 33.4 1656
Mogotio Constit-
60,136 30,003 30,133 11,908 28,170 14,533 19,529 29,613 2,353 0.996 1.031 0.951 0.079 32.2 38.4 29.3 11853
uency
Mogotio 27,016 13,472 13,544 5,116 12,265 6,396 9,030 13,672 1,079 0.995 0.976 0.897 0.079 34.9 38.7 26.4 5575
Emining 16,501 8,142 8,359 3,241 7,796 4,177 5,263 8,018 687 0.974 1.058 0.972 0.086 32.7 37.6 29.7 3243
Kisanana 16,619 8,389 8,230 3,551 8,109 3,960 5,236 7,923 587 1.019 1.098 1.023 0.074 26.8 38.8 34.4 3035
Eldama Ravine
104,183 52,174 52,009 18,961 46,181 23,998 36,336 54,433 3,569 1.003 0.914 0.848 0.066 38.5 37.5 24.0 22506
Constituency
Lembus 21,036 10,503 10,533 3,957 9,774 5,024 7,007 10,514 748 0.997 1.001 0.930 0.071 34.3 39.3 26.4 4303
Lembus Kwen 20,205 10,115 10,090 3,620 9,031 4,960 7,014 10,490 684 1.002 0.926 0.861 0.065 30.1 39.1 30.7 3892
Ravine 16,306 8,094 8,212 2,814 6,503 3,276 6,476 9,389 414 0.986 0.737 0.693 0.044 53.1 32.5 14.4 4363
Mumberes/
18,840 9,538 9,302 3,517 8,782 4,470 6,090 9,424 634 1.025 0.999 0.932 0.067 39.2 36.4 24.5 4078
Maji Mazuri
Lembus
15,834 7,871 7,963 2,868 6,788 3,519 5,713 8,477 569 0.988 0.868 0.801 0.067 36.9 40.0 23.1 3429
/Perkerra
Koibatek 11,962 6,053 5,909 2,185 5,303 2,749 4,036 6,139 520 1.024 0.949 0.864 0.085 34.0 39.1 26.9 2441

19
Pulling Apart or Pooling Together?
Exploring Kenya’s Inequality

Table 1.2: Employment by County, Constituency and Ward

County/ Constitu- Work for pay Family Family Intern/ Retired/ Fulltime Incapac- No work Number of
ency/ Ward Business Agricultural Volunteer Homemaker Student itated Individuals
Holding
Kenya 23.7 13.1 32.0 1.1 9.2 12.8 0.5 7.7 20,249,800
Rural 15.6 11.2 43.5 1.0 8.8 13.0 0.5 6.3 12,984,788
Urban 38.1 16.4 11.4 1.3 9.9 12.2 0.3 10.2 7,265,012

Baringo County 15.1 10.6 35.9 0.9 14.2 14.4 0.5 8.3 263,734

Tiaty Constituency 3.0 11.4 56.0 0.4 18.3 6.5 4.0 55,908
0.3

Tirioko 0.7 13.5 57.6 0.1 22.7 2.2 2.9 9,698

0.2

Kollowa 4.1 13.5 47.3 0.5 18.6 10.3 5.3 8,329

0.5

Ribkwo 5.0 12.4 47.1 0.9 22.3 9.7 2.4 6,053

0.4

Silale 0.3 10.8 72.0 0.3 13.9 0.3 2.4 9,210

0.1

Loiyamorok 5.6 11.0 48.4 0.4 18.9 8.7 6.7 5,942

0.4

Tangulbei/Korossi 2.7 9.7 54.9 0.5 21.3 5.6 5.1 7,497

0.2

Churo/Amaya 4.4 9.0 57.9 0.5 12.4 11.1 4.3 9,179

0.4
Baringo North
13.7 9.3 37.2 0.7 14.5 13.5 10.7 45,291
Constituency 0.5

Barwessa 9.3 8.4 43.7 0.6 12.3 13.7 11.5 11,163

0.5

Kabartonjo 20.9 8.8 31.3 0.8 12.1 14.4 11.5 9,839

0.3

Saimo/Kipsaram 16.1 8.5 39.3 0.8 11.1 15.7 8.0 10,457

0.5

Saimo/Soi 11.7 10.8 33.2 0.8 18.6 13.1 11.4 8,396

0.4

Bartabwa 8.1 11.3 36.8 0.5 23.2 7.7 11.5 5,436

0.9
Baringo Central
23.8 9.4 23.6 1.3 11.5 17.0 13.0 40,395
Constituency 0.5

Kabarnet 27.9 12.1 17.2 1.2 11.7 17.0 12.5 12,062

0.5

Sacho 19.8 7.5 35.9 1.2 8.0 16.7 10.1 7,053

0.7

Tenges 19.3 9.0 27.4 1.1 13.6 15.9 13.1 4,670

0.5

Ewalel/Chapchap 19.3 6.7 18.6 1.5 17.1 18.9 17.2 8,207

0.8

Kapropita 28.2 10.0 25.2 1.3 7.3 15.9 11.8 8,403

0.3
Baringo South
13.4 13.7 40.3 1.7 10.4 11.1 8.8 38,094
Constituency 0.7

Marigat 16.7 15.9 28.9 1.6 12.6 10.2 13.0 13,708

1.0

Ilchamus 10.6 20.1 29.1 2.3 11.0 18.0 8.4 7,253

0.5

Mochongoi 13.7 7.8 57.3 1.4 5.5 8.9 5.0 12,952

0.5

Mukutan 5.9 14.0 44.1 1.9 17.3 9.2 7.1 4,181

0.6

20 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Mogotio Constit-
16.1 10.3 18.1 1.0 21.5 23.3 9.2 29,613
uency 0.6

Mogotio 20.1 11.9 15.5 1.6 17.5 23.5 9.3 13,672

0.7

Emining 10.9 6.9 16.6 0.5 31.1 24.5 9.1 8,018

0.5

Kisanana 14.2 11.0 23.9 0.6 18.5 21.7 9.4 7,923

0.7
Eldama Ravine
23.2 9.8 30.2 0.7 10.3 19.0 6.4 54,433
Constituency 0.5

Lembus 11.8 8.0 51.2 0.5 8.8 17.0 2.2 10,514

0.6

Lembus Kwen 17.1 8.7 35.2 0.8 7.5 25.0 5.4 10,490
0.3

Ravine 39.7 13.6 9.4 0.8 13.2 13.9 9.0 9,389

0.3
Mumberes/Maji
19.1 10.6 40.6 0.5 6.6 17.6 4.6 9,424
Mazuri 0.5

Lembus/Perkerra 28.6 10.1 17.2 1.0 12.3 20.3 10.0 8,477

0.6

Koibatek 26.5 7.0 19.4 0.9 16.0 20.5 9.2 6,139

0.5

Table 1.3: Employment and Education Levels by County, Constituency and Ward

County / Education Work for Family Family Intern/ Retired/ Fulltime Incapaci- No work Number of
constituency/ Total level pay Business Agricultural Volun- Homemaker Student tated Individuals
Ward Holding teer
Kenya Total 23.7 13.1 32.0 1.1 9.2 12.8 0.5 7.7 20,249,800
Kenya None 11.1 14.0 44.4 1.7 14.7 0.8 1.2 12.1 3,154,356
Kenya Primary 20.7 12.6 37.3 0.8 9.6 12.1 0.4 6.5 9,528,270
Kenya Secondary+ 32.7 13.3 20.2 1.2 6.6 18.6 0.2 7.3 7,567,174
Rural Total 15.6 11.2 43.5 1.0 8.8 13.0 0.5 6.3 12,984,788
Rural None 8.5 13.6 50.0 1.4 13.9 0.7 1.2 10.7 2,614,951
Rural Primary 15.5 10.8 45.9 0.8 8.4 13.2 0.5 5.0 6,785,745
Rural Secondary+ 21.0 10.1 34.3 1.0 5.9 21.9 0.3 5.5 3,584,092
Urban Total 38.1 16.4 11.4 1.3 9.9 12.2 0.3 10.2 7,265,012
Urban None 23.5 15.8 17.1 3.1 18.7 1.5 1.6 18.8 539,405
Urban Primary 33.6 16.9 16.0 1.0 12.3 9.5 0.4 10.2 2,742,525
Urban Secondary+ 43.2 16.1 7.5 1.3 7.1 15.6 0.2 9.0 3,983,082
Baringo Total 15.1 10.6 35.9 0.9 14.2 14.4 0.5 8.3 263,734
Baringo None 4.7 11.6 55.2 0.7 20.2 0.2 1.0 6.5 67,711
Baringo Primary 13.6 10.4 34.4 0.9 14.0 17.6 0.4 8.8 117,138
Baringo Secondary+ 26.4 10.1 21.8 1.2 9.2 22.0 0.2 9.1 78,885
Tiaty Constitu- Total
3.0 11.4 56.0 0.4 18.3 6.5 0.3 4.0 55,908
ency
Tiaty Constitu- None
1.0 11.6 62.2 0.3 20.5 0.1 0.3 4.0 46,083
ency
Tiaty Constitu- Primary
5.4 11.1 31.4 0.9 9.7 37.6 0.1 4.0 6,704
ency
Tiaty Constitu- Secondary+
27.4 9.1 16.8 1.9 4.9 34.6 0.1 5.4 3,121
ency
Tirioko Ward Total 0.7 13.5 57.6 0.1 22.7 2.2 0.2 2.9 9,698
Tirioko Ward None 0.2 13.5 59.5 0.1 23.4 0.0 0.2 3.0 9,076
Tirioko Ward Primary 3.2 13.2 32.3 0.6 15.5 34.4 - 0.9 471

21
Exploring Kenya’s Inequality

Tirioko Ward Secondary+ 19.9 12.6 23.2 1.3 8.6 33.8 - 0.7 151
Kollowa Ward Total 4.1 13.5 47.3 0.5 18.6 10.3 0.5 5.3 8,329
Kollowa Ward None 1.6 15.0 54.1 0.2 22.4 0.2 0.5 6.0 6,366
Kollowa Ward Primary 5.5 10.4 29.4 0.8 7.3 43.6 0.1 2.9 1,419
Kollowa Ward Secondary+ 29.2 5.3 14.7 2.6 2.8 41.5 0.4 3.5 544
Ribkwo Ward Total 5.0 12.4 47.1 0.9 22.3 9.7 0.4 2.4 6,053
Ribkwo Ward None 0.9 13.6 55.2 0.5 27.2 0.1 0.5 2.1 4,436
Ribkwo Ward Primary 5.8 7.4 31.6 1.2 10.9 41.4 - 1.7 1,061
Ribkwo Ward Secondary+ 35.8 12.2 12.1 3.4 5.2 25.5 - 5.8 556
Silale Ward Total 0.3 10.8 72.0 0.3 13.9 0.3 0.1 2.4 9,210
Silale Ward None 0.3 10.8 72.6 0.2 14.0 - 0.1 2.2 8,983
Silale Ward Primary 1.2 11.0 53.1 1.8 12.8 12.2 - 7.9 164
Silale Ward Secondary+ 4.8 11.1 38.1 4.8 9.5 15.9 - 15.9 63
Loiyamorok Total
5.6 11.0 48.4 0.4 18.9 8.7 0.4 6.7 5,942
Ward
Loiyamorok None
2.4 10.3 56.8 0.3 22.8 0.2 0.6 6.6 4,339
Ward
Loiyamorok Primary
6.1 13.8 29.8 0.7 9.1 32.9 0.1 7.5 1,029
Ward
Loiyamorok Secondary+
28.9 11.0 17.8 0.7 6.6 29.8 - 5.2 574
Ward
Tangulbei/Koros- Total
2.7 9.7 54.9 0.5 21.3 5.6 0.2 5.1 7,497
si Ward
Tangulbei/Koros- None
0.8 9.7 59.4 0.4 23.9 0.1 0.3 5.5 6,150
si Ward
Tangulbei/Koros- Primary
5.4 11.0 37.5 0.9 10.8 30.6 0.2 3.5 989
si Ward
Tangulbei/Koros- Secondary+
27.1 5.9 25.4 0.8 6.7 30.5 - 3.6 358
si Ward
Churo/Amaya Total
4.4 9.0 57.9 0.5 12.4 11.1 0.4 4.3 9,179
Ward
Churo/Amaya None
1.8 8.3 70.7 0.4 14.5 0.1 0.5 3.8 6,733
Ward
Churo/Amaya Primary
5.5 11.8 27.6 0.8 8.5 40.8 0.1 5.0 1,571
Ward
Churo/Amaya Secondary+
22.9 8.8 14.2 1.5 3.1 42.4 0.1 7.1 875
Ward
Baringo North Total
13.7 9.3 37.2 0.7 14.5 13.5 0.5 10.7 45,291
Constituency
Baringo North None
7.9 10.6 46.0 1.0 19.2 0.2 2.1 13.0 5,819
Constituency
Baringo North Primary
10.0 9.5 39.8 0.6 15.2 13.9 0.3 10.7 24,654
Constituency
Baringo North Secondary+
22.0 8.4 29.4 0.9 11.4 18.0 0.2 9.8 14,818
Constituency
Barwessa Ward Total 9.3 8.4 43.7 0.6 12.3 13.7 0.5 11.5 11,163
Barwessa Ward None 5.6 9.3 55.4 1.0 16.2 0.2 1.8 10.5 1,708
Barwessa Ward Primary 7.2 8.6 45.6 0.5 12.0 14.5 0.4 11.2 6,828
Barwessa Ward Secondary+ 17.2 7.0 31.1 0.7 10.4 20.4 0.2 13.0 2,627
Kabartonjo Ward Total 20.9 8.8 31.3 0.8 12.1 14.4 0.3 11.5 9,839
Kabartonjo Ward None 18.4 6.1 39.2 0.9 15.4 0.5 2.2 17.4 643
Kabartonjo Ward Primary 15.7 9.3 33.6 0.6 13.3 14.4 0.2 12.9 4,751
Kabartonjo Ward Secondary+ 26.7 8.6 27.7 1.1 10.3 16.3 0.1 9.2 4,445
Saimo/Kipsaram Total
16.1 8.5 39.3 0.8 11.1 15.7 0.5 8.0 10,457
Ward

22 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Saimo/Kipsaram None
12.4 9.4 44.2 1.6 17.9 - 3.1 11.3 670
Ward
Saimo/Kipsaram Primary
13.2 8.7 43.8 0.7 12.3 13.6 0.4 7.4 5,220
Ward
Saimo/Kipsaram Secondary+
20.1 8.2 33.5 0.8 8.9 20.3 0.1 8.1 4,567
Ward
Saimo/Soi Ward Total 11.7 10.8 33.2 0.8 18.6 13.1 0.4 11.4 8,396
Saimo/Soi Ward None 6.6 11.6 43.3 1.0 21.5 0.2 1.2 14.8 1,814
Saimo/Soi Ward Primary 8.3 11.1 33.4 0.7 19.0 16.6 0.3 10.7 4,567
Saimo/Soi Ward Secondary+ 23.8 9.6 23.7 1.0 15.1 16.6 0.2 10.0 2,015
Bartabwa Ward Total 8.1 11.3 36.8 0.5 23.2 7.7 0.9 11.5 5,436
Bartabwa Ward None 4.8 15.0 40.4 0.7 23.7 - 3.5 12.0 984
Bartabwa Ward Primary 5.3 10.6 39.6 0.5 23.6 8.4 0.4 11.6 3,288
Bartabwa Ward Secondary+ 19.1 9.8 26.0 0.4 21.7 11.9 0.3 10.7 1,164
Baringo Central Total
23.8 9.4 23.6 1.3 11.5 17.0 0.5 13.0 40,395
Constituency
Baringo Central None
15.8 9.7 33.7 2.1 17.5 0.5 3.4 17.4 2,551
Constituency
Baringo Central Primary
18.0 8.8 28.3 1.0 14.3 15.7 0.5 13.4 18,586
Constituency
Baringo Central Secondary+
30.5 10.0 17.7 1.4 7.9 20.4 0.2 11.9 19,258
Constituency
Kabarnet Ward Total 27.9 12.1 17.2 1.2 11.7 17.0 0.5 12.5 12,062
Kabarnet Ward None 16.1 13.1 27.0 2.4 21.8 0.3 2.4 16.9 710
Kabarnet Ward Primary 21.2 12.3 23.0 0.9 14.4 14.5 0.5 13.1 5,085
Kabarnet Ward Secondary+ 34.7 11.9 11.3 1.4 8.2 20.8 0.2 11.5 6,267
Sacho Ward Total 19.8 7.5 35.9 1.2 8.0 16.7 0.7 10.1 7,053
Sacho Ward None 12.2 7.8 43.5 1.8 10.4 - 4.4 19.9 549
Sacho Ward Primary 15.9 7.4 39.4 1.1 10.2 15.1 0.6 10.3 3,618
Sacho Ward Secondary+ 26.2 7.7 30.1 1.2 4.8 21.9 0.2 7.9 2,886
Tenges Ward Total 19.3 9.0 27.4 1.1 13.6 15.9 0.5 13.1 4,670
Tenges Ward None 13.9 13.9 32.3 1.0 19.7 0.5 3.9 14.9 390
Tenges Ward Primary 15.0 7.5 30.5 0.8 16.4 16.3 0.3 13.3 2,370
Tenges Ward Secondary+ 25.8 10.0 22.5 1.6 8.9 18.6 0.1 12.6 1,910
Ewalel/Chap- Total
19.3 6.7 18.6 1.5 17.1 18.9 0.8 17.2 8,207
chap Ward
Ewalel/Chap- None
17.4 4.5 29.1 2.1 21.3 0.4 5.1 20.1 488
chap Ward
Ewalel/Chap- Primary
15.5 6.7 20.6 1.4 20.9 17.4 0.8 17.0 4,311
chap Ward
Ewalel/Chap- Secondary+
24.4 7.0 14.6 1.5 11.9 23.5 0.1 17.1 3,408
chap Ward
Kapropita Ward Total 28.2 10.0 25.2 1.3 7.3 15.9 0.3 11.8 8,403
Kapropita Ward None 19.8 8.5 38.7 2.9 12.8 1.5 1.5 14.5 414
Kapropita Ward Primary 21.1 8.3 32.8 0.9 8.3 15.5 0.3 12.8 3,202
Kapropita Ward Secondary+ 33.7 11.3 18.9 1.5 6.1 17.5 0.1 11.0 4,787
Baringo South Total
13.4 13.7 40.3 1.7 10.4 11.1 0.7 8.8 38,094
Constituency
Baringo South None
9.2 15.6 46.0 2.0 14.5 0.3 1.6 10.9 7,225
Constituency
Baringo South Primary
10.1 13.5 42.8 1.5 10.3 13.0 0.5 8.4 21,462
Constituency
Baringo South Secondary+
23.9 13.0 30.2 1.9 7.4 15.3 0.4 8.0 9,407
Constituency
Marigat Ward Total 16.7 15.9 28.9 1.6 12.6 10.2 1.0 13.0 13,708

23
Exploring Kenya’s Inequality

Marigat Ward None 10.1 15.0 37.6 2.1 14.2 0.2 2.4 18.5 2,146
Marigat Ward Primary 12.2 15.6 31.9 1.3 13.6 11.8 0.8 12.9 7,253
Marigat Ward Secondary+ 27.7 16.9 19.6 1.9 10.2 12.7 0.6 10.5 4,309
Ilchamus Ward Total 10.6 20.1 29.1 2.3 11.0 18.0 0.5 8.4 7,253
Ilchamus Ward None 8.4 25.7 36.0 1.9 16.6 0.5 1.7 9.2 1,673
Ilchamus Ward Primary 7.9 19.5 29.9 2.2 10.4 21.7 0.2 8.2 4,327
Ilchamus Ward Secondary+ 23.0 14.7 16.9 3.0 5.7 28.5 0.1 8.2 1,253
Mochongoi Ward Total 13.7 7.8 57.3 1.4 5.5 8.9 0.5 5.0 12,952
Mochongoi Ward None 13.5 8.5 59.6 2.2 9.2 0.2 1.1 5.7 2,044
Mochongoi Ward Primary 11.5 7.8 59.8 1.2 5.3 9.4 0.3 4.8 7,645
Mochongoi Ward Secondary+ 19.2 7.3 49.9 1.4 3.9 13.0 0.4 4.9 3,263
Mukutan Ward Total 5.9 14.0 44.1 1.9 17.3 9.2 0.6 7.1 4,181
Mukutan Ward None 2.4 14.6 51.2 1.5 20.4 0.1 1.1 8.7 1,362
Mukutan Ward Primary 3.3 14.2 44.5 2.0 17.1 12.2 0.3 6.4 2,237
Mukutan Ward Secondary+ 24.1 12.0 25.6 2.2 10.7 19.2 0.2 6.0 582
Mogotio Constit- Total
16.1 10.3 18.1 1.0 21.5 23.3 0.6 9.2 29,613
uency
Mogotio Constit- None
14.4 8.4 25.8 1.6 36.5 0.7 2.6 10.0 3,234
uency
Mogotio Constit- Primary
12.4 10.9 20.1 0.9 23.1 23.1 0.5 9.1 16,832
uency
Mogotio Constit- Secondary+
23.1 9.9 11.8 1.1 13.5 31.3 0.2 9.2 9,547
uency
Mogotio Ward Total 20.1 11.9 15.5 1.6 17.5 23.5 0.7 9.3 13,672
Mogotio Ward None 22.4 9.7 18.4 2.6 31.5 1.3 3.7 10.5 1,109
Mogotio Ward Primary 15.7 12.8 18.5 1.5 19.5 22.3 0.5 9.3 7,178
Mogotio Ward Secondary+ 25.7 11.0 11.1 1.5 12.0 29.6 0.2 9.0 5,385
Emining Ward Total 10.9 6.9 16.6 0.5 31.1 24.5 0.5 9.1 8,018
Emining Ward None 5.6 4.1 24.1 1.0 52.8 0.5 1.6 10.3 945
Emining Ward Primary 7.9 7.2 17.1 0.4 33.7 24.6 0.5 8.6 4,595
Emining Ward Secondary+ 18.5 7.4 12.7 0.5 18.0 33.4 0.1 9.5 2,478
Kisanana Ward Total 14.2 11.0 23.9 0.6 18.5 21.7 0.7 9.4 7,923
Kisanana Ward None 14.0 10.5 34.2 1.3 28.1 0.3 2.4 9.4 1,180
Kisanana Ward Primary 11.7 11.5 25.1 0.5 18.6 22.7 0.5 9.4 5,059
Kisanana Ward Secondary+ 21.9 9.9 12.9 0.5 11.4 33.9 0.2 9.4 1,684
Eldama Ravine Total
23.2 9.8 30.2 0.7 10.3 19.0 0.5 6.4 54,433
Constituency
Eldama Ravine None
25.4 8.8 34.8 2.4 15.3 1.1 3.7 8.6 2,799
Constituency
Eldama Ravine Primary
19.1 9.4 36.4 0.5 11.2 17.6 0.4 5.5 28,900
Constituency
Eldama Ravine Secondary+
28.1 10.4 21.7 0.9 8.5 23.0 0.2 7.3 22,734
Constituency
Lembus Ward Total 11.8 8.0 51.2 0.5 8.8 17.0 0.6 2.2 10,514
Lembus Ward None 11.0 5.8 62.2 2.4 9.9 0.7 5.4 2.6 463
Lembus Ward Primary 9.3 7.9 56.0 0.4 8.4 16.0 0.5 1.6 6,603
Lembus Ward Secondary+ 16.6 8.6 40.5 0.5 9.3 21.1 0.2 3.3 3,448
Lembus Kwen Total
17.1 8.7 35.2 0.8 7.5 25.0 0.3 5.4 10,490
Ward
Lembus Kwen None
19.7 7.7 39.7 3.9 13.6 1.0 5.5 9.0 310
Ward
Lembus Kwen Primary
11.5 7.6 42.9 0.6 8.5 24.1 0.3 4.6 5,482
Ward

24 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Lembus Kwen Secondary+

23.5 10.1 25.9 0.8 5.8 27.7 0.1 6.0 4,698
Ward
Ravine Ward Total 39.7 13.6 9.4 0.8 13.2 13.9 0.3 9.0 9,389
Ravine Ward None 32.8 13.7 13.0 2.1 19.7 1.0 3.1 14.7 524
Ravine Ward Primary 37.8 14.9 10.3 0.4 16.7 10.4 0.3 9.2 4,011
Ravine Ward Secondary+ 42.1 12.5 8.3 1.0 9.6 18.3 0.1 8.2 4,854
Mumberes/Maji Total
19.1 10.6 40.6 0.5 6.6 17.6 0.5 4.6 9,424
Mazuri Ward
Mumberes/Maji None
27.4 9.1 44.0 1.4 8.7 0.7 3.4 5.3 584
Mazuri Ward
Mumberes/Maji Primary
16.9 10.7 44.7 0.3 6.8 15.8 0.3 4.5 5,788
Mazuri Ward
Mumberes/Maji Secondary+
21.7 10.7 32.2 0.7 5.7 24.4 0.1 4.6 3,052
Mazuri Ward
Lembus/Perker- Total
28.6 10.1 17.2 1.0 12.3 20.3 0.6 10.0 8,477
ra Ward
Lembus/Perker- None
23.5 10.4 26.3 2.1 23.1 1.7 3.3 9.6 480
ra Ward
Lembus/Perker- Primary
26.2 9.6 20.1 0.6 14.1 19.7 0.5 9.2 3,962
ra Ward
Lembus/Perker- Secondary+
31.5 10.5 13.3 1.3 9.2 23.0 0.3 10.9 4,035
ra Ward
Koibatek Ward Total 26.5 7.0 19.4 0.9 16.0 20.5 0.5 9.2 6,139
Koibatek Ward None 35.4 4.6 25.6 3.4 16.9 1.6 2.1 10.5 438
Koibatek Ward Primary 24.3 5.9 22.2 0.6 19.3 19.8 0.4 7.5 3,054
Koibatek Ward Secondary+ 27.5 8.7 15.2 0.9 12.2 24.5 0.3 10.9 2,647

Table 1.4: Employment and Education Levels in Male Headed Household by County, Constituency and Ward

County, Constitu- Education Work for Family Family Ag- Internal/ Retired/ Fulltime Incapaci- No work Population
ency and Ward Level reached Pay Business ricultural Volun- Student tated
holding teer Home- (15-64)
maker

Kenya National Total 25.5 13.5 31.6 1.1 9.0 11.4 0.4 7.5 14,757,992

Kenya National None 11.4 14.3 44.2 1.6 13.9 0.9 1.0 12.6 2,183,284

Kenya National Primary 22.2 12.9 37.3 0.8 9.4 10.6 0.4 6.4 6,939,667

Kenya National Secondary+ 35.0 13.8 19.8 1.1 6.5 16.5 0.2 7.0 5,635,041

Rural Total 16.8 11.6 43.9 1.0 8.3 11.7 0.5 6.3 9,262,744

Rural None 8.6 14.1 49.8 1.4 13.0 0.8 1.0 11.4 1,823,487

Rural Primary 16.5 11.2 46.7 0.8 8.0 11.6 0.4 4.9 4,862,291

Rural Secondary+ 23.1 10.6 34.7 1.0 5.5 19.6 0.2 5.3 2,576,966

Urban Total 40.2 16.6 10.9 1.3 10.1 10.9 0.3 9.7 5,495,248

Urban None 25.8 15.5 16.1 3.0 18.2 1.4 1.3 18.7 359,797

Urban Primary 35.6 16.9 15.4 1.0 12.8 8.1 0.3 9.9 2,077,376

Urban Secondary+ 45.1 16.6 7.3 1.2 7.4 13.8 0.1 8.5 3,058,075

25
Exploring Kenya’s Inequality

Baringo Total 16.6 10.9 36.2 0.9 13.2 13.5 0.4 8.3 186,594

Baringo None 4.9 12.7 56.1 0.7 18.1 0.2 0.9 6.4 44,668

Baringo Primary 14.7 10.5 35.2 0.8 13.6 15.8 0.4 8.9 85,233

Baringo Secondary+ 28.6 10.2 22.0 1.2 8.6 20.4 0.2 8.8 56,693

Tiaty Constituency Total 3.6 12.7 56.9 0.4 16.4 6.0 0.3 3.9 37,586

Tiaty Constituency None 1.0 13.0 63.3 0.2 18.3 0.1 0.3 3.8 30,847

Tiaty Constituency Primary 6.3 12.0 33.1 0.8 9.6 34.1 0.1 4.0 4,396

Tiaty Constituency Secondary+ 32.0 9.4 16.2 1.7 4.2 30.9 0.1 5.3 2,343

Tirioko Ward Total 0.9 15.4 58.7 0.1 20.2 2.0 0.2 2.6 6,576

Tirioko Ward None 0.2 15.5 60.7 0.1 20.5 0.0 0.2 2.7 6,144

Tirioko Ward Primary 3.8 14.4 33.4 0.6 17.2 29.7 - 0.9 320

Tirioko Ward Secondary+ 25.9 11.6 23.2 0.9 10.7 27.7 - - 112

Kollowa Ward Total 4.9 14.6 47.5 0.4 17.5 9.5 0.3 5.2 5,703

Kollowa Ward None 1.7 16.0 54.7 0.2 21.1 0.1 0.3 5.8 4,338

Kollowa Ward Primary 6.7 12.3 29.6 0.8 7.2 39.9 0.1 3.4 953

Kollowa Ward Secondary+ 35.0 5.6 13.1 1.9 2.9 37.4 0.7 3.4 412

Ribkwo Ward Total 6.1 14.5 46.9 0.9 20.5 8.3 0.3 2.5 4,068

Ribkwo Ward None 0.9 16.0 55.2 0.4 24.9 0.0 0.4 2.1 2,977

Ribkwo Ward Primary 6.8 8.9 32.7 1.0 10.9 37.3 - 2.4 676

Ribkwo Ward Secondary+ 41.9 13.0 10.4 3.9 4.8 20.5 - 5.5 415

Silale Ward Total 0.3 12.3 73.6 0.3 11.2 0.3 0.1 2.1 6,327

Silale Ward None 0.2 12.3 74.2 0.2 11.3 - 0.1 1.8 6,158

Silale Ward Primary 1.6 12.8 56.8 1.6 9.6 8.8 - 8.8 125

Silale Ward Secondary+ 4.5 9.1 36.4 2.3 11.4 13.6 - 22.7 44

Loiyamorok Ward Total 6.8 11.1 49.1 0.4 18.6 7.7 0.4 5.9 4,021

Loiyamorok Ward None 2.6 10.4 57.2 0.3 22.8 0.2 0.5 6.1 2,958

Loiyamorok Ward Primary 7.4 14.2 31.7 0.9 9.0 30.3 0.2 6.3 653

Loiyamorok Ward Secondary+ 36.1 11.0 18.8 0.7 3.7 25.4 - 4.4 410
Tangulbei/Korossi
Ward Total 3.3 11.0 55.1 0.5 19.5 5.0 0.2 5.4 4,627
Tangulbei/Korossi
Ward None 0.9 11.3 59.6 0.4 21.6 0.1 0.2 5.9 3,759
Tangulbei/Korossi
Ward Primary 6.6 11.8 39.4 1.0 12.0 25.8 0.3 3.2 625

26 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Tangulbei/Korossi
Ward Secondary+ 33.3 5.8 24.7 0.8 5.8 26.3 - 3.3 243

Churo/Amaya Ward Total 5.0 9.6 59.3 0.5 10.1 10.9 0.3 4.2 6,264

Churo/Amaya Ward None 1.6 9.1 72.9 0.3 11.9 0.1 0.4 3.6 4,513

Churo/Amaya Ward Primary 6.2 11.8 30.7 0.6 7.5 38.3 0.1 4.9 1,044

Churo/Amaya Ward Secondary+ 24.3 9.6 14.7 1.4 3.0 39.6 - 7.4 707
Baringo North
Constituency Total 15.2 9.5 37.5 0.7 13.5 12.3 0.5 10.9 32,017
Baringo North
Constituency None 8.8 10.7 46.3 1.0 16.7 0.2 2.4 13.9 3,822
Baringo North
Constituency Primary 11.1 9.8 40.6 0.6 14.4 12.3 0.3 10.8 17,644
Baringo North
Constituency Secondary+ 24.5 8.5 29.0 0.9 10.7 16.5 0.1 9.8 10,551

Barwessa Ward Total 10.5 8.7 44.6 0.6 11.6 12.0 0.5 11.4 7,832

Barwessa Ward None 6.0 9.3 55.5 1.0 14.7 0.3 2.1 11.1 1,118

Barwessa Ward Primary 8.0 9.1 47.0 0.4 11.6 12.6 0.3 10.9 4,900

Barwessa Ward Secondary+ 20.0 7.3 31.4 0.7 9.7 17.6 0.1 13.2 1,814

Kabartonjo Ward Total 22.4 8.5 30.7 0.9 12.1 13.2 0.3 11.8 7,268

Kabartonjo Ward None 17.7 5.4 38.3 1.0 14.8 0.4 2.7 19.8 481

Kabartonjo Ward Primary 16.6 9.2 33.3 0.6 13.3 13.5 0.1 13.4 3,566

Kabartonjo Ward Secondary+ 29.6 8.3 26.7 1.2 10.4 14.7 0.2 8.8 3,221
Saimo/Kipsaram
Ward Total 17.6 8.8 39.1 0.8 10.4 14.8 0.4 8.2 7,447
Saimo/Kipsaram
Ward None 14.5 10.2 42.4 2.1 16.0 - 2.9 11.9 420
Saimo/Kipsaram
Ward Primary 14.4 9.0 44.0 0.7 11.6 12.4 0.3 7.5 3,763
Saimo/Kipsaram
Ward Secondary+ 21.7 8.4 33.1 0.7 8.2 19.5 0.1 8.5 3,264

Saimo/Soi Ward Total 13.3 11.4 33.7 0.8 17.0 11.7 0.5 11.5 5,679

Saimo/Soi Ward None 7.3 12.2 44.7 1.0 17.6 0.3 1.6 15.4 1,146

Saimo/Soi Ward Primary 9.4 11.8 34.1 0.7 18.4 14.4 0.3 10.9 3,102

Saimo/Soi Ward Secondary+ 26.5 10.1 24.0 1.0 13.3 15.0 0.2 9.8 1,431

Bartabwa Ward Total 9.5 11.3 38.0 0.5 20.7 7.0 0.9 12.1 3,791

Bartabwa Ward None 5.8 14.5 41.7 0.5 20.7 - 3.7 13.2 657

Bartabwa Ward Primary 6.1 10.9 41.5 0.6 21.1 7.3 0.3 12.1 2,313

Bartabwa Ward Secondary+ 21.9 9.6 25.5 0.4 19.2 11.9 0.4 11.1 821
Baringo Central
Constituency Total 25.7 9.5 23.8 1.3 10.8 15.5 0.5 13.0 28,559
Baringo Central
Constituency None 16.5 10.1 33.3 2.0 16.8 0.4 3.1 17.9 1,663

27
Exploring Kenya’s Inequality

Baringo Central
Constituency Primary 19.5 8.7 28.7 1.0 13.7 14.1 0.5 13.8 13,453
Baringo Central
Constituency Secondary+ 33.0 10.2 17.6 1.5 7.2 18.8 0.1 11.5 13,443

Kabarnet Ward Total 30.3 12.5 17.0 1.2 11.1 15.4 0.5 12.1 8,484

Kabarnet Ward None 16.5 12.8 26.3 2.2 22.0 0.4 2.6 17.2 460

Kabarnet Ward Primary 23.0 12.7 22.7 0.9 14.1 12.9 0.5 13.2 3,640

Kabarnet Ward Secondary+ 37.9 12.3 11.2 1.2 7.3 19.0 0.2 10.8 4,384

Sacho Ward Total 21.6 7.6 35.7 1.3 8.2 15.4 0.7 9.5 4,902

Sacho Ward None 12.2 8.7 43.1 1.2 12.8 - 3.5 18.4 343

Sacho Ward Primary 17.2 7.2 39.8 1.1 10.1 13.8 0.7 10.0 2,609

Sacho Ward Secondary+ 29.2 7.8 29.0 1.4 4.8 20.3 0.2 7.3 1,950

Tenges Ward Total 21.1 8.9 27.6 1.2 12.2 14.8 0.4 13.9 3,407

Tenges Ward None 15.1 14.3 31.3 1.1 17.0 - 3.4 17.7 265

Tenges Ward Primary 16.8 7.4 31.1 0.6 14.8 14.8 0.3 14.2 1,752

Tenges Ward Secondary+ 27.6 9.8 22.5 1.9 8.0 17.6 0.1 12.7 1,390
Ewalel/Chapchap
Ward Total 21.2 6.6 19.0 1.5 16.1 17.6 0.7 17.4 5,923
Ewalel/Chapchap
Ward None 18.4 29.4 2.1 19.9 0.3 4.3 20.6 326
Ewalel/Chapchap
Ward Primary 16.8 6.6 21.2 1.3 19.9 15.6 0.8 17.8 3,174
Ewalel/Chapchap
Ward Secondary+ 27.3 6.9 14.6 1.6 10.5 22.5 0.1 16.5 2,423

Kapropita Ward Total 29.5 9.9 26.2 1.4 6.5 14.2 0.2 12.0 5,843

Kapropita Ward None 20.8 9.3 39.4 3.3 8.9 1.1 1.5 15.6 269

Kapropita Ward Primary 22.1 8.0 34.2 0.9 7.4 14.0 0.2 13.1 2,278

Kapropita Ward Secondary+ 35.3 11.3 19.6 1.6 5.7 15.5 0.1 10.9 3,296
Baringo South
Constituency Total 14.7 14.0 40.5 1.6 9.9 9.8 0.6 8.8 26,658
Baringo South
Constituency None 10.0 16.1 46.5 1.9 13.1 0.3 1.6 10.5 4,503
Baringo South
Constituency Primary 10.8 13.8 43.4 1.5 10.4 11.0 0.4 8.5 15,411
Baringo South
Constituency Secondary+ 26.8 13.1 29.8 1.9 6.8 13.2 0.4 8.1 6,744

Marigat Ward Total 17.8 16.2 29.4 1.6 11.8 9.4 0.9 13.0 9,861

Marigat Ward None 10.8 16.1 39.4 1.9 13.1 0.2 2.2 16.2 1,394

Marigat Ward Primary 12.6 15.7 32.4 1.3 13.2 10.8 0.7 13.3 5,361

Marigat Ward Secondary+ 29.7 17.0 19.8 1.9 8.8 11.2 0.6 11.0 3,106

Ilchamus Ward Total 11.7 21.2 30.1 2.3 10.5 15.4 0.5 8.3 4,721

28 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Ilchamus Ward None 8.6 26.4 37.2 2.1 13.9 0.5 1.6 9.7 957

Ilchamus Ward Primary 8.2 21.1 31.6 2.1 11.0 17.8 0.2 8.0 2,911

Ilchamus Ward Secondary+ 27.2 15.6 16.9 3.3 5.4 23.8 0.1 7.7 853

Mochongoi Ward Total 15.4 8.1 56.2 1.3 5.5 8.0 0.4 5.1 9,293

Mochongoi Ward None 14.8 8.9 58.1 2.1 8.6 0.2 1.2 6.1 1,309

Mochongoi Ward Primary 12.6 8.2 59.1 1.2 5.5 8.2 0.3 4.9 5,599

Mochongoi Ward Secondary+ 22.1 7.4 48.5 1.4 3.7 11.8 0.3 4.9 2,385

Mukutan Ward Total 7.0 14.3 45.1 1.7 17.1 7.3 0.5 7.0 2,783

Mukutan Ward None 2.7 15.8 51.0 1.7 19.0 0.1 0.9 8.8 843

Mukutan Ward Primary 3.2 14.4 47.3 1.7 17.3 9.4 0.3 6.4 1,540

Mukutan Ward Secondary+ 30.8 11.3 24.3 1.8 12.3 14.3 0.3 5.3 400
Mogotio Constitu-
ency Total 17.2 10.7 18.9 1.0 20.6 21.6 0.6 9.4 21,261
Mogotio Constitu-
ency None 15.6 8.7 26.5 1.6 33.2 0.7 2.3 11.4 2,077
Mogotio Constitu-
ency Primary 13.2 11.3 21.0 0.9 22.7 21.1 0.5 9.4 12,502
Mogotio Constitu-
ency Secondary+ 25.1 10.3 12.4 1.1 12.9 29.1 0.2 8.9 6,682

Mogotio Ward Total 21.4 12.4 16.5 1.7 16.3 21.9 0.6 9.3 9,559

Mogotio Ward None 24.6 10.0 18.5 2.6 27.1 1.3 3.1 12.8 687

Mogotio Ward Primary 16.5 13.3 19.7 1.5 18.4 20.8 0.4 9.4 5,192

Mogotio Ward Secondary+ 27.9 11.5 11.5 1.7 11.5 27.2 0.2 8.5 3,680

Emining Ward Total 11.9 7.3 17.5 0.4 29.9 23.1 0.4 9.3 5,923

Emining Ward None 6.3 5.0 26.8 1.0 47.4 0.5 1.3 11.8 620

Emining Ward Primary 8.8 7.6 18.0 0.4 33.2 22.8 0.5 8.8 3,509

Emining Ward Secondary+ 20.0 7.6 13.5 0.3 17.4 31.5 0.1 9.5 1,794

Kisanana Ward Total 15.4 11.6 24.1 0.6 18.3 19.6 0.7 9.7 5,779

Kisanana Ward None 15.2 10.4 33.5 1.2 27.1 0.3 2.5 9.9 770

Kisanana Ward Primary 12.7 12.1 25.7 0.4 18.9 19.8 0.5 9.9 3,801

Kisanana Ward Secondary+ 24.2 10.8 13.3 0.7 10.5 31.0 0.2 9.2 1,208
Eldama Ravine
Constituency Total 24.2 9.5 31.1 0.7 9.8 18.2 0.4 6.1 40,513
Eldama Ravine
Constituency None 28.4 8.3 32.7 2.8 14.6 1.0 3.1 9.1 1,756
Eldama Ravine
Constituency Primary 19.8 9.2 37.6 0.4 10.9 16.5 0.3 5.2 21,827
Eldama Ravine
Constituency Secondary+ 29.4 10.1 22.5 0.8 8.0 22.2 0.1 6.9 16,930

29
Exploring Kenya’s Inequality

Lembus Ward Total 12.2 7.8 52.2 0.5 9.0 15.9 0.5 2.0 7,853

Lembus Ward None 12.3 5.4 59.6 4.0 11.2 0.4 4.0 3.2 277

Lembus Ward Primary 9.1 7.5 57.7 0.3 8.6 14.8 0.5 1.4 5,013

Lembus Ward Secondary+ 18.2 8.5 40.5 0.4 9.4 19.8 0.1 3.2 2,563

Lembus Kwen Ward Total 17.7 8.6 36.8 0.7 7.4 23.3 0.3 5.1 8,022

Lembus Kwen Ward None 21.1 6.2 39.7 2.9 12.9 1.4 6.2 9.6 209

Lembus Kwen Ward Primary 12.0 7.5 44.5 0.5 8.3 22.6 0.2 4.4 4,257

Lembus Kwen Ward Secondary+ 24.4 10.1 27.6 0.8 5.8 25.4 0.1 5.8 3,556

Ravine Ward Total 40.6 13.1 9.0 0.6 11.8 16.1 0.3 8.4 7,023

Ravine Ward None 38.5 12.7 12.7 1.6 16.5 0.6 2.5 14.9 322

Ravine Ward Primary 39.5 14.9 9.9 0.4 16.1 9.8 0.3 9.1 2,964

Ravine Ward Secondary+ 41.7 11.7 8.1 0.7 8.1 22.5 0.1 7.3 3,737
Mumberes/Maji
Mazuri Ward Total 20.6 9.9 42.0 0.6 6.2 16.2 0.3 4.3 6,843
Mumberes/Maji
Mazuri Ward None 29.2 9.1 42.3 2.5 9.1 0.3 2.5 5.0 319
Mumberes/Maji
Mazuri Ward Primary 17.8 10.1 46.3 0.3 6.3 14.8 0.3 4.2 4,283
Mumberes/Maji
Mazuri Ward Secondary+ 24.6 9.5 33.9 0.8 5.6 21.0 0.1 4.4 2,241
Lembus/Perkerra
Ward Total 30.3 10.4 17.7 0.9 11.7 18.8 0.5 9.8 6,269
Lembus/Perkerra
Ward None 26.2 10.0 24.6 2.2 22.1 1.2 3.1 10.6 321
Lembus/Perkerra
Ward Primary 27.8 10.0 20.5 0.5 13.7 18.1 0.4 8.9 3,014
Lembus/Perkerra
Ward Secondary+ 33.3 10.8 14.1 1.1 8.5 21.3 0.3 10.6 2,934

Koibatek Ward Total 28.2 7.1 20.2 0.9 15.7 18.6 0.4 8.9 4,503

Koibatek Ward None 38.6 5.2 23.1 3.9 14.9 1.9 1.6 10.7 308

Koibatek Ward Primary 25.5 6.1 22.8 0.5 19.2 18.1 0.3 7.5 2,296

Koibatek Ward Secondary+ 29.6 8.5 16.6 1.0 11.7 22.0 0.3 10.2 1,899

30 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Table 1.5: Employment and Education Levels in Female Headed Households by County, Constituency and Ward

County, Constitu- Education Work for Family Family Internal/ Retired/ Fulltime Inca- No Population
ency and Ward Level reached Pay Business Agricultural Volunteer Homemaker Student paci- work
holding tated (15-64)
Kenya National Total 18.87 11.91 32.74 1.20 9.85 16.66 0.69 8.08 5,518,645
Kenya National None 10.34 13.04 44.55 1.90 16.45 0.80 1.76 11.17 974,824
Kenya National Primary 16.74 11.75 37.10 0.89 9.82 16.23 0.59 6.89 2,589,877
Kenya National Secondary+ 25.95 11.57 21.07 1.27 6.59 25.16 0.28 8.11 1,953,944
Rural Total 31.53 15.66 12.80 1.54 9.33 16.99 0.54 11.60 1,781,078
Rural None 8.36 12.26 50.31 1.60 15.77 0.59 1.67 9.44 794,993
Rural Primary 13.02 9.90 43.79 0.81 9.49 17.03 0.60 5.36 1,924,111
Rural Secondary+ 15.97 8.87 33.03 1.06 6.80 27.95 0.34 5.98 1,018,463
Urban Total 12.83 10.12 42.24 1.04 10.09 16.51 0.76 6.40 3,737,567
Urban None 19.09 16.50 19.04 3.22 19.45 1.70 2.18 18.83 179,831
Urban Primary 27.49 17.07 17.79 1.13 10.76 13.93 0.55 11.29 665,766
Urban Secondary+ 36.81 14.50 8.06 1.51 6.36 22.11 0.22 10.43 935,481
Baringo Total 11.6 9.8 35.2 1.0 16.4 17.1 .6 8.3 77477
Baringo None 4.2 9.6 53.3 .8 24.2 .2 1.2 6.6 23041
Baringo Primary 10.8 9.9 32.1 .9 14.9 22.4 .5 8.6 31924
Baringo Secondary+ 20.4 9.9 21.1 1.2 10.7 26.8 .2 9.7 22512
Tiaty Constituency Total 1.8 8.8 54.3 .5 22.3 7.6 .4 4.4 18322
Tiaty Constituency None 1.0 8.7 60.0 .3 25.0 .1 .5 4.4 15236
Tiaty Constituency Primary 3.5 9.2 28.1 .9 9.8 44.4 .0 4.0 2307
Tiaty Constituency Secondary+ 13.4 8.1 18.4 2.2 6.8 45.7 .1 5.4 779
Tirioko Ward Total .4 9.5 55.2 .2 28.1 2.8 .2 3.6 3121
Tirioko Ward None .2 9.3 57.0 .2 29.3 .0 .2 3.7 2932
Tirioko Ward Primary 2.0 10.7 30.0 .7 12.0 44.0 0.0 .7 150
Tirioko Ward Secondary+ 2.6 15.4 23.1 2.6 2.6 51.3 0.0 2.6 39
Kollowa Ward Total 2.1 11.2 47.0 .6 20.9 12.1 .8 5.4 2627
Kollowa Ward None 1.3 12.7 53.0 .3 25.1 .3 1.0 6.3 2028
Kollowa Ward Primary 3.0 6.4 29.0 .6 7.5 51.3 .2 1.9 466
Kollowa Ward Secondary+ 11.3 4.5 19.5 4.5 2.3 54.1 0.0 3.8 133
Ribkwo Ward Total 2.6 8.0 47.4 .9 26.1 12.4 .5 2.1 1985
Ribkwo Ward None .8 8.7 55.0 .6 32.0 .1 .7 2.1 1459
Ribkwo Ward Primary 4.2 4.7 29.6 1.6 10.9 48.6 0.0 .5 385
Ribkwo Ward Secondary+ 17.7 9.9 17.0 2.1 6.4 40.4 0.0 6.4 141
Silale Ward Total .5 7.4 68.5 .3 19.8 .5 .0 3.0 2883
Silale Ward None .5 7.4 69.1 .2 19.8 0.0 .0 3.0 2825
Silale Ward Primary 0.0 5.1 41.0 2.6 23.1 23.1 0.0 5.1 39
Silale Ward Secondary+ 5.3 15.8 42.1 10.5 5.3 21.1 0.0 0.0 19
Loiyamorok Ward Total 3.0 10.7 46.8 .4 19.4 11.0 .5 8.1 1921
Loiyamorok Ward None 1.8 10.1 56.0 .4 22.8 .3 .7 7.8 1381
Loiyamorok Ward Primary 4.0 13.0 26.6 .3 9.3 37.2 0.0 9.6 376
Loiyamorok Ward Secondary+ 11.0 11.0 15.2 .6 14.0 40.9 0.0 7.3 164
Tangulbei/Korossi
Total 1.6 7.5 54.5 .5 24.3 6.6 .3 4.7 2870
Ward
Tangulbei/Korossi
None .8 7.2 58.9 .5 27.4 .0 .4 4.8 2391
Ward
Tangulbei/Korossi
Primary 3.3 9.6 34.3 .8 8.8 39.0 0.0 4.1 364
Ward

31
Exploring Kenya’s Inequality

Tangulbei/Korossi
Secondary+ 13.9 6.1 27.0 .9 8.7 39.1 0.0 4.3 115
Ward
Churo/Amaya
Total 3.2 7.6 54.9 .6 17.3 11.5 .5 4.4 2915
Ward
Churo/Amaya
None 2.0 6.8 66.1 .4 19.9 .1 .6 4.1 2220
Ward
Churo/Amaya
Primary 4.0 11.8 21.6 1.1 10.4 45.7 0.0 5.3 527
Ward
Churo/Amaya
Secondary+ 16.7 5.4 11.9 1.8 3.6 54.2 .6 6.0 168
Ward
Baringo North
Total 9.9 8.9 36.6 .7 16.8 16.4 .5 10.2 13275
Constituency
Baringo North
None 6.4 10.6 45.5 1.0 23.8 .1 1.5 11.2 1996
Constituency
Baringo North
Primary 7.3 8.7 37.8 .6 17.1 17.9 .4 10.3 7008
Constituency
Baringo North
Secondary+ 15.9 8.3 30.4 .8 13.2 21.6 .2 9.7 4271
Constituency
Barwessa Ward Total 6.4 7.4 41.4 .8 13.8 18.0 .5 11.7 3338
Barwessa Ward None 4.9 9.3 55.3 1.0 18.8 .2 1.0 9.5 590
Barwessa Ward Primary 4.9 7.3 41.7 .7 13.0 19.8 .4 12.1 1935
Barwessa Ward Secondary+ 11.1 6.2 30.6 .7 11.9 26.6 .4 12.5 813
Kabartonjo Ward Total 16.3 9.5 33.0 .7 11.9 17.7 .2 10.7 2573
Kabartonjo Ward None 20.4 8.0 42.0 .6 17.3 .6 .6 10.5 162
Kabartonjo Ward Primary 12.9 9.8 34.4 .7 13.2 17.1 .3 11.6 1185
Kabartonjo Ward Secondary+ 19.1 9.5 30.3 .7 10.0 20.6 0.0 10.0 1226
Saimo/Kipsaram
Total 12.5 7.8 39.8 .8 13.0 17.9 .7 7.5 3010
Ward
Saimo/Kipsaram
None 8.8 8.0 47.2 .8 21.2 0.0 3.6 10.4 250
Ward
Saimo/Kipsaram
Primary 9.9 7.8 43.2 .6 13.9 16.9 .5 7.2 1457
Ward
Saimo/Kipsaram
Secondary+ 16.1 7.9 34.5 1.1 10.4 22.6 .3 7.2 1303
Ward
Saimo/Soi Ward Total 8.2 9.7 32.1 .8 22.2 15.9 .2 11.0 2703
Saimo/Soi Ward None 5.3 10.5 41.0 1.1 27.9 0.0 .5 13.8 666
Saimo/Soi Ward Primary 5.8 9.8 31.8 .6 20.6 21.3 .2 9.9 1454
Saimo/Soi Ward Secondary+ 17.3 8.4 23.0 .9 19.6 20.4 0.0 10.5 583
Bartabwa Ward Total 5.0 11.3 33.9 .6 29.0 9.2 .9 10.1 1651
Bartabwa Ward None 2.7 16.2 37.5 1.2 29.6 0.0 3.0 9.8 328
Bartabwa Ward Primary 3.3 10.0 35.1 .4 29.4 11.2 .4 10.2 977
Bartabwa Ward Secondary+ 12.1 10.4 27.2 .6 27.2 12.4 .3 9.8 346
Baringo Central
Total 19.2 9.3 23.1 1.3 13.0 20.4 .6 13.0 11816
Constituency
Baringo Central
None 14.4 8.9 34.3 2.3 18.8 .7 4.1 16.6 887
Constituency
Baringo Central
Primary 14.2 8.9 27.1 1.1 16.0 19.8 .5 12.6 5129
Constituency
Baringo Central
Secondary+ 24.4 9.8 17.9 1.3 9.5 23.9 .2 12.9 5800
Constituency
Kabarnet Ward Total 22.1 11.3 17.7 1.4 13.1 20.6 .4 13.4 3568
Kabarnet Ward None 15.2 13.6 28.4 2.8 21.6 0.0 2.0 16.4 250
Kabarnet Ward Primary 16.6 11.4 23.9 .8 15.1 18.7 .4 13.0 1441
Kabarnet Ward Secondary+ 27.2 10.9 11.5 1.7 10.3 24.8 .3 13.3 1877
Sacho Ward Total 15.7 7.5 36.3 1.1 7.6 19.6 .9 11.4 2148
Sacho Ward None 12.2 6.3 43.9 2.9 6.3 0.0 5.9 22.4 205

32 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Sacho Ward Primary 12.4 7.8 38.2 1.1 10.6 18.4 .3 11.1 1007
Sacho Ward Secondary+ 20.0 7.4 32.5 .6 4.6 25.2 .4 9.3 936
Tenges Ward Total 14.6 9.4 26.7 1.0 17.5 19.0 .6 11.2 1263
Tenges Ward None 11.2 12.8 34.4 .8 25.6 1.6 4.8 8.8 125
Tenges Ward Primary 9.7 7.9 28.8 1.1 21.0 20.6 .2 10.7 618
Tenges Ward Secondary+ 21.2 10.4 22.3 1.0 11.3 21.3 .2 12.3 520
Ewalel/Chapchap
Total 14.2 6.9 17.6 1.4 19.9 22.4 .9 16.6 2289
Ward
Ewalel/Chapchap
None 15.4 3.7 28.4 1.9 24.1 .6 6.8 19.1 162
Ward
Ewalel/Chapchap
Primary 11.7 7.0 18.6 1.5 23.4 22.5 .7 14.6 1141
Ward
Ewalel/Chapchap
Secondary+ 17.0 7.2 14.7 1.3 15.1 25.9 .2 18.6 986
Ward
Kapropita Ward Total 25.0 10.2 22.8 1.2 9.2 19.7 .4 11.5 2548
Kapropita Ward None 17.9 6.9 37.2 2.1 20.0 2.1 1.4 12.4 145
Kapropita Ward Primary 18.3 9.0 29.2 .9 10.7 19.2 .7 12.0 922
Kapropita Ward Secondary+ 29.9 11.3 17.4 1.4 7.2 21.7 .1 11.1 1481
Baringo South
Total 10.3 13.0 39.6 1.8 11.4 14.3 .8 8.8 11468
Constituency
Baringo South
None 7.9 14.6 45.2 2.1 16.8 .3 1.7 11.5 2724
Constituency
Baringo South
Primary 8.3 12.5 41.0 1.6 10.1 17.9 .5 8.1 6051
Constituency
Baringo South
Secondary+ 17.0 12.4 30.9 2.0 8.9 20.6 .6 7.6 2693
Constituency
Marigat Ward Total 14.0 15.2 27.7 1.7 14.5 12.4 1.3 13.2 3861
Marigat Ward None 8.9 12.7 34.1 2.7 16.0 .3 2.7 22.7 754
Marigat Ward Primary 10.9 15.5 30.4 1.1 14.5 14.5 1.1 12.0 1892
Marigat Ward Secondary+ 22.1 16.3 19.6 2.0 13.7 16.6 .7 9.1 1215
Ilchamus Ward Total 9.0 18.0 27.1 2.2 11.9 22.7 .6 8.6 2544
Ilchamus Ward None 8.1 24.7 34.5 1.7 20.3 .6 1.8 8.4 716
Ilchamus Ward Primary 7.5 16.1 26.4 2.3 9.3 29.6 .1 8.7 1418
Ilchamus Ward Secondary+ 15.6 12.4 16.6 2.7 6.1 37.6 0.0 9.0 410
Mochongoi Ward Total 9.5 7.0 60.1 1.5 5.5 11.1 .5 4.8 3655
Mochongoi Ward None 11.2 7.9 62.4 2.4 10.1 .1 .8 5.0 735
Mochongoi Ward Primary 8.2 6.7 61.8 1.1 4.5 12.8 .3 4.6 2044
Mochongoi Ward Secondary+ 11.1 7.0 54.0 1.6 4.1 16.3 .8 5.1 876
Mukutan Ward Total 4.3 13.3 41.6 2.3 17.5 13.0 .7 7.3 1408
Mukutan Ward None 1.7 12.7 51.4 1.3 22.7 0.0 1.3 8.7 519
Mukutan Ward Primary 3.6 13.8 38.3 2.7 16.5 18.4 .4 6.3 697
Mukutan Ward Secondary+ 14.1 13.0 27.1 3.1 6.8 28.6 0.0 7.3 192
Mogotio Constit-
Total 13.2 9.0 15.9 1.0 23.4 27.9 .8 8.7 8397
uency
Mogotio Constit-
None 12.2 7.9 24.5 1.7 42.4 .7 3.1 7.5 1157
uency
Mogotio Constit-
Primary 10.0 9.5 17.3 .9 24.2 29.1 .7 8.4 4348
uency
Mogotio Constit-
Secondary+ 18.4 8.7 10.4 1.0 14.6 36.9 .2 9.8 2892
uency
Mogotio Ward Total 16.9 10.5 13.3 1.3 20.1 27.8 1.0 9.1 4157
Mogotio Ward None 18.7 9.2 18.2 2.6 38.6 1.2 4.7 6.6 422
Mogotio Ward Primary 13.4 11.4 15.1 1.2 22.3 27.0 .8 8.9 2004
Mogotio Ward Secondary+ 20.6 9.8 9.9 1.2 13.0 35.3 .2 9.9 1731

33
Exploring Kenya’s Inequality

Emining Ward Total 8.1 5.6 13.8 .8 34.5 28.3 .6 8.4 2096
Emining Ward None 4.3 2.5 19.1 .9 63.1 .6 2.2 7.4 325
Emining Ward Primary 5.2 5.8 14.3 .6 35.5 30.4 .4 8.0 1086
Emining Ward Secondary+ 14.5 6.9 10.5 1.0 19.4 38.1 .1 9.5 685
Kisanana Ward Total 10.9 9.4 23.2 .6 19.0 27.5 .9 8.4 2144
Kisanana Ward None 11.7 10.7 35.4 1.5 29.8 .2 2.2 8.5 410
Kisanana Ward Primary 8.7 9.7 23.5 .6 17.6 31.3 .7 7.9 1258
Kisanana Ward Secondary+ 16.0 7.6 11.8 0.0 13.7 41.0 .2 9.9 476
Eldama Ravine
Total 19.7 10.2 27.1 .9 11.3 23.0 .7 7.2 14199
Constituency
Eldama Ravine
None 20.4 9.6 38.4 1.7 16.3 1.2 4.6 7.7 1041
Constituency
Eldama Ravine
Primary 16.7 9.9 32.7 .6 12.0 21.4 .5 6.2 7081
Constituency
Eldama Ravine
Secondary+ 23.0 10.6 18.6 1.0 9.6 28.6 .2 8.2 6077
Constituency
Lembus Ward Total 10.5 8.7 48.3 .5 8.3 20.2 1.0 2.5 2655
Lembus Ward None 9.1 6.5 66.1 0.0 8.1 1.1 7.5 1.6 186
Lembus Ward Primary 9.8 8.8 50.6 .4 7.9 19.8 .5 2.1 1587
Lembus Ward Secondary+ 12.1 8.8 40.5 .6 9.2 24.8 .6 3.4 882
Lembus Kwen
Total 15.1 9.1 29.7 1.1 7.8 30.6 .4 6.2 2468
Ward
Lembus Kwen
None 16.8 10.9 39.6 5.9 14.9 0.0 4.0 7.9 101
Ward
Lembus Kwen
Primary 9.6 7.8 37.3 1.0 9.1 29.4 .3 5.4 1225
Ward
Lembus Kwen
Secondary+ 20.8 10.3 20.7 .8 5.8 34.6 .2 6.8 1142
Ward
Ravine Ward Total 33.0 13.3 9.5 1.1 15.4 17.5 .5 9.8 2663
Ravine Ward None 23.8 15.3 13.4 3.0 24.8 1.5 4.0 14.4 202
Ravine Ward Primary 32.5 14.6 11.1 .4 18.1 13.2 .5 9.7 1062
Ravine Ward Secondary+ 34.7 11.9 7.7 1.4 11.9 23.0 .1 9.2 1399
Mumberes/Maji
Total 15.2 12.5 36.9 .4 7.6 21.5 .8 5.3 2580
Mazuri Ward
Mumberes/Maji
None 25.3 9.1 46.0 0.0 8.3 1.1 4.5 5.7 265
Mazuri Ward
Mumberes/Maji
Primary 14.2 12.4 40.2 .4 8.4 18.5 .5 5.4 1504
Mazuri Ward
Mumberes/Maji
Secondary+ 13.6 13.7 27.6 .5 5.8 33.7 .1 5.1 811
Mazuri Ward
Lembus/Perkerra
Total 23.7 9.3 15.7 1.4 14.0 24.4 .7 10.8 2204
Ward
Lembus/Perkerra
None 18.2 11.3 29.6 1.9 25.2 2.5 3.8 7.5 159
Ward
Lembus/Perkerra
Primary 20.7 8.7 18.6 1.0 15.4 24.7 .7 10.2 947
Ward
Lembus/Perkerra
Secondary+ 27.0 9.6 11.2 1.6 11.2 27.3 .3 11.7 1098
Ward
Koibatek Ward Total 21.6 6.8 17.3 .9 16.9 25.8 .6 10.0 1629
Koibatek Ward None 26.6 3.1 32.0 2.3 21.9 .8 3.1 10.2 128
Koibatek Ward Primary 20.6 5.3 20.6 .9 19.6 24.9 .7 7.4 756
Koibatek Ward Secondary+ 21.7 9.0 11.4 .7 13.3 31.1 .1 12.6 745

34 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Table 1.6: Education by County, Constituency and Ward

County/Constituency/Ward Pop. Share Mean Consump. Share Gini

Kenya 1 3,440 1 0.445

Rural 0.688 2,270 0.454 0.361
Urban 0.312 6,010 0.546 0.368
Baringo County 0.015 2,430 0.010 0.356
Tiaty Constituency 0.004 1,610 0.0017 0.234
Tirioko 0.001 1,360 0.0003 0.167
Kollowa 0.001 1,630 0.0003 0.224
Ribkwo 0.000 1,770 0.0002 0.264
Silale 0.001 1,230 0.0002 0.124
Loiyamorok 0.000 1,610 0.0002 0.246
Tangulbei/Korossi 0.000 1,730 0.0003 0.239
Churo/Amaya 0.001 2,040 0.0003 0.254
Baringo North Constituency 0.002 1,970 0.0014 0.313
Barwessa 0.001 1,620 0.0003 0.258
Kabartonjo 0.001 2,440 0.0004 0.305
Saimo/Kipsaram 0.001 2,540 0.0004 0.295
Saimo/Soi 0.000 1,600 0.0002 0.294
Bartabwa 0.000 1,490 0.0001 0.241
Baringo Central Constituency 0.002 3,040 0.0019 0.379
Kabarnet 0.001 3,860 0.0007 0.397
Sacho 0.000 1,850 0.0002 0.326
Tenges 0.000 2,460 0.0002 0.298
Ewalel/Chapchap 0.000 2,630 0.0003 0.316
Kapropita 0.000 3,750 0.0005 0.345
Baringo South Constituency 0.002 2,330 0.0015 0.340
Marigat 0.001 2,910 0.0006 0.357
Ilchamus 0.000 1,640 0.0002 0.268
Mochongoi 0.001 2,410 0.0005 0.307
Mukutan 0.000 1,560 0.0001 0.242
Mogotio Constituency 0.002 2,540 0.0012 0.329
Mogotio 0.001 3,130 0.0007 0.323
Emining 0.000 2,220 0.0003 0.300
Kisanana 0.000 1,890 0.0002 0.279
Eldama Ravine Constituency 0.003 3,460 0.0028 0.335
Lembus 0.001 3,560 0.0006 0.309
Lembus Kwen 0.001 2,950 0.0005 0.319
Ravine 0.000 4,550 0.0006 0.353
Mumberes/Maji Mazuri 0.001 3,720 0.0005 0.323
Lembus/Perkerra 0.000 3,080 0.0004 0.329
Koibatek 0.000 2,770 0.0003 0.291

35
Exploring Kenya’s Inequality

Table 1.7: Education by County, Constituency and Ward

County/Constituency/Ward None Primary Secondary+ Total Pop

Kenya 25.2 52.0 22.8 34,024,396
Rural 29.5 54.7 15.9 23,314,262
Urban 15.8 46.2 38.0 10,710,134
Baringo County 35.7 47.9 16.5 491,567
Tiaty Constituency 81.6 15.7 2.8 117,218
Tirioko 91.1 8.1 0.7 20,772
Kollowa 69.1 27.6 3.3 17,158
Ribkwo 76.1 19.5 4.4 12,849
Silale 97.9 1.8 0.3 19,498
Loiyamorok 71.8 23.3 4.9 12,098
Tangulbei/Korossi 83.7 14.0 2.3 15,997
Churo/Amaya 73.5 21.6 4.9 18,846
Baringo North Constituency 22.2 59.7 18.2 84,137
Barwessa 25.8 61.7 12.5 21,295
Kabartonjo 15.0 58.6 26.4 17,390
Saimo/Kipsaram 16.2 59.0 24.9 19,108
Saimo/Soi 28.5 58.5 13.1 15,784
Bartabwa 28.1 60.6 11.4 10,560
Baringo Central Constituency 17.0 55.4 27.7 71,445
Kabarnet 16.1 52.6 31.3 20,401
Sacho 18.9 58.4 22.7 13,188
Tenges 19.4 57.9 22.6 8,639
Ewalel/Chapchap 16.6 59.7 23.7 14,856
Kapropita 15.5 50.3 34.2 14,361
Baringo South Constituency 28.3 58.2 13.5 70,883
Marigat 24.1 57.8 18.1 24,383
Ilchamus 32.7 58.2 9.1 14,004
Mochongoi 25.9 60.5 13.6 24,242
Mukutan 40.6 52.3 7.1 8,254
Mogotio Constituency 23.7 58.3 18.1 53,970
Mogotio 21.4 55.9 22.6 24,401
Emining 23.3 59.7 17.1 14,833
Kisanana 27.8 60.6 11.6 14,736
Eldama Ravine Constituency 17.2 58.0 24.8 93,914
Lembus 16.9 64.4 18.7 18,955
Lembus Kwen 16.1 57.7 26.3 18,260
Ravine 15.5 50.9 33.6 14,703
Mumberes/Maji Mazuri 18.7 62.7 18.5 16,976
Lembus/Perkerra 17.3 53.7 29.0 14,256
Koibatek 19.4 55.3 25.3 10,764

36 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Table 1.8: Education for Male and Female Headed Households by County, Constituency and Ward

County/Constitu- None Primary Secondary+ Total Pop None Primary Secondary+ Total Pop
ency/Ward
Male Female

Kenya 23.5 51.8 24.7 26.8 52.2 21.0 17,205,365

16,819,031

Rural 27.7 54.9 17.4 31.2 54.4 14.4 11,841,868

11,472,394

Urban 14.4 45.2 40.4 17.2 47.2 35.6 5,363,497

5,346,637

Baringo County 34.6 47.9 17.5 36.8 47.8 15.4 245,106

246,461

Tiaty Constituency 79.4 17.0 3.6 83.9 14.3 1.8 55,872

61,346

Tirioko 89.5 9.4 1.1 92.9 6.7 0.4 9,940

10,832

Kollowa 65.3 30.4 4.4 73.2 24.7 2.2 8,399

8,759

Ribkwo 72.3 21.8 5.9 79.9 17.3 2.9 6,371

6,478

Silale 97.4 2.1 0.4 98.5 1.3 0.2 8,005

11,493

Loiyamorok 68.2 25.7 6.2 75.6 20.8 3.6 5,890

6,208

Tangulbei/Korossi 79.7 16.9 3.4 87.5 11.3 1.2 8,189

7,808

Churo/Amaya 71.2 22.4 6.4 76.1 20.7 3.2 9,078

9,768
Baringo North Con-
20.5 59.7 19.9 23.8 59.7 16.5 42,821
stituency 41,316

Barwessa 24.0 61.2 14.8 27.5 62.2 10.3 10,801

10,494

Kabartonjo 14.4 57.9 27.7 15.7 59.2 25.2 8,713

8,677

Saimo/Kipsaram 14.5 59.4 26.2 17.8 58.6 23.6 9,866

9,242

Saimo/Soi 25.6 59.4 15.0 31.2 57.6 11.3 8,070

7,714

Bartabwa 26.6 60.3 13.1 29.5 60.9 9.7 5,371

5,189
Baringo Central
16.1 55.9 28.0 17.9 54.8 27.4 36,789
Constituency 34,656

Kabarnet 15.5 52.8 31.7 16.6 52.5 30.9 10,392

10,009

Sacho 18.1 58.8 23.1 19.7 58.0 22.3 6,766

6,422

Tenges 17.9 58.3 23.8 21.0 57.5 21.5 4,354

4,285

Ewalel/Chapchap 15.2 60.2 24.6 18.0 59.3 22.8 7,615

7,241

Kapropita 14.9 51.7 33.4 16.1 49.1 34.8 7,662

6,699
Baringo South Con-
25.4 58.6 16.0 31.3 57.7 11.0 35,501
stituency 35,382

Marigat 21.6 58.5 19.9 26.6 57.1 16.3 12,283

12,100

Ilchamus 28.8 59.0 12.2 36.6 57.4 6.1 7,032

6,972

Mochongoi 24.0 59.7 16.3 27.9 61.2 11.0 12,029

12,213

37
Exploring Kenya’s Inequality

Mukutan 35.2 54.7 10.1 45.9 49.9 4.2 4,157

4,097
Mogotio Constitu-
21.9 58.9 19.2 25.4 57.6 17.0 27,112
ency 26,858

Mogotio 20.2 56.7 23.1 22.7 55.2 22.1 12,274

12,127

Emining 21.2 60.3 18.5 25.3 59.1 15.7 7,525

7,308

Kisanana 25.5 61.0 13.5 30.2 60.2 9.6 7,313

7,423
Eldama Ravine
16.2 57.8 26.0 18.2 58.2 23.7 47,011
Constituency 46,903

Lembus 15.6 64.7 19.7 18.3 64.1 17.7 9,506

9,449

Lembus Kwen 15.6 57.4 27.0 16.5 57.9 25.6 9,178

9,082

Ravine 15.0 50.4 34.6 15.9 51.5 32.6 7,404

7,299
Mumberes / Maji
16.8 62.5 20.7 20.7 63.0 16.4 8,403
Mazuri 8,573

Lembus/ Perkerra 16.4 53.8 29.9 18.2 53.7 28.1 7,201

7,055

Koibatek 18.9 54.5 26.6 20.0 56.0 24.0 5,319

5,445

Table 1.9: Cooking Fuel by County, Constituency and Ward

County/ Constituency/ Electricity Paraffin LPG Biogas Firewood Charcoal Solar Other Households
Ward
Kenya 0.8 11.7 5.1 0.7 64.4 17.0 0.1 0.3 8,493,380
Rural 0.2 1.4 0.6 0.3 90.3 7.1 0.1 0.1 5,239,879
Urban 1.8 28.3 12.3 1.4 22.7 32.8 0.0 0.6 3,253,501
Baringo County 0.2 1.0 0.5 0.3 86.5 11.4 0.0 0.1 107,133
Tiaty Constituency - 0.3 0.1 0.2 96.9 2.3 0.0 0.2 21,152

Tirioko - 0.1 0.0 0.1 99.2 0.5 0.2 3,748

-

Kollowa - 0.5 0.0 0.1 97.8 1.3 0.3 3,069

-

Ribkwo - 0.6 0.4 0.1 93.2 5.3 0.4 2,511

-

Silale - 0.0 0.1 1.0 98.7 0.1 0.0 3,289

-
Loiyamorok - 0.1 0.1 0.1 92.8 6.6 0.1 0.3 1,977
Tangulbei/Korossi - 0.1 0.1 0.1 97.2 2.2 0.1 0.1 3,376

Churo/Amaya - 0.4 0.1 96.7 2.7 0.0 0.1 3,182

-
Baringo North Constit-
0.0 0.6 0.1 0.2 94.7 4.2 0.1 0.1 18,935
uency
Barwessa - 0.4 0.1 0.3 98.1 0.8 0.1 0.2 4,943

Kabartonjo - 0.9 0.2 0.1 91.1 7.8 3,811

- -
Saimo/Kipsaram 0.2 0.5 0.2 0.3 94.2 4.6 0.0 0.0 4,154
Saimo/Soi 0.0 0.8 0.3 0.2 92.2 6.1 0.1 0.2 3,663

Bartabwa 0.0 0.3 0.0 97.6 1.8 0.1 2,364

- -
Baringo Central Constit-
0.6 2.6 1.1 0.3 77.0 18.2 0.0 0.1 15,864
uency

38 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Kabarnet 0.4 4.0 1.8 0.7 62.1 30.7 0.2 5,419

-

Sacho 0.1 0.6 0.0 0.0 95.6 3.5 0.1 2,025

-

Tenges 0.4 2.2 0.4 0.1 89.0 7.9 0.1 1,967

-

Ewalel/Chapchap 0.4 2.2 0.2 93.4 3.9 0.0 3,245

- -
Kapropita 1.6 2.4 2.0 0.3 66.5 27.0 0.0 0.2 3,208
Baringo South Constit-
0.2 0.8 0.2 0.3 86.3 12.0 0.1 0.1 16,823
uency
Marigat 0.3 1.4 0.4 0.3 77.4 20.0 0.0 0.2 6,615
Ilchamus - 0.8 0.2 0.3 93.5 4.8 0.1 0.2 2,901
Mochongoi 0.1 0.3 0.1 0.2 90.4 8.8 0.1 0.1 5,651

Mukutan 0.1 0.3 0.3 0.4 95.1 3.7 0.1 1,656

-
Mogotio Constituency 0.1 0.5 0.2 0.3 88.0 10.7 0.0 0.1 11,853
Mogotio 0.2 0.8 0.4 0.4 81.4 16.7 0.0 0.1 5,575
Emining 0.1 0.3 0.1 0.2 93.0 6.2 0.0 0.2 3,243

Kisanana 0.0 0.3 0.1 0.1 94.6 4.6 0.1 0.1 3,035

Eldama Ravine Constit-

0.3 1.1 1.1 0.3 76.1 21.0 0.0 0.1 22,506
uency
Lembus 0.0 0.3 0.1 0.2 87.8 11.5 0.0 0.0 4,303
Lembus Kwen 0.3 0.8 0.7 0.3 86.5 11.3 0.1 0.2 3,892
Ravine 0.5 3.2 3.4 0.5 43.4 48.6 0.0 0.4 4,363
Mumberes/Maji Mazuri 0.2 0.5 0.7 0.1 83.7 14.7 0.0 0.0 4,078
Lembus/Perkerra 0.3 0.9 0.6 0.3 73.5 24.3 0.1 0.0 3,429

Koibatek 0.1 0.7 0.5 0.1 88.8 9.8 0.0 2,441

-

Table 1.10: Cooking Fuel for Male Headed Households by County, Constituency and Ward

County/ Constituency/ Electricity Paraffin LPG Biogas Firewood Charcoal Solar Other Households
Ward
Kenya 0.9 13.5 5.3 0.8 61.4 17.7 0.1 0.4 5,762,320
Rural 0.2 1.6 0.6 0.3 89.6 7.5 0.1 0.1 3,413,616
Urban 1.9 30.9 12.0 1.4 20.4 32.5 0.0 0.7 2,348,704
Baringo County 0.2 1.2 0.5 0.2 85.8 11.8 0.1 0.1 69,621
Tiaty Constituency 0.0 0.4 0.1 0.1 96.2 3.0 0.0 0.2 12,501
Tirioko 0.0 0.1 0.0 0.0 99.5 0.2 0.0 0.2 2,194
Kollowa 0.0 0.7 0.1 0.1 97.1 1.7 0.0 0.3 1,887
Ribkwo 0.0 0.9 0.5 0.2 90.9 7.0 0.0 0.5 1,496
Silale 0.0 0.1 0.1 0.2 99.5 0.2 0.0 0.1 1,952
Loiyamorok 0.0 0.2 0.1 0.1 90.3 9.0 0.1 0.3 1,238
Tangulbei/Korossi 0.0 0.3 0.1 0.1 96.3 2.9 0.1 0.3 1,775
Churo/Amaya 0.0 0.6 0.0 0.1 95.9 3.4 0.1 0.0 1,959
Baringo North Constit-
0.1 0.8 0.1 0.2 94.1 4.5 0.1 0.1 12,125
uency
Barwessa 0.0 0.5 0.0 0.3 97.6 1.0 0.2 0.3 3,143
Kabartonjo 0.0 1.1 0.2 0.2 90.8 7.7 0.0 0.0 2,621
Saimo/Kipsaram 0.2 0.6 0.2 0.4 93.6 5.0 0.0 0.0 2,655
Saimo/Soi 0.0 1.1 0.4 0.1 91.4 6.6 0.1 0.2 2,237

39
Exploring Kenya’s Inequality

Bartabwa 0.1 0.5 0.0 0.0 96.9 2.5 0.0 0.1 1,469
Baringo Central Constit-
0.6 3.2 1.3 0.3 76.9 17.5 0.0 0.2 10,369
uency
Kabarnet 0.4 4.8 2.0 0.6 60.8 31.0 0.0 0.3 3,517
Sacho 0.2 0.8 0.0 0.0 95.9 3.0 0.2 0.0 1,301
Tenges 0.4 2.5 0.5 0.2 88.9 7.5 0.2 0.0 1,313
Ewalel/Chapchap 0.6 2.4 0.3 0.0 92.9 3.9 0.0 0.0 2,176
Kapropita 1.5 3.1 2.4 0.4 68.0 24.3 0.0 0.2 2,062
Baringo South Constit-
0.2 1.0 0.3 0.3 85.1 12.9 0.1 0.1 10,976
uency
Marigat 0.4 1.7 0.3 0.4 76.4 20.5 0.0 0.2 4,401
Ilchamus 0.0 1.1 0.2 0.2 93.2 5.0 0.2 0.2 1,730
Mochongoi 0.1 0.3 0.2 0.2 89.2 9.9 0.1 0.0 3,853
Mukutan 0.1 0.5 0.4 0.2 94.2 4.4 0.0 0.2 992
Mogotio Constituency 0.2 0.6 0.3 0.3 88.5 10.0 0.1 0.1 7,914
Mogotio 0.2 1.0 0.5 0.4 82.2 15.6 0.1 0.1 3,649
Emining 0.1 0.3 0.0 0.2 93.7 5.6 0.0 0.0 2,166
Kisanana 0.0 0.4 0.1 0.1 94.2 4.9 0.1 0.1 2,099
Eldama Ravine Constit-
0.2 1.4 1.0 0.2 76.1 20.9 0.0 0.2 15,736
uency
Lembus 0.0 0.3 0.1 0.2 87.6 11.7 0.0 0.0 2,998
Lembus Kwen 0.1 0.8 0.5 0.2 87.7 10.4 0.0 0.2 2,799
Ravine 0.5 4.2 3.3 0.4 42.7 48.4 0.0 0.5 3,002
Mumberes/Maji Mazuri 0.3 0.6 1.0 0.1 81.8 16.1 0.0 0.1 2,787
Lembus/Perkerra 0.3 1.0 0.5 0.2 74.1 23.7 0.1 0.0 2,433
Koibatek 0.1 0.8 0.5 0.2 88.9 9.6 0.0 0.0 1,717

Table 1.11: Cooking Fuel for Female Headed Households by County, Constituency and Ward

County/ Constituency/ Electricity Paraffin LPG Biogas Firewood Charcoal Solar Other Households
Ward

Kenya 0.6 7.9 70.6 15.5 0.1 2,731,060

4.6 0.7 0.0

Rural 0.1 1.0 91.5 6.5 0.1 1,826,263

0.5 0.3 0.0

Urban 1.6 21.7 28.5 33.6 0.3 904,797

13.0 1.5 0.0

Baringo County 0.2 0.5 87.9 10.5 0.1 37,512

0.4 0.3 0.0

Tiaty Constituency - 0.1 98.0 1.3 - 0.2 8,651

0.1 0.4

Tirioko - - 98.9 0.8 - 0.1 1,554

0.1 0.1

Kollowa - 0.3 - 98.8 0.5 - 0.3 1,182

0.1

Ribkwo - 0.2 - 96.6 3.0 - 0.2 1,015

0.1

Silale - - 97.6 0.1 - - 1,337

0.1 2.2

Loiyamorok - - - 96.9 2.7 - 0.3 739

0.1

Tangulbei/Korossi - - 98.2 1.5 - - 1,601

0.1 0.2
Churo/Amaya - 0.2 - - 98.0 1.6 - 0.2 1,223

40 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Baringo North Constit-

0.0 0.2 95.7 3.6 0.1 6,810
uency 0.1 0.2 0.0

Barwessa - 0.1 98.9 0.4 - 0.1 1,800

0.2 0.3

Kabartonjo - 0.3 - 91.7 7.8 - - 1,190

0.2

Saimo/Kipsaram 0.1 0.3 95.3 3.8 - 0.1 1,499

0.2 0.1

Saimo/Soi - 0.4 93.5 5.5 0.2 1,426

0.1 0.2 0.1

Bartabwa - 0.1 - 98.8 0.8 - 0.2 895

0.1
Baringo Central Constit-
0.5 1.7 77.2 19.4 0.1 5,495
uency 0.8 0.4 0.0

Kabarnet 0.4 2.4 64.7 30.2 - 0.1 1,902

1.3 0.9

Sacho 0.1 0.3 94.9 4.4 - - 724

0.1 0.1

Tenges 0.3 1.5 - 89.3 8.7 - - 654

0.2

Ewalel/Chapchap - 1.7 - - 94.4 3.8 - 1,069

0.1

Kapropita 1.7 1.3 63.7 31.7 - 0.2 1,146

1.3 0.2
Baringo South Constit-
0.1 0.4 88.4 10.3 0.1 5,847
uency 0.2 0.3 0.0

Marigat 0.2 0.8 79.3 18.8 0.1 2,214

0.5 0.3 0.0

Ilchamus - 0.4 94.0 4.6 0.3 1,171

0.1 0.5 0.1

Mochongoi 0.1 0.2 93.0 6.3 - 0.1 1,798

0.1 0.1

Mukutan - - 96.5 2.7 - - 664

0.2 0.6

Mogotio Constituency 0.1 0.4 86.8 12.2 - 0.2 3,939

0.2 0.2

Mogotio 0.1 0.5 79.9 18.8 - 0.1 1,926

0.3 0.4

Emining 0.1 0.4 - 91.7 7.3 - 0.4 1,077

0.1

Kisanana - 0.1 - 95.4 4.2 - 0.1 936

0.2
Eldama Ravine Constit-
0.3 0.5 76.3 21.3 0.1 6,770
uency 1.1 0.4 0.1

Lembus - 0.2 88.4 11.0 - - 1,305

0.2 0.3

Lembus Kwen 0.6 0.6 83.3 13.5 0.1 1,093

1.1 0.5 0.2

Ravine 0.5 1.0 44.7 49.1 - 0.2 1,361

3.7 0.7

Mumberes/Maji Mazuri 0.2 0.2 - 87.9 11.5 - 1,291

0.2 0.1

Lembus/Perkerra 0.4 0.7 71.9 25.7 - - 996

0.7 0.6

Koibatek 0.1 0.6 - 88.4 10.5 - 724

0.3 0.1

41
Exploring Kenya’s Inequality

Table 1.12: Lighting Fuel by County, Constituency and Ward

County/ Constitu- Electricity Pressure Lantern Tin Lamp Gas Fuel Solar Other House-
ency/ Ward Lamp Lamp wood holds

Kenya 22.9 0.6 30.6 38.5 0.9 4.3 1.6 0.6

5,762,320

Rural 5.2 0.4 34.7 49.0 1.0 6.7 2.2 0.7

3,413,616

Urban 51.4 0.8 23.9 21.6 0.6 0.4 0.7 0.6

2,348,704

Baringo County 9.3 0.4 39.3 20.1 0.7 27.9 1.7 0.4
69,621

Tiaty Constituency 0.2 0.1 5.1 3.0 0.7 89.8 0.6 0.6
12,501

Tirioko 0.1 0.1 0.7 1.3 0.7 96.4 0.2 0.6

2,194

Kollowa 0.1 0.1 5.1 2.7 0.6 90.1 0.5 0.8

1,887

Ribkwo 1.2 0.3 12.3 1.8 0.8 82.7 0.6 0.3

1,496

Silale 0.0 0.0 0.1 0.1 0.3 98.4 1.1 0.0

1,952

Loiyamorok 0.4 0.1 13.2 7.0 1.4 77.2 0.3 0.5

1,238

Tangulbei/Korossi 0.0 0.0 5.5 3.1 0.7 88.8 0.5 1.3

1,775

Churo/Amaya 0.0 0.1 4.6 6.3 0.6 87.1 0.7 0.5

1,959
Baringo North Con-
6.1 0.2 42.8 22.6 0.9 24.9 2.1 0.5
stituency 12,125

Barwessa 0.1 0.3 30.3 30.6 0.9 35.3 2.0 0.5

3,143

Kabartonjo 15.4 0.3 54.6 18.5 0.8 8.4 1.7 0.2

2,621

Saimo/Kipsaram 9.9 0.2 59.1 21.3 0.7 6.4 2.4 0.0

2,655

Saimo/Soi 4.0 0.3 36.9 19.7 1.0 35.3 2.3 0.5

2,237

Bartabwa 0.1 0.0 30.6 19.1 1.1 45.9 1.6 1.5

1,469
Baringo Central
23.9 0.5 43.9 19.2 0.5 10.1 1.6 0.2
Constituency 10,369

Kabarnet 26.6 0.4 43.6 20.2 0.3 7.0 1.4 0.5

3,517

Sacho 13.1 0.3 49.4 17.6 0.6 17.0 1.9 0.1

1,301

Tenges 10.8 1.0 38.1 29.0 1.0 17.6 2.3 0.1

1,313

Ewalel/Chapchap 16.3 0.5 50.7 18.3 0.6 11.7 1.8 0.2

2,176

Kapropita 41.9 0.6 37.8 13.2 0.6 4.6 1.2 0.1

2,062
Baringo South Con-
5.1 0.6 42.4 30.4 1.0 17.9 2.0 0.6
stituency 10,976

Marigat 9.9 0.7 43.7 24.3 1.2 18.0 1.6 0.5

4,401

Ilchamus 3.2 0.2 44.1 36.4 0.7 11.7 2.9 0.8

1,730

Mochongoi 1.8 0.8 48.0 33.4 0.8 12.3 2.4 0.5

3,853

Mukutan 0.8 0.1 15.3 33.6 1.1 47.8 0.7 0.7

992

42 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Mogotio Constitu-
4.8 0.3 54.8 26.2 0.8 10.4 2.5 0.3
ency 7,914

Mogotio 8.1 0.4 63.8 19.1 0.8 4.4 3.1 0.2

3,649

Emining 2.3 0.2 52.7 25.4 1.0 15.8 2.3 0.4

2,166

Kisanana 1.4 0.1 40.3 40.1 0.8 15.4 1.6 0.4

2,099
Eldama Ravine
15.9 0.7 54.9 24.1 0.5 1.8 2.0 0.3
Constituency 15,736

Lembus 5.6 0.3 51.1 39.2 0.4 1.7 1.5 0.2

2,998

Lembus Kwen 11.6 0.1 64.0 20.9 0.4 1.3 1.4 0.3
2,799

Ravine 34.3 0.5 45.2 17.0 0.4 0.6 1.3 0.6

3,002
Mumberes/Maji
9.8 2.1 47.9 35.4 0.4 0.9 3.3 0.2
Mazuri 2,787

Lembus/Perkerra 20.6 0.3 59.4 12.5 0.6 3.7 2.4 0.5

2,433

Koibatek 11.3 0.5 69.4 12.2 1.0 3.6 1.8 0.1

1,717

Table 1.13: Lighting Fuel for Male Headed Households by County, Constituency and Ward

County/ Constit- Electricity Pressure Lantern Tin Lamp Gas Fuel wood Solar Other Households
uency/ Ward Lamp Lamp

Kenya 24.6 0.6 30.4 36.8 0.9 4.2 1.7 0.7

5,762,320

Rural 5.6 0.5 35.3 47.5 1.1 6.8 2.4 0.7

3,413,616

Urban 52.4 0.9 23.3 21.2 0.6 0.4 0.7 0.7

2,348,704

Baringo County 9.7 0.4 40.6 20.8 0.7 25.5 1.8 0.5
69,621
Tiaty Constitu-
0.3 0.1 5.9 3.2 0.7 88.6 0.5 0.7
ency 12,501

Tirioko 0.0 0.0 0.9 1.6 0.8 95.5 0.2 0.9

2,194

Kollowa 0.1 0.1 6.2 3.1 0.5 88.6 0.6 0.8

1,887

Ribkwo 1.8 0.4 14.3 2.2 0.9 79.3 0.7 0.3

1,496

Silale 0.0 0.0 0.1 0.1 0.3 99.2 0.3 0.0

1,952

Loiyamorok 0.6 0.1 14.1 6.0 1.5 77.0 0.2 0.6

1,238
Tangulbei/
0.0 0.1 6.0 4.1 0.7 86.9 0.6 1.7
Korossi 1,775

Churo/Amaya 0.1 0.2 5.4 6.2 0.8 86.1 0.9 0.5

1,959
Baringo North
6.6 0.2 43.1 23.3 0.9 23.2 2.2 0.5
Constituency 12,125

Barwessa 0.1 0.3 30.6 32.4 0.9 33.2 2.0 0.5

3,143

Kabartonjo 15.7 0.4 53.0 20.2 0.9 7.9 1.6 0.2

2,621

Saimo/Kipsaram 10.7 0.2 58.6 20.9 0.4 6.3 2.8 0.1

2,655

43
Exploring Kenya’s Inequality

Saimo/Soi 4.6 0.2 38.2 19.2 1.0 33.6 2.7 0.5

2,237

Bartabwa 0.1 0.1 31.4 19.8 1.4 44.0 1.6 1.5

1,469
Baringo Central
23.9 0.5 43.5 19.6 0.6 9.9 1.6 0.3
Constituency 10,369

Kabarnet 27.7 0.5 43.2 20.2 0.2 6.4 1.3 0.5

3,517

Sacho 12.8 0.5 48.0 19.4 0.7 16.5 2.1 0.2

1,301

Tenges 10.5 0.9 37.0 29.6 1.1 18.4 2.5 0.0

1,313

Ewalel/Chapchap 15.8 0.6 51.3 18.8 0.6 11.1 1.6 0.2

2,176

Kapropita 41.8 0.5 37.3 13.2 0.8 4.8 1.5 0.1

2,062
Baringo South
5.4 0.6 44.0 30.2 0.8 16.3 2.0 0.6
Constituency 10,976

Marigat 10.3 0.8 44.5 24.9 1.1 16.5 1.5 0.5

4,401

Ilchamus 3.4 0.2 45.9 36.4 0.6 9.9 2.9 0.7

1,730

Mochongoi 1.9 0.8 49.7 32.8 0.6 11.3 2.5 0.4

3,853

Mukutan 0.9 0.1 15.8 33.6 1.0 46.7 1.0 0.9

992
Mogotio Constit-
4.4 0.3 55.1 26.6 0.7 9.9 2.6 0.3
uency 7,914

Mogotio 7.6 0.5 63.8 19.2 0.7 4.6 3.3 0.2

3,649

Emining 1.8 0.1 53.6 26.3 0.8 14.5 2.5 0.3

2,166

Kisanana 1.5 0.2 41.5 39.9 0.7 14.2 1.5 0.5

2,099
Eldama Ravine
15.7 0.7 54.8 24.1 0.5 1.8 2.0 0.4
Constituency 15,736

Lembus 6.3 0.3 51.5 38.3 0.4 1.4 1.6 0.3

2,998

Lembus Kwen 10.5 0.2 65.5 20.5 0.4 1.3 1.4 0.3
2,799

Ravine 34.3 0.6 44.0 17.9 0.4 0.5 1.6 0.8

3,002
Mumberes/Maji
10.4 2.3 47.2 35.1 0.4 0.9 3.6 0.3
Mazuri 2,787

Lembus/Perkerra 19.8 0.5 59.4 13.4 0.5 3.7 2.2 0.5

2,433

Koibatek 10.6 0.5 68.2 13.5 1.0 4.2 1.9 0.1

1,717

Table 1.14: Lighting Fuel for Female Headed Households by County, Constituency and Ward

County/Constituen- Electricity Pressure Lantern Tin Gas Fuel Solar Other Households
cy/Ward Lamp Lamp Lamp wood
Kenya 19.2 0.5 31.0 42.1 0.8 4.5 1.4 0.5 2,731,060
Rural 4.5 0.4 33.7 51.8 0.8 6.5 1.8 0.5 1,826,263
Urban 48.8 0.8 25.4 22.6 0.7 0.6 0.6 0.5 904,797
Baringo County 8.7 0.3 36.9 18.9 0.8 32.4 1.6 0.4 37,512
Tiaty Constituency 0.1 0.0 4.0 2.6 0.6 91.5 .6 0.5 8,651
Tirioko 0.2 0.1 0.4 0.8 0.6 97.6 0.1 0.2 1,554

44 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Kollowa 0.1 - 3.4 2.2 0.8 92.5 0.2 0.9 1,182

Ribkwo 0.3 0.1 9.5 1.3 0.7 87.6 0.4 0.2 1,015

Silale - - 0.1 0.4 97.2 2.3 0.1 1,337

-
Loiyamorok - 0.1 11.6 8.8 1.2 77.7 0.3 0.3 739
Tangulbei/Korossi 0.1 - 5.0 1.9 0.7 90.9 0.4 0.9 1,601
Churo/Amaya - - 3.4 6.6 0.4 88.6 0.5 0.5 1,223
Baringo North Con-
5.1 0.2 42.3 21.4 0.9 27.8 1.8 0.5 6,810
stituency
Barwessa - 0.3 29.8 27.5 0.9 39.0 2.0 0.6 1,800
Kabartonjo 14.9 0.2 58.0 14.9 0.6 9.6 1.8 0.1 1,190
Saimo/Kipsaram 8.4 0.2 59.9 21.9 1.3 6.5 1.7 - 1,499
Saimo/Soi 3.1 0.5 34.7 20.6 0.9 37.9 1.7 0.6 1,426
Bartabwa 0.1 - 29.3 18.0 0.7 48.8 1.6 1.6 895
Baringo Central
23.8 0.5 44.7 18.3 0.2 5,495
Constituency 0.5 10.5 1.6
Kabarnet 24.5 0.4 44.4 20.1 0.6 8.2 1.5 0.3 1,902
Sacho 13.7 - 51.9 14.4 0.6 17.8 1.7 - 724
Tenges 11.5 1.1 40.4 28.0 0.6 16.2 2.0 0.3 654
Ewalel/Chapchap 17.4 0.3 49.4 17.3 0.5 12.8 2.2 0.2 1,069
Kapropita 42.1 0.7 38.7 13.3 0.2 4.2 0.9 - 1,146
Baringo South Con-
4.6 0.5 39.6 30.6 1.2 20.9 2.0 0.6 5,847
stituency
Marigat 9.1 0.5 42.3 23.2 1.4 20.9 1.9 0.6 2,214
Ilchamus 3.1 0.2 41.4 36.5 0.9 14.3 2.8 0.9 1,171
Mochongoi 1.4 0.8 44.4 34.8 1.2 14.6 2.1 0.6 1,798
Mukutan 0.6 - 14.5 33.6 1.2 49.4 0.3 0.5 664
Mogotio Constitu-
5.6 0.1 54.1 25.3 1.0 11.3 2.3 0.3 3,939
ency
Mogotio 8.9 0.2 64.0 18.8 0.9 4.2 2.8 0.2 1,926
Emining 3.3 0.2 50.9 23.6 1.2 18.3 2.0 0.5 1,077
Kisanana 1.2 - 37.4 40.5 1.1 17.9 1.8 0.1 936
Eldama Ravine Con-
16.3 0.5 54.9 24.0 0.5 1.8 1.8 0.2 6,770
stituency
Lembus 3.9 0.3 50.2 41.4 0.5 2.4 1.4 - 1,305
Lembus Kwen 14.5 - 60.3 21.9 0.3 1.4 1.5 0.2 1,093
Ravine 34.2 0.4 47.8 15.1 0.5 0.8 0.7 0.4 1,361
Mumberes/Maji
8.4 1.6 49.5 36.2 0.4 2.9 0.1 1,291
Mazuri 1.0
Lembus/Perkerra 22.5 0.1 59.4 10.3 0.8 3.7 2.7 0.4 996
Koibatek 12.8 0.4 72.2 9.3 1.0 2.3 1.8 0.1 724

Table 1.15: Main material of the Floor by County, Constituency and Ward

County/Constituency/ ward Cement Tiles Wood Earth Other Households

Kenya 41.2 1.6 0.7 56.0 0.5 8,493,380
Rural 22.1 0.3 0.7 76.5 0.4 5,239,879
Urban 71.8 3.5 0.9 23.0 0.8 3,253,501
Baringo County 24.5 0.3 1.7 73.1 0.4 107,133
Tiaty Constituency 4.0 0.0 0.7 95.1 0.2 21,152
Tirioko 0.6 0.0 1.0 98.2 0.2 3,748

45
Exploring Kenya’s Inequality

Kollowa 3.8 0.1 1.2 94.8 0.1 3,069

Ribkwo 9.7 0.0 0.6 89.4 0.2 2,511
Silale 0.1 - 0.5 99.3 0.1 3,289
Loiyamorok 10.5 - 0.2 89.2 0.1 1,977
Tangulbei/Korossi 3.9 0.0 0.7 95.1 0.4 3,376
Churo/Amaya 3.7 0.0 0.5 95.3 0.4 3,182
Baringo North Constituency 20.1 0.2 1.4 78.1 0.2 18,935
Barwessa 6.2 0.1 1.2 92.3 0.2 4,943
Kabartonjo 36.9 0.3 2.4 60.1 0.2 3,811
Saimo/Kipsaram 31.8 0.2 1.8 65.9 0.2 4,154
Saimo/Soi 17.6 0.1 0.8 81.2 0.2 3,663
Bartabwa 5.3 0.1 0.3 94.2 0.0 2,364
Baringo Central Constituency 46.0 0.8 0.8 52.1 0.4 15,864
Kabarnet 56.6 1.7 0.6 40.3 0.7 5,419
Sacho 27.9 0.0 0.6 71.3 0.1 2,025
Tenges 28.9 0.2 1.0 69.8 0.2 1,967
Ewalel/Chapchap 32.8 0.5 1.2 65.2 0.2 3,245
Kapropita 63.2 0.3 0.6 35.7 0.2 3,208
Baringo South Constituency 19.3 0.1 0.9 79.6 0.2 16,823
Marigat 33.3 0.1 0.5 66.0 0.1 6,615
Ilchamus 14.9 0.1 0.3 84.5 0.2 2,901
Mochongoi 8.8 0.1 1.8 89.2 0.2 5,651
Mukutan 6.9 - 0.2 92.5 0.4 1,656
Mogotio Constituency 22.7 0.4 0.4 75.8 0.7 11,853
Mogotio 31.3 0.8 0.4 66.2 1.3 5,575
Emining 19.3 0.1 0.3 80.2 0.2 3,243
Kisanana 10.7 0.1 0.4 88.7 0.1 3,035
Eldama Ravine Constituency 37.1 0.4 4.8 56.9 0.7 22,506
Lembus 20.6 0.1 7.0 71.3 1.0 4,303
Lembus Kwen 36.9 0.3 0.9 61.8 0.1 3,892
Ravine 55.0 0.9 0.7 43.0 0.4 4,363
Mumberes/Maji Mazuri 21.4 0.1 16.3 60.3 1.9 4,078
Lembus/Perkerra 51.9 0.7 0.8 46.5 0.1 3,429
Koibatek 40.2 0.2 1.3 57.3 0.9 2,441

Table 1.16: Main Material of the Floor in Male and Female Headed Households by County, Constituency and Ward

County/ Constitu- Cement Tiles Wood Earth Other House- Cement Tiles Wood Earth Other House-
ency/ ward holds holds
Male Female

Kenya 42.8 1.6 0.8 54.2 0.6 1.4 0.7 59.8 0.5
5,762,320 37.7 2,731,060

Rural 22.1 0.3 0.7 76.4 0.4 0.3 0.6 76.6 0.3
3,413,616 22.2 1,826,263

Urban 72.9 3.5 0.9 21.9 0.8 3.6 0.9 25.8 0.8
2,348,704 69.0 904,797

Baringo County 24.8 0.3 1.8 72.7 0.4 0.3 1.5 73.9 0.4
69,621 23.9 37,512

46 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Tiaty Constituency 5.1 0.1 0.7 93.9 0.3 0.0 0.7 96.7 0.2
12,501 2.4 8,651

Tirioko 0.7 0.0 0.9 98.1 0.3 - 1.2 98.3 0.1

2,194 0.4 1,554

Kollowa 5.1 0.2 1.4 93.3 0.1 0.1 1.0 97.0 0.1
1,887 1.8 1,182

Ribkwo 12.0 0.1 0.7 87.0 0.2 - 0.5 92.9 0.3

1,496 6.3 1,015

Silale 0.2 - 0.5 99.2 0.1 - 0.4 99.5 0.1

1,952 - 1,337

Loiyamorok 13.3 - 0.1 86.4 0.2 - 0.3 93.9 -

1,238 5.8 739

Tangulbei/Korossi 4.6 0.1 0.7 94.1 0.6 - 0.7 96.1 0.1

1,775 3.1 1,601

Churo/Amaya 4.7 0.1 0.6 94.3 0.4 - 0.5 97.0 0.4

1,959 2.1 1,223
Baringo North
20.6 0.2 1.4 77.7 0.2 0.1 1.4 78.9 0.2
Constituency 12,125 19.3 6,810

Barwessa 5.8 0.1 93.0 0.2 0.2 1.3 91.1 0.3

1.0 3,143 7.1 1,800

Kabartonjo 35.8 0.4 2.3 61.3 0.2 0.1 2.7 57.6 0.3
2,621 39.3 1,190

Saimo/Kipsaram 32.3 0.2 2.0 65.3 0.2 0.1 1.5 67.0 0.3
2,655 31.0 1,499

Saimo/Soi 19.2 0.2 0.8 79.5 0.3 0.1 1.0 83.8 0.1
2,237 15.1 1,426

Bartabwa 5.8 0.1 0.4 93.7 0.1 0.1 0.2 95.2 -

1,469 4.5 895
Baringo Central
45.1 0.8 0.8 52.9 0.3 0.7 0.7 50.5 0.4
Constituency 10,369 47.7 5,495

Kabarnet 57.2 2.0 0.6 39.6 0.6 1.2 0.6 41.8 0.9
3,517 55.6 1,902

Sacho 26.2 - 72.9 0.2 0.1 0.6 68.4 0.1

0.7 1,301 30.8 724

Tenges 27.0 - 71.7 0.2 0.5 0.9 65.7 0.2

1.0 1,313 32.7 654

Ewalel/Chapchap 30.9 0.3 67.4 0.2 0.9 1.3 60.9 0.3

1.2 2,176 36.6 1,069

Kapropita 62.6 0.3 0.9 36.0 0.2 0.2 0.2 35.2 0.1
2,062 64.4 1,146

Baringo South
19.1 0.1 1.0 79.6 0.2 0.1 0.6 79.5 0.2
Constituency 10,976 19.7 5,847

Marigat 32.7 0.0 0.5 66.7 0.1 0.1 0.6 64.6 -

4,401 34.6 2,214

Ilchamus 14.8 0.1 0.5 84.4 0.2 0.1 0.1 84.5 0.2
1,730 15.1 1,171

Mochongoi 8.7 0.1 2.1 89.0 0.2 0.1 0.9 89.5 0.3
3,853 9.2 1,798

Mukutan 7.4 - 0.2 92.0 0.4 - 0.2 93.2 0.3

992 6.3 664
Mogotio Constit-
21.1 0.5 0.4 77.4 0.6 0.3 0.3 72.5 0.7
uency 7,914 26.1 3,939

Mogotio 28.9 1.0 0.5 68.4 1.3 0.5 0.2 62.1 1.3
3,649 35.9 1,926

Emining 18.0 - 0.3 81.6 0.1 0.3 0.3 77.3 0.3

2,166 21.8 1,077

Kisanana 10.6 0.1 0.4 88.8 0.1 0.1 0.4 88.4 -

2,099 11.1 936
Eldama Ravine
36.3 0.4 4.8 57.9 0.7 0.4 4.9 54.6 0.9
Constituency 15,736 39.1 6,770

47
Exploring Kenya’s Inequality

Lembus 20.2 0.1 7.0 72.0 0.7 0.1 7.1 69.5

2,998 21.7 1.6 1,305

Lembus Kwen 35.6 0.2 0.9 63.2 0.1 0.5 0.8 58.3 0.1
2,799 40.3 1,093

Ravine 54.1 1.0 0.8 43.7 0.5 0.7 0.4 41.5 0.4
3,002 56.9 1,361
Mumberes/Maji
21.6 0.1 16.4 59.9 2.0 0.2 16.0 61.0 1.9
Mazuri 2,787 21.1 1,291

Lembus/Perkerra 50.4 0.7 0.8 48.0 0.1 0.9 0.7 43.0 -

2,433 55.4 996

Koibatek 38.2 0.2 1.0 59.9 0.6 0.3 1.9 51.1 1.7
1,717 45.0 724

Table 1.17: Main Roofing Material by County Constituency and Ward

County/ Constituency/ Corrugated Tiles Concrete Asbestos Grass Makuti Tin Mud/ Other Households
Ward Iron Sheets sheets Dung

Kenya 73.5 2.2 3.6 2.2 13.3 3.2 0.3 0.8 1.0 8,493,380
Rural 70.3 0.7 0.2 1.8 20.2 4.2 0.2 1.2 1.1 5,239,879
Urban 78.5 4.6 9.1 2.9 2.1 1.5 0.3 0.1 0.9 3,253,501
Baringo County 57.5 1.0 0.1 1.5 39.1 0.2 0.1 0.1 0.5 107,133
Tiaty Constituency 7.6 0.4 0.0 0.2 90.9 0.5 0.1 0.1 0.2 21,152
Tirioko 1.3 0.1 0.0 0.1 98.0 0.2 0.0 0.1 0.2 3,748
Kollowa 6.6 0.4 0.0 0.2 92.6 0.0 0.0 0.1 0.0 3,069
Ribkwo 15.7 0.3 0.0 0.3 83.2 0.0 0.1 0.1 0.3 2,511
Silale 0.2 0.1 0.0 0.1 97.3 2.2 0.0 0.0 0.1 3,289
Loiyamorok 15.9 2.1 0.1 0.1 81.6 0.0 0.1 0.1 0.2 1,977
Tangulbei/Korossi 7.1 0.4 0.1 0.0 91.5 0.1 0.2 0.2 0.4 3,376
Churo/Amaya 12.8 0.2 0.1 0.6 85.4 0.4 0.0 0.3 0.2 3,182
Baringo North Constit-
53.9 0.9 0.0 1.3 43.5 0.1 0.1 0.1 0.1 18,935
uency
Barwessa 26.0 0.9 0.1 0.8 72.1 0.1 0.0 0.0 0.0 4,943
Kabartonjo 77.9 1.2 0.1 1.4 19.1 0.0 0.2 0.1 0.0 3,811
Saimo/Kipsaram 86.3 0.8 0.0 0.5 12.1 0.2 0.0 0.0 0.1 4,154
Saimo/Soi 47.7 1.0 0.0 1.2 49.4 0.1 0.4 0.1 0.1 3,663
Bartabwa 26.5 0.3 0.0 3.5 69.3 0.0 0.1 0.0 0.2 2,364
Baringo Central Constit-
80.2 1.8 0.2 2.3 15.3 0.0 0.1 0.0 0.1 15,864
uency
Kabarnet 71.8 2.5 0.4 4.7 20.4 0.0 0.1 0.0 0.1 5,419
Sacho 84.2 1.0 0.0 1.5 13.1 0.0 0.0 0.0 0.0 2,025
Tenges 73.8 1.0 0.2 1.9 22.9 0.0 0.1 0.2 0.1 1,967
Ewalel/Chapchap 87.8 1.2 0.0 0.5 10.3 0.1 0.1 0.0 0.1 3,245
Kapropita 88.2 2.5 0.0 0.8 8.4 0.0 0.0 0.1 0.0 3,208
Baringo South Constit-
61.1 0.8 0.1 1.7 35.8 0.2 0.2 0.0 0.2 16,823
uency
Marigat 76.6 0.6 0.0 3.1 19.5 0.1 0.0 0.0 0.1 6,615
Ilchamus 37.6 0.9 0.1 0.1 60.3 0.2 0.5 0.1 0.1 2,901
Mochongoi 67.6 0.9 0.0 1.1 29.6 0.3 0.0 0.1 0.3 5,651
Mukutan 18.4 0.8 0.0 0.7 78.9 0.2 0.6 0.0 0.4 1,656
Mogotio Constituency 68.6 1.1 0.0 0.1 29.0 0.3 0.0 0.0 0.8 11,853
Mogotio 75.9 1.5 0.0 0.2 20.9 0.1 0.1 0.0 1.3 5,575

48 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Emining 63.5 0.5 0.0 0.1 35.7 0.0 0.0 0.0 0.1 3,243
Kisanana 60.7 1.0 0.0 0.0 36.6 0.9 0.0 0.0 0.8 3,035
Eldama Ravine Constit-
82.9 1.2 0.3 2.8 11.1 0.1 0.2 0.1 1.3 22,506
uency
Lembus 76.2 1.3 0.0 2.8 15.4 0.2 0.0 0.0 4.0 4,303
Lembus Kwen 78.2 0.6 0.0 8.0 13.0 0.0 0.1 0.1 0.0 3,892
Ravine 92.4 1.7 1.2 2.2 1.2 0.0 0.8 0.1 0.4 4,363
Mumberes/Maji Mazuri 87.9 1.1 0.0 2.3 6.4 0.4 0.0 0.0 1.8 4,078
Lembus/Perkerra 82.2 0.9 0.2 0.0 16.3 0.0 0.1 0.2 0.1 3,429
Koibatek 78.1 1.3 0.2 0.2 19.0 0.1 0.0 0.0 1.0 2,441

Table 1.18: Main Roofing Material in Male Headed Households by County, Constituency and Ward

County/Constituency/ Corrugated Tiles Concrete Asbestos Grass Makuti Tin Mud/Dung Other Households
Ward Iron Sheets sheets

Kenya 73.0 2.3 3.9 2.3 13.5 3.2 0.3 0.5 1.0 5,762,320

Rural 69.2 0.8 0.2 1.8 21.5 4.4 0.2 0.9 1.1 3,413,616

Urban 78.5 4.6 9.3 2.9 2.0 1.4 0.3 0.1 0.9 2,348,704

Baringo County 59.4 1.1 0.1 1.6 36.9 0.2 0.1 0.1 0.5 69,621

Tiaty Constituency 9.1 0.5 0.0 0.3 89.0 0.7 0.1 0.1 0.3 12,501

Tirioko 1.7 0.1 - 0.2 97.4 0.2 - 0.1 0.1 2,194

Kollowa 8.0 0.4 0.1 0.1 91.4 0.1 - 0.1 - 1,887

Ribkwo 19.0 0.3 0.1 0.5 79.6 0.1 0.1 0.1 0.3 1,496

Silale 0.3 0.1 - - 96.2 3.3 0.1 - 0.2 1,952

Loiyamorok 17.3 3.0 - 0.1 79.4 - - - 0.2 1,238

Tangulbei/Korossi 8.6 0.5 0.1 - 89.5 0.1 0.3 0.2 0.8 1,775

Churo/Amaya 14.8 0.3 0.1 1.0 82.8 0.6 - 0.2 0.2 1,959
Baringo North Constit-
uency 54.4 0.9 0.1 1.2 43.1 0.1 0.1 0.1 0.1 12,125

Barwessa 25.0 0.9 0.1 0.8 73.0 0.1 0.1 0.1 - 3,143

Kabartonjo 77.7 1.2 0.2 1.3 19.3 0.0 0.3 0.1 - 2,621

Saimo/Kipsaram 86.3 0.8 - 0.5 12.1 0.2 - 0.0 0.1 2,655

Saimo/Soi 49.6 0.9 - 1.0 47.9 0.2 0.3 0.1 0.0 2,237

Bartabwa 25.2 0.3 - 3.8 70.1 0.1 0.1 0.1 0.3 1,469
Baringo Central Con-
stituency 80.6 2.0 0.2 2.3 14.7 0.0 0.1 0.0 0.1 10,369

Kabarnet 72.7 2.8 0.5 4.8 18.9 0.1 0.1 - 0.1 3,517

Sacho 83.2 1.1 - 1.5 14.1 0.1 - - 0.1 1,301

49
Exploring Kenya’s Inequality

Tenges 73.2 1.1 0.1 2.0 23.5 - - 0.2 0.1 1,313

Ewalel/Chapchap 88.3 1.0 0.0 0.4 10.0 0.0 0.1 0.0 0.1 2,176

Kapropita 88.8 2.7 0.0 0.8 7.6 0.0 - 0.0 0.0 2,062
Baringo South Constit-
uency 63.0 0.8 0.1 1.9 33.6 0.2 0.2 0.0 0.2 10,976

Marigat 76.7 0.5 0.0 3.3 19.1 0.1 - 0.0 0.1 4,401

Ilchamus 37.9 1.0 0.2 0.2 59.8 0.2 0.5 0.1 0.1 1,730

Mochongoi 69.5 1.1 0.0 1.3 27.4 0.3 - 0.0 0.3 3,853

Mukutan 20.6 0.8 - 0.3 76.3 0.3 1.0 - 0.7 992

Mogotio Constituency 67.5 1.2 0.0 0.2 29.9 0.3 0.0 0.0 0.9 7,914

Mogotio 74.8 1.6 0.0 0.3 21.8 0.1 0.1 0.0 1.3 3,649

Emining 62.5 0.5 0.0 0.1 36.8 - - - 0.0 2,166

Kisanana 60.0 1.2 - 0.0 36.8 1.0 - - 1.0 2,099

Eldama Ravine Con-
stituency 82.8 1.3 0.3 2.8 11.2 0.1 0.2 0.1 1.2 15,736

Lembus 76.7 1.6 0.0 2.6 15.0 0.2 0.0 - 3.9 2,998

Lembus Kwen 79.3 0.8 - 8.0 11.8 - 0.1 0.1 - 2,799

Ravine 91.7 2.1 1.3 2.3 1.2 - 0.7 0.2 0.4 3,002

Mumberes/Maji Mazuri 87.8 1.1 0.0 2.4 6.5 0.4 - - 1.8 2,787

Lembus/Perkerra 81.5 0.9 0.2 0.0 17.1 0.0 0.1 0.2 0.1 2,433

Koibatek 77.1 1.3 0.2 0.2 20.2 0.2 0.1 0.1 0.6 1,717

Table 1.19: Main Roofing Material in Female Headed Households by County, Constituency and Ward

County/Constituen- Corrugated Iron Tiles Concrete Asbestos Grass Makuti Tin Mud/ Other Households
cy/Ward Sheets sheets Dung

Kenya 74.5 2.0 3.0 2.2 12.7 3.2 0.3 1.2 1.0 2,731,060

Rural 72.5 0.7 0.1 1.8 17.8 3.9 0.3 1.8 1.1 1,826,263

Urban 78.6 4.5 8.7 2.9 2.3 1.6 0.3 0.1 0.9 904,797

Baringo County 54.0 0.8 0.1 1.3 43.1 0.1 0.1 0.1 0.4 37,512

Tiaty Constituency 5.6 0.2 0.0 0.1 93.6 0.2 0.0 0.1 0.1 8,651

Tirioko 0.8 0.1 - - 98.8 0.1 - - 0.2 1,554

Kollowa 4.5 0.4 - 0.3 94.7 - - 0.1 0.1 1,182

Ribkwo 10.8 0.3 - 0.1 88.4 - - 0.2 0.2 1,015

50 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Silale 0.1 0.1 0.1 0.1 98.9 0.7 - - - 1,337

Loiyamorok 13.5 0.5 0.1 - 85.3 - 0.3 0.1 0.1 739

Tangulbei/Korossi 5.4 0.4 0.1 0.1 93.7 0.1 0.1 0.2 - 1,601

Churo/Amaya 9.7 0.1 0.1 - 89.5 0.2 - 0.3 0.1 1,223

Baringo North Con-
stituency 53.0 0.9 - 1.3 44.4 0.1 0.1 0.0 0.1 6,810

Barwessa 27.6 1.1 - 0.8 70.5 - - - 0.1 1,800

Kabartonjo 78.2 1.2 - 1.7 18.8 - - - 0.1 1,190

Saimo/Kipsaram 86.2 0.7 - 0.4 12.2 0.3 0.1 - 0.2 1,499

Saimo/Soi 44.7 1.1 - 1.5 51.9 0.1 0.5 0.1 0.1 1,426

Bartabwa 28.6 0.4 - 2.9 68.0 - - - - 895

Baringo Central Con-
stituency 79.5 1.6 0.1 2.3 16.3 0.0 0.1 0.1 0.0 5,495

Kabarnet 70.1 1.9 0.3 4.4 23.2 - 0.1 - 0.1 1,902

Sacho 86.0 0.8 0.1 1.5 11.5 - - - - 724

Tenges 75.1 0.8 0.3 1.7 21.7 - 0.2 0.3 - 654

Ewalel/Chapchap 86.6 1.6 - 0.7 10.9 0.2 - - - 1,069

Kapropita 87.1 2.2 - 0.9 9.8 - - 0.1 - 1,146

Baringo South Con-
stituency 57.5 0.7 0.0 1.3 39.9 0.2 0.2 0.1 0.1 5,847

Marigat 76.2 0.6 0.0 2.6 20.3 0.1 0.1 - 0.1 2,214

Ilchamus 37.1 0.9 - 0.1 61.1 0.1 0.6 0.1 - 1,171

Mochongoi 63.5 0.6 0.1 0.7 34.4 0.3 0.1 0.1 0.3 1,798

Mukutan 15.1 0.8 - 1.2 82.8 0.2 - - - 664

Mogotio Constituency 70.9 0.9 - 0.1 27.2 0.2 0.0 - 0.8 3,939

Mogotio 78.1 1.2 - 0.1 19.3 - - - 1.3 1,926

Emining 65.6 0.6 - 0.1 33.5 - 0.1 - 0.1 1,077

Kisanana 62.4 0.5 - - 36.1 0.6 - - 0.3 936

Eldama Ravine Con-
stituency 83.3 0.8 0.3 2.7 11.0 0.1 0.2 0.1 1.4 6,770

Lembus 75.3 0.7 - 3.3 16.3 0.1 - 0.2 4.1 1,305

Lembus Kwen 75.4 0.2 - 8.1 16.1 - 0.2 - - 1,093

Ravine 94.0 0.9 1.0 1.8 1.2 0.1 0.8 - 0.2 1,361

Mumberes/Maji Mazuri 88.0 1.0 - 2.2 6.3 0.5 0.2 - 1.9 1,291

Lembus/Perkerra 83.9 1.1 0.3 - 14.5 - - 0.2 - 996

51
Exploring Kenya’s Inequality

Koibatek 80.4 1.4 0.1 0.1 16.2 - - - 1.8 724

Table 1.20: Main material of the wall by County, Constituency and Ward

County/ Constituency/ Stone Brick/ Mud/ Mud/ Wood Corrugat- Grass/ Tin Other House-
Ward Block Wood Cement only ed Iron Reeds holds
Sheets
Kenya 16.7 16.9 36.5 7.7 11.1 6.7 3.0 0.3 1.2 8,493,380
Rural 5.7 13.8 50.0 7.6 14.4 2.5 4.4 0.3 1.4 5,239,879
Urban 34.5 21.9 14.8 7.8 5.8 13.3 0.8 0.3 0.9 3,253,501

Baringo County 5.1 3.5 50.6 6.2 25.8 6.5 1.6 0.1 0.8
107,133

Tiaty Constituency 1.6 1.1 60.4 3.2 25.3 0.7 6.7 0.1 0.9
21,152

Tirioko 0.1 0.3 32.6 0.8 58.1 0.1 7.9 0.0 0.1
3,748

Kollowa 1.7 1.6 77.8 3.6 13.0 0.1 2.2 0.0 0.1
3,069

Ribkwo 3.6 2.5 39.5 2.4 40.9 1.5 9.1 0.1 0.3
2,511

Silale 0.1 0.3 31.2 2.7 42.5 0.0 20.6 0.0 2.6
3,289

Loiyamorok 8.5 2.4 61.4 8.3 10.4 1.7 3.9 0.1 3.3
1,977

Tangulbei/Korossi 0.4 1.0 87.1 4.1 3.3 1.9 1.3 0.2 0.7
3,376

Churo/Amaya 0.4 0.5 94.2 2.5 0.8 0.5 0.8 0.0 0.2
3,182
Baringo North Constit-
2.1 2.8 56.7 8.8 25.9 2.9 0.5 0.0 0.2
uency 18,935

Barwessa 0.8 1.9 80.7 11.9 2.5 1.1 0.8 0.0 0.2
4,943

Kabartonjo 1.4 2.9 35.2 6.6 52.1 1.4 0.2 0.0 0.1
3,811

Saimo/Kipsaram 1.5 3.1 38.1 4.5 50.5 1.4 0.5 0.0 0.3
4,154

Saimo/Soi 5.6 3.7 53.2 12.7 14.1 9.9 0.7 0.1 0.1
3,663

Bartabwa 1.6 2.5 79.3 7.4 7.8 0.7 0.4 0.0 0.3
2,364
Baringo Central Constit-
5.5 9.6 39.0 7.4 34.3 3.8 0.2 0.1 0.3
uency 15,864

Kabarnet 8.3 10.8 30.5 10.4 35.5 3.5 0.2 0.1 0.7
5,419

Sacho 2.7 4.5 51.2 5.5 32.0 3.9 0.2 0.0 0.0
2,025

Tenges 2.9 7.3 54.2 13.1 11.7 10.1 0.5 0.1 0.1
1,967

Ewalel/Chapchap 3.9 4.8 46.7 3.5 38.4 2.5 0.1 0.0 0.1
3,245

Kapropita 5.5 17.0 28.6 3.9 43.3 1.6 0.1 0.0 0.1
3,208
Baringo South Constit-
1.6 2.6 48.0 6.1 15.8 24.8 0.4 0.2 0.3
uency 16,823

Marigat 2.2 4.5 34.3 4.6 12.0 41.5 0.4 0.2 0.1
6,615

Ilchamus 1.6 2.4 59.6 9.8 1.2 23.9 0.4 0.3 0.7
2,901

Mochongoi 1.0 0.9 49.1 5.7 31.4 11.1 0.4 0.0 0.5
5,651

52 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Mukutan 1.6 1.0 79.2 7.3 2.8 6.7 0.4 0.8 0.2
1,656

Mogotio Constituency 7.3 2.9 70.5 6.6 4.4 7.6 0.1 0.0 0.7
11,853

Mogotio 12.7 3.9 65.1 6.6 5.4 5.0 0.0 0.0 1.3
5,575

Emining 2.5 2.4 69.7 5.1 5.7 14.0 0.2 0.0 0.3
3,243

Kisanana 2.5 1.4 81.1 8.2 1.3 5.5 0.0 0.0 0.1
3,035
Eldama Ravine Constit-
11.9 3.2 35.8 5.7 38.8 2.4 0.2 0.1 1.8
uency 22,506

Lembus 3.1 1.7 30.6 2.4 58.0 1.6 0.4 0.0 2.3
4,303

Lembus Kwen 11.0 4.0 41.2 5.0 37.1 1.5 0.1 0.1 0.0
3,892

Ravine 18.5 4.1 42.8 9.7 18.5 3.5 0.1 0.1 2.8
4,363

Mumberes/Maji Mazuri 4.4 2.2 24.1 1.3 64.6 1.2 0.0 0.0 2.0
4,078

Lembus/Perkerra 26.9 3.5 33.3 10.3 19.0 3.9 0.3 0.1 2.7
3,429

Koibatek 8.8 4.3 47.3 6.6 28.6 3.5 0.0 0.0 0.9
2,441

Table 1.21: Main Material of the Wall in Male Headed Households by County, Constituency and Ward

County/ Constitu- Stone Brick/ Mud/ Mud/ Wood Corru- Grass/ Tin Other House-
ency/ Ward Block Wood Ce- only gated Reeds holds
ment Iron
Sheets

Kenya
17.5 16.6 34.7 7.6 11.4 7.4 3.4 0.3 1.2 5,762,320

Rural
5.8 13.1 48.9 7.3 15.4 2.6 5.2 0.3 1.4 3,413,616

Urban
34.6 21.6 14.0 7.9 5.6 14.4 0.7 0.3 0.9 2,348,704

Baringo County
5.2 3.6 50.1 6.3 26.1 6.5 1.4 0.1 0.8 69,621

Tiaty Constituency
2.0 1.4 59.2 3.4 25.3 0.9 6.9 0.1 0.9 12,501

Tirioko
0.1 0.4 30.9 0.8 60.1 0.1 7.5 - 0.1 2,194

Kollowa
2.2 2.0 76.9 3.9 12.0 0.1 2.7 - 0.1 1,887

Ribkwo
4.7 3.3 37.7 3.0 40.1 1.6 9.2 0.1 0.3 1,496

Silale
0.1 0.2 32.1 2.4 41.8 0.1 21.6 0.1 1.8 1,952

Loiyamorok
9.5 3.0 60.2 8.8 9.4 1.9 3.4 - 3.9 1,238

Tangulbei/Korossi
0.4 1.2 85.0 5.0 3.5 2.3 1.2 0.3 1.0 1,775

Churo/Amaya
0.4 0.6 93.3 2.5 0.9 0.7 1.3 0.1 0.3 1,959
Baringo North
Constituency 2.2 2.9 56.0 8.9 26.4 2.7 0.5 0.0 0.2 12,125

Barwessa
0.7 1.8 80.6 12.4 2.5 1.0 0.8 0.1 0.2 3,143

Kabartonjo
1.4 2.8 35.6 6.8 51.4 1.7 0.2 - 0.1 2,621

53
Exploring Kenya’s Inequality

Saimo/Kipsaram
1.8 3.5 36.9 4.6 50.8 1.5 0.6 0.0 0.3 2,655

Saimo/Soi
6.0 4.1 52.7 12.9 14.2 9.4 0.5 - 0.1 2,237

Bartabwa
2.0 2.3 79.6 6.9 7.8 0.5 0.4 0.1 0.4 1,469
Baringo Central
Constituency 5.4 9.3 39.3 7.6 34.3 3.6 0.2 0.1 0.3 10,369

Kabarnet
8.4 10.7 29.9 10.4 36.1 3.5 0.2 0.1 0.6 3,517

Sacho
2.6 4.7 52.1 6.1 31.1 3.1 0.2 - 0.1 1,301

Tenges
2.7 6.8 56.0 13.9 11.3 8.8 0.4 0.2 0.1 1,313

Ewalel/Chapchap
3.8 4.4 47.8 3.6 37.6 2.6 0.0 0.0 0.1 2,176

Kapropita
5.7 16.7 27.4 3.8 44.4 1.7 0.1 - 0.1 2,062
Baringo South
Constituency 1.6 2.6 47.1 6.3 16.6 25.0 0.3 0.3 0.3 10,976

Marigat
2.3 4.4 34.9 5.0 11.4 41.4 0.3 0.2 0.1 4,401

Ilchamus
1.3 2.6 59.4 9.7 1.4 24.2 0.3 0.3 0.8 1,730

Mochongoi
0.9 0.9 47.8 5.6 32.7 11.4 0.2 0.0 0.4 3,853

Mukutan
1.9 1.1 76.9 8.5 3.1 6.5 0.3 1.3 0.4 992
Mogotio Constit-
uency 6.8 2.7 72.3 5.9 4.3 7.1 0.1 0.0 0.7 7,914

Mogotio
12.0 3.7 67.3 5.6 5.2 4.9 0.0 0.0 1.3 3,649

Emining
2.2 2.3 71.7 4.8 5.6 12.6 0.2 - 0.5 2,166

Kisanana
2.5 1.5 81.4 7.6 1.3 5.5 0.0 - 0.1 2,099
Eldama Ravine
11.6
Constituency 3.1 36.2 5.8 38.8 2.5 0.1 0.1 1.8 15,736

Lembus
3.3 1.8 31.1 2.4 57.0 1.8 0.4 0.0 2.1 2,998

Lembus Kwen -
10.1 3.7 41.3 4.9 38.3 1.6 0.0 0.1 2,799

Ravine
18.4 3.8 42.7 9.7 19.1 3.3 0.1 0.2 2.8 3,002
Mumberes/Maji
Mazuri 4.8 2.2 24.4 1.3 64.2 1.2 - - 2.0 2,787

Lembus/Perkerra
25.4 3.6 33.4 11.2 19.2 4.0 0.3 0.1 2.8 2,433

Koibatek
8.3 3.8 49.0 6.5 28.4 3.4 - - 0.6 1,717

Table 1.22: Main Material of the Wall in Female Headed Households by County, Constituency and Ward

County/ Con- Stone Brick/ Mud/ Mud/ Wood only Corrugated Grass/ Tin Other Households
stituency Block Wood Cement Iron Sheets Reeds
Kenya 15.0 17.5 40.4 7.9 10.5 5.1 2.1 0.3 1.2 2,731,060
Rural 5.4 14.9 52.1 8.0 12.6 2.4 2.8 0.4 1.4 1,826,263
Urban 34.2 22.6 16.9 7.6 6.2 10.5 0.8 0.3 0.9 904,797

54 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Baringo
4.8 3.5 51.6 6.0 25.1 6.4 1.7 0.1 0.8 37,512
County
Tiaty Constit-
1.1 0.7 62.2 2.8 25.3 0.6 6.4 0.0 0.9 8,651
uency
Tirioko 0.1 0.3 35.0 0.8 55.2 - 8.5 - 0.1 1,554
Kollowa 0.8 0.8 79.3 3.0 14.6 - 1.4 - 0.1 1,182

Ribkwo 2.0 1.5 42.1 1.4 9.0 0.3 1,015

42.3 1.6 -

Silale 0.1 0.4 29.8 43.7 - 19.1 3.7 1,337

3.3 -

Loiyamorok 7.0 1.5 63.5 12.0 1.2 4.7 0.3 2.3 739
7.4
Tangulbei/
0.4 0.8 89.6 3.1 3.1 1.5 1.4 - 0.2 1,601
Korossi
Churo/Amaya 0.4 0.4 95.6 2.5 0.7 0.2 0.1 - 0.1 1,223
Baringo North
1.9 2.6 58.0 8.6 25.0 3.0 0.6 0.1 0.2 6,810
Constituency
Barwessa 1.1 2.1 81.0 11.1 2.4 1.2 1.0 - 0.1 1,800
Kabartonjo 1.5 3.1 34.4 6.2 53.7 0.8 0.3 - 0.1 1,190
Saimo/Kipsar-
1.0 2.5 40.3 4.3 49.9 1.1 0.3 0.1 0.5 1,499
am
Saimo/Soi 4.9 3.0 54.0 12.3 14.0 10.6 0.8 0.3 0.1 1,426
Bartabwa 1.0 2.8 78.9 8.2 7.8 1.0 0.3 - - 895
Baringo Cen-
tral Constitu- 5.5 10.1 38.5 7.1 34.2 .1 0.2 0.0 0.3 5,495
ency
Kabarnet 8.2 11.0 31.7 10.5 34.3 3.4 0.2 0.1 0.8 1,902
Sacho 2.9 4.3 49.4 4.3 33.6 5.4 0.1 - - 724
Tenges 3.4 8.4 50.6 11.6 12.7 12.7 0.6 - - 654
Ewalel/Chap-
4.1 5.7 44.5 3.3 39.9 2.2 0.2 - - 1,069
chap
Kapropita 5.2 17.4 30.5 4.2 41.3 1.3 - - 0.1 1,146
Baringo South
1.7 2.6 49.8 5.8 14.3 24.5 0.6 0.2 0.4 5,847
Constituency
Marigat 2.1 4.8 33.0 3.9 13.4 41.8 0.7 0.3 0.0 2,214
Ilchamus 2.1 2.1 59.9 9.8 1.0 23.5 0.4 0.4 0.7 1,171
Mochongoi 1.1 0.9 51.8 5.7 28.4 10.5 0.8 - 0.8 1,798
Mukutan 1.1 0.9 82.5 5.6 2.3 7.1 0.5 0.2 - 664
Mogotio Con-
8.3 3.1 66.9 7.9 4.8 8.4 0.1 - 0.6 3,939
stituency
Mogotio 14.0 4.3 61.1 8.4 5.9 5.2 - - 1.2 1,926

Emining 3.0 2.6 65.6 5.8 5.8 1,077

16.9 0.2 - 0.1
Kisanana 2.5 1.3 80.2 9.4 1.3 5.3 - - - 936
Eldama Ravine
12.7 3.5 34.9 5.5 38.9 2.4 0.2 0.0 2.0 6,770
Constituency
Lembus 2.5 1.3 29.4 2.4 60.2 1.1 0.5 - 2.6 1,305
Lembus Kwen 13.4 4.8 40.8 5.5 33.9 1.4 0.1 0.1 - 1,093
Ravine 18.6 5.0 43.0 9.7 17.1 4.0 0.1 - 2.6 1,361
Mumberes/
3.6 2.2 23.6 1.5 65.5 1.2 - 0.1 2.2 1,291
Maji Mazuri
Lembus/Perk-
30.4 3.4 33.0 7.9 18.6 3.7 0.3 - 2.6 996
erra
Koibatek 10.2 5.2 43.2 7.0 29.1 3.6 - - 1.5 724

Table 1.23: Source of Water by county, Constituency and Ward

55
 County/ Constitu- Pond Dam Lake Stream/ Unprotected Unprotected Jabia Water Other Unimproved Protected Protected Borehole Piped into Piped Rain Im- No/ Individuals
ency /Ward River Spring Well vendor Sources Spring Well Dwelling Water proved

56
Collection Sourc-
es
Kenya 2.7 2.4 1.2 23.2 5.0 6.9 0.3 5.2 0.4 47.4 7.6 7.7 11.6 5.9 19.2 0.7 52.6 37,919,647
Rural 3.6 3.2 1.5 29.6 6.4 8.7 0.4 2.2 0.5 56.0 9.2 8.1 12.0 1.8 12.1 0.8 44.0 26,075,195
Urban 0.9 0.7 0.5 9.2 1.9 2.9 0.2 11.8 0.1 28.3 4.0 6.8 10.7 14.7 34.9 0.5 71.7 11,844,452
Baringo County 2.4 4.7 2.0 52.9 3.9 6.0 0.1 0.8 3.8 76.5 2.6 2.0 6.9 1.5 10.2 0.3 23.5 548,635
Exploring Kenya’s Inequality

Tiaty Constitu-
ency 1.5 8.9 2.1 44.2 4.6 15.2 0.1 0.1 12.7 89.5 0.9 1.2 7.8 0.3 0.1 0.1 10.5 132,070
Tirioko 3.6 1.3 0.0 49.1 6.0 17.4 0.1 0.2 17.7 95.3 0.7 1.6 2.4 0.0 0.0 0.0 4.7 23,561
Kollowa 1.4 8.9 0.0 49.9 0.7 11.3 0.7 0.1 11.5 84.5 2.4 5.8 7.2 0.0 0.1 0.1 15.5 19,364
Ribkwo 1.3 0.5 0.0 52.5 6.1 22.2 0.0 0.1 0.0 82.7 2.0 0.1 12.1 2.2 0.9 0.1 17.3 14,433
Silale 0.1 0.6 0.0 74.9 2.3 5.6 0.0 0.3 16.1 99.8 0.1 0.0 0.1 0.0 0.0 0.0 0.2 21,804

A PUBLICATION OF KNBS AND SID

Loiyamorok 0.6 19.7 7.8 22.8 0.1 10.4 0.0 0.1 26.2 87.7 0.1 0.1 12.0 0.0 0.0 0.0 12.3 13,369
Tangulbei/Korossi 2.1 37.5 8.9 22.0 1.0 10.3 0.1 0.0 3.8 85.8 0.2 0.3 13.1 0.1 0.1 0.3 14.2 18,352
Churo/Amaya 1.1 0.2 0.2 29.1 13.8 28.5 0.0 0.1 12.8 85.7 1.1 0.2 12.4 0.0 0.1 0.3 14.3 21,187
Baringo North
Constituency 0.2 1.4 4.2 67.5 6.0 3.6 0.1 0.3 1.2 84.4 5.9 0.6 6.5 0.4 1.8 0.5 15.6 93,383
Barwessa 0.1 0.0 0.0 82.0 3.4 3.6 0.0 0.3 0.4 89.8 3.3 0.1 5.6 0.7 0.3 0.2 10.2 23,938
Kabartonjo 0.1 0.6 0.1 56.0 12.4 1.1 0.1 0.5 0.0 70.9 19.1 2.0 2.6 0.1 4.4 1.0 29.1 19,038
Saimo/Kipsaram 0.2 1.9 0.0 86.3 3.4 0.2 0.2 0.0 0.0 92.2 1.5 0.0 1.4 0.7 3.3 0.9 7.8 20,916
Saimo/Soi 0.8 1.5 21.9 32.0 5.5 11.7 0.0 0.4 2.7 76.5 3.4 0.6 18.9 0.0 0.5 0.1 23.5 17,668

Bartabwa 0.0 4.5 0.0 76.1 6.1 1.4 0.0 0.2 4.8 93.1 1.8 0.0 5.0 0.0 0.0 0.0 6.9 11,823
Baringo Central
Constituency 0.4 0.5 0.1 64.0 4.7 1.3 0.0 0.4 0.0 71.5 2.5 0.4 1.6 3.6 19.8 0.7 28.5 78,634
Kabarnet 0.2 0.1 0.0 57.3 1.7 2.2 0.1 1.0 0.0 62.7 1.3 0.1 0.6 6.8 27.6 0.9 37.3 22,370
Sacho 0.6 0.2 0.0 80.8 2.0 0.5 0.0 0.0 0.0 84.2 1.5 1.8 3.7 2.8 5.9 0.2 15.8 14,577
Tenges 1.7 2.2 0.0 72.0 3.9 0.2 0.0 0.3 0.0 80.4 3.8 0.1 0.5 0.7 14.3 0.2 19.6 9,524
Ewalel/Chapchap 0.3 0.0 0.0 73.1 13.7 0.4 0.0 0.1 0.0 87.7 4.5 0.1 1.9 0.9 4.2 0.7 12.3 16,349
Kapropita 0.0 0.9 0.4 43.7 2.6 2.4 0.0 0.1 0.0 50.1 2.1 0.2 1.2 4.2 41.0 1.2 49.9 15,814
Baringo South
Constituency 0.8 1.2 4.9 55.1 4.6 7.2 0.0 1.4 1.2 76.4 2.7 0.8 13.5 0.7 5.8 0.1 23.6 80,229
Marigat 0.4 1.3 0.0 50.7 3.5 3.6 0.0 3.5 0.0 63.0 1.3 1.1 22.0 1.6 10.9 0.0 37.0 27,242
Ilchamus 0.0 0.5 16.6 44.0 0.2 9.3 0.0 0.4 5.1 76.0 0.2 0.1 13.4 0.7 9.5 0.0 24.0 15,903
 Mochongoi 1.9 1.9 0.1 62.4 7.8 10.7 0.0 0.3 0.5 85.6 5.9 1.1 6.7 0.1 0.6 0.1 14.4 27,644
Mukutan 0.1 0.1 13.7 64.8 5.8 4.1 0.0 0.0 0.0 88.5 1.8 0.6 8.7 0.0 0.3 0.0 11.5 9,440
Mogotio Constit-
uency 11.8 17.5 0.1 46.0 0.9 1.2 0.0 1.6 3.4 82.6 3.5 0.6 5.9 0.6 6.6 0.2 17.4 60,136
Mogotio 11.5 16.0 0.2 45.9 0.5 0.4 0.0 2.5 0.0 77.0 6.3 0.6 2.9 1.0 11.9 0.3 23.0 27,016
Emining 0.2 16.3 0.0 60.3 1.3 1.2 0.0 1.7 12.2 93.2 1.6 0.1 0.9 0.5 3.6 0.1 6.8 16,501
Kisanana 23.9 21.1 0.2 31.8 1.1 2.6 0.1 0.2 0.0 80.9 1.1 1.0 15.8 0.0 1.0 0.2 19.1 16,619
Eldama Ravine
Constituency 2.6 0.8 0.1 44.9 1.9 2.0 0.0 1.3 0.0 53.6 1.2 7.1 5.5 3.4 28.7 0.4 46.4 104,183
Lembus 0.1 2.2 0.3 63.6 2.0 2.7 0.0 0.1 0.0 70.9 0.9 12.8 10.4 1.2 3.7 0.2 29.1 21,036
Lembus Kwen 0.2 0.3 0.0 47.7 0.7 0.5 0.0 0.2 0.1 49.7 0.5 2.5 7.6 3.6 35.5 0.5 50.3 20,205
Ravine 0.1 0.2 0.0 13.2 0.0 0.1 0.0 2.6 0.0 16.1 0.0 0.0 0.2 10.3 73.3 0.1 83.9 16,306
Mumberes/Maji
Mazuri 0.4 0.4 0.0 55.0 4.0 6.0 0.0 1.7 0.0 67.6 1.5 22.3 6.3 0.4 1.4 0.5 32.4 18,840
Lembus/Perkerra 0.8 0.7 0.0 43.7 0.2 0.1 0.1 3.1 0.1 48.6 0.1 0.1 3.8 4.9 41.4 1.1 51.4 15,834
Koibatek 20.6 0.7 0.1 36.2 5.3 2.0 0.1 0.4 0.0 65.4 5.9 0.1 1.5 0.5 26.4 0.3 34.6 11,962

Table 1.24: Source of Water of Male headed Household by County Constituency and Ward

County/Constituency/ Pond Dam Lake Stream/ Unpro- Unpro- Ja- Water Other Unim- Pro- Protected Borehole Piped Piped Rain Water Improved No. of Individuals
tected tected bia vendor proved tected Well into Collection Sources
Ward River Spring Well Sources Spring Dwell-
ing

Kenya 2.7 2.3 1.1 22.4 4.8 6.7 0.4 5.6 0.4 46.4 7.4 7.7 11.7 6.2 19.9 0.7 53.6 26,755,066

Rural 3.7 3.1 1.4 29.1 6.3 8.6 0.4 2.4 0.5 55.6 9.2 8.2 12.1 1.9 12.2 0.8 44.4 18,016,471

Urban 0.8 0.6 0.5 8.5 1.8 2.8 0.2 12.1 0.1 27.5 3.8 6.7 10.8 14.9 35.8 0.5 72.5 8,738,595

Baringo County 2.4 4.5 1.8 53.4 3.8 5.8 0.0 0.7 3.7 76.3 2.8 2.0 6.7 1.4 10.4 0.3 23.7 370,561

Tiaty Constituency 1.4 8.4 2.1 44.2 4.2 15.4 0.1 0.1 13.2 89.2 1.0 1.3 7.9 0.3 0.2 0.1 10.8 83,408

Tirioko 2.9 1.6 - 49.5 5.4 18.7 0.1 0.2 17.1 95.6 0.8 1.5 2.0 - - - 4.4 14,854

Kollowa 1.5 7.8 0.1 52.2 0.5 10.6 0.5 0.1 10.4 83.7 2.2 6.1 7.9 - 0.0 0.1 16.3 12,620

57
Pulling Apart or Pooling Together?

Ribkwo 1.4 0.3 0.0 53.9 5.5 19.9 - 0.1 - 81.1 2.0 0.2 13.1 2.3 1.0 0.2 18.9 9,258
 Silale 0.1 0.8 - 69.9 2.1 7.6 0.0 0.3 19.0 99.8 0.1 - 0.1 - - - 0.2 13,816

58
Loiyamorok 0.5 21.3 8.0 18.0 0.2 13.2 - 0.1 26.0 87.3 0.2 0.1 12.4 - - 0.0 12.7 8,709

Tangulbei/Korossi 1.8 36.7 10.3 22.4 0.8 9.4 - 0.1 4.5 86.0 0.2 0.4 12.7 0.2 0.1 0.3 14.0 10,277

Churo/Amaya 1.4 0.2 0.2 31.5 12.8 26.5 - 0.1 13.1 85.9 1.2 0.1 12.4 0.0 0.1 0.3 14.1 13,874
Exploring Kenya’s Inequality

Baringo North Constit-

uency 0.2 1.5 3.9 68.2 5.8 3.5 0.1 0.3 1.1 84.7 6.2 0.5 6.0 0.4 1.7 0.5 15.3 63,368

Barwessa 0.2 - - 82.4 3.2 3.7 0.0 0.3 0.3 90.1 3.6 0.1 5.1 0.6 0.3 0.2 9.9 16,285

Kabartonjo - 0.7 0.1 56.7 12.5 1.1 0.1 0.5 - 71.8 18.9 1.9 2.6 0.1 3.8 1.0 28.2 13,671

A PUBLICATION OF KNBS AND SID

Saimo/Kipsaram 0.2 2.1 - 86.2 3.0 0.1 0.2 0.0 - 91.8 1.5 0.0 1.4 1.0 3.1 1.1 8.2 14,252

Saimo/Soi 0.8 1.4 21.9 33.7 5.0 12.1 - 0.4 2.5 77.9 3.5 0.6 17.4 - 0.5 0.1 22.1 11,283

Bartabwa - 4.6 - 75.7 5.9 1.3 - 0.1 4.7 92.3 2.1 - 5.5 - 0.0 - 7.7 7,877
Baringo Central Con-
stituency 0.4 0.5 0.1 64.5 4.8 1.4 0.0 0.3 0.0 72.0 2.7 0.5 1.5 3.5 19.1 0.7 28.0 52,984

Kabarnet 0.1 0.1 0.0 57.1 1.9 2.1 0.1 1.0 0.1 62.5 1.4 0.1 0.5 6.8 27.7 1.0 37.5 14,850

Sacho 0.6 0.3 - 81.9 1.7 0.5 - - - 85.0 1.7 1.8 3.4 2.5 5.4 0.1 15.0 9,680

Tenges 1.9 1.9 0.0 73.1 3.9 0.3 - 0.1 - 81.1 4.4 0.1 0.6 0.5 13.1 0.2 18.9 6,637

Ewalel/Chapchap 0.2 0.1 - 73.6 13.7 0.4 - 0.1 - 88.1 4.6 0.1 2.0 0.8 3.8 0.6 11.9 11,236

Kapropita 0.0 0.9 0.3 43.7 2.7 2.8 0.1 0.1 - 50.6 2.6 0.2 1.4 4.7 39.2 1.2 49.4 10,581
Baringo South Constit-
uency 0.8 1.3 4.4 55.7 4.8 7.2 - 1.4 1.2 76.6 2.8 0.7 13.5 0.7 5.5 0.1 23.4 53,780

Marigat 0.5 1.4 - 51.1 3.6 3.5 - 3.4 - 63.5 1.4 0.9 21.9 1.6 10.8 0.0 36.5 18,689

Ilchamus - 0.4 16.0 45.3 0.2 9.4 - 0.5 5.3 77.2 0.3 0.2 13.2 0.6 8.6 - 22.8 9,968

Mochongoi 1.6 2.0 0.1 62.8 7.8 10.4 - 0.3 0.6 85.6 5.8 1.0 6.9 0.1 0.4 0.1 14.4 19,107

Mukutan 0.1 0.1 12.7 64.4 6.2 4.5 - - - 88.1 2.0 0.4 9.0 - 0.4 0.1 11.9 6,016
 Mogotio Constituency 12.0 17.5 0.2 47.0 0.9 1.2 0.0 1.3 3.4 83.5 3.6 0.5 5.5 0.5 6.1 0.2 16.5 42,026

Mogotio 12.1 16.0 0.2 46.9 0.5 0.3 0.0 2.1 0.0 78.2 6.5 0.5 2.6 0.7 11.2 0.3 21.8 18,271

Emining 0.1 16.1 - 61.0 1.4 1.3 - 1.3 12.1 93.2 1.8 - 0.7 0.6 3.6 0.1 6.8 11,820

Kisanana 23.7 21.2 0.2 33.3 0.9 2.5 0.1 0.1 0.0 81.9 1.0 1.1 14.8 0.0 1.0 0.2 18.1 11,935
Eldama Ravine Con-
stituency 2.6 0.7 0.1 45.4 1.9 1.9 0.0 1.3 0.0 53.9 1.3 6.9 5.5 3.2 28.8 0.4 46.1 74,995

Lembus 0.1 1.9 0.3 63.5 2.2 2.8 - 0.1 - 70.8 0.9 12.6 10.5 1.2 3.9 0.1 29.2 15,198

Lembus Kwen 0.3 0.3 - 48.6 0.9 0.4 - 0.3 0.1 50.9 0.6 2.7 7.4 3.3 34.5 0.6 49.1 15,138

Ravine 0.0 0.1 - 12.7 - 0.1 - 2.6 0.0 15.6 0.0 - 0.2 9.4 74.7 0.1 84.4 11,254

Mumberes/Maji Mazuri 0.5 0.4 - 55.3 3.9 5.9 0.0 1.6 - 67.6 1.6 21.9 6.5 0.5 1.6 0.4 32.4 13,202

Lembus/Perkerra 0.7 0.7 - 44.8 0.2 0.1 0.1 3.1 0.0 49.7 0.1 - 3.6 4.7 40.9 1.1 50.3 11,579

Koibatek 20.4 0.6 - 36.0 4.9 1.8 0.1 0.2 - 64.1 6.1 - 1.4 0.5 27.7 0.2 35.9 8,624

Table 1.25: Source of Water of Female headed Household by county Constituency and Ward

County/Constituency/ Pond Dam Lake Stream/ Unpro- Unpro- Jabia Water Other Unim- Pro- Protect- Bore- Piped into Piped Rain Water Improved No. of Individ-
Ward tected tected ven- proved tected ed Well hole Dwelling Collection Sources uals
River Spring Well dor Sources Spring

Kenya 2.8 2.7 1.3 25.2 5.3 7.4 0.3 4.4 0.3 49.7 8.1 7.7 11.3 5.1 17.5 0.7 50.3 11,164,581

Rural 3.4 3.5 1.6 30.6 6.5 8.9 0.3 1.8 0.4 57.0 9.5 8.0 11.5 1.6 11.7 0.8 43.0 8,058,724

Urban 1.0 0.8 0.6 11.1 2.3 3.4 0.2 11.1 0.1 30.5 4.7 7.0 10.5 14.2 32.5 0.6 69.5 3,105,857

Baringo County 2.3 5.0 2.2 51.9 4.2 6.4 0.1 0.8 4.0 77.0 2.3 1.9 7.2 1.5 9.9 0.3 23.0 178,074

Tiaty Constituency 1.7 9.8 1.9 44.3 5.2 14.8 0.2 0.1 11.9 89.9 0.9 1.1 7.7 0.2 0.1 0.1 10.1 48,662

59
Tirioko 4.6 0.9 - 48.4 6.9 15.1 0.0 0.2 18.7 94.8 0.5 1.7 3.0 - - 0.0 5.2 8,707
Pulling Apart or Pooling Together?
 Kollowa 1.2 10.8 - 45.6 1.1 12.4 1.1 - 13.7 86.0 2.7 5.1 5.8 0.1 0.2 0.1 14.0 6,744

60
Ribkwo 1.0 0.9 - 50.1 7.1 26.3 - 0.1 0.0 85.5 1.9 - 10.1 1.9 0.6 - 14.5 5,175

Silale 0.1 0.1 - 83.6 2.8 2.1 0.1 0.2 11.1 100.0 0.0 - - - - - 0.0 7,988

Loiyamorok 0.9 16.7 7.4 31.8 - 5.0 - 0.2 26.5 88.5 - - 11.5 - - - 11.5 4,660
Exploring Kenya’s Inequality

Tangulbei/Korossi 2.6 38.4 7.2 21.5 1.3 11.5 0.1 - 3.0 85.5 0.2 0.2 13.7 - 0.1 0.2 14.5 8,075

Churo/Amaya 0.6 0.1 0.0 24.5 15.7 32.3 - 0.2 12.2 85.5 1.1 0.4 12.5 - 0.2 0.4 14.5 7,313
Baringo North Constit-
uency 0.2 1.3 4.7 65.9 6.3 3.7 0.1 0.2 1.5 83.9 5.3 0.6 7.6 0.3 2.1 0.3 16.1 30,015

A PUBLICATION OF KNBS AND SID

Barwessa - - - 81.1 3.8 3.5 - 0.3 0.6 89.2 2.7 0.1 6.5 1.0 0.4 0.1 10.8 7,653

Kabartonjo 0.2 0.1 0.0 54.2 12.3 1.3 0.1 0.4 - 68.7 19.6 2.2 2.5 - 6.1 0.8 31.3 5,367

Saimo/Kipsaram 0.2 1.5 - 86.7 4.1 0.3 0.3 - - 92.9 1.3 0.1 1.5 0.1 3.5 0.6 7.1 6,664

Saimo/Soi 0.7 1.8 21.9 29.0 6.3 11.1 - 0.3 3.0 74.1 3.2 0.6 21.6 - 0.4 0.1 25.9 6,385

Bartabwa - 4.3 - 76.8 6.5 1.6 - 0.4 5.1 94.7 1.3 - 4.1 - - - 5.3 3,946
Baringo Central Con-
stituency 0.5 0.5 0.2 63.0 4.6 1.2 0.0 0.5 0.0 70.4 1.9 0.3 1.7 3.7 21.3 0.7 29.6 25,650

Kabarnet 0.3 0.0 - 57.8 1.5 2.3 0.1 1.0 0.0 63.0 1.1 0.0 1.0 6.9 27.3 0.6 37.0 7,520

Sacho 0.6 - 0.1 78.6 2.7 0.5 - 0.1 - 82.5 1.1 1.6 4.3 3.2 6.9 0.3 17.5 4,897

Tenges 1.3 3.0 - 69.5 4.1 - - 0.8 - 78.7 2.5 - 0.4 1.0 17.1 0.2 21.3 2,887

Ewalel/Chapchap 0.6 - - 72.1 13.8 0.4 - 0.1 - 86.9 4.3 - 1.7 1.3 4.9 0.9 13.1 5,113

Kapropita - 0.7 0.8 43.7 2.3 1.5 - 0.2 - 49.2 1.0 0.1 1.0 3.1 44.4 1.2 50.8 5,233
Baringo South Con-
stituency 0.9 1.1 6.0 53.9 4.2 7.3 - 1.3 1.2 75.9 2.5 1.0 13.4 0.7 6.4 0.0 24.1 26,449

Marigat 0.2 1.2 - 50.1 3.0 3.7 - 3.8 - 62.0 1.3 1.5 22.4 1.7 11.1 - 38.0 8,553

Ilchamus - 0.6 17.6 41.8 0.1 9.0 - 0.3 4.7 74.1 - - 13.9 0.8 11.1 0.1 25.9 5,935
 Mochongoi 2.4 1.7 0.0 61.6 8.0 11.4 - 0.2 0.4 85.8 5.9 1.4 6.1 - 0.8 - 14.2 8,537

Mukutan - 0.2 15.4 65.4 5.0 3.2 - - - 89.3 1.4 0.8 8.2 - 0.2 - 10.7 3,424

Mogotio Constituency 11.4 17.5 0.1 43.6 0.8 1.3 0.1 2.3 3.3 80.4 3.4 0.7 6.8 0.9 7.7 0.1 19.6 18,110

Mogotio 10.3 16.1 0.1 44.0 0.3 0.5 0.0 3.2 - 74.6 5.9 0.9 3.6 1.5 13.4 0.1 25.4 8,745

Emining 0.3 16.9 0.1 58.7 0.9 1.1 - 2.6 12.6 93.2 1.0 0.2 1.4 0.3 3.9 - 6.8 4,681

Kisanana 24.4 20.8 - 27.9 1.6 3.0 0.2 0.4 - 78.3 1.3 0.7 18.4 0.1 1.1 0.1 21.7 4,684
Eldama Ravine Con-
stituency 2.7 0.9 0.1 43.7 2.0 2.1 0.0 1.4 0.0 52.9 1.1 7.6 5.4 4.0 28.5 0.5 47.1 29,188

Lembus 0.2 2.9 0.3 63.9 1.6 2.4 - 0.1 - 71.3 1.0 13.3 10.0 1.0 3.0 0.4 28.7 5,838

Lembus Kwen 0.1 - - 45.2 0.2 0.6 - 0.1 - 46.2 0.1 2.0 8.2 4.4 38.6 0.5 53.8 5,067

Ravine 0.2 0.3 - 14.2 - - - 2.5 - 17.1 - 0.1 0.3 12.4 70.1 - 82.9 5,052

Mumberes/Maji Mazuri 0.2 0.4 0.1 54.2 4.5 6.4 - 2.0 - 67.7 1.4 23.1 5.9 0.3 0.8 0.8 32.3 5,638

Lembus/Perkerra 0.9 0.7 - 40.6 0.4 - - 2.9 0.2 45.8 - 0.5 4.2 5.4 43.0 1.1 54.2 4,255

Koibatek 21.1 0.8 0.2 36.8 6.3 2.4 0.1 0.9 - 68.6 5.2 0.2 1.8 0.7 23.0 0.6 31.4 3,338

61
Pulling Apart or Pooling Together?
Exploring Kenya’s Inequality

Table 1.26: Human Waste Disposal by County, Constituency and Ward

County/ Main Septic Cess VIP Pit La- Im- Pit Buck- Bush Other Unim- Number of
Constit- Sewer Tank Pool Latrine trine proved Latrine et proved HH Members
uency / Sanita- Uncov- Sanita-
Ward tion ered tion

Kenya 5.91 2.76 0.27 4.57 47.62 61.14 20.87 0.27 17.58 0.14 38.86
37,919,647

Rural 0.14 0.37 0.08 3.97 48.91 53.47 22.32 0.07 24.01 0.13 46.53
26,075,195

Urban 18.61 8.01 0.70 5.90 44.80 78.02 17.67 0.71 3.42 0.18 21.98
11,844,452
Baringo
0.22 0.67 0.05 4.69 33.70 39.34 15.19 0.03 45.40 0.05 60.66
County 548,635
Tiaty Con-
0.00 0.04 0.04 0.37 3.02 3.48 1.57 0.01 94.88 0.06 96.52
stituency 132,070

Tirioko 0.00 0.08 0.00 0.03 0.39 0.51 0.83 0.00 98.58 0.09 99.49
23,561

Kollowa 0.00 0.00 0.02 0.18 1.94 2.14 1.70 0.00 96.14 0.02 97.86
19,364

Ribkwo 0.00 0.03 0.00 0.95 7.16 8.13 1.11 0.06 90.59 0.11 91.87
14,433

Silale 0.00 0.00 0.03 0.06 0.14 0.24 1.29 0.00 98.47 0.00 99.76
21,804
Loiyam-
0.00 0.04 0.02 1.15 5.91 7.12 2.41 0.00 90.45 0.02 92.88
orok 13,369
Tangulbei/
0.00 0.07 0.04 0.09 4.00 4.20 0.88 0.02 94.88 0.02 95.80
Korossi 18,352
Churo/
0.00 0.06 0.15 0.62 4.42 5.25 2.95 0.00 91.63 0.17 94.75
Amaya 21,187
Baringo
North
0.02 0.04 0.03 3.50 47.41 51.00 9.67 0.02 39.25 0.05 49.00
Constitu- 93,383
ency

Barwessa 0.00 0.08 0.03 1.21 25.12 26.43 3.89 0.03 69.58 0.08 73.57
23,938

Kabartonjo 0.00 0.05 0.00 7.65 73.71 81.42 14.03 0.07 4.49 0.00 18.58
19,038
Saimo/
0.00 0.03 0.04 5.37 77.63 83.07 14.65 0.00 2.28 0.00 16.93
Kipsaram 20,916

Saimo/Soi 0.08 0.02 0.08 1.68 20.67 22.54 8.34 0.01 68.93 0.18 77.46
17,668

Bartabwa 0.00 0.01 0.00 0.84 36.69 37.54 7.56 0.00 54.90 0.00 62.46
11,823
Baringo
Central
0.99 1.56 0.20 8.33 57.74 68.81 19.40 0.00 11.77 0.02 31.19
Constitu- 78,634
ency

Kabarnet 1.77 3.22 0.59 9.83 48.09 63.51 21.52 0.00 14.94 0.02 36.49
22,370

Sacho 0.05 0.07 0.08 4.54 72.75 77.49 9.22 0.00 13.29 0.00 22.51
14,577

Tenges 0.07 0.10 0.00 4.04 56.46 60.68 20.56 0.00 18.76 0.00 39.32
9,524
Ewalel/
0.53 0.27 0.00 9.19 55.23 65.21 29.61 0.02 5.11 0.04 34.79
Chapchap 16,349

Kapropita 1.78 2.80 0.08 11.36 60.91 76.93 14.54 0.00 8.53 0.00 23.07
15,814
Baringo
South
0.03 0.27 0.01 3.64 24.43 28.38 20.78 0.03 50.79 0.02 71.62
Constitu- 80,229
ency

Marigat 0.01 0.65 0.00 4.74 45.73 51.13 7.30 0.03 41.54 0.00 48.87
27,242

62 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Ilchamus 0.07 0.05 0.02 3.36 16.76 20.26 7.14 0.00 72.57 0.03 79.74
15,903
Mochon-
0.04 0.11 0.00 3.89 12.14 16.18 48.46 0.07 35.26 0.03 83.82
goi 27,644

Mukutan 0.00 0.03 0.03 0.25 11.88 12.19 1.58 0.00 86.23 0.00 87.81
9,440
Mogotio
Constitu- 0.01 0.19 0.04 7.23 33.92 41.40 6.11 0.00 52.41 0.07 58.60
60,136
ency

Mogotio 0.00 0.39 0.04 15.31 47.53 63.27 8.51 0.00 28.19 0.03 36.73
27,016

Emining 0.00 0.01 0.01 0.20 33.08 33.31 4.17 0.01 62.35 0.17 66.69
16,501

Kisanana 0.05 0.05 0.08 1.08 12.63 13.89 4.15 0.00 81.92 0.04 86.11
16,619
Eldama
Ravine
0.37 1.95 0.03 7.84 49.18 59.37 35.14 0.09 5.36 0.05 40.63
Constitu- 104,183
ency

Lembus 0.58 0.17 0.00 14.17 33.30 48.21 50.83 0.03 0.92 0.00 51.79
21,036
Lembus
0.23 2.02 0.05 5.43 70.61 78.34 17.66 0.17 3.77 0.05 21.66
Kwen 20,205

Ravine 0.48 6.46 0.03 9.35 67.78 84.11 15.06 0.04 0.67 0.12 15.89
16,306
Mum-
beres/Maji 0.02 0.24 0.00 0.86 47.72 48.84 50.27 0.18 0.68 0.03 51.16
18,840
Mazuri
Lembus/
0.85 2.43 0.00 7.98 54.33 65.59 19.81 0.08 14.44 0.08 34.41
Perkerra 15,834

Koibatek 0.00 0.87 0.11 9.51 11.06 21.54 60.90 0.00 17.56 0.00 78.46
11,962

Table 1.27: Human Waste Disposal in Male Headed household by County, Constituency and Ward

County/ Main Septic Cess VIP Pit Improved Pit Bucket Bush Oth- Unim- Number of
Constituen- Sewer Tank Pool La- La- Sanita- Latrine er proved HH Mem-
cy/ward trine trine tion Uncov- Sanita- bers
ered tion

Kenya 6.30 2.98 0.29 4.60 47.65 61.81 20.65 0.28 17.12 0.14 38.19
26,755,066

Rural 0.15 0.40 0.08 3.97 49.08 53.68 22.22 0.07 23.91 0.12 46.32
18,016,471

Urban 18.98 8.29 0.73 5.89 44.69 78.58 17.41 0.70 3.13 0.18 21.42
8,738,595
Baringo
0.21 0.69 0.06 4.74 34.50 40.20 15.82 0.03 43.90 0.05 59.80
County 370,561
Tiaty Con-
0.00 0.04 0.03 0.44 3.60 4.10 1.74 0.01 94.05 0.09 95.90
stituency 83,408

Tirioko 0.00 0.07 0.00 0.05 0.45 0.57 1.08 0.00 98.21 0.14 99.43
14,854

Kollowa 0.00 0.00 0.03 0.20 2.63 2.86 2.27 0.00 94.87 0.00 97.14
12,620

Ribkwo 0.00 0.01 0.00 1.09 8.58 9.68 1.19 0.09 88.90 0.15 90.32
9,258

Silale 0.00 0.00 0.00 0.10 0.12 0.22 0.80 0.00 98.98 0.00 99.78
13,816

Loiyamorok 0.00 0.00 0.03 1.29 6.71 8.03 3.36 0.00 88.58 0.03 91.97
8,709
Tangulbei/
0.00 0.12 0.00 0.00 4.67 4.79 0.85 0.04 94.29 0.04 95.21
Korossi 10,277

63
Exploring Kenya’s Inequality

Churo/Ama-
0.00 0.09 0.12 0.75 5.25 6.21 2.91 0.00 90.62 0.27 93.79
ya 13,874
Baringo
North Con- 0.02 0.06 0.03 3.68 48.07 51.86 9.76 0.03 38.29 0.06 48.14
63,368
stituency

Barwessa 0.00 0.11 0.04 1.15 25.04 26.34 3.82 0.04 69.75 0.06 73.66
16,285

Kabartonjo 0.00 0.07 0.00 7.26 73.62 80.95 14.58 0.07 4.40 0.00 19.05
13,671
Saimo/
0.00 0.01 0.02 6.30 76.77 83.10 14.43 0.00 2.46 0.00 16.90
Kipsaram 14,252

Saimo/Soi 0.13 0.04 0.07 1.82 21.51 23.57 8.50 0.00 67.66 0.27 76.43
11,283

Bartabwa 0.00 0.01 0.00 0.65 37.46 38.12 7.02 0.00 54.86 0.00 61.88
7,877
Baringo
Central
0.94 1.58 0.22 7.98 57.92 68.63 19.91 0.01 11.44 0.02 31.37
Constitu- 52,984
ency

Kabarnet 1.75 3.14 0.64 10.24 48.28 64.05 22.15 0.00 13.76 0.03 35.95
14,850

Sacho 0.04 0.10 0.12 4.54 72.56 77.37 9.02 0.00 13.62 0.00 22.63
9,680

Tenges 0.11 0.11 0.00 3.65 55.24 59.09 21.49 0.00 19.42 0.00 40.91
6,637
Ewalel/
0.34 0.24 0.00 8.38 55.55 64.52 30.19 0.03 5.22 0.04 35.48
Chapchap 11,236

Kapropita 1.77 3.06 0.08 10.24 62.24 77.39 14.82 0.00 7.79 0.00 22.61
10,581
Baringo
South Con- 0.02 0.29 0.01 3.57 24.12 28.01 21.45 0.05 50.48 0.00 71.99
53,780
stituency

Marigat 0.01 0.69 0.01 4.29 45.10 50.09 7.63 0.05 42.23 0.00 49.91
18,689

Ilchamus 0.00 0.05 0.02 3.35 15.91 19.33 8.17 0.00 72.48 0.02 80.67
9,968

Mochongoi 0.05 0.09 0.00 3.97 11.95 16.06 48.09 0.10 35.75 0.00 83.94
19,107

Mukutan 0.00 0.05 0.05 0.40 11.24 11.74 1.81 0.00 86.45 0.00 88.26
6,016
Mogotio
Constitu- 0.00 0.16 0.04 6.58 33.29 40.06 6.25 0.00 53.65 0.03 59.94
42,026
ency

Mogotio 0.00 0.33 0.06 14.33 47.86 62.59 8.95 0.01 28.42 0.04 37.41
18,271

Emining 0.00 0.00 0.02 0.17 32.17 32.36 4.22 0.01 63.37 0.04 67.64
11,820

Kisanana 0.00 0.08 0.02 1.05 12.07 13.21 4.11 0.00 82.67 0.00 86.79
11,935
Eldama
Ravine
0.36 1.91 0.04 7.93 49.00 59.24 35.04 0.08 5.60 0.04 40.76
Constitu- 74,995
ency

Lembus 0.48 0.18 0.01 14.53 33.39 48.59 50.51 0.05 0.85 0.00 51.41
15,198
Lembus
0.17 1.85 0.07 5.46 70.02 77.57 18.54 0.09 3.78 0.03 22.43
Kwen 15,138

Ravine 0.59 6.56 0.04 9.81 67.43 84.43 14.75 0.05 0.72 0.04 15.57
11,254
Mumberes/
0.03 0.31 0.00 0.92 47.71 48.98 50.04 0.19 0.75 0.05 51.02 13,202
Maji Mazuri
Lembus/
0.86 2.37 0.00 7.92 53.82 64.97 19.67 0.06 15.18 0.11 35.03 11,579
Perkerra

64 A PUBLICATION OF KNBS AND SID

 Pulling Apart or Pooling Together?

Koibatek 0.00 0.86 0.15 8.89 11.07 20.98 60.89 0.00 18.14 0.00 79.02 8,624

Table 1.28: Human Waste Disposal in Female Headed Household by County, Constituency and Ward

County/ Con- Main Sep- Cess VIP Pit Improved Pit Buck- Bush Other Unim- Number of
stituency Sewer tic Pool Latrine Latrine Sanitation Latrine et proved HH Members
Tank Uncov- Sanita-
ered tion
Kenya 5.0 2.2 0.2 4.5 47.6 59.5 21.4 0.3 18.7 0.2 40.5 11,164,581.0
Rural 0.1 0.3 0.1 4.0 48.5 53.0 22.6 0.1 24.2 0.1 47.0 8,058,724.0
Urban 17.6 7.2 0.6 5.9 45.1 76.4 18.4 0.7 4.3 0.2 23.6 3,105,857.0
Baringo
0.2 0.6 0.1 4.6 32.0 37.6 13.9 0.0 48.5 0.0 62.4 178,074.0
County
Tiaty Constit-
0.0 0.0 0.1 0.3 2.0 2.4 1.3 0.0 96.3 0.0 97.6 48,662.0
uency
Tirioko 0.0 0.1 0.0 0.0 0.3 0.4 0.4 0.0 99.2 0.0 99.6 8,707.0
Kollowa 0.0 0.0 0.0 0.1 0.6 0.8 0.6 0.0 98.5 0.1 99.2 6,744.0
Ribkwo 0.0 0.1 0.0 0.7 4.6 5.4 1.0 0.0 93.6 0.0 94.6 5,175.0
Silale 0.0 0.0 0.1 0.0 0.2 0.3 2.1 0.0 97.6 0.0 99.7 7,988.0
Loiyamorok 0.0 0.1 0.0 0.9 4.4 5.4 0.6 0.0 93.9 0.0 94.6 4,660.0
Tangulbei/
0.0 0.0 0.1 0.2 3.1 3.4 0.9 0.0 95.6 0.0 96.6 8,075.0
Korossi
Churo/Amaya 0.0 0.0 0.2 0.4 2.8 3.4 3.0 0.0 93.6 0.0 96.6 7,313.0
Baringo North
0.0 0.0 0.0 3.1 46.0 49.2 9.5 0.0 41.3 0.0 50.8 30,015.0
Constituency
Barwessa 0.0 0.0 0.0 1.3 25.3 26.6 4.0 0.0 69.2 0.1 73.4 7,653.0
Kabartonjo 0.0 0.0 0.0 8.6 74.0 82.6 12.6 0.1 4.7 0.0 17.4 5,367.0
Saimo/Kipsar-
0.0 0.1 0.1 3.4 79.5 83.0 15.1 0.0 1.9 0.0 17.0 6,664.0
am
Saimo/Soi 0.0 0.0 0.1 1.4 19.2 20.7 8.1 0.0 71.2 0.0 79.3 6,385.0
Bartabwa 0.0 0.0 0.0 1.2 35.1 36.4 8.6 0.0 55.0 0.0 63.6 3,946.0
Baringo Cen-
tral Constitu- 1.1 1.5 0.2 9.0 57.4 69.2 18.4 0.0 12.4 0.0 30.8 25,650.0
ency
Kabarnet 1.8 3.4 0.5 9.0 47.7 62.4 20.3 0.0 17.3 0.0 37.6 7,520.0
Sacho 0.1 0.0 0.0 4.6 73.1 77.7 9.6 0.0 12.6 0.0 22.3 4,897.0
Tenges 0.0 0.1 0.0 5.0 59.3 64.3 18.4 0.0 17.2 0.0 35.7 2,887.0
Ewalel/Chap-
0.9 0.3 0.0 11.0 54.5 66.8 28.3 0.0 4.9 0.0 33.2 5,113.0
chap
Kapropita 1.8 2.3 0.1 13.6 58.2 76.0 14.0 0.0 10.0 0.0 24.0 5,233.0
Baringo South
0.0 0.2 0.0 3.8 25.1 29.2 19.4 0.0 51.4 0.0 70.8 26,449.0
Constituency
Marigat 0.0 0.5 0.0 5.7 47.1 53.4 6.6 0.0 40.0 0.0 46.6 8,553.0
Ilchamus 0.2 0.1 0.0 3.4 18.2 21.8 5.4 0.0 72.7 0.1 78.2 5,935.0
Mochongoi 0.0 0.2 0.0 3.7 12.5 16.4 49.3 0.0 34.2 0.1 83.6 8,537.0
Mukutan 0.0 0.0 0.0 0.0 13.0 13.0 1.2 0.0 85.8 0.0 87.0 3,424.0
Mogotio Con-
0.0 0.3 0.1 8.7 35.4 44.5 5.8 0.0 49.5 0.2 55.5 18,110.0
stituency
Mogotio 0.0 0.5 0.0 17.3 46.8 64.7 7.6 0.0 27.7 0.0 35.3 8,745.0
Emining 0.0 0.0 0.0 0.3 35.4 35.7 4.0 0.0 59.8 0.5 64.3 4,681.0
Kisanana 0.2 0.0 0.2 1.2 14.0 15.6 4.2 0.0 80.0 0.1 84.4 4,684.0
Eldama Ra-
vine Constit- 0.4 2.0 0.0 7.6 49.6 59.7 35.4 0.1 4.7 0.1 40.3 29,188.0
uency
Lembus 0.8 0.1 0.0 13.2 33.0 47.2 51.7 0.0 1.1 0.0 52.8 5,838.0
Lembus Kwen 0.4 2.5 0.0 5.3 72.4 80.7 15.1 0.4 3.7 0.1 19.3 5,067.0

65
Exploring Kenya’s Inequality

Ravine 0.3 6.2 0.0 8.3 68.6 83.4 15.7 0.0 0.6 0.3 16.6 5,052.0
Mumberes/
0.0 0.1 0.0 0.7 47.7 48.5 50.8 0.1 0.5 0.0 51.5 5,638.0
Maji Mazuri
Lembus/Perk-
0.8 2.6 0.0 8.1 55.7 67.3 20.2 0.1 12.4 0.0 32.7 4,255.0
erra
Koibatek 0.0 0.9 0.0 11.1 11.0 23.0 60.9 0.0 16.1 0.0 77.0 3,338.0

66 A PUBLICATION OF KNBS AND SID

Pulling Apart or Pooling Together?

67
Exploring Kenya’s Inequality

68 A PUBLICATION OF KNBS AND SID