Kenya: Housing and utilities price index, world average = 100: The latest value from 2021 is 39.48 index points, a decline from 64.588 index points in 2017. In comparison, the world average is 77.639 index points, based on data from 165 countries. Historically, the average for Kenya from 2017 to 2021 is 52.034 index points. The minimum value, 39.48 index points, was reached in 2021 while the maximum of 64.588 index points was recorded in 2017.

Kenya GDP: Real Estate data was reported at 342,531.000 KES mn in Sep 2024. This records an increase from the previous number of 339,174.000 KES mn for Jun 2024. Kenya GDP: Real Estate data is updated quarterly, averaging 184,455.000 KES mn from Mar 2009 (Median) to Sep 2024, with 63 observations. The data reached an all-time high of 342,531.000 KES mn in Sep 2024 and a record low of 60,023.000 KES mn in Mar 2009. Kenya GDP: Real Estate data remains active status in CEIC and is reported by Kenya National Bureau of Statistics. The data is categorized under Global Database’s Kenya – Table KE.A009: SNA 2008: GDP: by Industry: Current Price.

Kenya Number of Job Postings: New: Real Estate Rental and Leasing data was reported at 6.000 Unit in 28 Apr 2025. This records a decrease from the previous number of 7.000 Unit for 21 Apr 2025. Kenya Number of Job Postings: New: Real Estate Rental and Leasing data is updated weekly, averaging 0.000 Unit from Jan 2008 (Median) to 28 Apr 2025, with 904 observations. The data reached an all-time high of 58.000 Unit in 11 Oct 2021 and a record low of 0.000 Unit in 14 Apr 2025. Kenya Number of Job Postings: New: Real Estate Rental and Leasing data remains active status in CEIC and is reported by Revelio Labs, Inc.. The data is categorized under Global Database’s Kenya – Table KE.RL.JP: Number of Job Postings: New: by Industry.

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Abstract

The 2023/24 Kenya Housing Survey (2023/24 KHS) provides a comprehensive analysis of housing conditions, affordability and tenure across the country. The survey was conducted by the Kenya National Bureau of Statistics (KNBS) in collaboration with the State Department for Housing and Urban Development, the State Department for Labour and Skills Development, the Kenya Space Agency, the Directorate of Resource Survey and Remote Sensing and the Central Bank of Kenya. The primary objective of the 2023/24 KHS was to provide up-to-date housing statistics to facilitate evidence-based planning and decision making in the housing sector. In addition, the survey addressed housing challenges in line with national development goals and international commitments such as the Sustainable Development Goals (SDGs). Data collection was carried out from 7th March to 10th May 2024 in all the 47 counties and targeted both households and institutions. The survey collected data on various aspects of housing, including the stock of dwellings, household spending on housing, land and dwelling ownership, access to utilities, housing affordability, overcrowding, durability of construction materials, and economic and financial statistics related to housing. Additionally, it collected information on the age, size, and characteristics of dwellings. Satellite imagery analysis was also used to assess changes in built-up areas and green spaces in Nairobi City, Mombasa, Kisumu, and Nakuru counties. Different players in the housing sector including tenants and home owners, Housing Financiers, Developers, Water Service Providers, Built Environment Professionals and Housing Regulators (County Government Physical Planning Department, Lands Department and National Environmental Management Authority) were interviewed.

SURVEY DESIGN The survey employed a cross-sectional study design to collect data for estimating housing indicators at national, rural, urban and county levels. To achieve this, a hybrid data collection system was incorporated, targeting both households and institutions. The household component of the survey was designed independently from that of the institutions. A sample survey was conducted for the households, while a census was carried out for all identified institutions key in the housing sector.

SCOPE AND TARGET POPULATION The survey covered all 47 counties to ensure that the coverage was comprehensive and representative of the entire country. The household component targeted residential housing units in both urban and rural areas while the institutional component targeted housing developers, real estate firms, Water Service Providers, County Governments-Physical Planning Departments, NEMA and Land Administration Department. The professional component targeted members from Engineers Board of Kenya (EBK), Kenya Institute of Planners (KIPs) and Board of Registration of Architects and Quantity Surveyors (BORAQS).

DATA QUALITY The quality of data for the Housing Survey was ensured through a multi-step approach. This began with defining the survey's content and scope, designing survey instruments, conducting a pre-test and pilot survey, training survey personnel, and incorporating technology for data collection and transmission. Additionally, data validation, analysis, creation of final report tables, and stakeholder engagement were all integral parts of the process. A thorough process was undertaken to review and refine the survey instruments aimed at eliminating redundancies and ensuring the questions were accurate and relevant to the current housing development programs and addressed user needs. The data collection tools were integrated into CAPI with in-built checks and controls to ensure consistency and flag out any outliers in the data. A multilevel supervision of the data collection exercise also ensured that the probability of any errors going unnoticed was minimized significantly. To further support the data quality assurance, a dashboard based at the headquarters was also used to monitor the data as fieldwork continued. Upon completion of the data collection, edit specifications were developed by subject matter specialists to provide a basis for cleaning and editing of the data. The specifications were subsequently coded into programs using statistical applications and subjected on the raw data to derive a cleaned dataset that developed the tables in the report.

THE KENYA HOUSING SURVEY DATA COLLECTION TOOLS

I. Household Questionnaire The Household Questionnaire for the 2023/24 Kenya Housing Survey is structured into multiple sections, covering different aspects of housing and household characteristics. The key sections included; Information for Household Members; Household composition, age, gender, relationship to the head and the Socio-economic characteristics such as education and employment status. Household Amenities; Access to essential services (water, electricity, sanitation, internet), Cooking fuel and lighting sources. Dwelling Unit Characteristics; Type of dwelling unit (permanent, semi-permanent, informal), Construction materials (walls, floors, roofing), Number of rooms and occupancy. Environmental and Location Aspects; Waste disposal methods, Drainage and pollution concerns in the neighborhood. Transport and Infrastructure; Accessibility to roads, public transport, and major services (schools, hospitals, markets). Disability; the Accessibility of housing and services for persons with disabilities. Land Ownership and Tenure; Land ownership status, size, tenure system (freehold, leasehold, informal). Household Individual Integrated Module; Employment and economic activities of household members, Income sources and levels. Tenants' information; Rent payment details, lease agreements, landlord-tenant relationships. Owners' information; Mortgage details, home-ownership financing sources and common Challenges in acquiring housing.

II. Kenya Housing Survey Institutional Questionnaire The 2023/24 Kenya Housing Survey Institutional Questionnaire related to real estate development is structured into multiple sections. This Questionnaire was administered to developers and real estate firms and the key sections included: Types of real estate projects undertaken, Number of completed and ongoing projects, Challenges faced in real estate development, Information on specific housing projects (location, type, cost), Financing sources and ownership structure, Construction materials and environmental considerations, Details on commercial, industrial, and institutional buildings, Occupancy rates and rental/sale prices. Questions about market trends, demand, and pricing, Factors affecting property transactions, Prices, unit sizes, and buyer demand trends, Rental prices, occupancy rates, and tenancy duration, Market conditions for office spaces, retail, and mixed-use developments, Information on warehouse developments, rental prices, and usage.

III. County Government questionnaire This Questionnaire captured about basic details about Counties and Questions related to building applications and approvals (e.g., number of residential building applications received and approved in different years). Factors considered in approval of construction permits, such as existing use, visual impact, and emerging technologies. There are also Questions about urban planning and land use, including Number of urban centers classified as towns, municipalities, and cities. Finally, the number of approved and pending physical and land use development plans.

IV. Financiers' Questionnaire The 2023/24 KHS collected information on housing development financing with a focus on respondents within the housing development sector. These included commercial banks, microfinance banks, SACCOS and other institutions that provide finance for housing development, including financial details, funding information, and related metrics.

V. Lands Department Questionnaire This Questionnaire aimed at collecting data related to land administration and management. specific data related to land management, policies, financial data, or other related metrics.

VI. State Department for Housing and Urban Development Questionnaire This questionnaire was used to collect information from the State Department for Housing and Urban Development targeting policy housing and urban development issues.

VII. Built Environment Professionals Questionnaire This questionnaire collected information from built environment professionals involved in the planning, design, and construction of housing in Kenya. The data collected was be used to assess the state of the housing sector, challenges faced, and trends in building and urban development from the perspective of Built Environment Professionals Questionnaire. The Built Environment Professionals interviewed are Valuers, Architects, Planners, Engineers (Civil/Structural/Mechanical/Electrical), Building Surveyors, Land Surveyors, and Quantity Surveyors involved in the planning, design, construction, and maintenance of the built environment.

VIII. National Environment Management Authority Questionnaire This survey data collection tool targeted all the National Environment Management Authority offices (NEMA) to gather insights into their licensing process for housing development projects and related environmental regulations.

IX. Water Sewerage & Service Providers Questionnaire The Water Sewerage & Service Providers (WSSP) section - this was a structured data collection tool in the delivery of water and sanitation services and within the context of housing and urban development. The survey tool or a research questionnaire targeting WSSPs to collect data on Water and sewer connection applications, Types of developments being connected (residential vs. mixed-use), Sewer coverage percentages, Costs, timelines, and challenges in providing services and Plans for future infrastructure

Kenya Banking System: Credit Facilities: Private Sector: Real Estate data was reported at 369,430.000 KES mn in Jun 2018. This records an increase from the previous number of 368,913.000 KES mn for May 2018. Kenya Banking System: Credit Facilities: Private Sector: Real Estate data is updated monthly, averaging 29,110.500 KES mn from Jan 1999 (Median) to Jun 2018, with 234 observations. The data reached an all-time high of 369,430.000 KES mn in Jun 2018 and a record low of 19,135.190 KES mn in Jun 1999. Kenya Banking System: Credit Facilities: Private Sector: Real Estate data remains active status in CEIC and is reported by Central Bank of Kenya. The data is categorized under Global Database’s Kenya – Table KE.KB004: Banking System: Credit Facilities.

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Kenya: Property crimes per 100,000 people: The latest value from is crimes per 100,000 people, unavailable from crimes per 100,000 people in . In comparison, the world average is 0.00 crimes per 100,000 people, based on data from countries. Historically, the average for Kenya from to is crimes per 100,000 people. The minimum value, crimes per 100,000 people, was reached in while the maximum of crimes per 100,000 people was recorded in .

Feed the Future seeks to reduce poverty and undernutrition in 19 developing countries including Kenya by focusing on accelerating growth of the agricultural sector, addressing root causes of undernutrition, and reducing gender inequality. This dataset (n=3,662, vars=15) contain data from sub-Module E5 regarding non-food items that may or may not have been purchased (e.g., construction items such as wood poles and thatching grass). Each household with data for these construction items over the past 12 months has multiple records (for the two construction items in sub-Module E5). (3,662 records divided by 2 construction items = 1,831 Module E households with sub-Module E5 construction data.)

Abstract

The Kenya National Housing Survey (KNHS) was carried out in 2012 to 2013 in 44 counties of the Republic of Kenya. It was undertaken through the NASSEP (V) sampling frame. The objectives of the 2012/2013 KNHS were to: improve the base of housing statistics and information knowledge, provide a basis for future periodic monitoring of the housing sector, facilitate periodic housing policy review and implementation, assess housing needs and track progress of the National Housing. Production goals as stipulated in the Kenya Vision 2030 and its first and second Medium Term Plan, provide a basis for specific programmatic interventions in the housing sector particularly the basis for subsequent Medium Term frameworks for the Kenya Vision2030; and facilitate reporting on the attainment of the Millennium Development Goals (MDG) goals particularly goal 7, target 11.

The 2012/2013 KNHS targeted different players in the housing sector including renters and owner occupiers, housing financiers, home builders/developers, housing regulators and housing professionals. Whereas a census was conducted among regulators and financiers, a sample survey was conducted on renters and owner occupiers, home builders/developers and housing professionals. To cover renters and owner occupiers, the survey was implemented on a representative sample of households - National Sample Survey and Evaluation Program V (NASSEP V) frame which is a household-based sampling frame developed and maintained by KNBS - drawn from 44 counties in the country, in both rural and urban areas. Three counties namely Wajir, Garissa and Mandera were not covered because the household-based sampling frame had not been created in the region by the time of the survey due to insecurity.

Considering that the last Housing Survey was carried out in 1983, it is expected that this report will be a useful source of information to policy makers, academicians and other stakeholders. It is also important to note that this is a basic report and therefore there is room for further research and analysis of various chapters in the report. This, coupled with regularly carrying out surveys, will enrich the data available in the sector which in turn will facilitate planning within the government and the business community.

One of the main challenges faced during the survey process was insufficient information during data collection. This could serve as a wake-up call to all county governments on the need to keep proper records on such issues like the number of housing plans they approve, housing finance institutions within their counties, the number of houses that are built within the county each year and so on since they have the machinery all the way to sub-location level.

Geographic coverage

The survey covered all the districts in Kenya. The data representativeness are at the following levels -National -Urban/Rural -Provincial -District

Analysis unit

• Households
• Indviduals

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame utilized in the renters and owner occupiers and home builders/ developers was the current National Sample Survey and Evaluation Program V (NASSEP V) frame which is a household based sampling frame developed and maintained by KNBS. During the 2009 population and housing census, each sub-location was subdivided into approximately 96,000 census Enumeration Areas (EAs).

In cognizance of the devolved system of government and the need to have a static system of administrative boundaries, NASSEP V utilizes the county boundaries. The frame was implemented using a multi-tiered structure, in which a set of 4 sub-samples were developed. It is based on the list of EAs from the 2009 Kenya Population and Housing Census. The frame is stratified according to county and further into rural and urban areas. Each of the sub-samples is representative at county and at national (i.e. urban/rural) level and contains 1,340 clusters. NASSEP V was developed using a two-stage stratified cluster sampling format with the first stage involving selection of Primary Sampling Units (PSUs) which were the EAs using Probability Proportional to Size (PPS) method. The second stage involved the selection of households for various surveys.

2012/2013 KNHS utilized all the clusters in C2 sub-sample of the NASSEP V frame excluding Wajir, Garissa and Mandera counties. The target for the household component of the survey was to obtain approximately 19,140 completed household interviews.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The survey implemented a Paper and Pencil Interviewer (PAPI) technology administered by trained enumerators while data entry was decentralised to collection teams with a supervisor. Data was keyed from twelve (12) questionnaires namely household based questionnaire for renters, owner occupier and home builders, building financiers such as banks and SACCOs, building professionals such as architects, valuers etc., institutional questionnaires covering Local Authorities, Lands department, Ministry of Housing, National Environmental Management Authority, Physical Planning department and, Water and Sewerage Service providers and housing developers. Each of these questionnaires was keyed individually.

The data processing of the 2012/13 Kenya National Housing Survey results started by developing data capture application for the various questionnaires using CSPro software. Quality of the developed screens was informed by the results derived from 2012/2013 KNHS pilot survey. Every county data collection team had a trained data entry operator and two data analysts were responsible for ensuring data was submitted daily by the trained data entry operators. They also cross-checked the accuracy of submitted data by doing predetermined frequencies of key questions. The data entry operators were informed of detected errors for them to re-enter or ask the data collection team to verify the information.

Data entry was done concurrently with data collection therefore guaranteeing fast detection and correction of errors/inconsistencies. Data capture screens incorporated inbuilt quality control checks triggered in case of invalid entry. Such checks were necessary to guarantee minimal data errors that would be removed during the validation stage (data cleaning).

In data cleaning, a team comprising subject-matter specialists developed editing specifications which were programmed to cross-check raw data for errors and inconsistencies. The printed log file was evaluated with a view to fixing errors and inconsistencies found. Further on, they also developed data tabulation plans to be used on the final datasets and cross checked tabulated outputs were used in writing the survey basic report.

Kenya GDP: Output: Gross Value Added: Real Estate data was reported at 575,360.000 KES mn in 2017. This records an increase from the previous number of 532,121.000 KES mn for 2016. Kenya GDP: Output: Gross Value Added: Real Estate data is updated yearly, averaging 396,708.500 KES mn from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 575,360.000 KES mn in 2017 and a record low of 262,654.000 KES mn in 2010. Kenya GDP: Output: Gross Value Added: Real Estate data remains active status in CEIC and is reported by Kenya National Bureau of Statistics. The data is categorized under Global Database’s Kenya – Table KE.A018: SNA 2008: GDP: Output: Gross Value Added: Current Price.

Kenya GDP: Compensation of Employees: Real Estate data was reported at 48,658.000 KES mn in 2017. This records an increase from the previous number of 44,831.000 KES mn for 2016. Kenya GDP: Compensation of Employees: Real Estate data is updated yearly, averaging 34,540.000 KES mn from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 48,658.000 KES mn in 2017 and a record low of 21,975.000 KES mn in 2010. Kenya GDP: Compensation of Employees: Real Estate data remains active status in CEIC and is reported by Kenya National Bureau of Statistics. The data is categorized under Global Database’s Kenya – Table KE.A020: SNA 2008: GDP: Compensation of Employees: Current Price.

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Kenya GDP: Output: Intermediate Consumption: Real Estate data was reported at 79,718.000 KES mn in 2017. This records an increase from the previous number of 69,816.000 KES mn for 2016. Kenya GDP: Output: Intermediate Consumption: Real Estate data is updated yearly, averaging 47,416.500 KES mn from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 79,718.000 KES mn in 2017 and a record low of 33,245.000 KES mn in 2010. Kenya GDP: Output: Intermediate Consumption: Real Estate data remains active status in CEIC and is reported by Kenya National Bureau of Statistics. The data is categorized under Global Database’s Kenya – Table KE.A019: SNA 2008: GDP: Output: Intermediate Consumption: Current Price.

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: no - Households: A person or a group of persons who live together in the same dwelling unit or homestead and eat together. They may or may not be related by blood or marriage. - Group quarters: Group quarters consist of schools/colleges, barracks, prisons, hospitals and other institutions.

Universe

All persons who spent the Census Night in Kenya. Persons who sleep outdoors and travelers in hotels, lodges, and boarding houses

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Kenya National Bureau of Statistics

SAMPLE SIZE (person records): 3841935.

SAMPLE DESIGN: Systematic sample of every tenth household. Persons who sleep outdoors and travelers in hotels, lodges, and boarding houses

Mode of data collection

Face-to-face [f2f]

Research instrument

A long form was used to enumerate individuals in private households and in institutions such as schools, colleges, barracks, prisons, and hospitals. The long form includes both individual and housing characteristics. A greatly abbreviated form was used for persons in transit or who slept outdoors, in hotels or boarding houses.

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