2012/13 National Housing Survey
Kenya, 2012
Kenya National Bureau of Statistics
Created on
June 01, 2022
Last modified
June 01, 2022
Page views
113897
Download
2900
Documentation in PDF
Metadata
DDI/XML
JSON
Identification
Survey ID Number
KEN-KNBS-NHS-2012-v.1
Title
2012/13 National Housing Survey
Country
| Name | Country code |
|---|---|
| KENYA | KEN |
Study type
Sample Frame, Households [sf/hh]
Abstract
This Report presents findings from the 2012/2013 Kenya National Housing Survey (2012/2013 KNHS). The objectives of the survey 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.
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.
The survey targeted different players in the housing sector including renters and owner occupiers, housing financiers, home builders/developers, housing regulators and housing professionals. The key objective for the survey was to improve the base of housing statistics and information knowledge.
Some of the key findings include;
• Renting households spend more than 30% of their income on rent monthly. This percentage increases to 47% when housing related utilities are included.
• Over 90% of the financial institutions interviewed indicated that they did not have specific products geared towards savings for mortgage.
• Average banks mortgage interest rates in December 2010 and December 2011 stood at 14.36 per cent and 16.36 per cent respectively
• Housing developers quoted access to affordable land (45.9%), high returns on investment (43.7%), and prospective future returns on investment (41.4%) as the key factors in determining where to develop.
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.
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.
The survey targeted different players in the housing sector including renters and owner occupiers, housing financiers, home builders/developers, housing regulators and housing professionals. The key objective for the survey was to improve the base of housing statistics and information knowledge.
Some of the key findings include;
• Renting households spend more than 30% of their income on rent monthly. This percentage increases to 47% when housing related utilities are included.
• Over 90% of the financial institutions interviewed indicated that they did not have specific products geared towards savings for mortgage.
• Average banks mortgage interest rates in December 2010 and December 2011 stood at 14.36 per cent and 16.36 per cent respectively
• Housing developers quoted access to affordable land (45.9%), high returns on investment (43.7%), and prospective future returns on investment (41.4%) as the key factors in determining where to develop.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households Indviduals within Households Community
Version
Version Description
2012/13 National Housing Survey Version 1
Version Date
2014-08-12
Version Notes
.
Coverage
Geographic Coverage
The survey covered all the districts in Kenya. The data representativeness are at the following levels -National -Urban/Rural -Provincial -District
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Ministry of devolution and Planning |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Ministry of Land, Housing & Urban Development | GOK | Funding of Operational Cost |
Sampling
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.
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.
Weighting
The 2012/2013 KNHS sample was not self-weighted and thus a weighting adjustment was required to provide estimates representative of the target population. Weights were calculated for the household module only. The base weights incorporated the probabilities of selection of the clusters from the census EAs database into the NASSEP V sample frame and the probabilities of selection of the 15 households from each of the NASSEP V clusters. Base weights were then adjusted for cluster non-response and household non-response.
The 2012/2013 KNHS sample was not self-weighted and thus a weighting adjustment was required to provide estimates representative of the target population. Weights were calculated for the household module only. The base weights incorporated the probabilities of selection of the clusters from the census EAs database into the NASSEP V sample frame and the probabilities of selection of the 15 households from each of the NASSEP V clusters. Base weights were then adjusted for cluster non-response and household non-response.
The 2012/2013 KNHS sample was not self-weighted and thus a weighting adjustment was required to provide estimates representative of the target population. Weights were calculated for the household module only. The base weights incorporated the probabilities of selection of the clusters from the census EAs database into the NASSEP V sample frame and the probabilities of selection of the 15 households from each of the NASSEP V clusters. Base weights were then adjusted for cluster non-response and household non-response.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2012 | 2012 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Ministry of devolution and Planning |
Data Processing
Other Processing
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.
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.
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Kenya National Bureau of Statistics | Ministry of Devolution and Planning | directorgeneral@knbs.or.ke | www.knbs.or.ke |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director General | KNBS | directorgeneral@knbs.or.ke | www.knbs.or.ke |
Citation requirements
2011/12 National Housing Survey
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2012, Kenya National Bureau of Statistics
Metadata production
DDI Document ID
KEN-KNBS-NHS-2012-v.1.0
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Ministry of Devolution and Planning | Documentation of the Study |
Date of Metadata Production
2014-08-12