This data collection provides information on the characteristics of a national sample of housing units, including apartments, single-family homes, mobile homes, and vacant housing units. Unlike previous years, the data are presented in ten separate parts: Part 1, Work Done Record (Replacement or Additions to the House), Part 2, Housing Unit Record (Main Record), Part 3, Worker Record, Part 4, Mortgages (Owners Only), Part 5, Manager and Owner Record (Renters Only), Part 6, Person Record, Part 7, Ratio Verification, Part 8, Mover Group Record, Part 9, Recodes (One Record per Housing Unit), and Part 10, Weights. Data include year the structure was built, type and number of living quarters, occupancy status, access, number of rooms, presence of commercial establishments on the property, and property value. Additional data focus on kitchen and plumbing facilities, types of heating fuel used, source of water, sewage disposal, heating and air-conditioning equipment, and major additions, alterations, or repairs to the property. Information provided on housing expenses includes monthly mortgage or rent payments, cost of services such as utilities, garbage collection, and property insurance, and amount of real estate taxes paid in the previous year. Also included is information on whether the household received government assistance to help pay heating or cooling costs or for other energy-related services. Similar data are provided for housing units previously occupied by respondents who had recently moved. Additionally, indicators of housing and neighborhood quality are supplied. Housing quality variables include privacy of bedrooms, condition of kitchen facilities, basement or roof leakage, breakdowns of plumbing facilities and equipment, and overall opinion of the structure. For quality of neighborhood, variables include use of exterminator services, existence of boarded-up buildings, and overall quality of the neighborhood. In addition to housing characteristics, some demographic data are provided on household members, such as age, sex, race, marital status, income, and relationship to householder. Additional data provided on the householder include years of school completed, Spanish origin, length of residence, and length of occupancy. (Source: ICPSR, retrieved 06/28/2011)

This data collection provides information on the characteristics of the housing inventory in 15 Standard Metropolitan Statistical Areas (SMSAs). Data include year the structure was built, type and number of living quarters, occupancy status, presence of commercial establishments on the property, presence of a garage, and property value. Additional data focus on kitchen and plumbing facilities, type of heating fuel used, source of water, sewage disposal, and heating and air conditioning equipment. Information about housing expenses includes mortgage or rent payments, utility costs, garbage collection fees, property insurance, real estate taxes, and repairs, additions, or alterations to the property. Similar data are provided for housing units previously occupied by respondents who had recently moved. Indicators of housing and neighborhood quality are also supplied. Housing quality variables include privacy of bedrooms, condition of kitchen facilities, basement or roof leakage, presence of cracks or holes in walls, ceilings, or floor, reliability of plumbing and heating equipment, and concealed electrical wiring. The presence of storm doors and windows and insulation was also noted. Neighborhood quality variables indicate presence of and objection to street noise, odors, crime, litter, and rundown and abandoned structures, as well as the adequacy of street lighting, public transportation, public parks, schools, shopping facilities, and police and fire protection. Extensive information on the ability of handicapped persons to move around their homes is also provided. Respondents were asked if they needed special equipment to move around, or the help of another person. They were also asked about the presence or need for housing features to aid their movement, such as ramps, braille lettering, elevators, and extra wide doors. In addition to housing characteristics, demographic data for household members are provided, including sex, age, race, income, marital status, and household relationship. Additional data are available for the household head, including Hispanic origin, length of residence, and travel-to-work information. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08285.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Characteristics of the United States housing inventory listed in this file include the age, size, and type of living quarters, property values, and the presence of commercial establishments on the property. Additional data focus on the presence and condition of kitchen and plumbing facilities and the type and cost of utilities, as well as housing expenses, property repair or alteration, and insurance costs. Many of the same characteristics are given for housing previously occupied by recent movers. Information on age, sex, race, marital status, and income is provided for each household member, with additional data on education, Spanish origin, and household tenure for the head of household. Indicators provided for housing quality include privacy and structural condition. For neighborhood quality, indicators assess noise, crime, air quality, and the presence of abandoned structures, along with the adequacy of neighborhood services such as police protection, parks, health care, and public transportation. Supplements provide information on second homes, mobility, and energy assistance.

The AHS is the largest, regular national housing sample survey in the United States. The U.S. Census Bureau conducts the AHS to obtain up-to-date housing statistics for the Department of Housing and Urban Development (HUD). The AHS contains a wealth of information that can be used by professionals in nearly every field for planning, decisionmaking, market research, or various kinds of program development. It gives you data on apartments, single-family homes, mobile homes, vacant homes, family composition, income, housing and neighborhood quality, housing costs, equipment, fuels, size of housing unit, and recent movers.

Abstract copyright UK Data Service and data collection copyright owner. The English Housing Survey 2008-2009 Household Data Teaching Dataset is based on the English Housing Survey, 2008-2009: Household Data (available from the UK Data Archive under SN 6613) and constitutes real data which are used by the Department for Communities and Local Government and are behind many headlines. The teaching dataset is a subset which has been subjected to certain simplifications and additions for the purpose of learning and teaching. The main differences are:the number of variables has been reducedweighting has been simplifieda reduced codebook is providedFurther information is available in the study documentation (below) which includes a dataset user guide. Information about other teaching resources can be found on the Teaching resources webpage. Main Topics: The main topics covered are:housing characteristicshousehold characteristicssatisfaction with the home and local area Multi-stage stratified random sample Face-to-face interview Compilation or synthesis of existing material The EHS is collected by a face-to-face interview but the teaching dataset has been created by simplifying and altering the original data.

This data collection contains information from samples of housing units in 11 Metropolitan Statistical Areas (MSAs). Data include year the structure was built, type and number of living quarters, occupancy status, presence of commercial or medical establishments on the property, and property value. Additional data focus on kitchen and plumbing facilities, type of heating fuel used, source of water, sewage disposal, and heating and air-conditioning equipment. Questions concerning quality of housing include condition of walls and floors, adequacy of heat in winter, availability of electrical outlets, basement and roof water leakage, and exterminator service for mice or rats. Data on housing expenses include amount of mortgage or rent payments and costs of utilities, fuel, garbage collection, property insurance, and real estate taxes. Respondents who had moved recently were questioned about characteristics of the previous residence and reasons for moving. Residents were also asked to evaluate the quality of their neighborhoods with respect to such issues as crime, street noise, quality of roads, commercial activities, presence of trash, litter, abandoned structures or offensive odors, and adequacy of services such as police protection, shopping facilities, and schools. In addition to housing characteristics, some demographic information is provided on household members, such as age, sex, race, marital status, income, and relationship to householder. Additional data are available on the householder, including years of school completed, Spanish origin, and length of residence.

State and local government officials are asked their opinions about federal housing policy as part of the Housing Policy Review ordered by the President.Questions include priorities of federal housing program, most serious local and state housing problems, likes and dislikes with HUD home ownership and rental assistance programs, and changes to federal housing policy they would like to see.

The U.S. Census Bureau.s economic indicator surveys provide monthly and quarterly data that are timely, reliable, and offer comprehensive measures of the U.S. economy. These surveys produce a variety of statistics covering construction, housing, international trade, retail trade, wholesale trade, services and manufacturing. The survey data provide measures of economic activity that allow analysis of economic performance and inform business investment and policy decisions. Other data included, which are not considered principal economic indicators, are the Quarterly Summary of State & Local Taxes, Quarterly Survey of Public Pensions, and the Manufactured Homes Survey. For information on the reliability and use of the data, including important notes on estimation and sampling variance, seasonal adjustment, measures of sampling variability, and other information pertinent to the economic indicators, visit the individual programs' webpages - http://www.census.gov/cgi-bin/briefroom/BriefRm.

This CD-ROM contains software that permits users to create their own tabulations from the 2001 American Housing Survey microdata. Data files include statistics on the physical and economic characteristics of housing from the 2001 American Housing Survey. Data include year structure built, type and number of living quarters, occupancy status, number of rooms, and property value. Additional data focus on kitchen and plumbing facilities, type of heating fuel used, source of water, sewage disposa l, heating and air-conditioning equipment, and major additions, alterations, or repairs made to the property. Also furnished is data relating to housing expenses including monthly mortgage or rent payments, utility costs, property insurance costs, and the amount of real estate taxes paid. Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

The special survey in March 1993 is on the topic of extended housing survey ("Erweiterte Wohnungserhebung"), just as in the previous years. In addition, there are questions on energy consumption of the households.

The special survey in March is on the topic of extended housing survey ("Erweiterte Wohnungserhebung"), just as in the previous years (Mikrozensus MZ7001 and MZ6901) In addition, there are a few questions on intentions of housing. They resemble the questions of the special survey “Wohnungswechsel” (change of residence) in June 1969 (Mikrozensus MZ6902) and aim at complementing the then collected data with new information.

The English Housing Survey (EHS) is a continuous national survey commissioned by the Department for Communities and Local Government (DCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of the department's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public.

The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 14,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).

The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.

End User Licence and Special Licence Versions:
From 2014 data onwards, the End User Licence (EUL) versions of the EHS only include derived variables. In addition the number of variables on the EUL datasets from that date has been reduced and disclosure control increased on certain remaining variables. The new Special Licence versions of the EHS, which are subject to more restrictive access conditions, are of a similar nature to EHS EUL datasets prior to 2014 and include both derived and raw datasets.

Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.

The English Housing Survey, 2015: Housing Stock Data: Special Licence Access is available for all cases where a physical survey has been completed. For occupied cases the data comprises information from the household interview and from the physical survey. For vacant properties only, data from the physical survey are provided. The Special Licence version includes raw interview and physical datasets and derived data, whereas the EUL version (SN 8186) only includes derived variables. Users are advised to obtain SN 8186 to see whether it is suitable for their needs before making an application for the Special Licence version.

The data are made available for a two-year rolling sample i.e. approximately 12,000 cases together with the appropriate two-year weights. For example, the EHS Housing Stock results presented here are for 2015, but cover the period April 2014 to March 2016. This means that if you use more than one housing stock dataset, you must use either odd or even years. For example, you need to use the Housing Stock Dataset for '2012' and '2014' or '2013' and '2015', but not the dataset for '2014' and '2013' as you would double-count the cases surveyed between April 2013 and March 2014. The Housing Stock dataset should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income.

Users who only require data from the household interview should use the English Housing Survey, 2015-2016: Household Data EUL or Special Licence versions (SNs 8185 and 8254 respectively).

Unfinished Housing Survey for 2012. Each polygon represents a surveyed housing development which was deemed to be either a 'Substantially Complete Development' or an 'Unfinished Development'.

This data is also available on the MyPlan map viewer at http://www.myplan.ie/viewer/

This dataset includes Statistics Canada table 46-10-0045-01, titled “Housing characteristics, by tenure including first-time homebuyer status”. The table includes information on selected housing characteristics (difficulty meeting financial needs, visible minority status, household type, age group, and employment status) housing by tenure. The tenure category of 'owner' is split up into first-time home buyers and owner who is not a first-time home buyer. The table has been edited to include only geographies from British Columbia. The table is available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet. This data set was collected as part of the Canadian Housing Survey by Statistics Canada. Geographies: British Columbia, Large urban population centres in British Columbia, Medium population centres in British Columbia, Small population centres in British Columbia, Rural areas in British Columbia, Vancouver CMA, Other census metropolitan areas in British Columbia, Census agglomerations in British Columbia

調査時期に、統計局長が指定した調査の地域内に現住する住宅及び住宅以外の人が居住する建物並びにそこに居住する世帯をすべて調査の対象とした。 ただし、次に掲げる住宅、人が居住する住宅以外の建物およびそれらの居住世帯は調査の対象から除外した。 １．外国政府または国際機関の公務を帯びるものが管理する施設 ２．皇室用財産である施設 ３．拘置所、刑務所、少年院、少年鑑別所、婦人補導員及び入国者収容所 ４．自衛隊の営舎その他の施設 ５．在日米軍用施設

A survey of the design quality, as measured by CABE Building For Life criteria, of affordable housing in England, commissioned by the Homes and Communities Agency.

Source agency: Communities and Local Government

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: HCA survey

This data collection provides information on the characteristics of a national sample of housing units. Data include year the structure was built, type and number of living quarters, occupancy status, access, number of rooms, presence of commercial establishments on the property, and property value. Additional data focus on kitchen and plumbing facilities, types of heating fuel used, source of water, sewage disposal, heating and air-conditioning equipment, and major additions, alterations, or repairs to the property. Information provided on housing expenses includes monthly mortgage or rent payments, cost of services such as utilities, garbage collection, and property insurance, and amount of real estate taxes paid in the previous year. Also included is information on whether the household received government assistance to help pay heating or cooling costs or for other energy-related services. Similar data are provided for housing units previously occupied by respondents who have recently moved. Additionally, indicators of housing and neighborhood quality are supplied. Housing quality variables include privacy of bedrooms, condition of kitchen facilities, basement or roof leakage, breakdowns of plumbing facilities and equipment, and overall opinion of the structure. For quality of neighborhood, variables include use of an exterminator service, existence of boarded-up buildings, and overall quality of the neighborhood. In addition to housing characteristics, some demographic data are provided on household members, such as age, sex, race, marital status, income, and relationship to householder. Additional data provided on the householder include years of school completed, Spanish origin, length of residence, and length of occupancy.

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.