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 national survey was conducted annually from 1973-1981 and biennially (every two years) since 1983. Metropolitan area surveys have been conducted annually or biennially since 1974.

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 nine 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, Mover Group Record, Part 8, Recodes (One Record per Housing Unit), and Part 9, 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: 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/ICPSR02912.v2. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

CSV files for the 2023 American Housing Survey national survey, 2023 AHS metropolitan survey, and 2021 AHS national survey, as well as the 2023 AHS mini-codebook.

The purpose of the RHFS is to provide current and continuous measure of the financial health and property characteristics of single-family and multifamily rental housing properties in the United States. The survey provides information on the financing of single-family and multifamily rental housing properties with emphasis on new originations for purchase, refinancing, and loan terms associated with these originations. In addition, the survey includes information on property characteristics, such as number of units, amenities available, rental income and expenditure information. This survey was conducted in 2012 and will be conducted in 2015.

The American Housing Survey was first conducted in 1973. Between 1973 and 1981 it was conducted every year and was called the Annual Housing Survey. The last even-numbered year for the national survey was 1980. Since 1981, the survey has been conducted every other year. In 1984, the name was changed to the American Housing Survey. The 1997 national data are from a sample of housing units interviewed between August and November 1997. The CD-ROM contains data files in both SAS. and ASCII format s. The 1998 American Housing Survey Metropolitan Sample (AHS-MS)provides information on 15 metropolitan areas interviewed as part of the American Housing Survey (AHS),which was conducted by the U.S.Census Bureau for the Department of Housing and Urban Development. These metropolitan areas are: Baltimore, MD Birmingham, AL Boston, MA-NH Cincinnati, OH-KY-IN Houston, TX Minneapolis-St.Paul, MN-WI Norfolk-Virginia Beach-Newport News, VA-NC Oakland, CA Providence-Pawtucket-Warwick, RI-MA Rochester, NY Salt Lake City, UT San Francisco, CA San Jose, CA Tampa-St.Petersburg, FL, and Washington DC-MD-VA.

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.

Abstract

Housing Conditions statistics relating to households are an important instrument for making decisions, planning, and drawing up strategies for the environment. Due to the lack of data on this subject in Palestine, PCBS is building and developing a database on the housing in the household sector.

Housing Conditions survey is based on a household sample survey conducted during the period from 24 March 2015 to 31 May 2015. It provides basic statistics on various aspects of housing unit characteristics, housing conditions, and housing density, A special questionnaire was designed in accordance with United Nations standards and recommendations in the field of housing statistics and adapted to Palestinian conditions.

This survey aims to provide general reliable data on housing conditions in Palestine, regional data for the West Bank and Gaza Strip, and data by type of locality (urban, rural and refugee camps). The survey is to carried out once every three years.

Geographic coverage

Palestine

Analysis unit

households

Universe

It consists of all Palestinian households who are staying normally in Palestine during 2015.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The sampling frame was based on master sample which was update in 2013-2014 for (Expenditure and Consumption Survey (PECS) and Multiple Indicator Cluster Survey (MICS)) surveys, and the frame consists from enumeration areas. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sample size: The sample size is 7,690 households for Palestine level, 6,609 households responded.

Sampling Design: Two stage stratified cluster (PPS) sample as following:

First stage: selection of a PPS random sample of 370 enumeration areas.

Second stage: A systematic random sample of 20 households from each enumeration area selected in the first stage.

Sample strata: The population was divided by: 1- Governorate 2- locality type (Urban, rural, camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The housing questionnaire was designed in accordance with similar international experiences and with international standards and recommendations for the most important indicators, taking into account the special situation of Palestine.

Cleaning operations

The data processing stage consisted of the following operations: 1. Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field. 2. Data entry: The Housing Conditions survey questionnaire was programmed and the data were entered into the computer in the offices in Nablus, Hebron, Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: · To prevent the duplication of questionnaires during data entry. · To apply checks on the integrity and consistency of entered data. · To handle errors in a user friendly manner. · The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

89.5%

Sampling error estimates

Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators and the variance table is attached with the final report.

Data appraisal

The non-sampling errors are possible to occur at all phases of implementing the project, through data collection and entry which could be summarized as non-response errors, and responding errors (respondents), and interview errors (fieldworkers) and data-entry errors. To avoid errors and reduce the impact, it had been made ??great efforts through extensive training of fieldworkers on how to conduct interviews, things that ought to be followed during an interview, things that should be avoided, making some practical and theoretical exercises during training session, in addition to providing them with a manual booklet for fieldworkers which contained a private key questions of questionnaire, mechanism to fill questionnaire and methods of dealing with respondents to reduce refusal rates and providing correct and non-biased data, Also data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Full edition for scientific use. With about 20000 households surveyed per quarter, the Microcensus is the largest regularly conducted sample survey in Austria. It is an important data source for national and international labour market indicators and regularly provides information on housing and families. The survey is also known as the EU Labour Force Survey (EU-LFS).

This dataset was created on 2022-06-16.

The American Community Survey distributes downloadable data about United States communities. Download the 2006 microdata survey about housing for the state of Idaho using download.file() from here: https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Fss06pid.csv

The Department of Housing and Urban Development funds and provides oversight for the survey. The U.S. Census Bureau collects the data. For more than forty years the American Housing Survey has provided researchers, policy makers, academics, and others in the housing and urban planning professions with the most comprehensive up-to-date information on the size and composition of U.S. housing stock.

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. (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 at https://doi.org/10.3886/ICPSR09597.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]

How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.

The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.

Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.

Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.

[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.

[2] Ibid.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).

The Survey of English Housing (SEH) was a continuous annual survey series, which began in 1993. The survey provided key housing data on tenure, owner occupation and the social rented sector, and regular information about the private rented sector. The survey was originally sponsored by the Department of the Environment, which became the Department of the Environment, Transport and the Regions in time for the 1996-1997 survey, then the Department for Transport, Local Government and the Regions, by 2000-2001. Responsibility for the SEH was transferred to the Office of the Deputy Prime Minister after the fieldwork for the 2002-2003 survey commenced, and on 5 May 2006 the series became part of the remit of the newly-established Department for Communities and Local Government (DCLG).

The main aims of the SEH were to provide regular information about the main features of people's housing and their views about their circumstances, and information about the private rented sector (not covered by routine administrative statistics like the owner-occupied and social rented sectors).

From 2008, the SEH merged with the English House Condition Survey (EHCS) to form the new English Housing Survey (EHS). The last SEH dataset is the 2007-2008 study. The EHS data are available at the UK Data Archive under GN 33422.

Further information about the SEH and the EHS may be found on the DCLG web site Survey of English Housing and English Housing Survey web pages.
The SEH15 dataset combines key household variables from each of the fifteen annual SEH datasets. SEH15 aims to encourage and facilitate more effective time-series analysis of SEH data.

For the second edition (June 2010), the variable IFCAR has been corrected; previously all cases from 2000 onwards were set to 'yes'. Also a number of missing value labels have been updated.

This data collection provides information on the characteristics of a national sample of housing units. Data include the 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. Similar data are provided for housing units previously occupied by recent movers. Indicators of housing and neighborhood quality are also supplied. For housing quality, indicators include such things as 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, indicators include exterminator service, 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 are provided on the householder, including years of school completed, Spanish origin, length of residence, and length of occupancy. (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 at https://doi.org/10.3886/ICPSR09091.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Graph and download economic data for Fannie Mae's National Housing Survey: Home Purchase Sentiment Index (HPSI) (FMNHSHPSIUS) from Mar 2011 to Sep 2025 about fannie mae, consumer sentiment, purchase, housing, indexes, and USA.

China Real Estate Employee Survey: Housing Price Expectation: Secondary Market Residential in Next Six Months: % of 'Steady or Increased' option data was reported at 57.100 % in Nov 2024. This records a decrease from the previous number of 60.400 % for Oct 2024. China Real Estate Employee Survey: Housing Price Expectation: Secondary Market Residential in Next Six Months: % of 'Steady or Increased' option data is updated monthly, averaging 51.250 % from Aug 2024 (Median) to Nov 2024, with 4 observations. The data reached an all-time high of 60.400 % in Oct 2024 and a record low of 38.900 % in Aug 2024. China Real Estate Employee Survey: Housing Price Expectation: Secondary Market Residential in Next Six Months: % of 'Steady or Increased' option data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.EA: Real Estate Employee Survey.