78 datasets found
  1. Gross rent as a share of household income in the U.S. 2023

    • statista.com
    Updated May 7, 2025
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    Statista (2025). Gross rent as a share of household income in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/186732/gross-rent-as-a-percent-of-household-income-in-the-us/
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    Dataset updated
    May 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    Approximately 42.5 percent of residents in renter-occupied housing units in the United States paid gross rent which exceeded 35 percent of their income in 2023. In comparison, about 12.3 percent paid less than 15 percent of their gross household income.

  2. z

    Median Gross Rent As A Percentage Of Household Income (Dollars)

    • zipatlas.com
    Updated Dec 18, 2023
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    Zip Atlas Inc (2023). Median Gross Rent As A Percentage Of Household Income (Dollars) [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
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    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Median Gross Rent As A Percentage Of Household Income (Dollars) Report based on US Census and American Community Survey Data.

  3. t

    GROSS RENT AS PERCENTAGE OF INCOME - DP04_MAN_T - Dataset - CKAN

    • portal.tad3.org
    Updated Jul 23, 2023
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    (2023). GROSS RENT AS PERCENTAGE OF INCOME - DP04_MAN_T - Dataset - CKAN [Dataset]. https://portal.tad3.org/dataset/gross-rent-as-percentage-of-income-dp04_man_t
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    Dataset updated
    Jul 23, 2023
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    SELECTED HOUSING CHARACTERISTICS GROSS RENT AS PERCENTAGE OF INCOME - DP04 Universe - Occupied units paying rent Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Gross rent as a percentage of household income is a computed ratio of monthly gross rent to monthly household income (total household income divided by 12). The ratio is computed separately for each unit and is rounded to the nearest tenth. Units for which no rent is paid and units occupied by households that reported no income or a net loss comprise the category “Not computed."

  4. Cost-Burdened Households - Rent as a Percent of Household Income (ACS 2019)

    • data.bayareametro.gov
    csv, xlsx, xml
    Updated Jan 13, 2022
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    Metropolitan Transportation Commission (2022). Cost-Burdened Households - Rent as a Percent of Household Income (ACS 2019) [Dataset]. https://data.bayareametro.gov/Demography/Cost-Burdened-Households-Rent-as-a-Percent-of-Hous/pvis-acfc
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    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Jan 13, 2022
    Dataset authored and provided by
    Metropolitan Transportation Commission
    Description

    This data layer depicts, by census tracts, gross rent as a percentage of household income in the past 12 months for the San Francisco Bay Region. The source data, from the United States Census Bureau, has been reprocessed by the Metropolitan Transportation Commission.

    To produce this feature set, the Metropolitan Transportation Commission downloaded American Community Survey (ACS) table B25070 to create a feature set representing rent as a percentage of household income by the following categories: ● Rent less than 30% of household income ● Rent is 30.0% to 49.9% of household income ● Rent is greater than or equal to 50% of household income

    The resulting attribute table had all margin of error fields deleted, percentage fields added, county code field added, jurisdiction name added, and the source field names were changed.

    The source table used to develop this feature service is from the United States Census Bureau, 2015-2019 American Community Survey 5-Year Estimates and can be downloaded from https://data.census.gov/cedsci/table?q=B25070%3A%20GROSS%20RENT%20AS%20A%20PERCENTAGE%20OF%20HOUSEHOLD%20INCOME%20IN%20THE%20PAST%2012%20MONTHS&g=0400000US06%241500000&tid=ACSDT5Y2019.B25070

  5. Rent as a share of household income of U.S. Millennials 1980-2009

    • statista.com
    Updated Nov 16, 2011
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    Statista (2011). Rent as a share of household income of U.S. Millennials 1980-2009 [Dataset]. https://www.statista.com/statistics/223449/median-gross-rent-as-a-share-of-pre-tax-household-income-of-us-millennials/
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    Dataset updated
    Nov 16, 2011
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1980 - 2009
    Area covered
    United States
    Description

    The statistic shows the median gross rent* as a share of pre-tax household income of Millennials aged 18 to 34 in the United States from 1980 to 2009. In 2009, 18-to 24-year olds spent 32 percent of their household income on rent.

  6. z

    Gross Rent As A Percentage Of Household Income

    • zipatlas.com
    Updated Dec 18, 2023
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    Zip Atlas Inc (2023). Gross Rent As A Percentage Of Household Income [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
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    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Gross Rent As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

  7. 2020 Decennial Census of Island Areas: HBG59 | HOUSEHOLD INCOME IN 2019 BY...

    • data.census.gov
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    DEC, 2020 Decennial Census of Island Areas: HBG59 | HOUSEHOLD INCOME IN 2019 BY GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME IN 2019 (DECIA American Samoa Demographic and Housing Characteristics) [Dataset]. https://data.census.gov/table/DECENNIALDHCAS2020.HBG59?q=Decra+Scape+Inc
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    DEC
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2020
    Description

    Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see the 2020 Island Areas Censuses Technical Documentation..Due to COVID-19 restrictions impacting data collection for the 2020 Census of American Samoa, data tables reporting social and economic characteristics do not include the group quarters population in the table universe. As a result, impacted 2020 data tables should not be compared to 2010 and other past census data tables reporting the same characteristics. The Census Bureau advises data users to verify table universes are the same before comparing data across census years. For more information about data collection limitations and the impacts on American Samoa's data products, see the 2020 Island Areas Censuses Technical Documentation..Explanation of Symbols: 1.An "-" means the statistic could not be computed because there were an insufficient number of observations. 2. An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.3. An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.4. An "N" means data are not displayed for the selected geographic area due to concerns with statistical reliability or an insufficient number of cases.5. An "(X)" means not applicable..Source: U.S. Census Bureau, 2020 Census, American Samoa.

  8. 2011 American Community Survey: B25070 | GROSS RENT AS A PERCENTAGE OF...

    • data.census.gov
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    ACS, 2011 American Community Survey: B25070 | GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME IN THE PAST 12 MONTHS (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2011.B25070
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2011
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2011 American Community Survey

  9. Gross Rent as a Percentage of 2005 Household Income (10), Household Type...

    • data.wu.ac.at
    • open.canada.ca
    xml
    Updated Dec 1, 2016
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    Statistics Canada | Statistique Canada (2016). Gross Rent as a Percentage of 2005 Household Income (10), Household Type (11) and Age Groups of Primary Household Maintainer (8) for the Private Households with Household Income Greater than Zero, in Tenant-occupied Private Non-farm, Non-reserve Dwellings of Canada, Provinces, Territories, Census Metropolitan Areas and Census Agglomerations, 2006 Census - 20% Sample Data [Dataset]. https://data.wu.ac.at/schema/www_data_gc_ca/OGIyMDdiODAtZDI4Yy00YzNjLWJkMGYtYjc5MmU0NzcxZTgw
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    xmlAvailable download formats
    Dataset updated
    Dec 1, 2016
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

  10. g

    Gross Rent as a Percentage of 2005 Household Income (10), Household Type...

    • gimi9.com
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    Gross Rent as a Percentage of 2005 Household Income (10), Household Type (11) and Age Groups of Primary Household Maintainer (8) for the Private Households with Household Income Greater than Zero, in Tenant-occupied Private Non-farm, Non-reserve Dwellings | gimi9.com [Dataset]. https://gimi9.com/dataset/ca_8b207b80-d28c-4c3c-bd0f-b792e4771e80/
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    Description

    This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

  11. u

    Quality of Life Physical Environment Indicator - Percentage of Household...

    • data.urbandatacentre.ca
    • datasets.ai
    • +1more
    Updated Oct 19, 2025
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    (2025). Quality of Life Physical Environment Indicator - Percentage of Household Incomes with Owner's Major Payments (or gross rent) for Shelter being greater than or equal to 30 per cent of Household Income [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-ee8b950f-8893-11e0-ba0f-6cf049291510
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    Dataset updated
    Oct 19, 2025
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The physical environment represents the external conditions under which we live. This map shows the quality of the physical environment: the environment in which people live. It includes aspects of access to services, security and safety, and environmental conditions pertaining to air quality and housing. Eight indicators have been used to assess aspects of the quality of the physical environment.

  12. c

    Where are people affected by high rent costs?

    • hub.scag.ca.gov
    • hub.arcgis.com
    Updated Feb 1, 2022
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    rdpgisadmin (2022). Where are people affected by high rent costs? [Dataset]. https://hub.scag.ca.gov/maps/3a3207d9b7f0438e96270ffdef07a51d
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    Dataset updated
    Feb 1, 2022
    Dataset authored and provided by
    rdpgisadmin
    Area covered
    Description

    This map shows housing costs as a percentage of household income. Severe housing cost burden is described as when over 50% of income in a household is spent on housing costs. For renters it is over 50% of household income going towards gross rent (contract rent plus tenant-paid utilities). Miami, Florida accounts for the having the highest population of renters with severe housing burden costs.The map's topic is shown by tract and county centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. Current Vintage: 2015-2019ACS Table(s): B25070, B25091Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 10, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis map can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  13. ACS Housing Costs Variables - Boundaries

    • opendata.suffolkcountyny.gov
    • covid-hub.gio.georgia.gov
    • +7more
    Updated Dec 12, 2018
    + more versions
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    Esri (2018). ACS Housing Costs Variables - Boundaries [Dataset]. https://opendata.suffolkcountyny.gov/maps/9c7647840d6540e4864d205bac505027
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    Dataset updated
    Dec 12, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows housing costs as a percentage of household income. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Income is based on earnings in past 12 months of survey. This layer is symbolized to show the percent of renter households that spend 30.0% or more of their household income on gross rent (contract rent plus tenant-paid utilities). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25070, B25091 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  14. a

    Map Flint - 2017 Flint by tract ACS5YR Gross Rent as Percentage of Household...

    • mapflint-umich.opendata.arcgis.com
    Updated Feb 11, 2019
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    University of Michigan (2019). Map Flint - 2017 Flint by tract ACS5YR Gross Rent as Percentage of Household Income [Dataset]. https://mapflint-umich.opendata.arcgis.com/items/9b01000f812545e0b55601ae52e57a2d
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    Dataset updated
    Feb 11, 2019
    Dataset authored and provided by
    University of Michigan
    Area covered
    Description

    Map Flint - Feature Service layer(s) : ACS5YR 2013-2017 estimates for City of Flint, Michigan, USA by tract of Gross Rent as Percentage of Household Income.

    Data Dictionary: https://mapflint.org/dictionaries/2017_Flint_by_tract_ACS5YR_Gross_Rent_as_Percentage_of_Household_Income_vars011_data_dictionary.pdf

    Note: Layer(s) not initially visible and must be turned on.

    This feature layer is an American Community Survey (ACS) estimate (U.S. Census Bureau) that is derived from the National Historical Geographic Information System (NHGIS) and has been customized for various Map Flint analyses and projects pertaining to the City of Flint, Genesee County, Michigan U.S.A. and other surrounding counties - e.g., counties and communities in the greater Flint vicinity that also overlap with the mission of the University of Michigan-Flint EDA University Center for Community and Economic Development. All NHGiS layers in Map Flint projects maintain the uniquely-valued GISJOIN geographic ID assigned by the NHGIS in order to work with multiple data sets.

    For more information, visit https://mapflint.org

  15. d

    Housing Summaries (2005-2009)

    • catalog.data.gov
    • gstore.unm.edu
    • +3more
    Updated Dec 2, 2020
    + more versions
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    University of New Mexico, Bureau of Business and Economic Research (BBER) (Point of Contact) (2020). Housing Summaries (2005-2009) [Dataset]. https://catalog.data.gov/dataset/housing-summaries-2005-2009
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    Dataset updated
    Dec 2, 2020
    Dataset provided by
    University of New Mexico, Bureau of Business and Economic Research (BBER) (Point of Contact)
    Description

    The American Community Survey (ACS) is a nationwide survey conducted by the U.S. Census Bureau that is designed to provide communities a fresh look at how they are changing. It is a critical element in the Census Bureau's reengineered decennial census program, incorporating the detailed socioeconomic and housing questions that were previously asked on the decennial census long form into the ACS questionnaire. The ACS now collects and produces this detailed population and housing information every year instead of every ten years. Data are collected on an on-going basis throughout the year and are released each year for large geographic areas, those with 65,000 persons or more. However, sample sizes are not large enough for annual releases that cover smaller areas, those with less than 65,000 persons. Data that are suitable for areas with 20,000 to 65,000 persons are accumulated over three years and termed a three-year period estimate, the first of which was for the 2005-2007 period. Data that are suitable for areas with less than 20,000 persons are accumulated over five years and termed a five-year period estimate, the first of which was for the 2005-2009 period. The data in this series of RGIS Clearinghouse tables are for all New Mexico counties and are based on the 2005-2009 ACS Five-Year Period Estimates collected between January 2005 and December 2009. These data tables are a summary of all major housing topics published through the ACS, providing information about the condition of housing, and illuminating various financial characteristics of the housing stock. Major topics include housing occupancy, year structure built, rooms and bedrooms, housing tenure (owners and renters), year householder moved into unit, vehicles available, type of house heating fuel, units without complete plumbing and kitchen facilities or without telephone service, occupants per room, home value, mortgage status, monthly owner costs, owner costs as a percentage of household income, gross rent, and gross rent as a percentage of household income. Percentages are shown along with numeric estimates for most data items. Because the data are based on a sample the Census Bureau also provides information about the magnitude of sampling error. Consequently, the estimated margin of error (MOE) is shown next to each data item. Each housing topic is covered in a separate file in both Excel and CSV formats. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

  16. 2000 Decennial Census: H073 | HOUSEHOLD INCOME IN 1999 BY GROSS RENT AS A...

    • data.census.gov
    Updated Aug 14, 2024
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    DEC (2024). 2000 Decennial Census: H073 | HOUSEHOLD INCOME IN 1999 BY GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME IN 1999 [50] (DEC Summary File 3) [Dataset]. https://data.census.gov/table/DECENNIALSF32000.H073?q=IMPAC%20MEDICAL%20SYSTEMS%20INC
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    Dataset updated
    Aug 14, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    DEC
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2000
    Description

    NOTE: Data based on a sample except in P3, P4, H3, and H4. For.information on confidentiality protection, sampling error,.nonsampling error, definitions, and count corrections see.http://www.census.gov/prod/cen2000/doc/sf3.pdf

  17. a

    Housing Tenure and Costs - Seattle Neighborhoods

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    • +1more
    Updated Feb 29, 2024
    + more versions
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    City of Seattle ArcGIS Online (2024). Housing Tenure and Costs - Seattle Neighborhoods [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/housing-tenure-and-costs-seattle-neighborhoods/about
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    Dataset updated
    Feb 29, 2024
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Seattle
    Description

    Table from the American Community Survey (ACS) 5-year series on housing tenure and cost related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B25003 Tenure of Occupied Housing Units, B25070 Gross Rent as a Percentage of Household Income in the Past 12 Months, B25063 Gross Rent, B25091 Mortgage Status by Selected Monthly Owner Costs as a Percentage of Household Income in the Past 12 Months, B25087 Mortgage Stauts and Selected Monthly Owner Costs, B25064 Median Gross Rent, B25088 Median Selected Monthly Owner Costs by Mortgage Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B25003, B25070, B25063, B25091, B25087, B25064, B25088Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  18. Household rent to income ratio in the UK 2025, by region

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Household rent to income ratio in the UK 2025, by region [Dataset]. https://www.statista.com/statistics/752217/household-rent-to-income-ratio-by-region-uk/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    United Kingdom
    Description

    Renters in the UK spent on average 32.5 percent of their income on rent as of January 2025. Scotland and Yorkshire and Humber were the most affordable regions, with households spending less than 28 percent of their gross income on rent. Conversely, London, South West, and South East had a higher ratio. Greater London is the most expensive region for renters Greater London has a considerably higher rent than the rest of the UK regions. In 2024, the average rental cost in Greater London was more than twice higher than in the North West or West Midlands. Compared with Greater London, rent in the South East region was about 600 British pounds cheaper. London property prices continue to increase In recent years, house prices in the UK have been steadily increasing, and the period after the COVID-19 pandemic has been no exception. Prime residential property prices in Central London are forecast to continue rising until 2027. A similar trend in prime property prices is also expected in Outer London.

  19. 2018 American Community Survey: B25074 | HOUSEHOLD INCOME BY GROSS RENT AS A...

    • data.census.gov
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    ACS, 2018 American Community Survey: B25074 | HOUSEHOLD INCOME BY GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME IN THE PAST 12 MONTHS (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2018.B25074
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2018
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .ACS Technical Documentation..). The effect of nonsampling error is not represented in these tables..While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available....

  20. T

    SDG Indicator 11.1.2 Data - Housing Costs

    • opendata.sandag.org
    Updated Dec 14, 2022
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    Census Bureau (2022). SDG Indicator 11.1.2 Data - Housing Costs [Dataset]. https://opendata.sandag.org/w/vsxb-a2am/default?cur=zC9iPYMbboX
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    kml, application/geo+json, kmz, xlsx, csv, xmlAvailable download formats
    Dataset updated
    Dec 14, 2022
    Dataset authored and provided by
    Census Bureau
    Description

    Data for Indicator 11.1.2 comes from Census Bureau's American Community Survey (ACS) estimates. The Census Bureau defined households with Selected Monthly Owner Cost as A Percentage of Income (SMOCAPI) or Gross Rent as A Percentage of Income (GRAPI) that is over 35% of household income (excluding units where SMOCAPI and GRAPI cannot be computed). SMOCAPI only includes the count of households where the owner is still paying a mortgage. SMOCAPI does not include households where the owner has paid off the mortgage.

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Statista (2025). Gross rent as a share of household income in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/186732/gross-rent-as-a-percent-of-household-income-in-the-us/
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Gross rent as a share of household income in the U.S. 2023

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Dataset updated
May 7, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

Approximately 42.5 percent of residents in renter-occupied housing units in the United States paid gross rent which exceeded 35 percent of their income in 2023. In comparison, about 12.3 percent paid less than 15 percent of their gross household income.

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