100+ datasets found
  1. d

    Housing Cost Burden

    • catalog.data.gov
    • data.ca.gov
    • +2more
    Updated Nov 27, 2024
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    California Department of Public Health (2024). Housing Cost Burden [Dataset]. https://catalog.data.gov/dataset/housing-cost-burden-6a9ec
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Department of Public Health
    Description

    This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

  2. c

    Housing Affordability

    • data.ccrpc.org
    csv
    Updated Oct 17, 2024
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    Housing Affordability [Dataset]. https://data.ccrpc.org/dataset/housing-affordability
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    csv(2343)Available download formats
    Dataset updated
    Oct 17, 2024
    Dataset provided by
    Champaign County Regional Planning Commission
    Description

    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).

  3. Number of housing cost burdened households in the U.S. among renters...

    • statista.com
    Updated Jul 31, 2023
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    Statista (2023). Number of housing cost burdened households in the U.S. among renters 2003-2021 [Dataset]. https://www.statista.com/statistics/455762/housing-cost-burdneed-households-number-usa-among-renters/
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    Dataset updated
    Jul 31, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2021, there were approximately 21.6 million housing cost burdened households among renters in the United States. A household is considered to be moderately burdened when the housing costs exceed 30 percent of the family income. Severely burdened households, on the other hand, spend more than 50 percent of their income on rent.

  4. Number of cost burdened households among renters in the U.S. 2021, by income...

    • statista.com
    Updated Jul 31, 2023
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    Statista (2023). Number of cost burdened households among renters in the U.S. 2021, by income [Dataset]. https://www.statista.com/statistics/456850/cost-burdneed-renter-households-number-usa-by-income/
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    Dataset updated
    Jul 31, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In 2021, there were approximately 21.6 million housing cost burdened renter households in the United States, with close to 12 million being severely burdened. About six million households with an annual income below 15,000 U.S. dollars were severely burdened. A household is considered to be moderately cost burdened when the housing costs exceed 30 percent of the family income. Severely burdened households, on the other hand, spend over 50 percent of their income on rent.

  5. d

    Housing Cost Burden by Race

    • catalog.data.gov
    • data.seattle.gov
    • +1more
    Updated Jan 31, 2025
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    City of Seattle ArcGIS Online (2025). Housing Cost Burden by Race [Dataset]. https://catalog.data.gov/dataset/housing-cost-burden-by-race-cea20
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Displacement risk indicator showing how many households within the specified groups are facing either housing cost burden (contributing more than 30% of monthly income toward housing costs) or severe housing cost burden (contributing more than 50% of monthly income toward housing costs).

  6. Number of housing cost burdened households in the U.S. 2003-2021

    • statista.com
    Updated Jul 31, 2023
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    Statista (2023). Number of housing cost burdened households in the U.S. 2003-2021 [Dataset]. https://www.statista.com/statistics/455736/housing-cost-burdneed-households-number-usa/
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    Dataset updated
    Jul 31, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2021, there were approximately 41 million housing cost burdened households in the United States. A household is considered to be moderately cost burdened when the housing costs exceed 30 percent of the family income. Severely burdened households, on the other hand, spend over 50 percent of their income on housing.

  7. Rent Burden Greater than 30%

    • catalog.data.gov
    • data.seattle.gov
    • +2more
    Updated Jan 31, 2025
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    City of Seattle ArcGIS Online (2025). Rent Burden Greater than 30% [Dataset]. https://catalog.data.gov/dataset/rent-burden-greater-than-30-7408b
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    Description

    Displacement risk indicator showing how many households within the specified groups are facing housing cost burden (contributing more than 30% of monthly income toward housing costs).

  8. D

    Housing Affordability

    • catalog.dvrpc.org
    csv
    Updated Mar 17, 2025
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    DVRPC (2025). Housing Affordability [Dataset]. https://catalog.dvrpc.org/dataset/housing-affordability
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    csv(8938), csv(1368), csv(11692), csv(6237), csv(2548), csv(17918), csv(4449), csv(1396), csv(22352), csv(2636), csv(4792)Available download formats
    Dataset updated
    Mar 17, 2025
    Dataset authored and provided by
    DVRPC
    License

    https://catalog.dvrpc.org/dvrpc_data_license.htmlhttps://catalog.dvrpc.org/dvrpc_data_license.html

    Description

    A commonly accepted threshold for affordable housing costs at the household level is 30% of a household's income. Accordingly, a household is considered cost burdened if it pays more than 30% of its income on housing. Households paying more than 50% are considered severely cost burdened. These thresholds apply to both homeowners and renters.

    The Housing Affordability indicator only measures cost burden among the region's households, and not the supply of affordable housing. The directionality of cost burden trends can be impacted by changes in both income and housing supply. If lower income households are priced out of a county or the region, it would create a downward trend in cost burden, but would not reflect a positive trend for an inclusive housing market.

  9. Number of cost burdened renters in the U.S. 2019, by state

    • statista.com
    Updated Feb 15, 2022
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    Statista (2022). Number of cost burdened renters in the U.S. 2019, by state [Dataset]. https://www.statista.com/statistics/1074383/housing-cost-burdened-renters-volume-usa-by-state/
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    Dataset updated
    Feb 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    In 2019, there were 20.3 million cost-burdened renter households in the United States. A household is considered to be housing cost-burdened when the housing costs exceed 30 percent of the family income. California had three million cost-burdened renter households, which accounted for 51.6 percent of all renter households in the state.

  10. Number of cost burdened households among owners in the U.S. 2017, by income

    • statista.com
    Updated Mar 3, 2021
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    Statista (2021). Number of cost burdened households among owners in the U.S. 2017, by income [Dataset]. https://www.statista.com/statistics/455770/cost-burdneed-owner-households-number-usa-by-income/
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    Dataset updated
    Mar 3, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    United States
    Description

    This statistic presents the number of housing cost burdened households among household owners in the United States in 2017, by household income. A household is considered to be housing cost burdened when the housing costs exceed 30 percent of the family income. In 2017, there were approximately 38.58 million cost burdened households among owners in the United States with household income of over 75,000 U.S. dollars.

  11. ACS Housing Costs Variables - Boundaries

    • hub.arcgis.com
    • covid-hub.gio.georgia.gov
    • +8more
    Updated Dec 12, 2018
    + more versions
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    Esri (2018). ACS Housing Costs Variables - Boundaries [Dataset]. https://hub.arcgis.com/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.

  12. Rent Burden Greater than 50%

    • catalog.data.gov
    • data.seattle.gov
    • +1more
    Updated Dec 16, 2024
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    City of Seattle ArcGIS Online (2024). Rent Burden Greater than 50% [Dataset]. https://catalog.data.gov/dataset/rent-burden-greater-than-50-34b2f
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    Dataset updated
    Dec 16, 2024
    Dataset provided by
    Description

    Displacement risk indicator showing how many households within the specified groups are facing severely housing cost burden (contributing more than 50% of monthly income toward housing costs).

  13. Housing Cost Burden By Ownership and Income

    • internal.open.piercecountywa.gov
    • open.piercecountywa.gov
    Updated Apr 12, 2023
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    United States Census Bureau (2023). Housing Cost Burden By Ownership and Income [Dataset]. https://internal.open.piercecountywa.gov/Demographics/Housing-Cost-Burden-By-Ownership-and-Income/b2c8-cpv5
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    xml, tsv, application/rdfxml, csv, application/rssxml, application/geo+json, kml, kmzAvailable download formats
    Dataset updated
    Apr 12, 2023
    Dataset authored and provided by
    United States Census Bureauhttp://census.gov/
    Description

    Tenure by Housing Costs as a Percentage of Household Income in the Past 12 Months County and State values are from the American Community Survey (ACS) 1 Year Survey

  14. Share of cost burdened renters in the U.S. 2019, by state

    • statista.com
    Updated Feb 15, 2022
    + more versions
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    Statista (2022). Share of cost burdened renters in the U.S. 2019, by state [Dataset]. https://www.statista.com/statistics/1074165/housing-cost-burdened-renters-usa-by-state/
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    Dataset updated
    Feb 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    United States
    Description

    In 2019, almost half of all renters in the United States were considered to be either moderately or severely cost-burdened, but there was variation among U.S. states. For instance, 54 percent of renters in Florida were cost-burdened, whereas 38.1 percent of North Carolina renters were considered cost-burdened. A household is considered to be housing cost burdened when the housing costs exceed 30 percent of the family income.

  15. Cost Burdened Households

    • opendata.ramseycounty.us
    application/rdfxml +5
    Updated Jun 27, 2023
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    Urban Institute (2023). Cost Burdened Households [Dataset]. https://opendata.ramseycounty.us/d/um35-qu8s
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    xml, csv, application/rdfxml, tsv, json, application/rssxmlAvailable download formats
    Dataset updated
    Jun 27, 2023
    Dataset authored and provided by
    Urban Institutehttp://urban.org/
    Description

    Data from the U.S. Department of Housing and Urban Development Office of Policy Development and Research (HUD PD&R) and American Community Survey provided by the Urban Institute. This metric reports the share of low-income households at three income levels, low-income (below 80 percent of area median income, or AMI), very low-income (below 50 percent of AMI), and extremely low-income (below 30 percent of AMI), that spend more than half (>50%) of their household income on rent.

  16. s

    Housing Burden - Dataset - CKAN

    • ndp.sdsc.edu
    • nationaldataplatform.org
    Updated Mar 7, 2025
    + more versions
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    (2025). Housing Burden - Dataset - CKAN [Dataset]. https://ndp.sdsc.edu/catalog/dataset/clm-housing-burden3
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    Dataset updated
    Mar 7, 2025
    License

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

    Description

    Housing-Burdened Low-Income Households. Percent of households in a census tract that are both low income (making less than 80% of the HUD Area Median Family Income) and severely burdened by housing costs (paying greater than 50% of their income to housing costs). (5-year estimates, 2013-2017). The cost and availability of housing is an important determinant of well- being. Households with lower incomes may spend a larger proportion of their income on housing. The inability of households to afford necessary non-housing goods after paying for shelter is known as housing-induced poverty. California has very high housing costs relative to much of the country, making it difficult for many to afford adequate housing. Within California, the cost of living varies significantly and is largely dependent on housing cost, availability, and demand. Areas where low-income households may be stressed by high housing costs can be identified through the Housing and Urban Development (HUD) Comprehensive Housing Affordability Strategy (CHAS) data. We measure households earning less than 80% of HUD Area Median Family Income by county and paying greater than 50% of their income to housing costs. The indicator takes into account the regional cost of living for both homeowners and renters, and factors in the cost of utilities. CHAS data are calculated from US Census Bureau's American Community Survey (ACS).

  17. Median of the housing cost burden distribution by age group - EU-SILC survey...

    • db.nomics.world
    • data.europa.eu
    Updated Jun 12, 2024
    + more versions
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    DBnomics (2024). Median of the housing cost burden distribution by age group - EU-SILC survey [Dataset]. https://db.nomics.world/Eurostat/tessi301
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    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Eurostathttps://ec.europa.eu/eurostat
    Authors
    DBnomics
    Description

    This indicator is defined as the median of the distribution of the share of total housing costs (net of housing allowances) in the total disposable household income (net of housing allowances) presented by age group.

  18. a

    Median Housing Age and Cost-burden Housing

    • hub-lincolninstitute.hub.arcgis.com
    • center-for-community-investment-lincolninstitute.hub.arcgis.com
    Updated Jun 2, 2021
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    LincolnHub (2021). Median Housing Age and Cost-burden Housing [Dataset]. https://hub-lincolninstitute.hub.arcgis.com/items/080c38a1e2214de9a4897cac8fa288ab
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    Dataset updated
    Jun 2, 2021
    Dataset authored and provided by
    LincolnHub
    Area covered
    Description

    This map shows the relationship between the median age housing units were built and percent of cost-burdened renters in an area. The pop-up is configured to show:Median year housing units builtPercent of cost-burdened renter householdsThe data in this map contains the most recent American Community Survey (ACS) data from the U.S. Census Bureau. The Living Atlas layer in this map updates annually when the Census releases their new figures. To learn more, visit this FAQ, or visit the ACS website.

  19. T

    Netherlands - Median of the housing cost burden distribution: Cities

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 18, 2021
    + more versions
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    TRADING ECONOMICS (2021). Netherlands - Median of the housing cost burden distribution: Cities [Dataset]. https://tradingeconomics.com/netherlands/median-of-the-housing-cost-burden-distribution-cities-eurostat-data.html
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    json, xml, excel, csvAvailable download formats
    Dataset updated
    Jul 18, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Netherlands
    Description

    Netherlands - Median of the housing cost burden distribution: Cities was 17.20% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Netherlands - Median of the housing cost burden distribution: Cities - last updated from the EUROSTAT on March of 2025. Historically, Netherlands - Median of the housing cost burden distribution: Cities reached a record high of 28.90% in December of 2013 and a record low of 16.20% in December of 2021.

  20. Transportation Cost Burden: Household Characteristics and Income Sources

    • data.virginia.gov
    • catalog.data.gov
    Updated Nov 18, 2024
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    U.S Department of Transportation (2024). Transportation Cost Burden: Household Characteristics and Income Sources [Dataset]. https://data.virginia.gov/dataset/transportation-cost-burden-household-characteristics-and-income-sources
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    Dataset updated
    Nov 18, 2024
    Dataset provided by
    Bureau of Transportation Statisticshttp://www.rita.dot.gov/bts
    Authors
    U.S Department of Transportation
    Description

    Households earn and spend different amounts due in part to differences in composition. This page uses the Consumer Expenditure Survey to show the characteristics households in each income quintile and their income sources.

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California Department of Public Health (2024). Housing Cost Burden [Dataset]. https://catalog.data.gov/dataset/housing-cost-burden-6a9ec

Housing Cost Burden

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Dataset updated
Nov 27, 2024
Dataset provided by
California Department of Public Health
Description

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

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