100+ datasets found
  1. Average rent affordable for low-income households in the U.S. 2025

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Average rent affordable for low-income households in the U.S. 2025 [Dataset]. https://www.statista.com/statistics/1064468/average-rent-affordable-for-low-income-households-usa/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    United States
    Description

    In 2025, the average monthly rent affordable to a family of four with a household income at the poverty line was 804 U.S. dollars. However, the average fair market rent for a two-bedroom rental home was 1,749 U.S. dollars per month in that year.

  2. Mean rental costs for public housing in the U.S. 2023, by state

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Mean rental costs for public housing in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/1416783/mean-rent-public-housing-us/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, Alaska reported the highest rent for public housing among all the states in the United States. The average monthly rent in Alaska amounted to *** U.S. dollars for government-subsidized housing. California, New York, and Hawaii were some of the states with the highest average rent, with rental costs above *** U.S. dollars. On the other hand, Puerto Rico offered the most affordable public housing with the lowest rent among all states, coming in at just *** U.S. dollars. Some other affordable states for low-income families were Arkansas, Alabama, Oklahoma, and Ohio, all costing less than *** U.S. dollars.

  3. Housing Cost Burden

    • healthdata.gov
    • data.chhs.ca.gov
    • +5more
    csv, xlsx, xml
    Updated Apr 8, 2025
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    chhs.data.ca.gov (2025). Housing Cost Burden [Dataset]. https://healthdata.gov/State/Housing-Cost-Burden/8ma4-c4rx
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    xlsx, xml, csvAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    chhs.data.ca.gov
    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.

  4. C

    Housing Affordability

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

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    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).

  5. 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(17918), csv(11692), csv(22352), csv(8938), csv(6237), csv(4449), csv(2636), csv(4792), csv(1396), csv(1368), csv(2548)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.

  6. d

    Affordable Housing by Town 2011-2023

    • catalog.data.gov
    • data.ct.gov
    Updated Sep 14, 2025
    + more versions
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    data.ct.gov (2025). Affordable Housing by Town 2011-2023 [Dataset]. https://catalog.data.gov/dataset/affordable-housing-by-town-2011-present
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    Dataset updated
    Sep 14, 2025
    Dataset provided by
    data.ct.gov
    Description

    The Affordable Housing Appeals Procedure List is published annually on or about February 1. The data for the Affordable Housing Appeals Procedure List comes from different sources including federal, state and local programs. This makes it difficult to ensure complete accuracy, so DOH asks municipalities to provide a local administrative review of and input on the street addresses of units and projects as well as information on deed-restricted units. The responses received by DOH vary widely from each municipality. In developing the Affordable Housing Appeals Procedure List, DOH counts: -Assisted housing units or housing receiving financial assistance under any governmental program for the construction or substantial rehabilitation of low and moderate income housing that was occupied or under construction by the end date of the report period for compilation of a given year’s list; -Rental housing occupied by persons receiving rental assistance under C.G.S. Chapter 138a (State Rental Assistance/RAP) or Section 142f of Title 42 of the U.S. Code (Section 8); -Ownership housing or housing currently financed by the Connecticut Housing Finance Authority and/or the U.S. Department of Agriculture; and -Deed-restricted properties or properties with deeds containing covenants or restrictions that require such dwelling unit(s) be sold or rented at or below prices that will preserve the unit(s) as affordable housing as defined in C.G.S. Section 8-39a for persons or families whose incomes are less than or equal to 80% of the area median income.

  7. W

    Housing Burden

    • wifire-data.sdsc.edu
    geotiff, wcs, wms
    Updated Mar 25, 2025
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    California Wildfire & Forest Resilience Task Force (2025). Housing Burden [Dataset]. https://wifire-data.sdsc.edu/dataset/clm-housing-burden
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    geotiff, wms, wcsAvailable download formats
    Dataset updated
    Mar 25, 2025
    Dataset provided by
    California Wildfire & Forest Resilience Task Force
    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).

  8. e

    Households who spend 30 percent or more of income on housing

    • coronavirus-resources.esri.com
    • hub.arcgis.com
    • +3more
    Updated Dec 21, 2018
    + more versions
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    Urban Observatory by Esri (2018). Households who spend 30 percent or more of income on housing [Dataset]. https://coronavirus-resources.esri.com/maps/f9a964e38eae479dbe0b71ad6067e5f2
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    Dataset updated
    Dec 21, 2018
    Dataset authored and provided by
    Urban Observatory by Esri
    Area covered
    Description

    This map shows households that spend 30 percent or more of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities: Enroll eligible households in programs designed to assist them.Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

  9. C

    Affordable Rental Housing Developments

    • chicago.gov
    • data.cityofchicago.org
    • +3more
    csv, xlsx, xml
    Updated Dec 30, 2024
    + more versions
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    City of Chicago (2024). Affordable Rental Housing Developments [Dataset]. https://www.chicago.gov/city/en/depts/doh/provdrs/renters/svcs/affordable-rental-housing-resource-list.html
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    csv, xml, xlsxAvailable download formats
    Dataset updated
    Dec 30, 2024
    Dataset authored and provided by
    City of Chicago
    Description

    The rental housing developments listed below are among the thousands of affordable units that are supported by City of Chicago programs to maintain affordability in local neighborhoods. The list is updated periodically when construction is completed for new projects or when the compliance period for older projects expire, typically after 30 years. The list is provided as a courtesy to the public. It does not include every City-assisted affordable housing unit that may be available for rent, nor does it include the hundreds of thousands of naturally occurring affordable housing units located throughout Chicago without City subsidies. For information on rents, income requirements and availability for the projects listed, contact each property directly. For information on other affordable rental properties in Chicago and Illinois, call (877) 428-8844, or visit www.ILHousingSearch.org.

  10. a

    Location Affordability Index

    • hub.arcgis.com
    • hub-lincolninstitute.hub.arcgis.com
    • +6more
    Updated May 10, 2022
    + more versions
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    New Mexico Community Data Collaborative (2022). Location Affordability Index [Dataset]. https://hub.arcgis.com/maps/447a461f048845979f30a2478b9e65bb
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    Dataset updated
    May 10, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    There is more to housing affordability than the rent or mortgage you pay. Transportation costs are the second-biggest budget item for most families, but it can be difficult for people to fully factor transportation costs into decisions about where to live and work. The Location Affordability Index (LAI) is a user-friendly source of standardized data at the neighborhood (census tract) level on combined housing and transportation costs to help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest. Compare eight household profiles (see table below) —which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.*$11,880 for a single person household in 2016 according to US Dept. of Health and Human Services: https://aspe.hhs.gov/computations-2016-poverty-guidelinesThis layer is symbolized by the percentage of housing and transportation costs as a percentage of income for the Median-Income Family profile, but the costs as a percentage of income for all household profiles are listed in the pop-up:Also available is a gallery of 8 web maps (one for each household profile) all symbolized the same way for easy comparison: Median-Income Family, Very Low-Income Individual, Working Individual, Single Professional, Retired Couple, Single-Parent Family, Moderate-Income Family, and Dual-Professional Family.An accompanying story map provides side-by-side comparisons and additional context.--Variables used in HUD's calculations include 24 measures such as people per household, average number of rooms per housing unit, monthly housing costs (mortgage/rent as well as utility and maintenance expenses), average number of cars per household, median commute distance, vehicle miles traveled per year, percent of trips taken on transit, street connectivity and walkability (measured by block density), and many more.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/. There you will find some background and an FAQ page, which includes the question:"Manhattan, San Francisco, and downtown Boston are some of the most expensive places to live in the country, yet the LAI shows them as affordable for the typical regional household. Why?" These areas have some of the lowest transportation costs in the country, which helps offset the high cost of housing. The area median income (AMI) in these regions is also high, so when costs are shown as a percent of income for the typical regional household these neighborhoods appear affordable; however, they are generally unaffordable to households earning less than the AMI.Date of Coverage: 2012-2016 Date Released: March 2019Date Downloaded from HUD Open Data: 4/18/19Further Documentation:LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation_**The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updates**

    Title: Location Affordability Index - NMCDC Copy

    Summary: This layer contains the Location Affordability Index from U.S. Dept. of Housing and Urban Development (HUD) - standardized household, housing, and transportation cost estimates by census tract for 8 household profiles.

    Notes: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas.

    Prepared by: dianaclavery_uo, copied by EMcRae_NMCDC

    Source: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas. Check the source documentation or other details above for more information about data sources.

    Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=447a461f048845979f30a2478b9e65bb

    UID: 73

    Data Requested: Family income spent on basic need

    Method of Acquisition: Search for Location Affordability Index in the Living Atlas. Make a copy of most recent map available. To update this map, copy the most recent map available. In a new tab, open the AGOL Assistant Portal tool and use the functions in the portal to copy the new maps JSON, and paste it over the old map (this map with item id

    Date Acquired: Map copied on May 10, 2022

    Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 6

    Tags: PENDING

  11. d

    Percent of Households Burdened by Housing Costs Time Series

    • data.ore.dc.gov
    Updated Aug 20, 2024
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    City of Washington, DC (2024). Percent of Households Burdened by Housing Costs Time Series [Dataset]. https://data.ore.dc.gov/items/77614fc3961343738c2ad0e35bae1008
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    Dataset updated
    Aug 20, 2024
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Description

    2020 data points are the average of 2019 and 2021 data points and are included solely to maintain chart continuity. The U.S. Census Bureau did not release 2020 ACS 1-year estimates due to COVID-19. These figures should not be interpreted as an actual estimate for 2020. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

    Data Source: American Community Survey (ACS) 1-Year Estimates

    Why This Matters Housing is a basic necessity, and affordable housing is essential for individuals and families to live and thrive in DC.The rising cost of housing threatens residents’ access to safe and stable housing as well as their ability to cover other essential expenses like food, transportation, and childcare.Racial segregation, housing discrimination, and racist urban renewal programs, among other policies and practices, have meant that Black residents and residents of color in the District disproportionately experience the effects of rapidly rising housing costs. The District's Response Leading the nation in policies and investments for low-income rental households. Target of 12,000 new affordable housing units by 2025. Steps taken to preserve and expand affordable housing include the Housing Production Trust Fund, the Affordable Housing Preservation Fund, and the Home Purchasing Assistance Program, among others.

  12. c

    Data from: Low-Income-Rental-Housing Programs in the Fourth District

    • clevelandfed.org
    Updated Aug 30, 2013
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    Federal Reserve Bank of Cleveland (2013). Low-Income-Rental-Housing Programs in the Fourth District [Dataset]. https://www.clevelandfed.org/publications/working-paper/2013/wp-1311-low-income-rental-housing-programs-in-the-fourth-district
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    Dataset updated
    Aug 30, 2013
    Dataset authored and provided by
    Federal Reserve Bank of Cleveland
    Description

    In the aftermath of the Great Recession, many policy analysts are rethinking national housing policies, including affordable housing programs. We review the literature to compare the largest tenant-based (housing choice voucher or HCV) and place-based (low-income-housing tax credit or LIHTC) programs with respect to cost efficiency and access to better quality neighborhoods. We also provide an overview of low-income-rental-housing policy trends and perform a rough comparison of neighborhood quality across programs and counties, focusing on four main urban counties in the Fourth Federal Reserve District (Cuyahoga, Hamilton, and Franklin in Ohio, and Allegheny in Pennsylvania). We find that in spite of relatively stable real rents, affordability in the Ohio counties declined between 2005 and 2009 due to a drop in real incomes. We find that in Allegheny County during 2006-2009, neighborhood quality was comparable for rental units available through each of the two housing programs. We also find evidence that neighborhoods with LIHTC investments placed in service by 2000 in Allegheny County improved their quality by 2006-2009 relative to comparable neighborhoods, but we do not find similar evidence for the Ohio counties. Lacking tenant-level data on LIHTC renters, it is hard to explain these regional differences. Finally, we note that richer data reporting on various aspects of HCV and LIHTC would improve the ability of program administrators and policymakers to design, coordinate, and evaluate programs based on efficiency and effectiveness.

  13. a

    Households with Severe Housing Burden

    • egis-lacounty.hub.arcgis.com
    • geohub.lacity.org
    • +2more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Households with Severe Housing Burden [Dataset]. https://egis-lacounty.hub.arcgis.com/datasets/households-with-severe-housing-burden/about
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    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Severe housing burden is defined as spending 50% or more of monthly household income on housing. A small number of households without housing cost or income data were excluded from analyses.Given the high cost of housing in Los Angeles County, many residents spend a sizable portion of their incomes on housing every month. Severe housing burden disproportionately affects low-income individuals, renters, and communities of color. Severe housing burden can negatively impact health by forcing individuals and families into low quality or unsafe housing, by causing significant stress, and by limiting the amount of money people have available to spend on other life necessities, such as food or healthcare. It is also an important risk factor for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  14. Full-time jobs needed to afford two-bedroom housing in the U.S. in 2025, by...

    • statista.com
    Updated Jan 8, 2024
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    Statista Research Department (2024). Full-time jobs needed to afford two-bedroom housing in the U.S. in 2025, by state [Dataset]. https://www.statista.com/topics/5081/affordable-housing-in-the-us/
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    Dataset updated
    Jan 8, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    More than one minimum wage job was required to afford two-bedroom housing in all states in the United States in 2025. At mean wage, Hawaii was the most expensive state, requiring renters to hold about two full-time jobs at a mean wage to afford two-bedroom housing. The fair market rent value of two bedroom housing in Hawaii ranked second most expensive among all states in the United States in 2025.

  15. Data from: Low-income dynamics

    • gov.uk
    Updated Apr 29, 2014
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    Department for Work and Pensions (2014). Low-income dynamics [Dataset]. https://www.gov.uk/government/statistics/low-income-dynamics-1991-to-1998
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    Dataset updated
    Apr 29, 2014
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Work and Pensions
    Description

    On 16 March 2017, a new Income Dynamics (experimental) report was published based on Understanding Society data. This supersedes the publication on this page.

    The last Low Income Dynamics National Statistics produced by the Department for Work and Pensions were released on 23 September 2010 according to the arrangements approved by the UK Statistics Authority. The last release updates the statistics previously released on 24 September 2009.

    This publication is based on results from the British Household Panel Survey (BHPS) for the period 1991 to 2008. It analyses the movements around the income distribution by individuals between 1991 and 2008 and examines the extent to which individuals persistently experience low income, on both before housing costs (BHC) and after housing costs (AHC) bases. The report also contains tables showing the likelihood for individuals, of making a transition either into or out of low income, and identifies events and characteristics which are associated with the transitions.

    Main points from the latest release

    Tables on persistent low income (defined as 3 or 4 years out of any 4-year period in a household with below 60% of median income) show that:

    • there have been reductions in the level of persistent low income for all groups since 1991-1994
    • on a BHC basis, there were reductions in persistent low income for all groups over the period 1991-2008, with the largest reductions for children
    • on an AHC basis, there were reductions in persistent low income estimates for all groups over the period 1991-2008, with the largest reductions for children and pensioners

    Future publications

    The British Household Panel Survey (BHPS) was subsumed into the larger http://www.understandingsociety.org.uk/">Understanding Society survey from the start of 2009. This means that this edition of low income dynamics will be the final one in the current form.

    The following technical note outlined the future publications planning and details of the data source change, it also sought to capture user’s views on the content of future reports: http://webarchive.nationalarchives.gov.uk/20130513214236/http://statistics.dwp.gov.uk/asd/hbai/low_income/future_note.pdf">Low-income dynamics – moving to using the Understanding Society survey

    Previous publications

    http://webarchive.nationalarchives.gov.uk/20130513214236/http://statistics.dwp.gov.uk/asd/index.php?page=hbai_arc#low_income">Historical series

    Coverage: Great Britain

    Geographic breakdown: Great Britain

  16. F

    Other Financial Information: Estimated Monthly Rental Value of Owned Home by...

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2024
    + more versions
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    (2024). Other Financial Information: Estimated Monthly Rental Value of Owned Home by Income Before Taxes: $100,000 to $149,999 [Dataset]. https://fred.stlouisfed.org/series/CXU910050LB0221M
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    jsonAvailable download formats
    Dataset updated
    Sep 25, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Other Financial Information: Estimated Monthly Rental Value of Owned Home by Income Before Taxes: $100,000 to $149,999 (CXU910050LB0221M) from 2015 to 2023 about owned, information, rent, estimate, tax, financial, income, housing, and USA.

  17. D

    Multifamily Housing Construction Sites

    • detroitdata.org
    • data.detroitmi.gov
    • +2more
    Updated Sep 1, 2025
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    City of Detroit (2025). Multifamily Housing Construction Sites [Dataset]. https://detroitdata.org/dataset/multifamily-housing-construction-sites
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    geojson, html, kml, txt, gpkg, zip, xlsx, gdb, arcgis geoservices rest api, csvAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset provided by
    City of Detroit
    Description

    This dataset contains multifamily affordable and market-rate housing sites (typically 5+ units) in the City of Detroit that have been built or rehabbed since 2015, or are currently under construction. Most sites are rental housing, though some are for sale. The data are collected from developers, other government departments and agencies, and proprietary data sources in order to track new multifamily and affordable housing construction and rehabilitation occurring in throughout the city, in service of the City's multifamily affordable housing goals. Data are compiled by various teams within the Housing and Revitalization Department (HRD), led by the Preservation Team. This dataset reflects HRD's current knowledge of multifamily units under construction in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

  18. l

    Households with Housing Burden

    • geohub.lacity.org
    • data.lacounty.gov
    • +3more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Households with Housing Burden [Dataset]. https://geohub.lacity.org/datasets/lacounty::households-with-housing-burden
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    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Housing burden is defined as spending 30% or more of monthly household income on housing. A small number of households without housing cost or income data were excluded from analyses.Given the high cost of housing in Los Angeles County, many residents spend a sizable portion of their incomes on housing every month and are therefore susceptible to significant housing burden. Housing burden disproportionately affects low-income individuals, renters, and communities of color. Housing burden can negatively impact health by forcing individuals and families into low quality or unsafe housing, by causing significant stress, and by limiting the amount of money people have available to spend on other life necessities, such as food or healthcare. It is also an important risk factor for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  19. House-price-to-income ratio in selected countries worldwide 2024

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). House-price-to-income ratio in selected countries worldwide 2024 [Dataset]. https://www.statista.com/statistics/237529/price-to-income-ratio-of-housing-worldwide/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Worldwide
    Description

    Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

  20. D

    Existing Multifamily Housing Sites

    • detroitdata.org
    • data.ferndalemi.gov
    • +2more
    Updated Sep 1, 2025
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    City of Detroit (2025). Existing Multifamily Housing Sites [Dataset]. https://detroitdata.org/dataset/existing-multifamily-housing-sites
    Explore at:
    csv, html, gdb, xlsx, arcgis geoservices rest api, kml, txt, zip, gpkg, geojsonAvailable download formats
    Dataset updated
    Sep 1, 2025
    Dataset provided by
    City of Detroit
    Description

    This dataset contains existing multifamily rental sites in the City of Detroit with housing units that have been preserved as affordable since 2018 with assistance from the public sector.

    Over time, affordable units are at risk of falling off line, either due to obsolescence or conversion to market-rate rents. This dataset contains occupied multifamily rental housing sites (typically 5+ units) in the City of Detroit, including those that have units that have been preserved as affordable since 2015 through public funding, regulatory agreements, and other means of assistance from the public sector. Data are collected from developers, other governmental departments and agencies, and proprietary data sources by various teams within the Housing and Revitalization Department, led by the Preservation Team. Data have been tracked since 2018 in service of citywide housing preservation goals. This reflects HRD's current knowledge of multifamily units in the city and will be updated as the department's knowledge changes. For more information about the City's multifamily affordable housing policies and goals, visit here.

    Affordability level for affordable units are measured by the percentage of the Area Median Income (AMI) that a household could earn for that unit to be considered affordable for them. For example, a unit that rents at a 60% AMI threshold would be affordable to a household earning 60% or less of the median income for the area. Rent affordability is typically defined as housing costs consuming 30% or less of monthly income. Regulated housing programs are designed to serve households based on certain income benchmarks relative to AMI, and these income benchmarks vary based on household size. Detroit city's AMI levels are set by the Department of Housing and Urban Development (HUD) for the Detroit-Warren-Livonia, MI Metro Fair Market Rent (FMR) area. For more information on AMI in Detroit, visit here.

Share
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Close
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Statista (2025). Average rent affordable for low-income households in the U.S. 2025 [Dataset]. https://www.statista.com/statistics/1064468/average-rent-affordable-for-low-income-households-usa/
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Average rent affordable for low-income households in the U.S. 2025

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 29, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2025
Area covered
United States
Description

In 2025, the average monthly rent affordable to a family of four with a household income at the poverty line was 804 U.S. dollars. However, the average fair market rent for a two-bedroom rental home was 1,749 U.S. dollars per month in that year.

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