Graph and download economic data for Housing Affordability Index (Fixed) (FIXHAI) from Feb 2025 to Feb 2026 about fixed, housing, indexes, and USA.

This dataset presents the Rental Affordability Index (RAI) for 3 bedroom dwellings. The data uses different income values for each region within the Greater Capital Cities, and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory and Western Australia does not form part of this dataset. National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually. It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income: RAI = (Median income ∕ Qualifying Income) x 100 In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress. For more information on the Rental Affordability Index please refer to SGS Economics and Planning. The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia. AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

Comprehensive dataset ranking 100+ U.S. cities by rent affordability, including median rents, median incomes, and rent-to-income ratios.

This dataset presents the Rental Affordability Index (RAI) for all dwellings. The data uses different income values for each region within the Greater Capital Cities, and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory does not form part of this dataset. National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually. It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income: RAI = (Median Income ∕ Qualifying Income) x 100 In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress. For more information on the Rental Affordability Index please refer to SGS Economics and Planning. The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia. AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

The percentage of households that pay more than 30% of their total household income on rent and related expenses out of all households in an area. Source: American Community Survey Years Available: 2006-2010, 2007-2011, 2008-2012, 2009-2013, 2010-2014, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018-2022, 2019-2023Please note: We do not recommend comparing overlapping years of data due to the nature of this dataset. For more information, please visit: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html

United States Housing Affordability Index: Fixed data was reported at 146.900 NA in Oct 2018. This records a decrease from the previous number of 147.400 NA for Sep 2018. United States Housing Affordability Index: Fixed data is updated monthly, averaging 127.900 NA from Jan 1989 (Median) to Oct 2018, with 357 observations. The data reached an all-time high of 212.800 NA in Jan 2013 and a record low of 97.600 NA in May 1989. United States Housing Affordability Index: Fixed data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB018: Housing Affordability Index.

Affordability ratios calculated by dividing house prices by gross annual workplace-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

This is the median housing affordability ratio (residence-based) and is calculated by dividing house prices by gross annual earnings, based on the median of both house prices and earnings.

This measure of affordability shows what the people who live in a given area earn in relation to that area's house prices, even if they work elsewhere. This measure does not consider that people may be getting higher earnings from working in other areas.

A higher ratio indicates that on average, it is less affordable for a resident to purchase a house. Conversely, a lower ratio indicates higher affordability in a local authority.

The earnings data are from the Annual Survey of Hours and Earnings which provides a snapshot of earnings at April in each year. Earnings relate to gross full-time individual earnings on a place of work basis. The house price statistics come from the House Price Statistics for Small Areas, which report the median and lower quartile price paid for residential property and refer to a 12-month period with April in the middle (year ending September).

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Portugal, Canada, and the Netherlands 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 114.8 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, 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.

Portugal, Hungary, and Mexico were the countries with the highest house price-to-rent-ratio in the ranking in the second quarter of 2025. In all three countries, the ratio exceeded *** index points, meaning that house price growth had outpaced rents by over ** percent between 2015 and 2025. What does the house-price-to-rent ratio show? The house-price-to-rent-ratio measures the evolution of house prices compared to rents. It is generally calculated by dividing the median house price by the median annual rent. In this statistic, the values have been normalized with 100 equaling the 2015 ratio. Consequentially, a value under 100 means that rental rates have risen more than house prices. When all OECD countries are considered as a whole, the gap between house prices and rents was wider than in the Euro area. Measures of housing affordability The national house-price-to-rent ratio may not fully reflect the cost of housing in a particular country, as it does not capture the price variations that can exist between different regions. It also does not take into consideration the relationship between incomes and housing costs, which is measured by the house-price-to-income and household-rent-to-income ratios. Taking both these factors into account uncovers vast differences in housing affordability between different regions and different professions.

United States Housing Affordability Index: Median Family Income data was reported at 77,021.000 USD in Oct 2018. This records an increase from the previous number of 76,754.000 USD for Sep 2018. United States Housing Affordability Index: Median Family Income data is updated monthly, averaging 53,251.500 USD from Jan 1989 (Median) to Oct 2018, with 358 observations. The data reached an all-time high of 77,021.000 USD in Oct 2018 and a record low of 33,287.000 USD in Jan 1989. United States Housing Affordability Index: Median Family Income data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB018: Housing Affordability Index.

The Housing Affordability Index value in the United States plummeted in 2022, surpassing the historical record of ***** index points in 2006. In 2025, the housing affordability index measured ***** index points, making it the third-worst year for homebuyers since the start of the observation period. What does the Housing Affordability Index mean? The Housing Affordability Index uses data provided by the National Association of Realtors (NAR). It measures whether a family earning the national median income can afford the monthly mortgage payments on a median-priced existing single-family home. An index value of 100 means that a family has exactly enough income to qualify for a mortgage on a home. The higher the index value, the more affordable a house is to a family. Key factors that drive the real estate market Income, house prices, and mortgage rates are some of the most important factors influencing homebuyer sentiment. When incomes increase, consumer power also increases. The median household income in the United States declined in 2022, affecting affordability. Additionally, mortgage interest rates have soared, adding to the financial burden of homebuyers. The sales price of existing single-family homes in the U.S. has increased year-on-year since 2011 and reached ******* U.S. dollars in 2023.

This dataset presents the Rental Affordability Index (RAI) for all dwellings. The data uses a single median income value for all of Australia (enabling comparisons across regions), and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory does not form part of this dataset.

National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually.

It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income:

RAI = (Median income ∕ Qualifying Income) x 100

In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress.

For more information on the Rental Affordability Index please refer to SGS Economics and Planning.

The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia.

AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

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 2024, 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 2024 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, 2024 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (3 December 2025).; 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).

Esri’s Housing Affordability Index (HAI) measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only.

Description: This metric examines how affordable the average First Time Buyer (FTB) priced property would be for a couple earning the average FTB disposable income by NUTS 2 Region, NUTS 3 Region and County, for each year between 2016 and 2021, with this ratio expressed as a percentage (i.e. average monthly mortgage repayment due on the average FTB priced property as a percentage of the average monthly disposable income of an FTB couple). This percentage should be compared relative to the standard affordability mark of 30% (i.e. housing costs should be below 30% of a household’s disposable income). For example, in the attached excel file, the data shows that the Border recorded an Average Mortgage Repayment to Disposable Income Ratio for First Time Buyers of 17.1% in 2021, which was below the standard affordability mark of 30%. This implies that a FTB couple from the Border – on average disposable income levels in the Border and adjusted to reflect incomes of people aged 40 or below in the Border – would only typically have to pay 17.1% of their joint monthly disposable income on their mortgage instalments on the average priced FTB property in the Border. In contrast, the corresponding ratio for Dublin and the Mid-East is 35% and 31.5%, which are both above the standard affordability mark and show that housing for FTBs – on average – is relatively unaffordable in these areas.Basic Calculations = (Average mortgage repayment on average FTB priced property / Average disposable income of a couple under the age of 40).For full detail on the methodology for the development of this ratio please see the RDM FAQ section.This ratio has been developed by the Regional Economist at the three Regional Assemblies and is primarily based on the CSO County Income and Regional GDP as well as the CSO Regional Property Price Index.Geography available in RDM: State, Regional Assembly and Strategic Planning Area (SPA), County (26).Source: Regional AssembliesWeblink: n/aDate of last source data update: April 2023Update Schedule: Annual

View monthly updates and historical trends for US Fixed Housing Affordability Index. from United States. Source: National Association of Realtors. Track e…

United States Housing Affordability Index: Median Price data was reported at 260,500.000 USD in Sep 2018. This records a decrease from the previous number of 268,200.000 USD for Aug 2018. United States Housing Affordability Index: Median Price data is updated monthly, averaging 167,800.000 USD from Jan 1989 (Median) to Sep 2018, with 357 observations. The data reached an all-time high of 276,500.000 USD in Jun 2018 and a record low of 90,300.000 USD in Jan 1989. United States Housing Affordability Index: Median Price data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB018: Housing Affordability Index.

United States Housing Affordability Index: Payment as a % of Income data was reported at 17.000 % in Oct 2018. This stayed constant from the previous number of 17.000 % for Sep 2018. United States Housing Affordability Index: Payment as a % of Income data is updated monthly, averaging 19.200 % from Jan 1989 (Median) to Oct 2018, with 358 observations. The data reached an all-time high of 24.700 % in Jul 2006 and a record low of 11.700 % in Jan 2013. United States Housing Affordability Index: Payment as a % of Income data remains active status in CEIC and is reported by National Association of Realtors. The data is categorized under Global Database’s United States – Table US.EB018: Housing Affordability Index.