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.

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.

United States US: Price to Income Ratio: sa data was reported at 130.892 2015=100 in 2024. This records an increase from the previous number of 129.315 2015=100 for 2023. United States US: Price to Income Ratio: sa data is updated yearly, averaging 113.539 2015=100 from Dec 1970 (Median) to 2024, with 55 observations. The data reached an all-time high of 132.929 2015=100 in 1979 and a record low of 90.287 2015=100 in 2012. United States US: Price to Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database.

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.

The Global Housing Watch tracks developments in housing markets across the world on a quarterly basis. It provides current data on house prices as well as metrics used to assess valuation in housing markets, such as house price‑to‑rent and house-price‑to‑income ratios.

This collection includes only a subset of indicators from the source dataset.

Japan JP: Standardised Price-Income Ratio: sa data was reported at 87.536 Ratio in 2024. This records a decrease from the previous number of 89.289 Ratio for 2023. Japan JP: Standardised Price-Income Ratio: sa data is updated yearly, averaging 113.262 Ratio from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 163.202 Ratio in 1973 and a record low of 73.471 Ratio in 2009. Japan JP: Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

Australia Standardised Price-Income Ratio: sa data was reported at 149.268 Ratio in Dec 2024. This records a decrease from the previous number of 152.371 Ratio for Sep 2024. Australia Standardised Price-Income Ratio: sa data is updated quarterly, averaging 82.643 Ratio from Mar 1970 (Median) to Dec 2024, with 220 observations. The data reached an all-time high of 153.422 Ratio in Jun 2024 and a record low of 62.554 Ratio in Sep 1983. Australia Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

Germany DE: Standardised Price-Income Ratio: sa data was reported at 88.538 Ratio in 2024. This records a decrease from the previous number of 93.578 Ratio for 2023. Germany DE: Standardised Price-Income Ratio: sa data is updated yearly, averaging 95.901 Ratio from Dec 1980 (Median) to 2024, with 45 observations. The data reached an all-time high of 146.141 Ratio in 1981 and a record low of 76.343 Ratio in 2010. Germany DE: Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Germany – Table DE.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

Israel IL: Price to Income Ratio: sa data was reported at 104.421 2015=100 in 2016. This records an increase from the previous number of 100.000 2015=100 for 2015. Israel IL: Price to Income Ratio: sa data is updated yearly, averaging 91.925 2015=100 from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 109.755 2015=100 in 1997 and a record low of 70.115 2015=100 in 2007. Israel IL: Price to Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Israel – Table IL.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database.

Context

This dataset is created via OECD datasource which is consisted of 2000 between 2020. https://data.oecd.org/price/housing-prices.htm

Content

The housing prices indicator shows indices of residential property prices over time. Included are rent prices, real and nominal house prices, and ratios of price to rent and price to income; the main elements of housing costs. In most cases, the nominal house price covers the sale of newly-built and existing dwellings, following the recommendations from RPPI (Residential Property Prices Indices) manual. The real house price is given by the ratio of nominal price to the consumers’ expenditure deflator in each country, both seasonally adjusted, from the OECD national accounts database. The price to income ratio is the nominal house price divided by the nominal disposable income per head and can be considered as a measure of affordability. The price to rent ratio is the nominal house price divided by the rent price and can be considered as a measure of the profitability of house ownership. This indicator is an index with base year 2015.

This table shows the average House Price/Earnings ratio, which is an important indicator of housing affordability. Ratios are calculated by dividing house price by the median earnings of a borough.

The Annual Survey of Hours and Earnings (ASHE) is based on a 1 per cent sample of employee jobs. Information on earnings and hours is obtained in confidence from employers. It does not cover the self-employed nor does it cover employees not paid during the reference period. Information is as at April each year. The statistics used are workplace based full-time individual earnings.

Pre-2013 Land Registry housing data are for the first half of the year only, so that they are comparable to the ASHE data which are as at April. This is no longer the case from 2013 onwards as this data uses house price data from the ONS House Price Statistics for Small Areas statistical release. Prior to 2006 data are not available for Inner and Outer London.

The lowest 25 per cent of prices are below the lower quartile; the highest 75 per cent are above the lower quartile.
The "lower quartile" property price/income is determined by ranking all property prices/incomes in ascending order.
The 'median' property price/income is determined by ranking all property prices/incomes in ascending order. The point at which one half of the values are above and one half are below is the median.

Regional data has not been published by DCLG since 2012. Data for regions has been calculated by the GLA. Data since 2014 has been calculated by the GLA using Land Registry house prices and ONS Earnings data.

Link to DCLG Live Tables

An interactive map showing the affordability ratios by local authority for 2013, 2014 and 2015 is also available.

This dataset contains the ratio of lower quartile/median house price to lower quartile/median earnings in England

This dataset contains the ratio of median house price to median earnings by district from 1997 to 2012.

This data set uses the median house price data from Land Registry on residential house price transactions at full market value, this means it excludes all: commercial transactions, transfer, conveyances, assignments or lease at a premium with nominal rent which are: Right to Buy sales at a discount, subject to a lease, subject to an existing mortgage, by way of a gift or exchange or under a court order or Compulsory Purchase Order. This is compared to the median income data of full time workers from the Annual Survey of Hours and Earnings (ASHE) produced by the ONS.

This data was derived from Table 577, available for download as an Excel spreadsheet.

Norway NO: Price to Income Ratio: sa data was reported at 109.547 2015=100 in Mar 2025. This records an increase from the previous number of 108.324 2015=100 for Dec 2024. Norway NO: Price to Income Ratio: sa data is updated quarterly, averaging 81.128 2015=100 from Mar 1978 (Median) to Mar 2025, with 189 observations. The data reached an all-time high of 117.142 2015=100 in Mar 2022 and a record low of 50.333 2015=100 in Mar 1993. Norway NO: Price to Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Norway – Table NO.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database.

About this file add_comment Add Suggestion The California housing dataset contains information on various socio-economic features of block groups in California. Each row in the dataset represents a single block group, and there are 20,640 observations, each with 10 attributes.The Features are as follows: 1.Longitude: The longitude of the center of each block group in California. 2.Latitude: The latitude of the center of each block group in California. 3.Housing Median Age: The median age of the housing units in each block group. 4.Total Rooms: The total number of rooms in the housing units in each block group. 5.Total Bedrooms: The total number of bedrooms in the housing units in each block group. 6.Population: The total population of the block group. 7.Households: The total number of households in the block group. 8.Median Income: The median income of the block group. 9.Median House Value: The median value of the housing units in the block group. 10.Ocean Proximity: The proximity of the block group to the ocean or other bodies of water. Table

Housing affordability (house prices to earnings ratio)

*This indicator has been discontinued

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

The Housing Affordability Data System (HADS) is a set of files derived from the 1985 and later national American Housing Survey (AHS) and the 2002 and later Metro AHS. This system categorizes housing units by affordability and households by income, with respect to the Adjusted Median Income, Fair Market Rent (FMR), and poverty income. It also includes housing cost burden for owner and renter households. These files have been the basis for the worst case needs tables since 2001. The data files are available for public use, since they were derived from AHS public use files and the published income limits and FMRs. These dataset give the community of housing analysts the opportunity to use a consistent set of affordability measures. The most recent year HADS is available as a Public Use File (PUF) is 2013. For 2015 and beyond, HADS is only available as an IUF and can no longer be released on a PUF. Those seeking access to more recent data should reach to the listed point of contact.

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.