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.

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.

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.

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.

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.

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.

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.

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.

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.

Annual house price data based on a sub-sample of the Regulated Mortgage Survey.

The purpose of this study was to understand the relationship between happiness and housing prices in Canada. The happiness data were obtained from the General Social Survey between 2009 and 2013, asking respondents to report overall happiness level by using scale ranging between 1 to 10 points. House Price Indexes at the provincial level were constructed to cover the same period. The relationship between average house price change and average happiness was estimated using Ordinary Least Square and Logistic Regression techniques. Individual's characteristics were used as control variables. The study found that average happiness level is positively and significantly related to the change in housing prices for one group and not for another - for homeowners but not for renters. In addition, individuals with better health are much happier than individuals with poor health. Similarly, individuals with higher income are happier than individuals with less income. The implication of this study is that the government should design attractive policies to encourage homeownerships.

Housing Index in Poland increased to 213.20 points in the first quarter of 2025 from 211.65 points in the fourth quarter of 2024. This dataset provides the latest reported value for - Poland Housing Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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

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.

EnhancedHousingMarketData.csv is an auxiliary dataset for the "Housing Prices" competition, containing key economic and demographic indicators vital for real estate market analysis. It includes data on non-farm employment, housing price index, per capita income, total quarterly wages, quantitative indexes of real GDP, total GDP, real GDP, stable population, employed individuals, and the average weekly wage in the private sector, along with the unemployment rate. This dataset aids in better understanding the factors influencing housing prices and allows for a more in-depth analysis of the real estate market.

"**TotalNonfarmEmployees**" - reflects the total number of employees working outside the agricultural sector. This figure includes workers in industries such as manufacturing, construction, trade, transportation, education, healthcare, and other non-agricultural sectors, making it a key indicator of economic activity and employment in the region.

"**HousingPriceIndex**" - represents a housing price index, reflecting changes in real estate prices in a specific region for a given month. This index can be used to analyze trends in the real estate market and assess the overall economic conditions.

"**AnnualPerCapitaIncome**" - represents the annual per capita income, measured yearly. This indicator reflects the average income per resident in a specific region over a year, serving as an important measure of the population's economic well-being.

"**QuarterlyTotalWages**" - represents the total quarterly wages, measured in dollars and adjusted for seasonal variations. This metric reflects the sum of wages paid by employers insured for unemployment insurance over a calendar quarter. It includes components such as vacation pay, bonuses, and tips.

"**TotalRealGDPChainIndex**" - represents the total annual quantitative index of real GDP, encompassing data from all private sectors and the government. It is based on the Fisher chain-weighted method, tracking changes in production volume or expenditures while eliminating the effects of price changes. This index is useful for comparing the volumes of production or expenditures across different time periods.

"**TotalGDP**" - describes the total Gross Domestic Product (GDP), measured in millions of dollars and calculated annually without seasonal adjustments. This metric encompasses all private sectors and the government, reflecting the market value of all final goods and services produced within an agglomeration. The agglomeration GDP represents the gross output minus intermediate costs, serving as a key indicator of economic activity and production volume.

"**TotalRealGDP**" - represents the total real Gross Domestic Product, measured in millions of chained 2012 dollars and calculated annually without seasonal adjustments. This metric includes data from all private sectors and the government. The real GDP for agglomerations is a measure of the gross product of each agglomeration, adjusted for inflation, and based on national prices for goods and services produced in the agglomeration.

"**StablePopulation**" - reflects the stable population, measured in thousands of people and calculated annually without seasonal adjustments. This metric represents population estimates as of July 1st each year, providing reliable data for analyzing demographic trends and planning purposes.

"**EmployedIndividuals**" - represents the number of employed individuals, measured in persons without seasonal adjustment and updated monthly. The data are derived from the Current Population Survey (CPS). Employed individuals include those who did any paid work, owned a business or farm, worked 15 hours or more as unpaid workers in a family business, or were temporarily absent from their job for various reasons. This metric is important for analyzing employment levels and the economic activity of the population.

"**AverageWeeklyWagePrivate**" - denotes the average weekly wage of private enterprise employees, measured in dollars per week and calculated quarterly without seasonal adjustment. It includes payments made by employers insured against unemployment over the quarter, encompassing vacation pay, bonuses, stock options, tips, and other components. This metric is important for assessing the level of wages in the private sector.

"**UnemploymentRate**" - represents the unemployment rate, measured in percentages and calculated monthly without seasonal adjustments. This metric indicates the proportion of the unemployed within the total labor force, providing key information about the labor market's condition and the population's economic activity.

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

This dataset uses the median/lower quartile house price data sourced from ONS House Price Statistics for Small Areas (HPSSA) statistical release for years 2013-2015 and house price data sourced directly from Land Registry prior to 2013. This leads to slight differences in the distribution of affordability ratios before and after 2013 which should be noted if the dataset is used as a time series. It is planned to update the ratios with the HPSSA dataset for all years in the future.

The house price data is then compared to the median/lower quartile 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 576 and 577, available for download as an Excel spreadsheet from the Live tables page (https://www.gov.uk/government/statistical-data-sets/live-tables-on-housing-market-and-house-prices). More details about the data sources are also available in the link provided.

House prices capture the financial burden of purchasing a dwelling, and their development over time is measured by a (real) house price index. The evolution of rental prices can be monitored over time by the (real) rent price index. Alternatively, house prices can be compared to income (price-to-income ratio) as a measure of the affordability of owning a dwelling. If the price-to-income ratio is above (below) their long-term average, house prices are considered to be overvalued (undervalued). Meanwhile, the OECD database on regional house price indices shows how house price developments vary across regions and cities within countries (for further discussion, see the OECD National and Regional House Price Indices Database, as well as OECD, 2020a).

Housing Index in Hungary increased to 337.54 points in the first quarter of 2025 from 320.75 points in the fourth quarter of 2024. This dataset provides - Hungary House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The price to income ratio is the nominal house price index divided by the nominal disposable income per head and can be considered as a measure of affordability.