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.

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

Context

Demand for houses has exploded in the UK in the last two years due to the pandemic. As a result, it feels like it is becoming more difficult for young people to afford to buy a house in the near future. I wanted to collect data to see if this sentiment is backed up by numbers.

Content

In this folder you will find the average house price in the UK between between 1975 and 2020, the median wage in the UK between 1999 and 2020. Both of these metrics have been adjusted by inflation up to 2020.

This folder also contains a table containing data on the wage gap in 2021, in the UK and by age group.

Sources

Statista: https://www.statista.com/statistics/802183/annual-pay-employees-in-the-uk/ and https://www.statista.com/statistics/1002964/average-full-time-annual-earnings-in-the-uk/.

allAgents: https://www.allagents.co.uk/house-prices-adjusted/.

Bank of England: https://www.bankofengland.co.uk/monetary-policy/inflation/inflation-calculator.

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.

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 synthetic data representing key economic indicators and housing market trends in the UK from 2002 to 2023. The dataset includes quarterly data points for the following variables:

Date: Quarterly timestamps from Q1 2002 to Q4 2023. Housing Cost Index: An index representing the general trend in UK housing prices over time. The values are generated to simulate a typical upward trend observed in real estate markets. Interest Rate (%): The Bank of England's base interest rate, represented as a percentage. The values range from 0.5% to 6%, reflecting typical interest rate fluctuations. Inflation Rate (%): The Consumer Price Index (CPI) values, represented as a percentage, ranging from 1% to 5%, simulating typical inflation trends. Employment Levels (000s): The number of employed individuals in the UK, represented in thousands. The data simulates employment levels ranging from 25 million to 35 million. Growth in Wage (%): The average wage growth rate per quarter, represented as a percentage, ranging from 2% to 7%. GDP Growth Rate (%): The quarterly growth rate of the UK's Gross Domestic Product (GDP), represented as a percentage, with values ranging from -2% to 5%, simulating economic growth and contraction periods. This dataset can be used for educational purposes, including time series analysis, regression modeling, and economic research. Please note that the data is synthetic and not derived from actual historical records. It aims to replicate realistic patterns and trends observed in the UK economy and housing market during the specified period.

This is the unadjusted lower quartile house priced for residential property sales (transactions) in the area for a 12 month period with April in the middle (year-ending September). These figures have been produced by the ONS (Office for National Statistics) using the Land Registry (LR) Price Paid data on residential dwelling transactions.

The LR Price Paid data are comprehensive in that they capture changes of ownership for individual residential properties which have sold for full market value and covers both cash sales and those involving a mortgage.

The lower quartile is the value determined by putting all the house sales for a given year, area and type in order of price and then selecting the price of the house sale which falls three quarters of the way down the list, such that 75Percentage of transactions lie above and 25Percentage lie below that value. These are particularly useful for assessing housing affordability when viewed alongside average and lower quartile income for given areas.

Note that a transaction occurs when a change of freeholder or leaseholder takes place regardless of the amount of money involved and a property can transact more than once in the time period.

The LR records the actual price for which the property changed hands. This will usually be an accurate reflection of the market value for the individual property, but it is not always the case. In order to generate statistics that more accurately reflect market values, the LR has excluded records of houses that were not sold at market value from the dataset. The remaining data are considered a good reflection of market values at the time of the transaction. For full details of exclusions and more information on the methodology used to produce these statistics please see http://www.ons.gov.uk/peoplepopulationandcommunity/housing/qmis/housepricestatisticsforsmallareasqmi

The LR Price Paid data are not adjusted to reflect the mix of houses in a given area. Fluctuations in the types of house that are sold in that area can cause differences between the lower quartile transactional value of houses and the overall market value of houses.

If, for a given year, for house type and area there were fewer than 5 sales records in the LR Price Paid data, the house price statistics are not reported." Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

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 residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Ratio of median quartile workplace earnings to median quartile house prices. The statistics used are workplace based full-time individual earnings. Source: Land Registry/Annual Survey of Hours and Earnings Publisher: Communities and Local Government (CLG) Geographies: Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 1997 to 2009 Type of data: Survey

Ratio of lower quartile workplace earnings to lower quartile house prices. The statistics used are workplace based full-time individual earnings. The ""lower quartile"" property price/income is determined by ranking all property prices/incomes in ascending order. The lowest 25 per cent of prices are below the lower quartile; the highest 75 per cent are above the lower quartile." Source: Land Registry/Annual Survey of Hours and Earnings Publisher: Communities and Local Government (CLG) Geographies: Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 1997 to 2009 Type of data: Survey

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

Stock Price Time Series for Realty Income Corporation. Realty Income (NYSE: O), an S&P 500 company, is real estate partner to the world's leading companies. Founded in 1969, we serve our clients as a full-service real estate capital provider. As of June 30, 2025, we have a portfolio of over 15,600 properties in all 50 U.S. states, the U.K., and seven other countries in Europe. We are known as The Monthly Dividend Company and have a mission to invest in people and places to deliver dependable monthly dividends that increase over time. Since our founding, we have declared 661 consecutive monthly dividends and are a member of the S&P 500 Dividend Aristocrats index for having increased our dividend for over 30 consecutive years.

This dataset contains the indices of UK hourly Construction Wage Costs (quarterly; not seasonally adjusted; 2000 = 100) and UK Construction Material Prices for New Housing, Other New Work, Repair and Maintenance, and All Work (monthly; 2010 = 100).

This data sets out the percentage of residents of the Cambridge housing sub-region who are unable to afford housing, based on contemporary income data and housing costs, broken down into percentage for 1, 2 and 3 bedroom homes. The data comes from the housing sub-region's Strategic Housing Market Assessment, or SHMA, which is updated regularly. The data provided in this open data set comes from: SHMA 2013, based on 2011/12 data SHMA 2012, based on 2009/10 data SHMA 2010, based on 2008/9 data SHMA 2009, based on mostly 2007/8 data The data is all published in chapters of our strategic housing market assessment which are used as part of our calculations around the need for affordable housing, particularly where we need to work out the proportion of people unlikely to be able to afford housing via the private market (owned or rented) and thus potentially in need of "sub market" or affordable housing.

Price-Earnings-Ratio Time Series for Segro Plc. SEGRO is a UK Real Estate Investment Trust (REIT), listed on the London Stock Exchange and Euronext Paris, and is a leading owner, manager and developer of modern warehouses, industrial property and data centres. It owns or manages 10.8 million square metres of space (116 million square feet) valued at £21.4 billion serving customers from a wide range of industry sectors. Its properties are located in and around major cities and at key transportation hubs in the UK and in seven other European countries. For over 100 years SEGRO has been creating the space that enables extraordinary things to happen. From modern big box warehouses, used primarily for regional, national and international distribution hubs, to urban warehousing, located close to major population centres and business districts, it provides high-quality assets that allow its customers to thrive. A commitment to be a force for societal and environmental good is integral to SEGRO's purpose and strategy. Its Responsible SEGRO framework focuses on three long-term priorities where the company believes it can make the greatest impact: Championing Low-Carbon Growth, Investing in Local Communities and Environments and Nurturing Talent. Striving for the highest standards of innovation, sustainable business practices and enabling economic and societal prosperity underpins SEGRO's ambition to be the best property company.

Net-Income Time Series for Savills. Savills plc, together with its subsidiaries, engages in the provision of real estate services in the United Kingdom, Continental Europe, the Asia Pacific, Africa, North America, and the Middle East. The company advises on commercial, residential, rural, and leisure properties; and provides corporate finance advisory, investment management, and a range of property-related financial services. It operates through Transaction Advisory, Property and Facilities Management, Investment Management, and Consultancy segments. The Transaction Advisory segment offers commercial, residential, leisure, and agricultural leasing services; and tenant representation, as well as investment advice on purchases and sales. The Property and Facilities Management segment manages commercial, residential, leisure, and agricultural properties for owners; and provides services to occupiers of properties, including strategic advice and project management, as well as various services relating to a property. The Investment Management segment is involved in the investment management of commercial and residential property portfolios for institutional, corporate, or private investors on a pooled or segregated account basis. The Consultancy segment offers various professional property services, such as valuation, project management and housing consultancy, environmental consultancy, landlord and tenant, rating, development, planning, strategic projects, and corporate services and research. Savills plc was founded in 1855 and is headquartered in London, the United Kingdom.

Total-Other-Income-Expense-Net Time Series for Workspace Group PLC. Workspace is London's leading owner and operator of flexible workspace, currently managing 4.3 million sq. ft. of sustainable space at 65 locations in London and the South East. We are home to some 4,000 of London's fastest growing and established brands from a diverse range of sectors. Our purpose, to give businesses the freedom to grow, is based on the belief that in the right space, teams can achieve more. That in environments they tailor themselves, free from constraint and compromise, teams are best able to collaborate, build their culture and realise their potential. We have a unique combination of a highly effective and scalable operating platform, a portfolio of distinctive properties, and an ownership model that allows us to offer true flexibility. We provide customers with blank canvas space to create a home for their business, alongside leases that give them the freedom to easily scale up and down within our well-connected, extensive portfolio. We are inherently sustainable - we invest across the capital, breathing new life into old buildings and creating hubs of economic activity that help flatten London's working map. We work closely with our local communities to ensure we make a positive and lasting environmental and social impact, creating value over the long term. Workspace was established in 1987, has been listed on the London Stock Exchange since 1993, is a FTSE 250 listed Real Estate Investment Trust (REIT) and a member of the European Public Real Estate Association (EPRA). Workspace is a registered trademark of Workspace Group PLC, London, UK.

Through reading this publication you will: • gain an understanding of how house prices are set in economics terms, how they are measured, and why the cost of housing matters for London’s economy and its residents • see whether incomes and earnings in London have kept pace with the costs of home ownership in London, and see how affordability may be affected by future changes in interest rates • find out about the drivers of demand for residential property in London, and how the supply of homes has responded to changing conditions

An overview of the affordability and availability of home ownership and social renting at the local authority level in England and Wales, as well as the affordability of private rented housing. Statistics include information on average house prices and annual salaries, mortgages, the rental market, housing stock, the number of dwellings completed and vacant housing stock.