Median price paid for residential property in England and Wales by property type and electoral ward. Annual data.

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.

FOCUSON**LONDON**2011: HOUSING:A**GROWING**CITY

With the highest average incomes in the country but the least space to grow, demand for housing in London has long outstripped supply, resulting in higher housing costs and rising levels of overcrowding. The pressures of housing demand in London have grown in recent years, in part due to fewer people leaving London to buy homes in other regions. But while new supply during the recession held up better in London than in other regions, it needs to increase significantly in order to meet housing needs and reduce housing costs to more affordable levels.

This edition of Focus on London authored by James Gleeson in the Housing Unit looks at housing trends in London, from the demand/supply imbalance to the consequences for affordability and housing need.

REPORT:

Read the report in PDF format.

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PRESENTATION:

How much pressure is London’s popularity putting on housing provision in the capital? This interactive presentation looks at the effect on housing pressure of demographic changes, and recent new housing supply, shown by trends in overcrowding and house prices. Click on the start button at the bottom of the slide to access.

View Focus on London - Housing: A Growing City on Prezi

HISTOGRAM:

This histogram shows a selection of borough data and helps show areas that are similar to one another by each indicator.

Histogram

MOTION CHART:

This motion chart shows how the relationship, between key housing related indicators at borough level, changes over time.

Motion Chart

MAP:

These interactive borough maps help to geographically present a range of housing data within London, as well as presenting trend data where available.

MAP

DATA:

All the data contained within the Housing: A Growing City report as well as the data used to create the charts and maps can be accessed in this spreadsheet.

FACTS:

Some interesting facts from the data…

● Five boroughs with the highest proportion of households that have lived at their address for less than 12 months in 2009/10:

1. Westminster – 19 per cent
2. Wandsworth – 17 per cent
3. Camden – 16 per cent
4. Lambeth – 14 per cent
5. Southwark – 13 per cent

-31. Harrow – 6 per cent

-32. Havering – 5 per cent

● Five boroughs with the highest percentage point increase between 2004 and 2009 of households in the ‘private rented’ sector:

1. Newham – 17 per cent
2. Greenwich – 11 per cent
3. Enfield – 10 per cent
4. Camden – 9 per cent
5. Harrow – 8 per cent

-32. Islington – 1 per cent

-33. Bexley – 1 per cent

● Five boroughs with the highest percentage difference in median house prices between 2007 Q4 and 2010 Q4:

1. Kensington & Chelsea – 29 per cent
2. Westminster – 19 per cent
3. Camden – 15 per cent
4. Islington – 14 per cent
5. Southwark – 10 per cent

-31. Newham – down 9 per cent

-32. Barking & D’ham – down 9 per cent

The average transaction price of new housing in Europe was the highest in Norway, whereas existing homes were the most expensive in Austria. Since there is no central body that collects and tracks transaction activity or house prices across the whole continent or the European Union, not all countries are included. To compile the ranking, the source weighed the transaction prices of residential properties in the most important cities in each country based on data from their national offices. For example, in Germany, the cities included were Munich, Hamburg, Frankfurt, and Berlin. House prices have been soaring, with Sweden topping the ranking Considering the RHPI of houses in Europe (the price index in real terms, which measures price changes of single-family properties adjusted for the impact of inflation), however, the picture changes. Sweden, Luxembourg and Norway top this ranking, meaning residential property prices have surged the most in these countries. Real values were calculated using the so-called Personal Consumption Expenditure Deflator (PCE), This PCE uses both consumer prices as well as consumer expenditures, like medical and health care expenses paid by employers. It is meant to show how expensive housing is compared to the way of living in a country. Home ownership highest in Eastern Europe The home ownership rate in Europe varied from country to country. In 2020, roughly half of all homes in Germany were owner-occupied whereas home ownership was at nearly 97 percent in Romania or around 90 percent in Slovakia and Lithuania. These numbers were considerably higher than in France or Italy, where homeowners made up 65 percent and 72 percent of their respective populations.For more information on the topic of property in Europe, visit the following pages as a starting point for your research: real estate investments in Europe and residential real estate in Europe.

Data relating to the price of houses sold in the Glasgow Area from the years 1991 - 2013.Some elements of the dataset are derived from information produced by Registers of ScotlandCLASS Administrative Classification onlySTNO Street NumberSTnu Street NumberFLATPOSN Flat PositionSTNAME Street NamePOSTCODE Post CodeMONTH OF SALE Month of SaleYEAR OF SALE (CALENDAR) YEAR OF SALE (CALENDAR)YEAR OF SALE (BUSINESS) YEAR OF SALE (BUSINESS)MONTH AND YEAR MONTH AND YEARQUARTER_(CALENDAR) QUARTER_(CALENDAR)ACTUAL PRICE AT POINT OF SALE Actual Price RPI Retail Price Index - Published every month and available for the last 20 yearsDEFLATOR Figure used to to determine change in house prices over time - calculated fromthe Retail Price Index and other dataPRICE CONSTANT AT July 2013 Actual Price multiplied by the Deflator. This is the price if RPI is applied to original sale price - How much would the property be valued at now. ORIGINOFBUY Council area or Country where the buyer comes fromOMIT OR USE Oroginal data also included retail and commercial data. - Not reproduced hereNEWBUILD OR RESALE Is it a newbuild house or a resaleLHF Local Housing Forum Area

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2023. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 117.5 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.

The primary data source for these tenure estimates is the Council Tax Register compiled by the City Assessor. Stores, garages and properties relating to hostels and institutions have been excluded from the total stock count. Ownership information from this source relies to a considerable extent on residents notifying the Council that a change of tenure has taken place. Accordingly, the figures contained within this file may differ slightly from other estimates available which make use of additional data sources, such as tenure data from the Housing Benefits system, a housing stock file from the Glasgow Housing Association and the Statutory Register of Private Landlords. These tenure estimates were last undertaken for housing stock as it was in 2018, with the report going to Council committee in 2019. These estimates which are aggregated to neighbourhood level are available at: https://www.glasgow.gov.uk/CHttpHandler.ashx?id=46229&p=0The ownership information from the various data sources does not always agree. This is a particular issue for private renting. For dwellings where the available evidence from the Council Tax Register and the Statutory Register of Private Landlords is not consistent, a more detailed tenure assessment was carried out, using a sample. The proportions for owner occupation and private renting from the sample have been used to estimate the tenure for dwellings where the tenure position is unclear.The owner occupied stock figures include shared ownership and shared equity properties. The social rented stock figures include mid-market rent housing. Housing at full market rent has been classified as private rented stock, irrespective of ownership.

PLEASE NOTE: This record has been retired. It has been superseded by: https://environment.data.gov.uk/dataset/4c8981b3-11c1-40ca-b7a2-7c3f45a97397

This dataset is a product of a national assessment of flood risk for England produced using local expertise.

This dataset is produced using the Risk of Flooding from Rivers and Sea data which shows the chance of flooding from rivers and/or the sea, based on cells of 50m. Each cell is allocated one of four flood risk categories, taking into account flood defences and their condition.

This dataset uses OS data to assign one of four flood risk categories to each property, based simply on the category allocated to the cell that the property is in. Individual addresses are not provided, but OS referencing is included to enable the data to be linked to address databases.

NOTE: We have paused quarterly updates of this dataset. Please visit the “Pause to Updates of Flood Risk Maps” announcement on our support pages for further information. We will provide notifications on the Check Your Long-Term Flood Risk website to indicate where we have new flood risk information.

Geneva, Switzerland, was the most expensive city to buy an apartment in Europe in the first quarter of 2024. The square meter price in Geneva was nearly 15,650 euros in that quarter, about 2,000 euros higher than the second city in the ranking, Zurich. Cost of rent Rents across the major cities in Europe increased significantly in 2023. One of the main factors driving high rents across European cities is the same as any other consumer-driven business. If demand outweighs supply, prices will inflate. The drive for high paid professionals to be located centrally in prime locations, mixed with the low levels of available space, high land, and construction costs, all help keep rental prices increasing. Mortgage rates The average mortgage interest rates across Europe in 2023 were all under five percent, except in Czechia, Romania, Hungary, and Poland. On an individual level, a difference of one percent would most likely mean thousands of euros in interest on the mortgage a person is paying, making timing key in house purchasing. Mortgage interest rates tend to be lower in Nordic countries due to the financial stability and reliability of its borrowers. Other factors that influence the mortgage interest rates include inflation, economic growth, monetary policies, the bond market and the overall conditions of the housing market. More stable markets also tend to have higher average prices.

This dataset contains data from reporting years 2023 & 2024 and is therefore indicative of allocations and lets within the Stirling Council area, rather than an as is indicator. The Allocation Area boundaries are defined by the intersection of Stirling Council properties and postcode geographies (as defined by The National Records of Scotland Scottish Postcode Directory Scottish Postcode Directory (SPD) | National Records of Scotland (nrscotland.gov.uk) )Schema;Allocation Area Number,Allocation Area Name, Property Types and Numbers,Properties by Bedrooms, Percentage Turnover of Lets, and the number of Properties Let in period.

The Scotland Heat Map provides estimates of annual heat demand for almost 3 million properties in Scotland. Demand is given in kilowatt-hours per year (kWh/yr). Property level estimates can be combined to give values for various geographies. Both domestic and non-domestic properties are included. This dataset gives the density of heat demand of properties for each 2011 Data Zone (in kWh/yr per meter squared). Heat demand is calculated by combining data from a number of sources, ensuring that the most appropriate data available is used for each property. Density of demand is calculated by dividing the total heat demand for all properties in the Data Zone by the area of the Data Zone (in m2). The data can be used by local authorities and others to identify or inform opportunities for low carbon heat projects such as district heat networks. The Scotland Heat Map is produced by the Scottish Government. The most recent version is the Scotland Heat Map 2022, which was released to local authorities in November 2023. More information can be found in the documentation available on the Scottish Government website: https://www.gov.scot/publications/scotland-heat-map-documents/

What is the average price of residential property in the Netherlands? In the third quarter of 2024, a single-family home cost approximately 434,000 euros. There were large differences between the Dutch provinces, however. Single-family homes were most expensive in the central province of Utrecht with an average price of 731,000 euros, whereas a similar house in Groningen had an average price tag of 384,000 euros. Overall, the average price a private individual would pay when buying any type of existing residential property (such as single-family homes but also, for example, an apartment) was approximately 416,000 euros in 2023. Do the Dutch prefer to buy or to rent a house? The Netherlands had a slightly higher homeownership rate (the share of owner-occupied dwellings of all homes) in 2023 than other countries in Northwestern Europe. About 70 percent of all Dutch houses were owned, whereas this percentage was lower in Germany, France, and the United Kingdom. This is an effect of past developments: the price to rent ratio (the development of the nominal purchase price of a house divided by the annual rent of a similar place with 2015 as a base year) shows that the gap between house prices and rents has continuously widened in recent years. Despite a slight decline in the ratio due to slowing house price growth and accelerating rental growth, in 2023, the cost of buying a home had grown significantly faster relative to the cost of renting. Mortgages in the Netherlands Additionally, the Netherlands has one of the highest mortgage debts among private individuals in Europe. In 2024, total debt exceeded 839 billion euros. This has a political background, as the Dutch tax system allowed homeowners for many years to deduct interest paid on mortgage from pre-tax income for a maximum period of thirty years, essentially allowing for income support for homeowners. In the Netherlands, this system is known as hypotheekrenteaftrek. Note that since 2014, the Dutch government is slowly scaling this down, with a planned acceleration from 2020 onwards.

The Properties Vulnerable to Heat Impact report, produced by Arup, maps London's heat risk across homes, neighbourhoods, and essential properties in the wake of climate change.

The study focused on essential settings, emphasising areas where occupants are especially vulnerable to heat-related hazards. This included schools, hospitals, care homes residential properties and neighbourhoods.

Properties Vulnerable to Heat Impact Report | London City Hall

This layer of the map based index (GeoIndex) shows the location of onshore UK boreholes known to BGS that have digital or paper geophysical borehole logs. The details given for each borehole are, the name of the borehole, the grid reference and the format, ie. paper or digital. Scattered distribution of boreholes, locally dense coverage, few logs from Scotland. The GeoIndex is updated at regular intervals but more information may be available than is shown at any one time.

Current resister of community based assets (buildings and land) owned by Glasgow City Council and associated bodies. These may include but not be limited to community centres, local halls and play areas.

This web map service (WMS) depicts estimates of mean values of soil bacteria, invertebrates, carbon, nutrients and pH within selected habitats and parent material characteristics across GB . Estimates were made using CS data using a mixed model approach. The estimated means of habitat/parent material combinations using 2007 data are modelled on dominant habitat and parent material characteristics derived from the Land Cover Map 2007 and Parent Material Model 2009, respectively. Bacteria data is representative of 0 - 15 cm soil depth and includes bacterial community structure as assessed by ordination scores. Invertebrate data is representative of 0 - 8 cm soil depth and includes Total catch, Mite:Springtail ratio, Number of broad taxa and Shannon diversity. Gravimetric moisture content (%) data is representative of 0 - 15 cm soil depth Carbon data is representative of 0-15 cm soil depth and includes Loss-on-ignition (%), Carbon concentration (g kg-1) and Carbon density (t ha-1). Loss-on-ignition was determined by combustion of 10g dry soil at 375 deg C for 16 hours; carbon concentration was estimated by multiplying LOI by a factor of 0.55, and carbon density was estimated by combining carbon concentration with bulk density estimates. Nutrient data is representative of 0 - 15 cm soil depth and includes total nitrogen (N) concentration (%), C:N ratio and Olsen-Phosphorus (mg/kg). pH and bulk density (g cm-3) data is representative of 0 - 15 cm soil depth. Topsoil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight; bulk density was estimated by making detailed weight measurements throughout the soil processing procedure. Areas, such as urban and littoral rock, are not sampled by CS and therefore have no associated data. Also, in some circumstances sample sizes for particular habitat/parent material combinations were insufficient to estimate mean values.

The house price to income index in Europe declined in almost all European countries in 2023, indicating that income grew faster than house prices. Portugal, Luxembourg, and the Netherlands led the house price to income index ranking in 2023, with values exceeding 125 index points. Romania, Bulgaria, and Finland were on the other side of the spectrum, with less than 100 index points. The house price to income ratio is an indicator for the development of housing affordability across OECD countries and is calculated as the nominal house prices divided by nominal disposable income per head, with 2015 chosen as a base year. A ratio higher than 100 means that the nominal house price growth since 2015 has outpaced the nominal disposable income growth, and housing is therefore comparatively less affordable. In 2023, the OECD average stood at 117.4 index points.

This MSOA atlas provides a summary of demographic and related data for each Middle Super Output Area in Greater London. The average population of an MSOA in London in 2010 was 8,346, compared with 1,722 for an LSOA and 13,078 for a ward.

The profiles are designed to provide an overview of the population in these small areas by combining a range of data on the population, births, deaths, health, housing, crime, commercial property/floorspace, income, poverty, benefits, land use, environment, deprivation, schools, and employment.

If you need to find an MSOA and you know the postcode of the area, the ONS NESS search page has a tool for this.

The MSOA Atlas is available as an XLS as well as being presented using InstantAtlas mapping software. This is a useful tool for displaying a large amount of data for numerous geographies, in one place (requires HTML 5).

CURRENT MSOA BOUNDARIES (2011)

Excel

Instant Atlas

PREVIOUS MSOA BOUNDARIES (2001)

Excel

Instant Atlas

NB. It is currently not possible to export the map as a picture due to a software issue with the Google Maps background. We advise you to print screen to copy an image to the clipboard.

Tips:

1. - Select a new indicator from the Data box on the left. Select the theme, then indicator and then year to show the data.

2. - To view data just for one borough*, use the filter tool.

3. - The legend settings can be altered by clicking on the pencil icon next to the MSOA tick box within the map legend.

4. - The areas can be ranked in order by clicking at the top of the indicator column of the data table.

Themes included here are Census 2011 Population, Mid-year Estimates, Population by Broad Age, Households, Household composition, Ethnic Group, Country of Birth, Language, Religion, Tenure, Dwelling type, Land Area, Population Density, Births, General Fertility Rate, Deaths, Standardised Mortality Ratio (SMR), Population Turnover Rates (per 1000), Crime (numbers), Crime (rates), House Prices, Commercial property (number), Rateable Value (£ per m2), Floorspace; ('000s m2), Household Income, Household Poverty, County Court Judgements (2005), Qualifications, Economic Activity, Employees, Employment, Claimant Count, Pupil Absence, Early Years Foundation Stage, Key Stage 1, GCSE and Equivalent, Health, Air Emissions, Car or Van availability, Income Deprivation, Central Heating, Incidence of Cancer, Life Expectancy, and Road Casualties.

• The London boroughs are: City of London, Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Camden, Croydon, Ealing, Enfield, Greenwich, Hackney, Hammersmith and Fulham, Haringey, Harrow, Havering, Hillingdon, Hounslow, Islington, Kensington and Chelsea, Kingston upon Thames, Lambeth, Lewisham, Merton, Newham, Redbridge, Richmond upon Thames, Southwark, Sutton, Tower Hamlets, Waltham Forest, Wandsworth, Westminster.

These profiles were created using the most up to date information available at the time of collection (Spring 2014).

You may also be interested in LSOA Atlas and Ward Atlas.

This is a 25m pixel data set representing the land surface of Great Britain, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band raster in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2022 products are available from the LCM2022 product documentation.

This web map service (WMS) depicts estimates of mean values of soil bacteria, invertebrates, carbon, nutrients and pH within selected habitats and parent material characteristics across GB . Estimates were made using CS data using a mixed model approach. The estimated means of habitat/parent material combinations using 2007 data are modelled on dominant habitat and parent material characteristics derived from the Land Cover Map 2007 and Parent Material Model 2009, respectively. Bacteria data is representative of 0 - 15 cm soil depth and includes bacterial community structure as assessed by ordination scores. Invertebrate data is representative of 0 - 8 cm soil depth and includes Total catch, Mite:Springtail ratio, Number of broad taxa and Shannon diversity. Gravimetric moisture content (%) data is representative of 0 - 15 cm soil depth Carbon data is representative of 0-15 cm soil depth and includes Loss-on-ignition (%), Carbon concentration (g kg-1) and Carbon density (t ha-1). Loss-on-ignition was determined by combustion of 10g dry soil at 375 deg C for 16 hours; carbon concentration was estimated by multiplying LOI by a factor of 0.55, and carbon density was estimated by combining carbon concentration with bulk density estimates. Nutrient data is representative of 0 - 15 cm soil depth and includes total nitrogen (N) concentration (%), C:N ratio and Olsen-Phosphorus (mg/kg). pH and bulk density (g cm-3) data is representative of 0 - 15 cm soil depth. Topsoil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight; bulk density was estimated by making detailed weight measurements throughout the soil processing procedure. Areas, such as urban and littoral rock, are not sampled by CS and therefore have no associated data. Also, in some circumstances sample sizes for particular habitat/parent material combinations were insufficient to estimate mean values.