Housing Index in the United Kingdom increased to 514.30 points in July from 512.40 points in June of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Nationwide Housing Prices in the United Kingdom increased to 543.94 points in July from 541.85 points in June of 2025. This dataset provides - United Kingdom Nationwide Housing Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Housing prices and number of transactions by dwelling type.

House sales not at full market value are excluded.

Ownership of this dataset remains with the Communities and Local Government (CLG). Information can only be reproduced if the source is fully acknowledged.

The Land Registry (LR) and CLG have provided these datasets drawn from the Land Register.

Information on outliers, that is transactions involving a very low or very high price, is included so that users can take their impact into account when using the data.

Available for Middle Layer Super Output Area (MSOA).

NOTE: This data has not been updated since 2009.

See more on the ONS NESS website.

Average house price (with regular updates) Source: Land Registry Publisher: Communities and Local Government (CLG) Geographies: Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England Time coverage: 1996 to 2009 Type of data: Administrative data

Industry Analysts discuss the UK inflation rate and movements in house prices.

Abstract copyright UK Data Service and data collection copyright owner.The English Housing Survey (EHS) is a continuous national survey commissioned by the Department for Communities and Local Government (DCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of the department's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public. The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 14,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC). The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire. End User Licence and Special Licence Versions: From 2014 data onwards, the End User Licence (EUL) versions of the EHS only include derived variables. In addition the number of variables on the EUL datasets from that date has been reduced and disclosure control increased on certain remaining variables. The new Special Licence versions of the EHS, which are subject to more restrictive access conditions, are of a similar nature to EHS EUL datasets prior to 2014 and include both derived and raw datasets. Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages. The English Housing Survey, 2018: Housing Stock Data: Special Licence Access is available for all cases where a physical survey has been completed. For occupied cases the data comprises information from the household interview and from the physical survey. For vacant properties only, data from the physical survey are provided. The Special Licence version includes raw interview and physical datasets and derived data, whereas the EUL version (SN 8670) only includes derived variables. Users are advised to obtain SN 8670 to see whether it is suitable for their needs before making an application for the Special Licence version.The data are made available for a two-year rolling sample i.e. approximately 12,000 cases together with the appropriate two-year weights. For example, the EHS Housing Stock results presented here are for 2018, but cover the period April 2017 to March 2019. This means that if you use more than one housing stock dataset, you must use either odd or even years. For example, you need to use the Housing Stock Dataset for '2012' and '2014' or '2013' and '2015', but not the dataset for '2014' and '2013' as you would double-count the cases surveyed between April 2013 and March 2014. The Housing Stock dataset should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income.Users who only require data from the household interview should use the English Housing Survey, 2018-2019: Household Data EUL or Special Licence versions (SNs 8669 and 8719 respectively). Main Topics: The EHS Housing survey consists of two components. Interview Survey (Household) An interview is first conducted with the householder. The interview topics include: household characteristics, satisfaction with the home and the area, disability and adaptations to the home, ownership and rental details and income details. All interviewees are guaranteed confidentiality and all data is anonymised. Physical Survey (Housing Stock) Where interviews were achieved (the ‘full household sample’), each year all rented properties and a sub-sample of owner occupied properties are regarded as eligible for the physical survey and the respondent’s consent is sought. A proportion of vacant properties were also sub-sampled. For all physical survey cases, a visual inspection of the property, both internal and external is carried out by a qualified surveyor. Multi-stage stratified random sample Physical measurements and tests

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is UK Commercial Property REIT (UKCM) a Wise Buy?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Abstract copyright UK Data Service and data collection copyright owner. The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included). The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. Data are revised on a wave by wave basis, as a result of backwards imputation from the current wave's data. These revisions are due to improvements in the imputation methodology.Note from the WAS team - November 2023:“The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates.” Survey Periodicity - "Waves" to "Rounds" Due to the survey periodicity moving from “Waves” (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019. A Secure Access version of the WAS, subject to more stringent access conditions, is available under SN 6709; it contains more detailed geographic variables than the EUL version. Users are advised to download the EUL version first (SN 7215) to see if it is suitable for their needs, before considering making an application for the Secure Access version.Further information and documentation may be found on the ONS Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.Occupation data for 2021 and 2022 data files The ONS have identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.Latest edition informationFor the 18th edition (May 2023), the inheritance variables 'ivalb1r7' and 'ivalb1r7_i' which had been omitted in error have been added. Main Topics: The WAS questionnaire is divided into two parts with all adults aged 16 years and over (excluding those aged 16 to 18 currently in full-time education) being interviewed in each responding household. Household schedule: This is completed by one person in the household (usually the head of household or their partner) and predominantly collects household level information such as the number, demographics and relationship of individuals to each other, as well as information about the ownership, value and mortgages on the residence and other household assets. Individual schedule: This is given to each adult in the household and asks questions about economic status, education and employment, business assets, benefits and tax credits, saving attitudes and behaviour, attitudes to debt, insolvency, major items of expenditure, retirement, attitudes to saving for retirement, pensions, financial assets, non-mortgage debt, investments and other income. Multi-stage stratified random sample Telephone interview Face-to-face interview 2006 2020 ADOPTION PAY AGE AIRCRAFT ASSETS ATTITUDES TO SAVING BANK ACCOUNTS BICYCLES BOATS BONDS BUSINESS OWNERSHIP BUSINESS RECORDS BUSINESSES CARAVANS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD BENEFITS CHILD SUPPORT PAYMENTS CHILD TRUST FUNDS COHABITING COMMERCIAL BUILDINGS COST OF LIVING COSTS CREDIT CARD USE DEBILITATIVE ILLNESS DEBTS DISABILITIES EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL STATUS EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ESTATES ETHNIC GROUPS FAMILY BENEFITS FAMILY INCOME FAMILY MEMBERS FINANCIAL ADVICE FINANCIAL COMPENSATION FINANCIAL DIFFICULTIES FINANCIAL SERVICES FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GIFTS Great Britain HEALTH HEALTH STATUS HIRE PURCHASE HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S SO... HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSING AGE HOUSING ECONOMICS HOUSING FINANCE HOUSING TENURE ILL HEALTH INCOME INCONTINENCE INFORMAL CARE INHERITANCE INSOLVENCIES INSURANCE CLAIMS INTELLECTUAL IMPAIR... INVESTMENT Income JOB HUNTING JOB SEEKER S ALLOWANCE LAND OWNERSHIP LANDLORDS LOANS Labour and employment MAIL ORDER SERVICES MARITAL STATUS MATERNITY BENEFITS MATERNITY PAY MATHEMATICS MOBILE HOMES MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLE VALUE MOTOR VEHICLES MOTORCYCLES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE BENEFITS ONE PARENT FAMILIES OVERDRAFTS PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PATERNITY BENEFITS PATERNITY PAY PENSION BENEFITS PENSION CONTRIBUTIONS PENSIONS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PHYSICAL MOBILITY PLACE OF BIRTH PRIVATE PENSIONS PRIVATE PERSONAL PE... PROFIT SHARING PROFITS QUALIFICATIONS REDUNDANCY PAY RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RETIREMENT AGE SAVINGS SAVINGS ACCOUNTS AN... SECOND HOMES SELF EMPLOYED SELLING SHARED HOME OWNERSHIP SHARES SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STAKEHOLDER PENSIONS STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT LOANS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS TAX RELIEF TENANTS HOME PURCHA... TIED HOUSING TOP MANAGEMENT TRANSPORT FARES TRUSTS UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WEALTH WILLS WINNINGS WORKPLACE property and invest...

Abstract copyright UK Data Service and data collection copyright owner.The English Housing Survey (EHS) is a continuous national survey commissioned by the Department for Communities and Local Government (DCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of the department's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public. The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 14,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC). The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire. End User Licence and Special Licence Versions: From 2014 data onwards, the End User Licence (EUL) versions of the EHS only include derived variables. In addition the number of variables on the EUL datasets from that date has been reduced and disclosure control increased on certain remaining variables. The new Special Licence versions of the EHS, which are subject to more restrictive access conditions, are of a similar nature to EHS EUL datasets prior to 2014 and include both derived and raw datasets. Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages. The English Housing Survey, 2016: Housing Stock Data: Special Licence Access is available for all cases where a physical survey has been completed. For occupied cases the data comprises information from the household interview and from the physical survey. For vacant properties only, data from the physical survey are provided. The Special Licence version includes raw interview and physical datasets and derived data, whereas the EUL version (SN 8350) only includes derived variables. Users are advised to obtain SN 8350 to see whether it is suitable for their needs before making an application for the Special Licence version. The data are made available for a two-year rolling sample i.e. approximately 12,000 cases together with the appropriate two-year weights. For example, the EHS Housing Stock results presented here are for 2016, but cover the period April 2015 to March 2017. This means that if you use more than one housing stock dataset, you must use either odd or even years. For example, you need to use the Housing Stock Dataset for '2012' and '2014' or '2013' and '2015', but not the dataset for '2014' and '2013' as you would double-count the cases surveyed between April 2013 and March 2014. The Housing Stock dataset should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income. Users who only require data from the household interview should use the English Housing Survey, 2016-2017: Household Data EUL or Special Licence versions (SNs 8384 and 8386 respectively). Main Topics: The EHS Housing Stock survey consists of two components. Interview Survey An interview is first conducted with the householder. The interview topics include: household characteristics, satisfaction with the home and the area, disability and adaptations to the home, ownership and rental details and income details. All interviewees are guaranteed confidentiality and all data are anonymised. Physical Survey Where interviews were achieved (the 'full household sample'), each year all rented properties and a sub-sample of owner occupied properties are regarded as eligible for the physical survey and the respondent’s consent is sought. A proportion of vacant properties were also sub-sampled. For these cases a visual inspection of the property, both internal and external is carried out by a qualified surveyor. Multi-stage stratified random sample Face-to-face interview Physical measurements House inspection; Surveyor property inspection.

I recently submitted my dissertation for my MSc in Business Analytics titled: Understanding & Predicting Student Rental Prices in a U.K. city: Machine Learning & Traditional Methods.

I chose this dissertation research area due to the lacking literature investigating U.K. rental dynamics (particularly in Northern Ireland) and due to the real and very current issue of rising rent felt in Belfast by students.

Based on a selection of 36 property variables such as geographic location, bedroom number & property size - I built multiple machine learning models to predict the price of rent and to understand the most important variables in selected models.

No existing dataset was available that combined all the required information for Belfast and therefore I chose to complete the task of data mining and cleaning the information, pulling it all into one dataset. I sourced the info from Property Pal and Property News. Please check the dataset as there may be minor repetition or some columns which should not be used.

Finally, I leveraged these findings into an interactive dashboard (you can view a link below) which enables students to view all available properties and determine which one has the required features alongside appropriate pricing.

PLEASE NOTE: This record has been retired. It has been superseded by: https://environment.data.gov.uk/dataset/dcbad548-ba75-4f32-bf22-306f9059343e These documents are designed to provide a simple, easy to refer to analysis of the numbers of people, property and extent of land within areas at risk of flooding taken from the risk of flooding from rivers and sea (RoFRS) products. We use them in Environment Agency publications and reports; and to answer queries.

We use the Risk of Flooding from Rivers and Sea products and the National Receptor Dataset (NRD) 2023* to provide a breakdown of numbers and areas of land at risk of flooding within England, English Local Authorities, English MP Constituencies, Lead Local Flood Authorities and Environment Agency Partnership and Strategic Overview areas.

There are 5 spreadsheets available which provide the following summary information: • Number of properties in areas at risk from flooding from rivers and sea • Number of people in areas at risk from flooding from rivers and sea • Number of deprived properties in areas at risk of flooding from rivers and sea • Change in number of properties in areas at risk of flooding from rivers and sea (since previous update) • Change in area of land at risk of flooding from rivers and sea (since previous update)

Further explanations about the information presented in the spreadsheets such as flood likelihood category, property types and how numbers are calculated are presented in the first tab of each spreadsheet.

*NRD2023 was developed by the Environment Agency, however it is based on Ordnance Survey data (OS Address Base Premium) and we do not have permission to release as Open Data.

Construction Orders in the United Kingdom increased 10.50 percent in March of 2025 over the same month in the previous year. This dataset provides - United Kingdom Construction Orders- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The English Housing Survey (EHS) is a continuous national survey commissioned by the Department for Communities and Local Government (DCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous surveys into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available from the Archive under GN 33277). The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of the department's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public. The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 14,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).

The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.

The EHS is used to derive two types of datasets: Household and Housing Stock. These are available separately for the End User Licence (EUL) and Special Licence (SL) versions, but are combined into one study for the Secure Access EHS:

• Household datasets comprise the full interview data (plus associated derived variables) for all cases where an interview has been completed. Datasets are provided for single financial years together with annual weights. The survey consists of a detailed interview using a CAPI based program. An interview is first conducted with the householder. Household datasets should be used for any analysis where only information from the household interview is required.
• Housing Stock data are available for all cases where a physical survey has been completed. For occupied properties, the datasets include data from the household interview as well as data from the physical survey. For vacant properties, only data for the physical survey are provided. The data are made available for a two year rolling sample i.e. approximately 12,000 cases together with the appropriate 2-year weights. This means that if you use more than one housing stock dataset, you must use either odd or even years. For example, you need to use the Housing Stock Dataset for '2012' and '2014' or '2013' and '2015', but not the dataset for '2014' and '2013' as you would double-count the cases surveyed between April 2013 and March 2014. The Housing Stock datasets should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income.

Secure Access EHS data:
Secure Access datasets for the EHS up to 2013/14 are available under UK Data Archive SN 6923 and include two detailed geographical variables that are not available in the standard EUL versions: Postcodes and Lower Layer Super Output Areas. These variables have been merged into the General derived data file within each Household and Housing Stock dataset. The two variables are also available in a separate Detailed Geography data file, along with the key variable 'aacode', allowing the user to merge with other files of their choice. All other files are the same as in the EUL versions. Secure Access datasets for the EHS from 2014/15 are available under Archive SN 8121. From the submission of the 2014/15 datasets onwards, the EHS Secure Access approach was changed by the Department of Communities and Local Government (DCLG). The Postcode and Lower Layer Super Output Area variables remain available and DCLG also provide versions of the full EHS datasets as used internally, i.e. not disclosure controlled, for Secure Access. For the 2015/16 datasets, the Secure Access version includes the Special Licence version data also available under SNs 8254 and 8255, as well as detailed geography files containing postcodes and Lower Layer Super Output Area variables.

Prospective users of the Secure Access version of the EHS will need to fulfil additional requirements, commencing with the completion of extra application forms to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access users must also complete face-to-face training and agree to Secure Access' User Agreement and Licence Compliance Policy (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL and/or Special Licence versions of the data prior to ordering a Secure Access version.

Related UK Data Archive studies:
EUL versions of the EHS studies are available under GN 33422, and further details and links for these can be found via the EHS list of datasets. From 2014/15 data onwards, the EUL versions of the EHS only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS have been deposited, which are of a similar nature to previous EHS EUL datasets and include derived and raw datasets. Special Licence versions of the data from 2014/15 onwards are available under Archive GN 33515.

Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.
Latest edition
For the third edition (February 2018), data and documentation for 2015-16 have been added.

The English Housing Survey (EHS) is a continuous national survey commissioned by the Department for Communities and Local Government (DCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous surveys into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available from the Archive under GN 33277). The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of the department's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public. The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 14,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).

The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.

The EHS is used to derive two types of datasets: Household and Housing Stock. These are available separately for the End User Licence (EUL) and Special Licence (SL) versions, but are combined into one study for the Secure Access EHS:

• Household datasets comprise the full interview data (plus associated derived variables) for all cases where an interview has been completed. Datasets are provided for single financial years together with annual weights. The survey consists of a detailed interview using a CAPI based program. An interview is first conducted with the householder. Household datasets should be used for any analysis where only information from the household interview is required.
• Housing Stock data are available for all cases where a physical survey has been completed. For occupied properties, the datasets include data from the household interview as well as data from the physical survey. For vacant properties, only data for the physical survey are provided. The data are made available for a two year rolling sample i.e. approximately 12,000 cases together with the appropriate 2-year weights. This means that if you use more than one housing stock dataset, you must use either odd or even years. For example, you need to use the Housing Stock Dataset for '2012' and '2014' or '2013' and '2015', but not the dataset for '2014' and '2013' as you would double-count the cases surveyed between April 2013 and March 2014. The Housing Stock datasets should be used for any analysis requiring information relating to the physical characteristics and energy efficiency of the housing stock. Derived datasets provide key analytical variables compiled post-fieldwork including energy efficiency ratings, decent home indicators and equivalised income.

Secure Access EHS data:
Secure Access datasets for the EHS up to 2013/14 are available under UK Data Archive SN 6923 and include two detailed geographical variables that are not available in the standard EUL versions: Postcodes and Lower Layer Super Output Areas. These variables have been merged into the General derived data file within each Household and Housing Stock dataset. The two variables are also available in a separate Detailed Geography data file, along with the key variable 'aacode', allowing the user to merge with other files of their choice. All other files are the same as in the EUL versions. Secure Access datasets for the EHS from 2014/15 are available under Archive SN 8121. From the submission of the 2014/15 datasets onwards, the EHS Secure Access approach was changed by the Department of Communities and Local Government (DCLG). The Postcode and Lower Layer Super Output Area variables remain available and DCLG also provide versions of the full EHS datasets as used internally, i.e. not disclosure controlled, for Secure Access. For the 2015/16 datasets, the Secure Access version includes the Special Licence version data also available under SNs 8254 and 8255, as well as detailed geography files containing postcodes and Lower Layer Super Output Area variables.

Prospective users of the Secure Access version of the EHS will need to fulfil additional requirements, commencing with the completion of extra application forms to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access users must also complete face-to-face training and agree to Secure Access' User Agreement and Licence Compliance Policy (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL and/or Special Licence versions of the data prior to ordering a Secure Access version.

Related UK Data Archive studies:
EUL versions of the EHS studies are available under GN 33422, and further details and links for these can be found via the EHS list of datasets. From 2014/15 data onwards, the EUL versions of the EHS only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS have been deposited, which are of a similar nature to previous EHS EUL datasets and include derived and raw datasets. Special Licence versions of the data from 2014/15 onwards are available under Archive GN 33515.

Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.

For the sixth edition (March 2017), the physical data file for each year has been updated; a new cavity wall insulation variable, wins95x, has been added. In compliance with Building Regulations, an increasing proportion of dwellings built in 1991 or after with cavity walls had cavity wall insulation fitted at the time of construction (known as 'as built' insulation), although compliance could also be achieved through other techniques. The non-intrusive survey undertaken in the EHS would not always be able to identify as built insulation (though the surveyor might have found out from the occupant), so dwellings built in 1991 or after with cavity walls with no evidence of insulation in the survey have been assumed to be insulated. The category 'cavity walls with evidence of insulation' includes both dwellings with evidence of cavity wall insulation (e.g. drill holes or information from occupants) and those built in 2003 or after. A separate category identifies cavity walled dwellings built in 1991 or after where no evidence of cavity wall insulation was seen by the surveyors and where no assumptions have been made based on the construction date. This category therefore includes dwellings built in 1991 or after up to and including in 2002, with no evidence of CWI from the physical survey. For the 2014/15 Headline Report a new variable for cavity wall insulation was introduced (wins95x, which has been added to EHS physical files from 2007/8 onwards). From the submission of the 2015 data, wins95x will replace wins90x.