The statistic shows the unemployment rate in the United Kingdom from 1999 to 2024. The UK's unemployment rate decreased to 4.11 percent in 2024. Unemployment and the economy of the United Kingdom The global financial crisis of 2008 left many nations with high inflation and increasing unemployment rates. The United Kingdom, however, has attempted and successfully lowered the unemployment rate since 2009. The UK is a member of the Commonwealth of Nations, the Council of Europe, the G7, the G8, the G20, NATO, and World Trade Organization. It is therefore one of the biggest and most important economic powers in the world. It consists of England, Scotland, Wales and Northern Ireland, and in 2014, the UK population amounted to over 64 million people. The same year, it reported the sixth largest gross domestic product in the world, reaching more than 2.8 billion U.S. dollars - and with a prospering economy, its GDP is on the upswing: It is estimated that the GDP in the United Kingdom will grow by approximately 3 percent in 2015 in comparison to the previous year. Regarding unemployment, the UK has never been "typically European". Europe's unemployment rate has been relatively high in comparison to other world regions; the unemployment rate in developed countries and the European Union in 2014 was around 7.8 percent. Meanwhile, the global unemployment rate in 2014 was an estimated 5.9 percent. Despite reporting the third highest unemployment rate in major industrial and emerging countries, behind France and India, the unemployment rate in the United Kingdom is much lower than the European Union rate.

United Kingdom UK: Unemployment Rate: % Change data was reported at -10.357 % in 2017. This records a decrease from the previous number of -8.703 % for 2016. United Kingdom UK: Unemployment Rate: % Change data is updated yearly, averaging -1.107 % from Dec 1952 (Median) to 2017, with 66 observations. The data reached an all-time high of 160.470 % in 2009 and a record low of -34.366 % in 1997. United Kingdom UK: Unemployment Rate: % Change data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Labour Force, Employment and Unemployment: Annual.

United Kingdom UK: Unemployment Rate: % Change data was reported at -8.472 % in Mar 2018. This records an increase from the previous number of -9.338 % for Dec 2017. United Kingdom UK: Unemployment Rate: % Change data is updated quarterly, averaging -3.261 % from Mar 1958 (Median) to Mar 2018, with 241 observations. The data reached an all-time high of 195.950 % in Jun 2009 and a record low of -39.339 % in Dec 1997. United Kingdom UK: Unemployment Rate: % Change data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Labour Force, Employment and Unemployment: Quarterly.

With the collapse of the U.S. housing market and the subsequent financial crisis on Wall Street in 2007 and 2008, economies across the globe began to enter into deep recessions. What had started out as a crisis centered on the United States quickly became global in nature, as it became apparent that not only had the economies of other advanced countries (grouped together as the G7) become intimately tied to the U.S. financial system, but that many of them had experienced housing and asset price bubbles similar to that in the U.S.. The United Kingdom had experienced a huge inflation of housing prices since the 1990s, while Eurozone members (such as Germany, France and Italy) had financial sectors which had become involved in reckless lending to economies on the periphery of the EU, such as Greece, Ireland and Portugal. Other countries, such as Japan, were hit heavily due their export-led growth models which suffered from the decline in international trade. Unemployment during the Great Recession As business and consumer confidence crashed, credit markets froze, and international trade contracted, the unemployment rate in the most advanced economies shot up. While four to five percent is generally considered to be a healthy unemployment rate, nearing full employment in the economy (when any remaining unemployment is not related to a lack of consumer demand), many of these countries experienced rates at least double that, with unemployment in the United States peaking at almost 10 percent in 2010. In large countries, unemployment rates of this level meant millions or tens of millions of people being out of work, which led to political pressures to stimulate economies and create jobs. By 2012, many of these countries were seeing declining unemployment rates, however, in France and Italy rates of joblessness continued to increase as the Euro crisis took hold. These countries suffered from having a monetary policy which was too tight for their economies (due to the ECB controlling interest rates) and fiscal policy which was constrained by EU debt rules. Left with the option of deregulating their labor markets and pursuing austerity policies, their unemployment rates remained over 10 percent well into the 2010s. Differences in labor markets The differences in unemployment rates at the peak of the crisis (2009-2010) reflect not only the differences in how economies were affected by the downturn, but also the differing labor market institutions and programs in the various countries. Countries with more 'liberalized' labor markets, such as the United States and United Kingdom experienced sharp jumps in their unemployment rate due to the ease at which employers can lay off workers in these countries. When the crisis subsided in these countries, however, their unemployment rates quickly began to drop below those of the other countries, due to their more dynamic labor markets which make it easier to hire workers when the economy is doing well. On the other hand, countries with more 'coordinated' labor market institutions, such as Germany and Japan, experiences lower rates of unemployment during the crisis, as programs such as short-time work, job sharing, and wage restraint agreements were used to keep workers in their jobs. While these countries are less likely to experience spikes in unemployment during crises, the highly regulated nature of their labor markets mean that they are slower to add jobs during periods of economic prosperity.

United Kingdom UK: Unemployment Rate: % Change over Previous Period data was reported at -2.285 % in Mar 2018. This records an increase from the previous number of -5.074 % for Dec 2017. United Kingdom UK: Unemployment Rate: % Change over Previous Period data is updated quarterly, averaging -0.000 % from Jun 1957 to Mar 2018, with 244 observations. The data reached an all-time high of 84.122 % in Mar 2009 and a record low of -21.141 % in Mar 1997. United Kingdom UK: Unemployment Rate: % Change over Previous Period data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Labour Force, Employment and Unemployment: Quarterly.

Social protection spending on unemployment in the United Kingdom was 1.3 billion pounds in 2024/25, compared with 1.21 billion in the previous financial year.

United Kingdom UK: Unemployment Rate: % Change over Previous Period data was reported at -2.996 % in Mar 2018. This records a decrease from the previous number of 1.367 % for Feb 2018. United Kingdom UK: Unemployment Rate: % Change over Previous Period data is updated monthly, averaging 0.000 % from Feb 1957 (Median) to Mar 2018, with 734 observations. The data reached an all-time high of 76.572 % in Feb 2009 and a record low of -15.859 % in Jan 1997. United Kingdom UK: Unemployment Rate: % Change over Previous Period data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s United Kingdom – Table UK.IMF.IFS: Labour Force, Employment and Unemployment.

Scotland's unemployment rate in the second quarter of 2025 was 3.7 percent, compared with 3.8 percent in the previous quarter. During this time period, Scotland's unemployment rate was at its highest in the fourth quarter of 2011 when it reached 8.6 percent.

Unemployment rate of people from non-white ethnic groups Source: Annual Population Survey (APS) Publisher: Nomis Geographies: Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 2004 to 2009 Type of data: Survey

Two years after the UK recession ended in the final quarter of 2009, came a decrease in GDP in the final quarter of 2011 and the first quarter of 2012, signifying an official “double dip” recession. This Update looks at key labour market indicators since the beginning of the recession period in 2008. It presents the latest national and London figures of those claiming Jobseekers’ Allowance (JSA), known as the claimant count, and also shows the official unemployment measure: the International Labour Organisation (ILO) definition, which is derived from the Labour Force Survey. It gives some detail on the geography and characteristics of those looking for work. In addition, it gives figures for employment levels.

Abstract copyright UK Data Service and data collection copyright owner.

Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.

Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

Occupation data for 2021 and 2022 data files

The ONS has 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. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2022 Weighting

The population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution....

Background The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.

Longitudinal data The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary. LFS Documentation The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.Occupation data for 2021 and 2022 data filesThe ONS has 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. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2022 WeightingThe population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust. For the second edition (May 2012), a new data file has been deposited, weighted to 2010 population figures. A new version of the longitudinal user guide has been added to the documentation.

United Kingdom UK: Unemployment: % Change data was reported at -9.862 % in 2017. This records a decrease from the previous number of -7.843 % for 2016. United Kingdom UK: Unemployment: % Change data is updated yearly, averaging -3.197 % from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 34.109 % in 2009 and a record low of -17.731 % in 2014. United Kingdom UK: Unemployment: % Change data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Labour Force, Employment and Unemployment: Annual.

The Crime Survey for England and Wales (CSEW) asks a sole adult in a random sample of households about their, or their household's, experience of crime victimisation in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked, covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS). These variables are contained within the non-victim form (NVF) data file. In 2009, the survey was extended to children aged 10-15 years old; one resident of that age range was also selected from the household and asked about their experience of crime and other related topics. The first set of children's data covered January-December 2009 and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main study.

The Telephone-operated Crime Survey for England and Wales (TCSEW) became operational on 20 May 2020. It was a replacement for the face-to-face CSEW, which was suspended on 17 March 2020 because of the coronavirus (COVID-19) pandemic. It was set up with the intention of measuring the level of crime during the pandemic. As the pandemic continued throughout the 2020/21 survey year, questions have been raised as to whether the year ending March 2021 TCSEW is comparable with estimates produced in earlier years by the face-to-face CSEW. The ONS Comparability between the Telephone-operated Crime Survey for England and Wales and the face-to-face Crime Survey for England and Wales report explores those factors that may have a bearing on the comparability of estimates between the TCSEW and the former CSEW. These include survey design, sample design, questionnaire changes and modal changes.

More general information about the CSEW may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page.

History - the British Crime Survey

The CSEW was formerly known as the British Crime Survey (BCS), and has been in existence since 1981. The 1982 and 1988 BCS waves were also conducted in Scotland (data held separately under SNs 4368 and 4599). Since 1993, separate Scottish Crime and Justice Surveys have been conducted. Up to 2001, the BCS was conducted biennially. From April 2001, the Office for National Statistics took over the survey and it became the CSEW. Interviewing was then carried out continually and reported on in financial year cycles. The crime reference period was altered to accommodate this.

Secure Access CSEW data
In addition to the main survey, a series of questions covering drinking behaviour, drug use, self-offending, gangs and personal security, and intimate personal violence (IPV) (including stalking and sexual victimisation) are asked of adults via a laptop-based self-completion module (questions may vary over the years). Children aged 10-15 years also complete a separate self-completion questionnaire. The questionnaires are included in the main documentation, but the data are only available under Secure Access conditions (see SN 7280), not with the main study. In addition, from 2011 onwards, lower-level geographic variables are also available under Secure Access conditions (see SN 7311).

New methodology for capping the number of incidents from 2017-18
The CSEW datasets available from 2017-18 onwards are based on a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old datasets are not, comparability has been lost with years prior to 2012-2013. More information can be found in the 2017-18 User Guide (see SN 8464) and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’.

Extending the BCS to Children
Following the 'Smith Review', 'Crime statistics: an independent review', the BCS has included children aged 10-15 years, through screening at sampled addresses. The British Crime Survey Experimental Data: Children Aged 10-15 Years, January-December, 2009 comprises the first set of BCS children's data to become available.

The primary aim of extending the BCS to children is to provide estimates of the levels of crime experienced by children and their risk of victimisation. In addition to questions about experience of crime, the BCS children's survey also gathers information on a number of crime-related topics such as perceptions and attitudes to the police, anti-social behaviour, crime prevention and personal security. It is therefore envisaged that the BCS children's survey will also provide a rich source of data to assist in understanding the nature and circumstances of crimes experienced by children aged 10 to 15 years.

Estimates published based on these data have been published as 'Experimental Statistics'. In accordance with the Code of Practice for Official Statistics, 'Experimental Statistics' are new official statistics undergoing evaluation and published to involve users and stakeholders in their development as a means to build in quality at an early stage. As such, these data are subject to future revision and change.

Comparing the children's data with the adult BCS
The BCS children's experimental dataset has been developed as an extension to the existing adult BCS to children aged 10 to 15 years. However, methodological differences between the adult and child BCS mean that direct comparisons cannot be made between the adult and child data. That said, while the questions asked and levels of detail collected differ between the data sources there is a common approach to the classification of incidents to offences in law. For further details of the methodology, see documentation.

Findings publication
The findings from the first set of children's data have been published as:
Millard, B. and Flatley, J. (ed.) (2010) Experimental statistics on victimisation of children aged 10 to 15: findings from the British Crime Survey for the year ending December 2009 England and Wales, Home Office Statistical Bulletin 11/01, London: Home Office. Retrieved October 26, 2010 from http://www.homeoffice.gov.uk/rds/pdfs10/hosb1110.pdf

These ward level well being scores present a combined measure of well-being indicators of the resident population based on 12 different indicators. Where possible each indicator score is compared with the England and Wales average, which is zero. Scores over 0 indicate a higher probability that the population on average will experience better well-being according to these measures. Users can adjust the weight of each indicator depending on what they consider to be the more or less important, thus generating bespoke scores. This is done either by entering a number between 0 and 10. The scores throughout the spreadsheet will update automatically. The tool combines data across a range of themes for the last five years of available data (2009-2013). View the results in the online interactive tool here, The well-being scores are then presented in a ranked bar chart for each borough, and a ward map of London. The spreadsheet also highlights wards in the top and bottom 25 per cent in London. Wards that have shown significant improvement or reduction in their scores relative to the average over the five year period are also highlighted. Borough figures are provided to assist with comparisons. Rankings and summary tables are included. The source data that the tool is based on is included in the spreadsheet. Detailed information about definitions and sources is contained within the spreadsheet. The 12 measures included are: Health Life Expectancy Childhood Obesity Incapacity Benefits claimant rate Economic security Unemployment rate Safety Crime rate Deliberate Fires Education GCSE point scores Children Unauthorised Pupil Absence Families Children in out-of-work households Transport Public Transport Accessibility Scores (PTALs) Environment Access to public open space & nature Happiness Composite Subjective Well-being Score (Life Satisfaction, Worthwhileness, Anxiety, and Happiness) (New data only available since 2011/12) With some measures if the data shows a high figure that indicates better well-being, and with other measures a low figure indicates better well-being. Therefore scores for Life Expectancy, GCSE scores, PTALs, and Access to Public Open Space/Nature have been reversed so that in all measures low scores indicate probable lower well-being. The data has been turned into scores where each indicator in each year has a standard deviation of 10. This means that each indicator will have an equal effect on the final score when the weightings are set to equal. Why should measuring well-being be important to policy makers? Following research by the Cabinet Office and Office for National Statistics, the government is aiming to develop policy that is more focused on ‘all those things that make life worthwhile’ (David Cameron, November 2010). They are interested in developing new and better ways to understand how policy and public services affect well-being. Why measure well-being for local areas? It is important for London policy makers to consider well-being at a local level (smaller than borough level) because of the often huge differences within boroughs. Local authorities rely on small area data in order to target resources, and with local authorities currently gaining more responsibilities from government, this is of increasing importance. But small area data is also of interest to academics, independent analysts and members of the public with an interest in the subject of well-being. How can well-being be measured within small areas? The Office for National Statistics have been developing new measures of national well-being, and as part of this, at a national and regional level, the ONS has published some subjective data to measure happiness. ONS have not measured well-being for small areas, so this tool has been designed to fill this gap. However, DCLG have published a tool that models life satisfaction data for LSOAs based on a combination of national level happiness data, and 'ACORN' data. Happiness data is not available for small areas because there are no surveys large enough for this level of detail, and so at this geography the focus is on objective indicators. Data availability for small areas is far more limited than for districts, and this means the indicators that the scores are based on are not all perfect measures of well-being, though they are the best available. However, by using a relatively high number of measures across a number of years, this increases the reliability of the well-being scores. How can this tool be used to help policy makers? Each neighbourhood will have its own priorities, but the data in this tool could help provide a solid evidence base for informed local policy-making, and the distribution of regeneration funds. In addition, it could assist users to identify the causes behind an improvement in well-being in certain wards, where examples of good practice could be applied elsewhere. Differences to the previous report This is the 2013 edition of this publication, and there is one change from 2012. Indicators of Election turnout has been replaced with a composite score of subjective well-being indicators. This tool was created by the GLA Intelligence Unit. Please contact datastore@london.gov.uk for more information.

Recent changes in labour markets have increased employment instability. Under these conditions, in male breadwinner families women might increase their labour supply when their male partners become unemployed. Previous studies have extensively investigated the role played by household and individual characteristics in explaining such increases in the labour supply of women. However, studies which examine the moderating role of specific welfare policies are missing. Our study contributes to the literature by investigating the moderating effect of childcare and tax-benefit policies for the labour supply response of women following the unemployment of their partner. We focus on a sample of 24 EU member states and the UK, during the period 2009-2019, combining longitudinal microdata from EU-SILC with country-period specific policy indicators generated with the use of the tax-benefit simulation model EUROMOD, UKMOD and country-period specific indicators of childcare use. We find that women indeed respond to men’s unemployment by increasing their labour supply though the response is fairly weak. We also find the response is not restricted by having children at home or availability of public childcare and does not depend on the generosity of unemployment benefits. It is, however, negatively affected by marginal tax rates.

United Kingdom UK: Unemployment: % Change data was reported at -7.633 % in Mar 2018. This records an increase from the previous number of -8.649 % for Dec 2017. United Kingdom UK: Unemployment: % Change data is updated quarterly, averaging -3.497 % from Mar 1984 (Median) to Mar 2018, with 137 observations. The data reached an all-time high of 46.064 % in Jun 2009 and a record low of -19.931 % in Dec 2014. United Kingdom UK: Unemployment: % Change data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s UK – Table UK.IMF.IFS: Labour Force, Employment and Unemployment: Quarterly.

The Crime Survey for England and Wales (CSEW) asks a sole adult in a random sample of households about their, or their household's, experience of crime victimisation in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked, covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS). These variables are contained within the non-victim form (NVF) data file. In 2009, the survey was extended to children aged 10-15 years old; one resident of that age range was also selected from the household and asked about their experience of crime and other related topics. The first set of children's data covered January-December 2009 and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main study.

The Telephone-operated Crime Survey for England and Wales (TCSEW) became operational on 20 May 2020. It was a replacement for the face-to-face CSEW, which was suspended on 17 March 2020 because of the coronavirus (COVID-19) pandemic. It was set up with the intention of measuring the level of crime during the pandemic. As the pandemic continued throughout the 2020/21 survey year, questions have been raised as to whether the year ending March 2021 TCSEW is comparable with estimates produced in earlier years by the face-to-face CSEW. The ONS Comparability between the Telephone-operated Crime Survey for England and Wales and the face-to-face Crime Survey for England and Wales report explores those factors that may have a bearing on the comparability of estimates between the TCSEW and the former CSEW. These include survey design, sample design, questionnaire changes and modal changes.

More general information about the CSEW may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page.

History - the British Crime Survey

The CSEW was formerly known as the British Crime Survey (BCS), and has been in existence since 1981. The 1982 and 1988 BCS waves were also conducted in Scotland (data held separately under SNs 4368 and 4599). Since 1993, separate Scottish Crime and Justice Surveys have been conducted. Up to 2001, the BCS was conducted biennially. From April 2001, the Office for National Statistics took over the survey and it became the CSEW. Interviewing was then carried out continually and reported on in financial year cycles. The crime reference period was altered to accommodate this.

Secure Access CSEW data
In addition to the main survey, a series of questions covering drinking behaviour, drug use, self-offending, gangs and personal security, and intimate personal violence (IPV) (including stalking and sexual victimisation) are asked of adults via a laptop-based self-completion module (questions may vary over the years). Children aged 10-15 years also complete a separate self-completion questionnaire. The questionnaires are included in the main documentation, but the data are only available under Secure Access conditions (see SN 7280), not with the main study. In addition, from 2011 onwards, lower-level geographic variables are also available under Secure Access conditions (see SN 7311).

New methodology for capping the number of incidents from 2017-18
The CSEW datasets available from 2017-18 onwards are based on a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old datasets are not, comparability has been lost with years prior to 2012-2013. More information can be found in the 2017-18 User Guide (see SN 8464) and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’.