This dataset contains Qatar Economically Active Population (15 Years & Above) By Nationality , Gender and Age Groups. Data from Qatar Planning and Statistics Authority.

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Not including persons seeking work for the first time

Russia Economically Active Population: Period Avg: Male: Employed data was reported at 37,648.167 Person th in 2023. This records an increase from the previous number of 37,035.547 Person th for 2022. Russia Economically Active Population: Period Avg: Male: Employed data is updated yearly, averaging 35,837.700 Person th from Dec 1992 (Median) to 2023, with 32 observations. The data reached an all-time high of 37,648.167 Person th in 2023 and a record low of 30,613.000 Person th in 1998. Russia Economically Active Population: Period Avg: Male: Employed data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GB001: Economically Active Population: Employed and Unemployed. Data since 2009 are given as annual average, data of 2008-1999 - for the end of November, 1996 - for the end of March, 1998, 1997 and 1995-1992 - for the end of October.

These data are taken from the ANNUAL datasets from the Labour Force Survey (LFS) carried out by the Office for National Statistics (ONS), providing labour market data back to 1996 for the NUTS2 areas in Wales, and back to 2001 for the local authorities in Wales. The availability of local authority data is dependent upon on an enhanced sample (around 350 per cent larger) for the annual LFS, which commenced in 2001. For years labelled 1996 to 2004 in this dataset, the actual periods covered are the 12 months running from March in the year given to February in the following year (e.g. 2001 = 1 March 2001 to 28 February 2002). Since 2004, the annual data have been produced on a rolling annual basis, updated every three months, and the dataset is now referred to as the Annual Population Survey (APS). The rolling annual averages are on a calendar basis with the first rolling annual average presented here covering the period 1 January 2004 to 31 December 2004, followed by data covering the period 1 April 2004 to 31 March 2005, with rolling quarterly updates applied thereafter. Note therefore that the consecutive rolling annual averages overlap by nine months, and there is also a two-month overlap between the last period presented on the former March to February basis, and the first period on the new basis. The population can be broken down into economically active and economically inactive populations. The economically active population is made up of persons in employment, and persons unemployed according to the International Labour Organisation (ILO) definition. This report allows the user to access these data. Although each measure is available for different population bases, there is an official standard population base used for each of the measures, as follows. Population aged 16 and over: Economic activity level, Employment level, ILO unemployment level Population aged 16-64: Economic inactivity level 16-64 population is used as the base for economic inactivity. By excluding persons of pensionable age who are generally retired and therefore economically inactive, this gives a more appropriate measure of workforce inactivity. Rates for each of the above measures are also calculated in a standard manner and are available in the dataset. With the exception of the ILO unemployment rate, each rate is defined in terms of the shares of population that fall into each category. The ILO unemployment rate is defined as ILO unemployed persons as a percentage of the economically active population. Although each rate is available for the different population bases, there is an official standard population base used for each of the rates, as follows. Percentage of population aged 16-64: Economic activity, Employment,. Economic inactivity Percentage of economically active population aged 16 and over: ILO unemployment

Kazakhstan Population: Economically Active: Employed data was reported at 9,233.828 Person th in Sep 2024. This records an increase from the previous number of 9,190.346 Person th for Jun 2024. Kazakhstan Population: Economically Active: Employed data is updated quarterly, averaging 8,462.500 Person th from Mar 2001 (Median) to Sep 2024, with 95 observations. The data reached an all-time high of 9,233.828 Person th in Sep 2024 and a record low of 6,221.900 Person th in Mar 2001. Kazakhstan Population: Economically Active: Employed data remains active status in CEIC and is reported by Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.G015: Economically Active and Non Active Population.

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.

New reweighting policy
Following the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.

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.

Additional data derived from the QLFS
The Archive also holds further QLFS series: End User Licence (EUL) quarterly data; Secure Access datasets; household datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

Variables DISEA and LNGLST
Dataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018.

An article explaining the quality assurance investigations that have been conducted so far is available on the ONS Methodology webpage. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk.

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: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/revisionofmiscodedoccupationaldataintheonslabourforcesurveyuk/january2021toseptember2022" style="background-color: rgb(255, 255, 255);">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. Estimates of rates will, however, be robust.

Economic activity rates, employment rates and unemployment rates broken down by ethnic group. The economically active population comprises those who are either employed or unemployed and excludes those who are economically inactive. The data are taken from the Annual Population Survey (APS), produced by the Office for National Statistics.

Economic activity rates broken down by gender. The economically active population comprises those who are either employed or unemployed and excludes those who are economically inactive. The data are taken from the Annual Population Survey, produced by the Office for National Statistics.

Analysis of ‘Inactive population who have worked previously and left their last job more than 1 years ago by economic sector of last job, sex and age group. Percentages with regards the total in each age group. EPA (API identifier: 5353)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-347-5353 on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Inactive population who have worked previously and left their last job more than 1 years ago by economic sector of last job, sex and age group. Percentages with regards the total in each age group. Annual. National. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---

The FAOSTAT PopSTAT module contains timeseries on population and economically active population. The series consist of both estimates and projections for different periods as available from the original sources, namely: Population data from the UN Population Division and the data refers to the UN Revision 2012. Long term series estimates and projects from 1961 to 2050. Economically active population from the ILO and the data refers to the 5th edition, revision 2009. Long term series estimates and projects from 1980 to 2020.

Russia Economic Activity Rate: Age 15 and Above data was reported at 62.900 % in Dec 2018. This records a decrease from the previous number of 63.100 % for Sep 2018. Russia Economic Activity Rate: Age 15 and Above data is updated quarterly, averaging 62.800 % from Mar 2018 (Median) to Dec 2018, with 4 observations. The data reached an all-time high of 63.100 % in Sep 2018 and a record low of 62.600 % in Mar 2018. Russia Economic Activity Rate: Age 15 and Above data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GB001: Economically Active Population: Employed and Unemployed.

Analysis of ‘Unemployed population who have previously worked by economic sector of last job, sex and autonomous community. Absolute values. EPA (API identifier: 5354)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-347-5354 on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Unemployed population who have previously worked by economic sector of last job, sex and autonomous community. Absolute values. Annual. Autonomous Communities and Cities. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---

Counts and proportions of males and females economically active or inactive and whether working full time, part time or whether self employed, unemployed etc. 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

Abstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.Occupation data for 2021 and 2022The 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. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. 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 2022APS Well-Being DatasetsFrom 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.APS disability variablesOver time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage. End User Licence and Secure Access APS dataUsers should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to: age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family nationality and country of origin geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district health: including main health problem, and current and past health problems education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from system variables: including week number when interview took place and number of households at address The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Latest edition informationFor the seventh edition (July 2023), the variables FDPCH16, TRVDRV and TRVMTH were added to the study. Also, SOC variables NSECM20, NSECMJ20, SC20LMJ, SC20LMN, SC20MMJ, SC20MMN, SC20SMJ, SC20SMN, SOC20M, SC2010M and the person income weight PIWTA22 were replaced with revised versions. Further information on the SOC revisions 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. Main Topics:Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS. Multi-stage stratified random sample Face-to-face interview Telephone interview 2021 ADULT EDUCATION AGE ANXIETY APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BONUS PAYMENTS BUSINESSES CARE OF DEPENDANTS CHRONIC ILLNESS COHABITATION CONDITIONS OF EMPLO... COVID 19 DEBILITATIVE ILLNESS DEGREES DISABILITIES Demography population ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS FAMILIES FAMILY BENEFITS FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER HAPPINESS HEADS OF HOUSEHOLD HEALTH HIGHER EDUCATION HOME OWNERSHIP HOURS OF WORK HOUSEHOLDS HOUSING HOUSING BENEFITS HOUSING TENURE INCOME INDUSTRIES JOB CHANGING JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS Labour and employment MANAGERS MARITAL STATUS NATIONAL IDENTITY NATIONALITY OCCUPATIONS OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE SECTOR PUBLIC SECTOR RECRUITMENT REDUNDANCY REDUNDANCY PAY RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL MOBILITY SELF EMPLOYED SICK LEAVE SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS STATE RETIREMENT PE... STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS TAX RELIEF TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TRAINING TRAINING COURSES TRAVELLING TIME UNEMPLOYED UNEMPLOYMENT UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WELL BEING HEALTH WELSH LANGUAGE WORKING CONDITIONS WORKPLACE vital statistics an...

Economically active population by sex, age and other typologies

This dataset contains statistics on economically active population (15 years and above) by nationality, gender and age groups based on labor force sample survey.The data is updated quarterly from 2017 until the first quarter of 2020.

The table contains quarterly data on the number of economically active population broken down by sex and education.

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.

New reweighting policy
Following the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.

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.

Additional data derived from the QLFS
The Archive also holds further QLFS series: End User Licence (EUL) quarterly data; Secure Access datasets; household datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

Variables DISEA and LNGLST
Dataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will...

Ukraine Labour Force: Working Age: Male: Economically Active Population data was reported at 8,755.200 Person th in 2021. This records a decrease from the previous number of 8,889.100 Person th for 2020. Ukraine Labour Force: Working Age: Male: Economically Active Population data is updated yearly, averaging 10,809.350 Person th from Dec 2004 (Median) to 2021, with 18 observations. The data reached an all-time high of 11,119.700 Person th in 2008 and a record low of 8,755.200 Person th in 2021. Ukraine Labour Force: Working Age: Male: Economically Active Population data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.G010: Labour Force: Annual. Data release delayed due to the Ukraine-Russia conflict. No estimation on next release date can be made.
Economically active population comprises all population aged 15–70 of either sex who during reporting period performed the work related to the production of goods and services.

Analysis of ‘Unemployed population who have previously worked and left their last job more than 1 year ago by professional situation in last job, sex and age group. Percentages with respect to the total of each age group. EPA (API identifier: 5262)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-347-5262 on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Unemployed population who have previously worked and left their last job more than 1 year ago by professional situation in last job, sex and age group. Percentages with respect to the total of each age group. Annual. National. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Active population by sex, marital status and studies in progress. EPA (API identifier: 4071)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-330-4071 on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Active population by sex, marital status and studies in progress. Quarterly. National. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---