This dataset is about countries in Central America. It has 8 rows. It features 3 columns: country full name, and self-employed workers.

This dataset is about countries per year in Central America. It has 512 rows. It features 4 columns: country, self-employed workers, and access to electricity.

Employees and self-employed, by industry sectors and sex, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

Nonemployer Statistics for Economics: National Ocean Watch (ENOW NES) contains annual time-series data for over 400 coastal counties, 30 coastal states, and the nation, derived from the United States Census Bureau. ENOW NES data report the number of nonemployer establishments and gross receipts, within the six sectors of the ocean and Great Lakes economy, .

The data in this dataset relates to the status of persons employed in Wales, breaking the total down into those who are self-employed or employees and those who are in full time or part time. As the data come from a survey, the results are sample-based estimates and therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value. This range or sampling variability increases as the detail in the data increases, for example individual local authority data are subject to higher variability than Wales data. LFS data is collected throughout the year, and is available from the ONS in a variety of ways. This dataset contains the latest annual results, as referred to in the second bullet below. Key data on the labour market is updated every month showing the position for the latest three months, for the UK and each of the UK countries and English regions. Note these data are seasonally adjusted and also that no sub-regional (i.e. local authority) data are published by the ONS to a monthly timetable. Annual results covering the periods described earlier are also available from the ONS, providing more detailed data from the LFS, including data for sub-Wales geographies. These annual datasets use results from the samples for the quarterly surveys used for the key series, together with results from additional persons sampled to provide a more robust (boosted) dataset, with estimates subject to much lower sampling variability. Quarterly results are also available, again providing more detailed data from the LFS than the key series, including data for sub-Wales geographies. However, although these data are available earlier than the data taken from the annual datasets, data for sub-Wales geographies taken from the quarterly datasets are no longer included on StatsWales as the results are far less robust than those which come from the annual datasets. Note that as data are taken from the ANNUAL Labour Force Survey datasets they do NOT exactly match annual averages derived from the 4 QUARTERLY datasets in the relevant 12 month period covered due to differences in the sampling structure.

Forecast: Self-Employed People in IT services Sector in the US 2022 - 2026 Discover more data with ReportLinker!

This dataset is about countries per year in Central America. It has 512 rows. It features 4 columns: country, self-employed workers, and health expenditure.

Employment (workplace) by industry from the Business register and employment survey (BRES). This data excludes self-employed but includes proprietors Employment = employees + working proprietors. Working Proprietors are sole traders, sole proprietors, partners and directors. This does not apply to registered charities. Numbers have all been rounded to the nearest 100 Before the BRES first existed in 2009, the ABI collected employment data by industry. The two surveys are not directly comparable. The BRES is a business survey which collects both employment and financial information. Only employment information for the location of an employees workplace is available from Nomis The BRES is based on a sample of approximately 80,000 businesses and is used to provide an estimate of the number of employees. The difference between the estimate and its true value is known as the sampling error. The actual sampling error for any estimate is unknown but we can estimate, from the sample, a typical error, known as the standard error. This provides a means of assessing the precision of the estimate; the lower the standard error, the more confident we can be the estimate is close to the true value. NOMIS website article

This dataset excludes farm based agriculture data contained in SIC class 0100.

Data and charts accompanying the 'Business Register Employment Survey 2010: London' publication

The ABI was replaced by the Business Register and Employment Survey (BRES) from 2009 onwards, therefore this dataset will no longer be updated.

More on ONS website

https://data.london.gov.uk/dataset/workplace-employment-industry-borough

License: UK Open Government Licence

The dataset contains estimates of employed, jobseekers (unemployed) and inactive people, broken down by gender, from 2004 onwards. The source is the Continuous Labour Force Survey (RCFL) conducted quarterly by ISTAT: since this is a sample survey, the data are estimated. For further information on the RCFL: www.istat.it. The data are released in two versions with different reference population: age group :15-64 years and 15 years and over. Here is a brief definition of the data: * EMPLOYED: include persons aged 15 years and over in the reference week of the interview: have worked at least one hour in any activity involving monetary consideration or in kind or have worked at least one hour of unpaid work in the firm of a family member in which they habitually work; are absent from work (e.g. due to holidays or illness), but the absence does not exceed 3 months (in the case of employees and family workers) or maintain the activity (in the case of self-employed persons, excluding family workers). * PEOPLE LOOKING FOR EMPLOYMENT: include persons aged 15 and over who are not in employment and who: have carried out at least one active job-search activity in the 30 days preceding the interview and are available to work (or to start a self-employed activity) within two weeks of the interview; or, they will start a job within three months from the date of the interview and are available to work (or to start a self-employed activity) within two weeks after the interview, if it is possible to anticipate the start of the job. * INACTIVE: are people who do not work and do not look for work (population under 15 years of age, students, housewives, pensioners and those who are not active in the search for a job). This dataset has been issued by the Municipality of Milan. Dataset based on ISTAT source Labour Force Surveys: http://www.istat.it/en/archive/8263. The path to be used to find the original dataset on sisi.comune.milano.it is: sisi.comune.milano.it - Work and business - Labour Forces - Residents in Milan

The dataset contains estimates of employed, job-seeking (unemployed) and inactive people, broken down by gender, from 2004 onwards. The source is the Continuous Labor Force Survey (RCFL) conducted quarterly by ISTAT: since it is a sample survey, the data are estimated. For further information on the RCFL: www.istat.it. The data is released in two versions with different reference populations: age group: 15-64 years and 15 years and over. A brief definition of the data follows: * EMPLOYEES: include people aged 15-64 who, in the reference week of the interview: carried out at least one hour of work in any activity that provides for a monetary or in-kind payment or at least one hour of unpaid work in the company of a family member in which they usually collaborate, are absent from work (for example, due to holidays or illness), but the absence does not exceed 3 months (in the case of employees and family assistants) o maintain the business (in the case of self-employed persons, excluding family workers). * PEOPLE SEEKING EMPLOYMENT: include unemployed persons aged between 15 and 64 who: have carried out at least one active job-seeking action in the thirty days preceding the interview and are available to work (or to set up a business independent) within two weeks following the interview; or, will start a job within three months from the date of the interview and are available to work (or to start a self-employment) within two weeks following the interview, if it is possible to anticipate the start of the job * LABOR FORCE: are people employed or looking for work: they are obtained by adding the two previous items. * INACTIVE: people who are not working and are not looking for work (population under the age of 15, students, housewives, pensioners and those who are not active in looking for a job). This dataset was released by the municipality of Milan. Dataset based on ISTAT source Labor force surveys: http://www.istat.it/it/archivio/8263. The path to use to find the original dataset on sisi.comune.milano.it is: sisi.comune.milano.it - ​​Employment and business - Labor Forces - Residents of Milan

The dataset consists of the average number of hours actually worked as reported by people during the Periodic Labour Force Survey. The data is available by region- urban and rural, gender- male and female, and by status of employment- self employed, salaried, and casual labourers. The years covered in the survey are from July to June. For instance, 2023-24 refers to the period July 2023 to June 2024 and likewise for other years.

This dataset is about countries per year in South America. It has 12 rows and is filtered where the date is 2021. It features 4 columns: country, self-employed workers, and nitrous oxide emissions.

This table provides information on the number of young people aged 0 to 25 living in welfare families. For the demarcation of a social assistance family, we looked at social assistance benefits under the Participation Act or social assistance-related benefits under the Income Provision for Older and Partially Disabled Unemployed Workers Act (IOAW), the Income Provision for Older and Partially Disabled Former Self-Employed Persons Act (IOAZ), the Self-Employed Persons Assistance Decree (Bbz) and the Work and Income Artists Act (WWIK).

Benefits under the Temporary Bridging Scheme for Self-Employed Entrepreneurs (Tozo) are not included in this table. The Tozo provides self-employed people with an additional living allowance and a loan for working capital to deal with liquidity problems caused by the coronavirus crisis.

This table shows figures (31 December of the reference year) for young people living in welfare families, with a possible breakdown by region (including municipality level), type of household and the age of the youngest child in the household.

In order to show how young people in the Netherlands are doing, the National Youth Monitor describes more than 70 topics in addition to this topic. The topics are called indicators.

Data available from 2007.

Status of figures The figures for all years are final.

Changes as of 26 June 2024: None, this is a new table. This table is the successor of: Young people in welfare families; 0 to 25 year olds, 2023 region. See paragraph 3.

When will there be new figures? New figures are expected in the second quarter of 2025. The table is then replaced by a new table with the then most recent area layouts.

The Labour Market Indicators spreadsheet for boroughs and regions will no longer be updated from March 2015. The final version from March 2015 will still be available to download at the bottom of this page. Most of the data is available within datasets elsewhere on the Datastore.

Workforce Jobs
Unemployment
Model based Unemployment for Boroughs
Claimant Count rates for Boroughs and Wards
Employment Rate Trends
Employment rates by Gender, Age and Disability
Number of Self Employed, Full and Part Time Employed
Employment by Occupation
Employment by Industry
Employment, Unemployment, Economic Activity and Inactivity Rates by Disability
Employment by Ethnicity
Economic Inactivity by Gender and Reason
Qualifications of Economically Active, Employed and Unemployed
Qualification levels of working-age population
Apprenticeship Starts and Achievements
Young People Not in Employment, Education or Training (NEET), Borough
19 year olds Qualified to NVQ Level 3
GCE A level examination results of 16-18 year olds
GCSE Results by Pupil Characteristics
People Claiming Out-of-Work Benefits
People Claiming Incapacity Benefit
Children Living in Workless Households
Gross Value Added, and Gross Disposable Household Income
Earnings by place of residence
Earnings by place of work
Business Demographics
Employment projections by sector
Jobs Density
Population Estimates
Population Migration

Core Indicators

Number of London residents of working age in employment
Employment rate
Number of male London residents of working age in employment
Male employment rate
Number of female London residents of working age in employment
Female employment rate
Workforce jobs
Jobs density
Number of London residents of working age who are economically inactive
Economic inactivity rate
Number of London residents aged 16+ who are unemployed (model based)
Proportion of London residents aged 16+ who are unemployed (model based)
Claimant unemployment
Claimant Count as a proportion of the working age population
Incidence of skill gaps (Numbers and rates)
GCSE (5+ A*–C) attainment including English and Maths
Number of working age people in London with no qualifications
Proportion of working age people in London with no qualifications
Number of working age people in London with Level 4+ qualifications
Proportion of working age people in London with Level 4+ qualifications
Number of people of working age claiming out of work benefits
Proportion of the working age population who claim out of work benefits
Number of young people aged 16-18 who are not in

Global Self-Employed People in IT services Sector Share by Country (Thousand Units (Persons)), 2023 Discover more data with ReportLinker!

The Labour Market Indicators spreadsheet for boroughs and regions will no longer be updated from March 2015. The final version from March 2015 will still be available to download at the bottom of this page. Most of the data is available within datasets elsewhere on the Datastore.

Workforce Jobs
Unemployment
Model based Unemployment for Boroughs
Claimant Count rates for Boroughs and Wards
Employment Rate Trends
Employment rates by Gender, Age and Disability
Number of Self Employed, Full and Part Time Employed
Employment by Occupation
Employment by Industry
Employment, Unemployment, Economic Activity and Inactivity Rates by Disability
Employment by Ethnicity
Economic Inactivity by Gender and Reason
Qualifications of Economically Active, Employed and Unemployed
Qualification levels of working-age population
Apprenticeship Starts and Achievements
Young People Not in Employment, Education or Training (NEET), Borough
19 year olds Qualified to NVQ Level 3
GCE A level examination results of 16-18 year olds
GCSE Results by Pupil Characteristics
People Claiming Out-of-Work Benefits
People Claiming Incapacity Benefit
Children Living in Workless Households
Gross Value Added, and Gross Disposable Household Income
Earnings by place of residence
Earnings by place of work
Business Demographics
Employment projections by sector
Jobs Density
Population Estimates
Population Migration

Core Indicators

Number of London residents of working age in employment
Employment rate
Number of male London residents of working age in employment
Male employment rate
Number of female London residents of working age in employment
Female employment rate
Workforce jobs
Jobs density
Number of London residents of working age who are economically inactive
Economic inactivity rate
Number of London residents aged 16+ who are unemployed (model based)
Proportion of London residents aged 16+ who are unemployed (model based)
Claimant unemployment
Claimant Count as a proportion of the working age population
Incidence of skill gaps (Numbers and rates)
GCSE (5+ A*–C) attainment including English and Maths
Number of working age people in London with no qualifications
Proportion of working age people in London with no qualifications
Number of working age people in London with Level 4+ qualifications
Proportion of working age people in London with Level 4+ qualifications
Number of people of working age claiming out of work benefits
Proportion of the working age population who claim out of work benefits
Number of young people aged 16-18 who are not in employment, education or training NEET)
Proportion of 16-18 year olds who are NEET

Additional Indicators

Economy and Productivity
Business Demography (active enterprises, births and deaths of enterprises)
Business Demography (active enterprises, births and deaths of enterprises): Index
Business Demography (National indicators)

Demand for labour: Jobs, vacancies and skills needs
Total vacancies reported by employers
Skill shortage vacancies
JobCentre vacancies - notified
JobCentre vacancies - unfilled
Number employed by industry (working age)
Employment rates by industry (working age)
Number employed by occupation
Employment rates by occupation
Working age who are self-employed
Numbers employed in the civil service

Population and supply of labour
Population estimates (working age)
National Insurance Number Registrations of overseas nationals
Employment projections
Number employed by ethnic groups (working age)
Employment rates by ethnic groups (working age)
Number employed by age groups
Employment rates by age groups
Number employed by disability (working age)
Employment rates by disability (working age)
Employment: Part time/ Full time
Inactivity by reason (working age)
Inactivity rates by reason (working age)
JSA claimants by ethnic groups
Incapacity Benefit claimants by duration
Working age benefit claimants by statistical group
Aged 18-24, claiming JSA for over 6 months
Aged 18-24, claiming JSA for over 9 months
Aged over 25, claiming JSA for over 1 year
JSA claimant flows
JSA claimant flows: index

Skills and learning
Total achieving 5+ A*-C grades inc. English & Mathematics by characteristics
Percentage achieving 5+ A*-C grades inc. English & Mathematics by characteristics
GCE A level examination results of 16-18 year olds
Working age population by qualification level and sex
Working age rates by qualification level and sex
Qualification levels of those in employment (working age)
Number with no adult learning (working age)
Proportion with no adult learning (working age)
Received job related training in last 13 wks (working age)
Apprenticeship Programme starts and achievements - summary
Apprenticeship Programme starts and achievements - index
Apprenticeship Programme starts by level and age
Apprenticeship Programme achievements by level and age
Number of 19 year olds qualified to Level 3
Proportion of 19 year olds qualified to Level 3

Worklessness and NEETS
Worklessness by sex and age (working age)
Worklessness rates by sex and age (working age)
Worklessness numbers and rates by qualification levels (working age)

Within the borough spreadsheet, statistics are shown for boroughs, inner London, outer London, Thames Gateway London, Olympic Host Boroughs, West London, and West London Alliance.

Further Labour Market Indicator tools are available from the CESI website.

https://londondatastore-upload.s3.amazonaws.com/images/esf-logo-web.jpg" alt="" title="ESF logo"> https://londondatastore-upload.s3.amazonaws.com/images/london-enterprise-panel-logo.jpg" alt="" title="LEP logo">

Forecast: Self-Employed People in IT services Sector in Poland 2022 - 2026 Discover more data with ReportLinker!

Global Self-Employed People in Media Sector by Country, 2023 Discover more data with ReportLinker!

Global Self-Employed People in Human Health Activities Sector by Country, 2023 Discover more data with ReportLinker!

Forecast: Self-Employed People in IT services Sector in Germany 2022 - 2026 Discover more data with ReportLinker!