The revenue is forecast to experience significant growth in all segments in 2029. The trend observed from 2024 to 2029 remains consistent throughout the entire forecast period. There is a continuous increase in the indicator across all segments. Notably, the Other IT Outsourcing segment achieves the highest value of 1.1 billion U.S. dollars at 2029. Find other insights concerning similar markets and segments, such as a comparison of revenue in Finland and a comparison of revenue in Portugal. The Statista Market Insights cover a broad range of additional markets.

Employment Rate in the United States decreased to 59.90 percent in February from 60.10 percent in January of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job’s issues –occupation, the sector of economic activity, hours worked, contracts’ type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of the population. Starting from the first quarter of 2021, the indications of European Regulation 1700/2019 have been transposed, which concern in particular the changes in the definitions of family and employee, and a new questionnaire has been adopted (see notes). The questionnaire is divided into several sections. In particular, in addition to the first socio-demographic information, the first section covers the employment status during the interview’s week, dealing with questions about the type of work, hours worked, reasons for not working. The second section – reserved for employed people – covers the main job, investigating, in particular, the position in the profession, the industry in which he works, the company he works for, the type of contract, working full-time or part-time and reasons for his selection, working hours, overtime hours, shift work, night and weekend work, job transfer, salary, job satisfaction. The third section – always reserved for employed people – concerns the secondary work (if any). It’s exclusively addressed to respondents who carry out another activity compared to the main one and only detects certain information such as the type of activity, type of contract, occupation, the economic sector he works in, hours worked. The fourth section – for unemployed people – collects information about previous work experiences: last work, type of contract, occupation, economic sector, the reasons for the interruption of work. The fifth section deals with the job search. It investigates the reason for seeking a job, the actions put in place to look for it, the channels used to look for and the type of work sought. The sixth section deals with self-perceived employment conditions, and retirement. The seventh section concerns employment services and employment agencies, and investigates their use by the respondents: quantity of contacts, reason for contact, services required. The eighth section concerns education and training: degree obtained, course of study currently attended, professional training. The last section focuses on the self-perception of the employment status, compared to the previous year. 124,614 individuals, 54,668 families. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job’s issues –occupation, the sector of economic activity, hours worked, contracts’ type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of the population. Starting from the first quarter of 2021, the indications of European Regulation 1700/2019 have been transposed, which concern in particular the changes in the definitions of family and employee, and a new questionnaire has been adopted (see notes). The questionnaire is divided into several sections. In particular, in addition to the first socio-demographic information, the first section covers the employment status during the interview’s week, dealing with questions about the type of work, hours worked, reasons for not working. The second section – reserved for employed people – covers the main job, investigating, in particular, the position in the profession, the industry in which he works, the company he works for, the type of contract, working full-time or part-time and reasons for his selection, working hours, overtime hours, shift work, night and weekend work, job transfer, salary, job satisfaction. The third section – always reserved for employed people – concerns the secondary work (if any). It’s exclusively addressed to respondents who carry out another activity compared to the main one and only detects certain information such as the type of activity, type of contract, occupation, the economic sector he works in, hours worked. The fourth section – for unemployed people – collects information about previous work experiences: last work, type of contract, occupation, economic sector, the reasons for the interruption of work. The fifth section deals with the job search. It investigates the reason for seeking a job, the actions put in place to look for it, the channels used to look for and the type of work sought. The sixth section deals with self-perceived employment conditions, and retirement. The seventh section concerns employment services and employment agencies, and investigates their use by the respondents: quantity of contacts, reason for contact, services required. The eighth section concerns education and training: degree obtained, course of study currently attended, professional training. The last section focuses on the self-perception of the employment status, compared to the previous year. 127,919 individuals, 59,475 families. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job's issues - occupation, sector of economic activity, hours worked, contracts' type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of population. About 70.000 families, 150.000 individuals. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job’s issues – occupation, the sector of economic activity, hours worked, contracts’ type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of the population. The questionnaire is divided into several sections. In particular, in addition to the first socio-demographic information, the first section covers the employment status during the interview’s week, dealing with questions about the type of work, hours worked, motivations about the unemployment status, the type of contract. The second section – reserved for employed people – covers the main job, investigating, in particular, the position in the profession, the industry in which he works, the company he works for, working full-time or part-time and reasons for his selection, working hours, overtime hours, shift work, job transfer, salary, job satisfaction. The third section – always reserved for employed people – concerns the secondary work (if any). It’s exclusively addressed to respondents who carry out another activity compared to the main one and only detects certain information such as the type of activity, type of contract, occupation, the economic sector he works in. The fourth section – for unemployed people – collects information about previous work experiences: last work, type of contract, occupation, economic sector, the reasons why it stopped working. The fifth section deals with the job search. It investigates the reason for seeking a job, the actions put in place to look for it, the channels used to look for and the type of work sought. The sixth section deals with employment and temp agencies and investigates their use by the respondents: the number of contacts, the reason for contact, services required. The seventh section covers education and vocational education. It deals with the training courses respondents are attending. The last section focuses on the auto-perception of their employment status, compared to the previous year. 93,406 individuals, 42,497households. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. LFS revisions: LFS estimates were previously based on the 2001 Census population estimates. These data have been adjusted to reflect 2006 Census population estimates and were revised back to 1996. The census metropolitan area (CMA) variable has been expanded from the three largest CMAs in Canada to nine. Two occupation variables based on the 2016 National Occupation Classicifcation have been reintroduced: a generic 10- category variable (NOC_10) and a detailed 40-category variable (NOC_40). A new variable on immigrant status (IMMIG) has been introduced, which distingushes between recent immigrants and established immigrants. Fourteen variables related to family and spouse/partner's

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job’s issues –occupation, the sector of economic activity, hours worked, contracts’ type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of the population. Starting from the first quarter of 2021, the indications of European Regulation 1700/2019 have been transposed, which concern in particular the changes in the definitions of family and employee, and a new questionnaire has been adopted (see notes). The questionnaire is divided into several sections. In particular, in addition to the first socio-demographic information, the first section covers the employment status during the interview’s week, dealing with questions about the type of work, hours worked, reasons for not working. The second section – reserved for employed people – covers the main job, investigating, in particular, the position in the profession, the industry in which he works, the company he works for, the type of contract, working full-time or part-time and reasons for his selection, working hours, overtime hours, shift work, night and weekend work, job transfer, salary, job satisfaction. The third section – always reserved for employed people – concerns the secondary work (if any). It’s exclusively addressed to respondents who carry out another activity compared to the main one and only detects certain information such as the type of activity, type of contract, occupation, the economic sector he works in, hours worked. The fourth section – for unemployed people – collects information about previous work experiences: last work, type of contract, occupation, economic sector, the reasons for the interruption of work. The fifth section deals with the job search. It investigates the reason for seeking a job, the actions put in place to look for it, the channels used to look for and the type of work sought. The sixth section deals with self-perceived employment conditions, and retirement. The seventh section concerns employment services and employment agencies, and investigates their use by the respondents: quantity of contacts, reason for contact, services required. The eighth section concerns education and training: degree obtained, course of study currently attended, professional training. The last section focuses on the self-perception of the employment status, compared to the previous year.

The Italian Labour Force Survey is the main source of statistical information on the Italian labor market. The information gathered from the population constitutes the basis on which official estimations of employment and unemployment are calculated, as well as information on the main job's issues - occupation, sector of economic activity, hours worked, contracts' type and duration, training. The survey data are used to analyze a number of individual, family and social factors too, such as the increasing labor mobility, changing professions, the growth in female participation, etc.., which determine the difference in labor participation of population. The questionnaire is divided into several sections. In particular, in addition to the first socio-demographic information, the first section covers the employment status during the interview's week, dealing with questions about the type of work, hours worked, motivations about the unemployment status, the type of contract. The second section - reserved for employed people - covers the main job, investigating in particular the position in the profession, the industry in which he works, the company he works for, working full-time or part-time and reasons for his selection, working hours, overtime hours, shift work, job transfer, salary, job satisfaction. The third section - always reserved for employed people - concerns the secondary work (if any). It's exclusively addressed to respondents who carry out another activity compared to the main one and only detects certain information such as: type of activity, type of contract, occupation, economic sector he works in. The fourth section - for unemployed people - collects information about previous work experiences: last work, type of contract, occupation, economic sector, the reasons why it stopped working. The fifth section deals with the job search. It investigates the reason for seeking a job, the actions put in place to look for it, the channels used to look for and the type of work sought. The sixth section deals with employment and temp agencies and investigates their use by the respondents: number of contacts, reason for contact, services required. The seventh section covers education and vocational education. It deals with the training courses respondents are attending. The last section focuses on the auto-perception of their employment status, compared to the previous year. 43,478 families, 96,123 individuals. Two-stage stratified random sample Computer-Assisted Telephone Interviewing (CATI) Computer-Assisted Personal Interviewing (CAPI)

According to Cognitive Market Research, The Global Head Hunting Services market size was USD 17.6 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 6.70% from 2023 to 2030. Rise in Demand for Skilled and Specialized Talent Drives the Market

Many of the best-suited candidates for specialized roles are often not actively searching for new job opportunities. Headhunters excel at reaching out to passive candidates who might not be visible on job boards or traditional recruitment channels.

Headhunters often specialize in specific industries or sectors, giving them a deep understanding of the roles, skills, and qualifications required. This expertise enables them to identify candidates who possess the necessary technical skills and the industry-specific knowledge and cultural fit that companies seek.

For instance, in September 2022, Organizations are increasingly experimenting with what they think is a better approach, according to a worldwide Deloitte poll of more than 1,200 experts. People can be liberated from being defined by their jobs by decoupling some of their work from the job—either by atomizing it into projects or tasks or broadening it to focus on problems to be solved, outcomes to be achieved, or value to be created—and instead be viewed as whole individuals with skills & capabilities that can be fluidly deployed to work that matches their interests, as well as evolving business priorities.

(Source:www2.deloitte.com/us/en/insights/topics/talent/organizational-skill-based-hiring.html)

Market Dynamics of Head Hunting Services

Rise of Industry-Specific Knowledge Helps in the Growth of the Market

Head-hunters who specialize in specific industries develop a deep understanding of the roles they are recruiting for. They know the intricacies of job responsibilities, required skill sets, and the qualifications that make a candidate successful in those roles. This knowledge allows them to assess candidates' fit for a position accurately. Different industries have unique cultures, work environments, and values. Industry-specialized headhunters understand these nuances and can evaluate candidates for their technical skills and cultural alignment with the hiring company. It is critical for long-term success to find a candidate that fits smoothly into the company's culture.

According to a Forbes report published in April 2023, rapid technological breakthroughs, shifting market dynamics, and the rising need for specialized skills have all made upskilling an essential component of professional success.

(Source:www.forbes.com/sites/karadennison/2023/04/13/the-importance-of-upskilling-and-continuous-learning-in-2023/?sh=4be1c54e5909)

The Factors Are Limiting the Growth of the Head Hunting Services Market

Budget Allocations and a Lack of Competent Labor Limit Market Growth

One of the primary motivations for companies to rely on internal recruitment teams is cost savings. Internal recruiters are salaried employees, and utilizing their expertise can be more cost-effective than paying external headhunters' fees, often a percentage of the hired candidate's salary. Companies that have invested in building strong internal recruitment teams want to make the most of their investment. These teams have the skills, tools, and networks to source, evaluate, and hire candidates. Using internal resources aligns with their strategic goal of optimizing their HR functions.

Impact of COVID-19 on the Head Hunting Services Market

Many businesses, especially in the early stages of the pandemic, imposed hiring freezes and reduced recruitment efforts due to the economic uncertainty caused by lockdowns and reduced consumer activity. This likely led to a decreased demand for headhunting services. The shift towards remote work and the need for physical distancing prompted a shift in recruitment processes. Virtual interviews and remote hiring became the norm, altering the way headhunters and recruiters engaged with clients and candidates.

The COVID-19 pandemic and global lockdown limitations were affecting industrial activities. Supply chain interruptions, lack of raw materials required in the manufacturing process, labor shortages, pricing volatility that might lead end-product production to inflate, budget overruns, and shipping challenges are among the effects of the lockdown. Introduction of Head H...

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOL) from Dec 2000 to Jan 2025 about job openings, vacancy, nonfarm, and USA.

The City funds a number of full-service WorkSource Centers in the City of Los Angeles that provide a full range of assistance to job seekers and employers under one roof. Job seekers can receive career counseling, job listings, labor market information, training referrals, and other employment-related services. Employers can avail themselves of business services such as recruiting, posting job vacancies, human resources services, and customized training.

The Labour Force Survey provides estimates of employment and unemployment. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, data on wage rates, union status, job permanency and establishment size are also produced.

This table has been discontinued as of April 20, 2017. The reason for this is that a new table was published on 19 April 2017 based on the 2016 regional classification (see section 3). In addition, information has been added within the new table about whether or not you are registered with the UWV Werkbedrijf. The new table contains final figures for 2013 and 2014 and provisional figures for 2015. This table contains information about the regional labor market situation of young people aged 15 to 27 in the Netherlands. It is indicated whether young people work or go to school and whether they receive benefits. For employed young people, a distinction is made between employees and the self-employed. The reporting period is the month of October of the reference year. Whether someone goes to school is determined on the basis of registration in government-funded education on 1 October of the reference year. The municipalities are classified according to the situation on 1 January 2014. Data available from: 2005 The figures relate to the situation in October of the year in question. Status of the figures: The figures for the years 2005 to 2012 in this table are final. The figures for 2013 are provisional. Changes as of April 20, 2017: Table has been discontinued. Compared to the table with the regional breakdown for 2013 (see section 3), the figures for 2011 have been adjusted from provisional to final and the final 2012 figures and provisional 2013 figures have been added. In this table, persons with income from other work are included in the self-employed group. In the previous publication, these persons were included in the group of employees. As a result, the figures for employees in this table are lower than the previously published figures, while the numbers of self-employed are actually higher. In this table, the figures are rounded to hundreds and not to tens. The reason for this is that the figures on the self-employed are not accurate enough to be rounded to tens. For example, it is known to the self-employed whether they have worked as a self-employed person in a certain year. It is assumed that this situation applies for the entire year and that the income is evenly distributed. In addition, part of the data of the self-employed is estimated, because the tax data of these persons will become available later. When will new numbers come out? Table has been discontinued. Figures for more recent years are included in the table Labor market situation for young people (15 to 27 years); region 2016, see section 3.

In 2024, the annual unemployment rate of the United Kingdom is expected to be 4.3 percent, compared with four percent in 2023. Unemployment is forecast to fall to 4.1 percent in 2025, before falling again to four percent in 2026. A common indicator of an economy’s relative health, the unemployment rate has generally been falling in the United Kingdom since its 2011 peak of 8.1 percent. Uptick in unemployment in 2023 In the aftermath of the COVID-19 pandemic, the unemployment rate in the United Kingdom grew steadily, from just 3.9 percent at the start of 2020, to 5.1 percent by the end of the year. This was followed by a steep decline in unemployment that lasted until August 2022, when the unemployment rate was just 3.5 percent. There was a slight uptick in unemployment following this low, with the unemployment rate rising to 4.3 percent the following July. This has been matched by a fall in the number of UK job vacancies, which reached a peak of 1.3 million in May 2022, but has been falling in every subsequent month, with approximately 932,000 vacancies in January 2024. Other UK key economic indicators Although the UK's labor market was quite well protected from the economic fallout of the COVID-19 pandemic, other parts of the economy took a more severe hit. The initial lockdown measures resulted in a huge fall to UK GDP, in April 2020 which took over a year to reach its pre-pandemic size. Economic growth has remained sluggish ever since the initial recovery, with the UK economy alternating between weak growth and slight contractions. The UK even entered a technical recession at the end of 2023, following two quarters of negative growth. Inflation also skyrocketed from late 2021 onwards, reaching a peak of 11.1 percent in October 2022. Even one year after that peak, inflation has proven stubborn to get down, with a rate of 4.6 percent in October 2023.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

In any society, the human element represents the basis of the work force which exercises all the service and production activities. Therefore, it is a mandate to produce labor force statistics and studies, that is related to the growth and distribution of manpower and labor force distribution by different types and characteristics.

In this context, the Central Agency for Public Mobilization and Statistics conducts "Quarterly Labor Force Survey" which includes data on the size of manpower and labor force (employed and unemployed) and their geographical distribution by their characteristics.

By the end of each year, CAPMAS issues the annual aggregated labor force bulletin publication that includes the results of the quarterly survey rounds that represent the manpower and labor force characteristics during the year.

---> Historical Review of the Labor Force Survey:

1- The First Labor Force survey was undertaken in 1957. The first round was conducted in November of that year, the survey continued to be conducted in successive rounds (quarterly, bi-annually, or annually) till now.

2- Starting the October 2006 round, the fieldwork of the labor force survey was developed to focus on the following two points: a. The importance of using the panel sample that is part of the survey sample, to monitor the dynamic changes of the labor market. b. Improving the used questionnaire to include more questions, that help in better defining of relationship to labor force of each household member (employed, unemployed, out of labor force ...etc.). In addition to re-order of some of the already existing questions in much logical way.

3- Starting the January 2008 round, the used methodology was developed to collect more representative sample during the survey year. this is done through distributing the sample of each governorate into five groups, the questionnaires are collected from each of them separately every 15 days for 3 months (in the middle and the end of the month)

4- Starting the January 2012 round, in order to follow the international recommendation, to avoid asking extra questions that affect the precision and accuracy of the collected data, a shortened version of the questionnaire was designed to include the core questions that enable obtaining the basic Egyptian labor market indicators. The shortened version is collected in two rounds (January-March), (April-June), and (October-December) while the long version of the questionnaire is collected in the 3rd round (July-September) that includes more information on housing conditions and immigration.

---> The survey aims at covering the following topics:

1- Measuring the size of the Egyptian labor force among civilians (for all governorates of the republic) by their different characteristics. 2- Measuring the employment rate at national level and different geographical areas. 3- Measuring the distribution of employed people by the following characteristics: Gender, age, educational status, occupation, economic activity, and sector. 4- Measuring unemployment rate at different geographic areas. 5- Measuring the distribution of unemployed people by the following characteristics: Gender, age, educational status, unemployment type “ever employed/never employed”, occupation, economic activity, and sector for people who have ever worked.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

---> Sample Design and Selection

The sample of the LFS 2014 survey is a self-weighted two-stage stratified cluster sample. The main elements of the sampling design are described as follows:

• Sample Size The sample size in each quarter is 23,864 households with a total number of 95,456 households annually. These households are distributed on the governorate level (urban/rural), according to the estimated number of households in each governorate in accordance with the percentage of urban and rural population in each governorate.

• Cluster size The cluster size is 19 households.

• Sampling stages:

  ---> A- First stage sample

  (1) Primary Sampling Unit (PSU): The 2006 Population Census provided sufficient data at the level of the Enumeration Area (EA). Hence, the electronic list of EA's represented the frame of the first stage sample; in which the corresponding number of households per EA was taken as a measure of size. The size of an EA is almost 200 households on average, with some variability expected. The size of first stage national sample was estimated to be 5,024 EA.

  (2) Sample Distribution by Governorate: The primary stratifying variable is the governorate of residence, which in turn is divided into urban and rural sub-strata, whenever applicable.

  (3) First Stage Sample frame: The census lists of EAs for each substratum, associated with the corresponding number of households, constitute the frame of the first stage sample. The identification information appears on the EA's list includes the District code, Shiakha/Village code, Census Supervisor number, and Enumerator number. Prior to the selection of the first stage sample, the frame was arranged to provide implicit stratification with regard to the geographic location. The urban frame of each governorate was ordered in a serpentine fashion according to the geographic location of kism/ district capitals. The same sort of ordering was made on the rural frame, but according to the district location. The systematic selection of EA's sample from such a sorted frame will ensure a balanced spread of the sample over the area of respective governorates. The sample was selected with Probability Proportional to Size (PPS), with the number of census households taken as a Measure of Size (MOS).

  (4) Core Sample allocation The core sample EAs (5,024) were divided among the survey 4 rounds, each round included 1,256 EAs (573 in urban areas and 683 in rural areas).

  ---> B- Second Stage Sample:

This is the final stage sample and was implemented in 2 stages: 1- Selection of the New sample 2- Selection of the panel sample

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire design follows the latest International Labor Organization (ILO) concepts and definitions of labor force, employment, and unemployment.

The questionnaire comprises 4 tables in addition to the identification and geographic data of household on the cover page.

---> Table 1- The housing conditions of the households

This table includes information on the housing conditions of the household: - Type of the dwelling, - Tenure of the dwelling (owned/rent) , - Availability of facilities and services connected to the house - Ownership of durables.

---> Table 2- Demographic and employment characteristics and basic data for all household individuals

Including: gender, age, educational status, marital status, residence mobility and current work status

---> Table 3- Employment characteristics table

This table is filled by employed individuals at the time of the survey or those who were engaged to work during the reference week, and provided information on: - Relationship to employer: employer, self-employed, waged worker, and unpaid family worker - Economic activity - Sector - Occupation - Effective working hours - Health and social insurance - Work place - Contract type - Average monthly wage

---> Table 4- Unemployment characteristics table

This table is filled by all unemployed individuals who satisfied the unemployment criteria, and provided information on: - Type of unemployment (unemployed, unemployed ever worked) - Economic activity and occupation in the last held job before being unemployed - Last unemployment duration in months - Main reason for unemployment

Cleaning operations

---> Raw Data

Office editing is one of the main stages of the survey. It started once the questionnaires were received from the field and accomplished by the selected work groups. It includes: a-Editing of coverage and completeness b-Editing of consistency

---> Harmonized Data

• The SPSS package is used to clean and harmonize the datasets.
• The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency.
• All cleaned data files are then merged to produce one data file on the individual

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. 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 2023 2024 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...

Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. The Labour Force Survey provides estimates of employment and unemployment which are among the most timely and important measures of performance of the Canadian economy. With the release of the survey results only 13 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Human Resources Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.

The Labour Force Survey provides estimates of employment and unemployment which are among the most timely and important measures of performance of the Canadian economy. With the release of the survey results only 13 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Human Resources Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. LFS revisions: LFS estimates were previously based on the 2001 Census population estimates. These data have been adjusted to reflect 2006 Census population estimates and were revised back to 1996.

The Labour Force Survey provides estimates of employment and unemployment. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, data on wage rates, union status, job permanency and establishment size are also produced. (2024-06-17)