The labour market statistics information release combines data from three surveys to present a broad picture of the labour market.

From the Household Labour Force Survey (HLFS) we provide a picture of New Zealand's labour force – these statistics relate to employment, unemployment, and people not in the labour force.

The Quarterly Employment Survey (QES) estimates the demand for labour by New Zealand businesses – the levels and changes in employment, total weekly gross earnings, total weekly paid hours, average hourly and average weekly earnings, and average weekly paid hours in the industries we survey.

The Labour Cost Index (LCI) measures changes in salary and wage rates for a fixed quantity and quality of labour input. It is a measure of wage inflation, reflecting changes in the rates that employers pay to have the same job done to the same standard.

In 2024, nearly 53 percent of employees in Thailand were in informal employment. Informal employment in the country is mainly in the agricultural industry.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

The metadata set does not comprise any description or summary. The information has not been provided.

The latest National Statistics on forestry produced by the Forestry Commission were released on 24 September 2015 according to the arrangements approved by the UK Statistics Authority.

Detailed statistics are published in the web publication Forestry Statistics 2015, with an extract in Forestry Facts & Figures 2015. They include UK statistics on woodland area, planting, timber, trade, climate change, environment, recreation, employment and finance & prices as well as some statistics on international forestry. Where possible, figures are also provided for England, Wales, Scotland and Northern Ireland.

This dataset covers statistics on employment in forestry and wood processing, health and safety and businesses.

Labour Force Survey 2015, 2nd quarter. As of the 1st quarter of 1972, SSB has conducted official quarterly labour force surveys (AKU). These surveys aim to give the labour force authorities (and other people interested) knowledge of the occupational structure of the population and how it develops over time. The surveys are meant to give a foundation and statistical material for occupational prognoses and labour research. The samples in AKU are from 1992 representative at county level. In the period 1972-1991 they were representative on county pair level. As from January 2006 some major changes were introduced to AKU in order to enhance its comparability to similar surveys in other countries. The changes consist of minor definitional adjustments of unemployment, some adjustments and enlargement of the questionnaire and a change in age definition (age at reference point instead of at the end of the year). Simultaneously the lower age limit to be included in AKU was lowered from 16 to 15 years. This led to some breaks in the time series in the aforementioned areas. As of the 1st quarter of 2009 the new classification of economic activities: SN2007/ISIC rev 5 replaces SN2002/ISIC Rev 4. As of the 1st quarter of 2011 the new classification of occupants STYRK-08/ISCO-08 replaces STYRK/ISCO-88. From 2011 the new standard classification of occupations STYRK-08 replaces the previously used STYRK. From 1st quarter of 2011 professions are coded for both old and new occupational standards. On the basis of this double coding transition keys between old and new standards is calculated. The occupational figures for 2011, will because of this, not be comparable with previous years. -------------------------------------------- Originally, AKU respondents were interviewed in two consecutive quarters of a year, followed by a pause of two quarters, and then another two quarters of interviews. The sample was approximately 10-11.000 respondents in each quarter up until 1988. Originally, AKU was intended to be an analytical supplement to the monthly occupational statistics that was based on the social security membership index file. However, the social security-based statistics disappeared when the sickness benefit was included in the National Insurance as of 1st of January 1971, and AKU has after gradually developed into the most significant source of knowledge of the state of the labour market and its development. In 1975, Statistics Norway changed the sampling frame of survey research, see article 37: "Om bruk av stikkprøver ved kontoret for intervjuundersøkelser", SSB (About the Use of Random Samples at the Office for Survey Research, Statistics Norway) by Steinar Tamsfoss, and SØS 33: "Prinsipper og metoder for Statistisk sentralbyrås utvalgsundersøkelse (Principles and Methods for Statistics Norway's sample research) by Ib Thomsen. Simultaneously, the method for estimation of inflation to national numbers was changed, so that reasonable numbers for regions do exist from 1975 and onwards. The change in 1975 led to a different way of interviewing in groups. This caused amongst other things a break with the AKU panel systematics. In the AKU survey of 1976, a slightly changed questionnaire was introduced. Also, there was a return to the original 6-quarter rotation scheme. The new questionnaire implied a better identification of family workers and persons that are temporarily without paid work. Thus, 30-35 000 more people were defined as employed. The group of "job-seekers without income" were also extended to include persons that were on an involuntary leave of absence. The questions concerning underemployment and "over employment" in the original questionnaire were abandoned. From the 1st quarter of 1987, the estimation method (inflation to national numbers) was slightly changed. There was also a minor adjustment in the definition of employment. In order to ensure that the numbers were to be comparable to earlier surveys, new versions of the 1980-1986 AKU-files were drawn up. Consequently two versions of the 1980-1987 files - respectively with the old and new methods of estimation - exist. The "old" means that the data are comparable to the original numbers published in the period of 1972 - 1987, whilst the "new" implies that the data are comparable to numbers published after 1987. ------------------------------------------------------------- Between the 1st and 2nd quarter of 1988, the AKU file description was changed. The variable "Labour-market status" was given a different coding. In addition, adjustments in the data collections were made - from interviewing a specific week every quarter to carry out continuous weekly interviews. In addition, an escalation scheme to increase the sample size was started. This affected the weights, and from the 2nd quarter of 1988, these were recalculated monthly. To balance out the quarterly or yearly files to total national numbers, the monthly weights therefore had to be divided in three or twelve to give the correct total number. In 1996, AKU was significantly revised: The questionnaire, the file description and the standard for coding of industry and occupation. The data collection also changed to CATI - Computer Assisted Telephone Interviewing. A new classification of industry was put into use (NOS C 182, based on the EU standard NACE, Rev.1). This standard was updated in 2002 and 2007. Also, the new Norwegian standard classification of occupations (STYRK) based on ISCO 88 was used from 1996 and onwards. The variable indicating socio-economic status was omitted, as a similar variable was not developed in the new occupational classification.

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Employment and unemployment data by city for places in San Mateo County. CDP is "Census Designated Place" - a recognized community that was unincorporated at the time of the 2000 Census.

1) Data may not add due to rounding. All unemployment rates shown are calculated on unrounded data. 2) These data are not seasonally adjusted.

Methodology: Monthly city and CDP labor force data are derived by multiplying current estimates of county employment and unemployment by the employment and unemployment shares (ratios) of each city and CDP at the time of the 2000 Census. Ratios for cities of 25,000 or more persons were developed from special tabulations based on household population only from the Bureau of Labor Statistics. For smaller cities and CDP, ratios were calculated from published census data.

City and CDP unrounded employment and unemployment are summed to get the labor force. The unemployment rate is calculated by dividing unemployment by the labor force. Then the labor force, employment, and unemployment are rounded.

This method assumes that the rates of change in employment and unemployment, since 2000, are exactly the same in each city and CDP as at the county level (i.e., that the shares are still accurate). If this assumption is not true for a specific city or CDP, then the estimates for that area may not represent the current economic conditions. Since this assumption is untested, caution should be employed when using these data.

Abstract

Bangladesh Bureau of Statistics (BBS), the National Statistical Organization of the country, has been conducting Labour Force Survey (LFS) since 1980 and repeated it every three/four year until 2013. The surveys could not be held at uniform time intervals due to resource constraint and other reasons. Finally, from July 2015, BBS has undertaken a development project and started implementation of quarterly labour force survey to provide labour market indicators. Gender disaggregated data on labour force, employment, unemployment, underemployment, not in labour force, hours worked, earnings, informal employment. Non-economic activities, volunteer activities are available in this report. The survey found that around half (51.2 per cent) of the 30.5 million employed persons worked more than 48 hours per week. By sex, the proportion of male workers working more than 48 hours (60.9 per cent) was higher than that of female workers (28.4 per cent). By industry, the highest rates of persons in excessive hours were in the Accommodation and food service activities (78.4 per cent), wholesale and retail trade sector (72.9 per cent), manufacturing (69.3 per cent), and households (61.5 per cent).

The primary objective of the survey was to collect comprehensive data on the Labour Force, employment and unemployment of the population aged 15 or older for use by the Government, international organizations, NGOs, researchers and others to efficiently provide targeted interventions. Specific objectives of the survey:

• Provide relevant information regarding the characteristics of the population and household that relate to housing, household size, female-headed households;

• Provide detailed information on education and training, such as literacy, educational attainment and vocational training;

• Provide relevant information on economic activities and the labour force regarding the working-age population, economic activity status and Labour Force participation;

• Provide detailed information on employment and informal employment by occupation and industry, education level and status in employment;

• Provide relevant information on unemployment, the youth labour force participation, youth employment, and youth unemployment;

• Provide other information on decent work regarding earnings from employment, working hours and time-related underemployment, quality and stability of employment, social security coverage, and safety at work, equal opportunities;

• Provide relevant information on non-economic activities, volunteer activities etc.

Geographic coverage

National coverage.

Analysis unit

• Individuals

• Household

Universe

Age is a strong determinant of labour market so a common age cut-off and categories are important. The labour related questions of the survey refer to the population of 15 years old and over. The following age ranges is used in presenting the statistics: 15–24; 25–34; 35–44; 45–54; 55–64; and 65 and over. Besides, LMI is provided separately for youths as the youths are more prone to unstable transition to labour market. However, in setting the minimum LFS coverage age is the fact that the Government of Bangladesh, being aware that many young people, who are unable to continue with higher schooling, enter the labour market instead, has set the legal age for admission to employment at 14 completed years. Given that, inclusion of persons aged 15 years and over may result in the undercount of persons employed or unemployed in the country.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used for the selection of sample for the survey was based on the Population and Housing Census 2011. Sampling Frame which was made up of preparing of PSUs that is consists of collapsing one or more Enumeration Area (EAs) that was created for the Population and Housing Census 2011. EAs is geographical contiguous areas of land with identifiable boundaries. On average, each PSUs has 225 households. All the Enumeration areas of the country was identified into three segments viz. Strong, Semi-strong and not-strong based on the housing materials. The frame has 1284 PSUs/EAs spread all over the country, and covers all socio-economic classes and hence able to get a suitable and representative sample of the population. The survey was distributed into twenty-one domains viz. Rural, Urban and City corporations of seven administrative divisions.

From each selected PSUs/EAs, an equal number of 24 households were selected systematically, with a random start. The systematic sampling method was adopted as it enables the distribution of the sample across the cluster evenly and yields good estimates for the population parameters. Selection of the households was done at the HQ and assigned to the Enumerators, with strictly no allowance for replacement of non-responding households. The Bangladesh Quarterly Labor Force Survey (QLFS) sample will be selected in two stages, with small area units called Primary Sampling Units (PSUs) in the first stage and a cluster of 24 households per PSU in the second stage. Both stages are random selections. The survey will implement a rotational panel strategy, in which some of the households in each cluster will be replaced by new households each quarter. The survey launched in July 2015, with a total sample size of about 30,800 households (1,284 PSUs) in each quarter and 123634 in the year 2015-16, intended to deliver reliable quarterly estimates of unemployment and other relevant labor force indicators for of the country's seven divisions and locality viz. national level estimates with disaggregation by City Corporations, Rural and Urban.

The survey involved a sample of 30816 households from 1284 PSUs/sample enumeration areas distributed across all the 64 Districts for each quarter and the ultimate sample households for the year 2015-16 was 126000 in total. The survey covered both urban and rural areas and dwelling households, including one person households. The institutional households, that is, those living in hostels, hotels, hospitals, old homes, military and police barracks, prisons, welfare homes and other institutions were excluded from the coverage of the survey.

Sampling deviation

Most BBS household surveys use a two-stage sampling strategy similar to that of the QLFS, and most of them share a common set of PSUs – the Integrated Multi-Purpose Sample (IMPS) – as a basis for their first sampling stage. However, the QLFS, given the specificities of its rotational strategy, has opted for choosing an independent set of PSUs for this purpose. The first stage sample frame of the QLFS was developed on the basis of the list of Enumeration Areas (EAs) generated by the 2011 Census. Some of the original 293,093 EAs were deemed too small to support the adopted rotational panel strategy, and were joined to neighboring EAs in order to create 146,576 PSUs of more adequate size: most of the resulting PSUs have between 150 and 300 households, with an average of 217. Whenever possible, the EAs with less than 150 households were appended to EAs from the same village, although in the most sparsely populated areas it was sometimes necessary to append entire villages to neighboring villages within the same mauza or mahalla (the lower level administrative division of the country.)2 Entire mauzas or mahallas were never appended to neighboring areas, even if they were too small – they remained as individual PSUs in the sample frame. The second stage sample frame will be a full listing of all households in the selected PSUs. The listings were completed between February and March 2015. If the survey indeed becomes a regular exercise, they should be permanently updated so that they are never older than two years.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Quarterly Labour Force Survey 2015-16 questionnaire comprised 14 sections, as follows:

• Section 1. Household basic information

• Section 2. Household roster (members’ basic information)

• Section 3. General education (for persons aged 5 years or older) & vocational training (for persons aged 15 years or older)

• Section 4. Working status (for persons aged 15 years or older)

• Section 5. Main activities (for persons aged 15 years or older)

• Section 6. Secondary activities (for employed persons aged 15 years or older)

• Section 7. Occupational safety and health within the previous 12 months (for persons aged 15 years or older)

• Section 8. Underemployment (for employed persons aged 15 years or older)

• Section 9. Unemployment (for not employed persons aged 15 years or older)

• Section 10. Own use production of goods (for persons aged 15 years or older)

• Section 11. Own use provision of services (for persons aged 15 years or older)

• Section 12. Unpaid trainee/apprentice work (for persons aged 15 years or older)

• Section 13. Volunteer work (for persons aged 15 years or older)

• Section 14. Migration (for persons aged 15 years or older)

Cleaning operations

With regard to editing and processing errors, several consistency checks were done, both manually and computerized programme using CSPro; batch editing was done using Stata, to ensure the quality and acceptability of the data produced. The Non-sampling error is to ensure high quality data, several steps were taken to minimize non-sampling errors. Unlike sampling errors, these errors cannot be measured and can only be overcome through several administrative procedures. These errors can arise as a result of incomplete survey coverage, frame defect, response error, non-response and

The statistic above presents employment data from the U.S. information industry in 2015, by state. In 2015, over 123.4 thousand people were employed in the information industry in Illinois.

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 2015 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 22,896 households with a total number of 91,584 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 18 households.

• Sampling stages:

  (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 1,272 EAs (588 in urban areas and 684 in rural areas).

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 level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A

Abstract

The Labour Force Survey represents research conducted to gather data on the basic characteristics of the working-age population, based on which the total labour force in the country is reviewed, together with data on demographics, education, socio-economic standing and other characteristics of the population. The main goal of the research is to gather data on the three main, mutually exclusive segments of population: the employed, the unemployed and the inactive. The data are also to be used to monitor, measure, and estimate the economic and social changes in Bosnia and Herzegovina.

Data source for Bosnia and Herzegovina and District of Brcko is Agency for Statistics of Bosnia and Herzegovina. Data sources for entity level are Republika Srpska Institute of Statistics and Federal Institute of Statistics.

Geographic coverage

National

Analysis unit

Persons of 15 years of age or older

Kind of data

Sample survey data [ssd]

Sampling procedure

UNDP supported formulation and implementation of the Sample Frame Update project, for which funding was provided by the Government of the UK through its Department for International Development (DFID), 10501 households from Bosnia and Herzegovina were selected from the Expanded Master Sample, namely: 5935 for the Federation of Bosnia and Herzegovina, 3564 for the Republic of Srpska and 1002 for Brcko District.

The sample was designed as a stratified two-stage random sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The sections included in the questionnaire are: A. Labour activity during the reference week B. Employment characteristics of the main job C. Second - additional job D. Previous work experience E. Search for employment F. Methods used during the last four weeks to find job G. Education H. Situation one year before survey I. Income J. Ad Hoc module of labour force survey 2011 enployment of people disabilities

Abstract

Department of Census and Statistics (DCS) designed a Labour Force Survey(LFS) on a quarterly basis to measure the levels and trends of employment, unemployment and labour force in Sri Lanka on a continuous basis. This survey commenced from the first quarter 1990 with USAID technical assistance and is being continued by the DCS. Mainly, following information can be obtained by the survey. 1.The economically active / inactive from population. 2.Employment by major industry group and employment status. 3.Unemployment rates by level of education and by age group 4.The informal sector employment. 5.The underemployment rates by sector and by major industries 6.Total Jobs in Sri Lanka with Secondary Employment 7.Literacy 8.Computer Literacy

Geographic coverage

National Coverage

Analysis unit

Individuals from the population aged 15 years or more

Universe

Working age population (15 years and above) living in the non-institutional households in Sri Lanka.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling plan and the sampling frame Two stage stratified sampling procedure is adopted to select a sample of 25,000 housing units to be enumerated at the survey. The sampling frame prepared in 2011 for Census of Population and Housing 2012 is used as the sampling frame for the sample selection of LFS in 2015.

Sample size At the beginning in 1990, the sample size was 2,000 housing units per quarter in areas other than North and East, and the sample size was increased to 4,000 housing units per quarter in 1996 and continued thereafter. In 1992 and 1997, an annual sample of 20,000 housing units was selected to give reliable estimates by district level. In 2004 again 20,000 housing units were selected for the survey. However, in order to provide district level estimates precisely, it was decided to use 20,000 -25,000 housing units as the annual sample from 2006 to 2010. From 2011 onward annual sample of 25,000 housing units were selected.

Sample Allocation In 2015, 2500 Primary sampling Units (PSUs) are allocated to each district and to each sector (Urban,Rural and Estate) by using the Neymann allocation method which considers the variance of unemployment rate as usually. The allocated sample for each district then equally distributedfor 12 months. The survey was conducted from January till December in 2015.

Selection of Primary Sampling Units (PSU) Primary sampling units are the census blocks prepared at the Census of Population and Housing -2012.

Selection of Secondary Sampling Units (SSU) Secondary Sampling Units are the housing units in the selected 2500 primary sampling units (census blocks). From each selected primary sampling unit, 10 housing units (SSU) are selected for the survey using systematic random sampling method.

Mode of data collection

Face-to-face [f2f]

Research instrument

Survey Schedule Current survey concepts and methods are very similar to those introduced at the beginning.However, some changes have been made over the years to improve the accuracy and usefulness of the data.In 2006, some significant improvements were madeto LFS schedule to fulfill the requirements of data users and also to provide additional information for planning purposes. The revision focused on literacy, household economic activities, informal sector employment and underemployment etc. and that had been using from first quarter 2006, till 4th quarter 2012. In 2013, new questions were included to the surveyschedule. These were to improve statistics onemployment, employment on informal sector, secondary occupation, training received and on computer literacy. The questionnaire is attached as an external resource.

Sampling error estimates

The estimation procedure is given in the section 2.6 in the Annual Report.The Annual Report is attched in the External Resources Section.

Data appraisal

The adjustments for non-response is given in the section 2.7 in the Annual Report.The Annual Report is attched in the External Resources Section.

United States Employment: NF: PW: Mfg: Communications Equip data was reported at 43.400 Person th in May 2018. This records a decrease from the previous number of 43.500 Person th for Apr 2018. United States Employment: NF: PW: Mfg: Communications Equip data is updated monthly, averaging 71.400 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 116.700 Person th in Dec 1997 and a record low of 38.500 Person th in Jan 2015. United States Employment: NF: PW: Mfg: Communications Equip data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G030: Current Employment Statistics Survey: Employment: Production Worker: Non Farm.

Finland's employment rate has shown a steady upward trend over the past decade, reaching 72.1 percent in 2024. The employment rate increased steadily from around 68 percent in 2015 to 73.6 percent in 2023. Unemployment trends and gender disparities While employment rates have generally improved, unemployment remains a concern. In 2023, Finland reported 204,000 unemployed individuals, an increase of 14,000 from the previous year. The unemployment rate in Finland stood at 7.2 percent in 2023, down from its peak of 9.6 percent in 2015. Notably, a gender gap persists in unemployment, with men experiencing a 1.4 percent higher unemployment rate (7.9 percent) compared to women (6.5 percent) in 2023. Gender equality in the workforce In 2023, Finland demonstrated a unique aspect of its labor market, with women slightly outpacing men in employment rates. Women's employment rate stood at 74.1 percent, compared to 73.1 percent for men. This narrow gap highlights Finland's progress in workplace gender equality, with the country's female employment rate consistently surpassing the EU average. The employment rates across different age groups varied, with the highest rates observed among 45- to 54-year-olds and 35- to 44-year-olds.

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms by Sector, Gender, Ethnicity, Race, Veteran Status, and Employment Size of Firm for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms by Sector, Gender, Ethnicity, Race, Veteran Status, and Employment Size of Firm for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. . The data are shown for:. . All firms classifiable by gender, ethnicity, race, and veteran status. . Gender. . Female-owned. Male-owned. Equally male-/female-owned. . . Ethnicity. . Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . . Race. . White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. . . Veteran Status. . Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. . . . . Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. Employment size of firm during the March 12 pay period for firms with paid employees at any time during 2015. . All firms. Firms with no employees. Firms with 1 to 4 employees. Firms with 5 to 9 employees. Firms with 10 to 19 employees. Firms with 20 to 49 employees. Firms with 50 to 99 employees. Firms with 100 to 249 employees. Firms with 250 to 499 employees. Firms with 500 employees or more. . . . ..Sort Order. . Data are presented in ascending levels by:. . Geography (GEO_ID). NAICS code (NAICS2012). Gender (SEX). Ethnicity (ETH_GROUP). Race (RACE_GROUP). Veteran Status (VET_GROUP). Employment size of firm (EMPSZFI). . The data are sorted on underlying control field values, so control fields may not appear in alphabetical order.. ..FTP Download. . Download the entire SE1500CSA04 table at: https://www2.census.gov/programs-surveys/ase/data/2015/SE1500CSA04.zip. ..Contact Information. . To contact the Annual Survey of Entrepreneurs staff:. . Visit the website at http://www.census.gov/programs-surveys/ase.html.. Em...

This dataset tracks annual hispanic student percentage from 2015 to 2023 for Richmond Career Education And Employment Charter School vs. Virginia and Richmond City School District

This statistic shows a timeline of the employment rate among the population aged 5 to 17 in Mexico in 2015 and 2017. Employment rate among minors in Mexico (age 5-17) was at 11 percent in 2017, down from 12.4 percent in 2015. To find out more about the employment rate among minors by gender in Mexico in 2015 and 2017, please click here.