Employment by age and sex for UK regions and countries, rolling three-monthly figures published monthly, not seasonally adjusted. Labour Force Survey.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by province, gender and age group. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. 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.

This dataset provides the unemployment rates (in percent) for individuals or youth aged 15-29 years, based on usual status (ps+ss), as estimated from the Periodic Labour Force Survey (PLFS). Sourced from the Ministry of Statistics and Programme Implementation, this data highlights youth unemployment trends over time. The years covered in the survey are from July to June. For instance, 2023-24 refers to the period July 2023 to June 2024 and likewise for other years.

Unemployment numbers and rates for those aged 16 or over. The unemployed population consists of those people out of work, who are actively looking for work and are available to start immediately.

Unemployed numbers and rates also shown for equalities groups, by age, sex, ethnic group, and disability. Economic inactivity rates and numbers for regions.

The data are taken from the Labour Force Survey and Annual Population Survey, produced by the Office for National Statistics.

The data are produced monthly on a rolling quarterly basis. The month shown is the month the quarter ends on.

International Labour Organization define unemployed people as: without a job, want a job, have actively sought work in the last 4 weeks and are available to start work in the next 2 weeks, or, out of work, have found a job and are waiting to start it in the next 2 weeks.

The figures in this dataset are adjusted to compensate for seasonal variations in employment (Seasonally adjusted).

Data by equalities groups has a longer time lag and is only available quarterly from the Annual Population Survey, which is not seasonally adjusted.

Click http://www.ons.gov.uk/ons/rel/subnational-labour/regional-labour-market-statistics/index.html">here for Regional labour market statistics from the Office for National Statistics

Click http://www.ons.gov.uk/ons/rel/lms/labour-market-statistics/index.html">here for Labour market statistics from the Office for National Statistics

Unemployed: Youth: Female data was reported at 146,576.000 Person in 2017. Unemployed: Youth: Female data is updated yearly, averaging 146,576.000 Person from Dec 2017 (Median) to 2017, with 1 observations. Unemployed: Youth: Female data remains active status in CEIC and is reported by Central Statistical Office. The data is categorized under Global Database’s Zambia – Table ZM.G026: Labour Force Survey: Unemployment: Youth: by Sex and Settlement Type.

Youth unemployment stood at 9.7 percent in February 2025. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends. The unemployment rate by state can be found here, and the annual national unemployment rate can be found here. Youth unemployment in the United States The United States Bureau of Labor Statistics track unemployment of persons between the ages of 16 and 24 years each month. In analyzing the data, the Bureau of Labor Statistics performed a seasonal adjustment—removing seasonal influences from the time series, such that one month’s rate of unemployment could be analyzed in comparison with another month’s rate of unemployment. During the period in question, youth unemployment ranged from a high of 9.9 percent in April 2021, to a low of 6.5 percent in April 2023. The national youth unemployment rate can be compared to the monthly national unemployment rate in the United States, although youth unemployment tends to be much higher due to higher rates of participation in education. In May 2023, U.S. unemployment was at 3.7 percent, compared with 7.4 percent amongst those 16 to 24 years old. Additionally, as of May 2023, Nevada had the highest state unemployment rate of all U.S. states, at 5.4 percent.

Abstract

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Geographic coverage

National coverage.

There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.

Analysis unit

• Households (for food insecurity module questionnaire)
• Individuals.

Universe

Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.

Kind of data

Sample survey data [ssd]

Sampling procedure

2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.

1. Computation of the survey parameters: Total sample size per strata, number of households to interview in each Primary Sampling Unit (PSU = census block) and number of PSUs to select The stratification of the survey is the geographical breakdown by island group (6 stratas Tongatapu urban, Tongatapu rural, Vava'u, Ha'apai, 'Eua, Niuas)
2. The selection strategy is a 2 stages random survey where: Random selection of census blocks within each
3. Census blocks are randomly selected in first place, using probability proportional to size

4. 15 households per block are randomly selected using uniform probability

5. The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.

The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.

Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.

Sampling deviation

No major deviation from the original sample has taken place.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2018 Tonga Labour Force Survey questionnaire included 15 sections:

IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO

The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.

The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.

Cleaning operations

The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.

Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.

Response rate

A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.

Response rates were higher in urban areas than in the rural area of Tongatapu.

-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00% -4 Ha'pai: 100.00% -5 Eua: 95.20% -6 Niuas: 80.00% -Total: 96.20%.

Sampling error estimates

Sampling errors were computed and are presented in the final report.

The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error

-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.

-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.

Canada LFS: Youth Unemployment data was reported at 304.300 Person th in Jan 2019. This records an increase from the previous number of 240.400 Person th for Dec 2018. Canada LFS: Youth Unemployment data is updated monthly, averaging 382.800 Person th from Jan 1976 (Median) to Jan 2019, with 517 observations. The data reached an all-time high of 692.000 Person th in Jul 1982 and a record low of 233.600 Person th in Dec 2017. Canada LFS: Youth Unemployment data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.G010: Labour Force Survey Estimates: Unemployment.

Educational status and labour market status of people aged 16 to 24 years, by sex, in and out of full-time education, UK, rolling three-monthly figures published monthly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

China resumed the release of youth unemployment data in January 2024 after publication had been suspended for six months, using a new statistical methodology. Youth unemployment hit a record high of 21.3 percent in June 2023 after having increased for several years in a row, when a spokesman of the National Bureau of Statistics of China announced that the statistical methodology for calculating age specific unemployment rates needed improvement and publication would be temporarily suspended. The new methodology does not include university students anymore, resulting in a youth unemployment rate of **** percent in June 2025. Youth jobless figures fluctuate over the year and normally peak in July in China, when the largest number of graduates enter the job market.

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

As of the first quarter of 2025, the youth unemployment rate in the UK was highest in London at 18.6 percent, compared with the UK average of 14.2 percent. As of this quarter, Northern Ireland had the lowest youth unemployment rate at just 5.1 percent.

From 2000 until 2019, youth unemployment fluctuated between 13 and 15.5 percent, before it rose above 17 percent in 2020 during the Covid-19 pandemic. Youth unemployment Just like the general unemployment rate, youth unemployment is recorded and monitored to gauge the job market situation in a country and worldwide. Youth unemployment includes unemployed individuals aged 15 to 24, typically referring to those who have either just finished school or graduated and are looking for jobs. In order to be registered as unemployed, a person must be able to work, unemployed, and looking for a job. Usually youth unemployment is higher than adult unemployment, as many graduates do not find employment right after they have graduated. Regional breakdown The world region with the highest youth unemployment rate has been the Arab World for the past two decades, while East Asia and the Pacific has generally had the lowest rate. Apart from the sharp rise in 2020, the most notable increase came in 2009 as a result of the Great Recession; while this increase can be observed on a global scale, its impact on youth unemployment was more severely felt in more advanced economies in Europe and North America.

Zambia Unemployed: Youth: Urban data was reported at 210,288.000 Person in 2017. Zambia Unemployed: Youth: Urban data is updated yearly, averaging 210,288.000 Person from Dec 2017 (Median) to 2017, with 1 observations. Zambia Unemployed: Youth: Urban data remains active status in CEIC and is reported by Central Statistical Office. The data is categorized under Global Database’s Zambia – Table ZM.G026: Labour Force Survey: Unemployment: Youth: by Sex and Settlement Type.

The youth unemployment rate is calculated by dividing the number of unemployed persons aged 15 to 24 by the total active population of the same age group. The indicator is based on the EU Labour Force Survey.

The youth unemployment rate is calculated by dividing the number of unemployed persons aged 15 to 24 by the total active population of the same age group. The indicator is based on the EU Labour Force Survey.

The Australian Government Department of Jobs and Small Business publishes a range of labour market data on its Labour Market Information Portal website (lmip.gov.au). The link below provides data from the Labour Force Survey conducted by the Australian Bureau of Statistics. The boundaries used in this survey are known as Statistical Area 4 regions. The data provided includes unemployment rate, employment rate, participation rate, youth unemployment rate, unemployment duration, population by age group and employment by industry and occupation.

Abstract

Bangladesh Bureau of Statistics (BBS) has initiated the labor force survey on a quarterly basis, to measure the levels and trends of employment, unemployment and labor force in the country on a continuous basis. In the past, labor force surveys conducted at four-five yearly time intervals since 1980.

Detailed information on labor force characteristics has been collected from representative sample of 123 thousand households to produce gender disaggregated national and divisional level estimates with urban/rural/city corporation breakdown. The survey also provides quarterly representative results and sample size for each quarter was 30,816 households. The survey, along with the quantification of core variables, also estimates important attributes of literacy, migration, own use production of goods and own use provision of services, volunteer work, occupational safety and health etc. The estimates are profiled according to latest classifications viz Bangladesh Standard Industrial Classification (BSIC 2009 based on ISIC rev-4) and Bangladesh Standard Classification of Occupations (BSCO- 2012 in line with ISCO-2008).

The primary objective of the survey was to collect comprehensive data on the Labor 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 labor force regarding the working-age population, economic activity status and Labor 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 labor 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

• Individual
• Household

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The quarterly Labor Force Survey questionnaire comprised of 14 sections:

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. Time-related 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

Editing and processing errors, several consistency checks were done, both manually and computerized program 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 processing errors such as during editing, coding and data capture.

Sampling error estimates

Sampling error is a result of estimating data based on a probability sampling, not on census. Such error in statistics is termed as relative standard error and often denoted as RSE which is given in percentage. This error is an indication to the precision of the parameter under study. In other words, it reflects the extent of variation with other sample-based estimates. Sampling errors of estimates on a few important variables at national levels are calculated separately as shown in the annex. For example, the labor force participation rate at the national level was 67.0 per cent with an RSE of 0.23 per cent and standard error (SE) of 0.16 per cent. At 95 per cent confidence interval (a = 0.05), the labor force participation rate was in the range of 66.69-67.31 per cent.

Kosovo Youth Unemployment Rate: 15-24 Years data was reported at 26.900 % in Mar 2019. This records a decrease from the previous number of 31.400 % for Dec 2018. Kosovo Youth Unemployment Rate: 15-24 Years data is updated quarterly, averaging 29.400 % from Mar 2016 (Median) to Mar 2019, with 13 observations. The data reached an all-time high of 31.400 % in Dec 2018 and a record low of 26.200 % in Jun 2016. Kosovo Youth Unemployment Rate: 15-24 Years data remains active status in CEIC and is reported by Kosovo Agency of Statistics. The data is categorized under Global Database’s Kosovo – Table KS.G009: Labour Force Survey: Unemployment Rate.

Canada LFS: Youth Unemployment: Male data was reported at 185.900 Person th in Jan 2019. This records an increase from the previous number of 141.600 Person th for Dec 2018. Canada LFS: Youth Unemployment: Male data is updated monthly, averaging 221.200 Person th from Jan 1976 (Median) to Jan 2019, with 517 observations. The data reached an all-time high of 423.300 Person th in Mar 1983 and a record low of 138.400 Person th in Dec 2017. Canada LFS: Youth Unemployment: Male data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.G010: Labour Force Survey Estimates: Unemployment.