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.

Youth Unemployment Rate in South Korea increased to 7 percent in February from 6 percent in January of 2025. This dataset provides - South Korea Youth Unemployment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two-limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial variability in returns to education across schools and evidence of diminishing marginal effects of compulsory attendance on high school completion. The simulation results suggest that increasing the compulsory attendance age raises the probability of completing high school and reduces the proportion of time the individuals are unemployed. These effects are much more pronounced for disadvantaged students but less pronounced for advantaged students, suggesting the potential effects of compulsory attendance on reducing the inequality in education and employment.

In 2023, the estimated youth unemployment rate in India was at 15.67 percent. According to the source, the data are ILO estimates. For the past decade, India’s youth unemployment rate has been hovering around the 22 percent mark. What is the youth unemployment rate?The youth unemployment rate refers to those in the workforce who are aged 15 to 24 years and without a job, but actively seeking one. Generally, youth unemployment rates are higher than the adult unemployment rates, and India is no exception: youth unemployment in India is significantly higher than the national unemployment rate. The Indian workforce, young and oldIndia’s unemployment rate in general is not remarkably high when compared to those of other countries. Both India’s unemployment rate and youth unemployment rate are below their global equivalents. In a comparison of the Asia-Pacific region countries, India ranks somewhere in the middle, with Cambodia’s unemployment rate being estimated to be below one percent, and Afghanistan’s the highest at 8.8 percent.

Unemployment rates of 25- to 29-year-olds, by educational attainment, Canada and jurisdictions. This table is included in Section E: Transitions and outcomes: Labour market outcomes of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Unemployment Rate in South Africa decreased to 31.90 percent in the fourth quarter of 2024 from 32.10 percent in the third quarter of 2024. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2023, the estimated youth unemployment rate in Nigeria was at almost 5.13 percent. According to the source, the data are estimates from the International Labour Organization, an agency of the United Nations developing policies to set labor standards. Employment in Nigeria The youth unemployment rate refers to the percentage of the unemployed in the age group of 15 to 24 years as compared to the total labor force. Youth unemployment rates are often higher than overall unemployment rates, which is true in Nigeria as well: the general rate of unemployment was approximately six percent in 2018. One reason for this contrast is that many of the youth under age 24 are studying full-time and are unavailable for work due to this. Education in Nigeria Nigeria’s population has a large percentage of young inhabitants, and there is a high demand for educational opportunities for its young populace. After severe cuts in governmental aid following a nationwide recession in 2016, Nigeria’s underfunded higher education system became the focus of ongoing student protests and strikes. Other families have taken a different approach: Nigeria is the top country of origin for international students from the continent of Africa. For example, Nigeria sent over 12,600 students to the U.S. in 2017/18, the most of any African country.

This paper analyses the risk of unemployment, unemployment duration, and the risk of longterm unemployment immediately after apprenticeship graduation. Unemployed apprenticeship graduates constitute a large share of unemployed youth in Germany but unemployment incidence within this group is unequally distributed. Our paper extends previous research in three dimensions. It shows that (i) individual productivity assessment of the training firm, (ii) initial selection into high reputation training firms and occupations, and (iii) adverse selection of employer moving graduates are correlated with unemployment after apprenticeship graduation. The empirical evidence is obtained from the second longitudinal version of the linked employer-employee panel data from the IAB (LIAB). This large data set allows us to calculate the exact unemployment spell length of apprenticeship graduates. In addition, we can include individual, employer, occupation as well as industrial relation characteristics before and after apprenticeship graduation into our list of explanatory variables for unemployment risk. We show in several robustness checks that our results are remarkably stable when we vary the employees included in the sample, the definition of unemployment, and the list of explanatory variables.

The IZA Evaluation Dataset Survey (IZA ED) was developed in order to obtain reliable longitudinal estimates for the impact of Active Labor Market Policies (ALMP). Moreover, it is suitable for studying the processes of job search and labor market reintegration. The data allow analyzing dynamics with respect to a rich set of individual and labor market characteristics. It covers the initial period of unemployment as well as long-term outcomes, for a total period of up to 3 years after unemployment entry. A longitudinal questionnaire records monthly labor market activities and their duration in detail for the mentioned period. These activities are, for example, employment, unemployment, ALMP, other training etc. Available information covers employment status, occupation, sector, and related earnings, hours, unemployment benefits or other transfer payments. A cross-sectional questionnaire contains all basic information including the process of entering into unemployment, and demographics. The entry into unemployment describes detailed job search behavior such as search intensity, search channels and the role of the Employment Agency. Moreover, reservation wages and individual expectations about leaving unemployment or participating in ALMP programs are recorded. The available demographic information covers employment status, occupation and sector, as well as specifics about citizenship and ethnic background, educational levels, number and age of children, household structure and income, family background, health status, and workplace as well as place of residence regions. The survey provides as well detailed information about the treatment by the unemployment insurance authorities, imposed labor market policies, benefit receipt and sanctions. The survey focuses additionally on individual characteristics and behavior. Such co-variates of individuals comprise social networks, ethnic and migration background, relations and identity, personality traits, cognitive and non-cognitive skills, life and job satisfaction, risky behavior, attitudes and preferences. The main advantages of the IZA ED are the large sample size of unemployed individuals, the accuracy of employment histories, the innovative and rich set of individual co-variates and the fact that the survey measures important characteristics shortly after entry into unemployment.

Youth Unemployment Rate in Nigeria decreased to 6.50 percent in the second quarter of 2024 from 8.40 percent in the first quarter of 2024. This dataset provides - Nigeria Youth Unemployment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Youth Unemployment Rate in Sweden decreased to 25.20 percent in February from 26.80 percent in January of 2025. This dataset provides the latest reported value for - Sweden Youth Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Unemployment rate, participation rate, and employment rate by educational attainment, gender and age group, annual.

South Africa is expected to register the highest unemployment rate in Africa in 2024, with around 30 percent of the country's labor force being unemployed. Djibouti and Eswatini followed, with unemployment reaching roughly 28 percent and 25 percent, respectively. On the other hand, the lowest unemployment rates in Africa were in Niger and Burundi. The continent’s average stood at roughly seven percent in the same year.

Large shares of youth among the unemployed

Due to several educational, socio-demographic, and economic factors, the young population is more likely to face unemployment in most regions of the world. In 2024, the youth unemployment rate in Africa was projected at around 11 percent. The situation was particularly critical in certain countries. In 2022, Djibouti recorded a youth unemployment rate of almost 80 percent, the highest rate on the continent. South Africa followed, with around 52 percent of the young labor force being unemployed.

Wide disparities in female unemployment

Women are another demographic group often facing high unemployment. In Africa, the female unemployment rate stood at roughly eight percent in 2023, compared to 6.6 percent among men. The average female unemployment on the continent was not particularly high. However, there were significant disparities among African countries. Djibouti and South Africa topped the ranking once again in 2022, with female unemployment rates of around 38 percent and 31 percent, respectively. In contrast, Niger, Burundi, and Chad were far below Africa’s average, as only roughly one percent or lower of the women in the labor force were unemployed.

We analyze the relationship between early-career unemployment and prime-age earnings with German administrative linked employer-employee data. The careers of more than 720,000 male apprenticeship graduates from the cohorts of 1978 to 1980 are followed over 24 years. On average, early-career unemployment has substantial negative effects on earnings accumulated later
in life. An identification strategy based on plant closure of the training firm at the time of graduation suggests that the revealed correlation is not the result of unobserved heterogeneity. Scarring effects also vary considerably across the earnings distribution. Workers with a high earning potential are able to offset adverse consequences of early-career unemployment to a large extent.
Workers who are located at the bottom of the prime-age earnings distribution, in contrast, suffer substantial and persistent losses. Our findings imply that a policy with the aim of preventing early-career unemployment would have long-lasting beneficial effects on future earnings.

Graph and download economic data for Unemployment Rate - 16-24 Yrs. (LNS14024887) from Jan 1948 to Feb 2025 about 16 to 24 years, unemployment, rate, and USA.

Kenya’s unemployment rate was 5.57 percent in 2023. This represents a steady decline from the increase after the financial crisis. What is unemployment? The unemployment rate of a country refers to the share of people who want to work but cannot find jobs. This includes workers who have lost jobs and are searching for new ones, workers whose jobs ended due to an economic downturn, and workers for whom there are no jobs because the labor supply in their industry is larger than the number of jobs available. Different statistics suggest which factors contribute to the overall unemployment rate. The Kenyan context The first type, so-called “search unemployment”, is hardest to see in the data. The closest proxy is Kenya’s inflation rate. As workers take new jobs faster, employers are forced to increase wages, leading to higher employment. Jobs lost due to economic downturns, called “cyclical unemployment”, can be seen by decreases in the GDP growth rate, which are not significant in Kenya. Finally, “structural unemployment” refers to workers changing the industry, or even economic sector, in which they are working. In Kenya, more and more workers switch to the services sector. This is often a result of urbanization, but any structural shift in the economy’s composition can lead to this unemployment.

Abstract

South Asia Regional Flagship: More and Better Jobs in South Asia

Employment is a major issue throughout the world. To enjoy life, people need productive jobs that remove them from the daily struggle of making ends meet. According to the International Labour Organization (ILO), as many as 30 million people lost their jobs as a result of the 2008 crisis. Youth unemployment is especially high and inequality has increased. As recent events in the Middle East and North Africa demonstrate, joblessness and inequality can trigger political instability and unrest.

When the World Bank South Asia Region decided to initiate a yearly Flagship Report series, it was clear that the very first report needed to concentrate on the important topic of More and Better Jobs in South Asia. Although one of the fastest growing regions, South Asia is still home to the largest number of the world's poor and the pace of creating productive jobs has lagged behind economic growth. Conflict and social and gender issues also increase the challenge of generating more and more productive jobs. Without urgent action, the potential for the demographic dividend from about 150 million entrants to the labor force over the next decade may not be realized.

The Flagship seeks to answer four questions, which could have implications beyond South Asia. - How is South Asia performing in creating more and better jobs? - Where are the better jobs? - What are constraints in supply and demand in moving towards better jobs? - How does conflict affect job creation?

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Somalia SO: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data was reported at 33.816 % in 2019. Somalia SO: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data is updated yearly, averaging 33.816 % from Dec 2019 (Median) to 2019, with 1 observations. The data reached an all-time high of 33.816 % in 2019 and a record low of 33.816 % in 2019. Somalia SO: Unemployment: National Estimate: Youth: % of Total Labour Force Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank.WDI: Employment and Unemployment. Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.;International Labour Organization. “Labour Force Statistics database (LFS)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

We analyze the relationship between early-career unemployment and prime-age earnings with German administrative linked employer-employee data. The careers of more than 720,000 male apprenticeship graduates from the cohorts of 1978 to 1980 are followed over 24 years. On average, early-career unemployment has substantial negative effects on earnings accumulated later in life. An identification strategy based on plant closure of the training firm at the time of graduation suggests that the revealed correlation is not the result of unobserved heterogeneity. Scarring effects also vary considerably across the earnings distribution. Workers with a high earning potential are able to offset adverse consequences of early-career unemployment to a large extent. Workers who are located at the bottom of the prime-age earnings distribution, in contrast, suffer substantial and persistent losses. Our findings imply that a policy with the aim of preventing early-career unemployment would have long-lasting beneficial effects on future earnings.

Somalia SO: Unemployment: Modeled ILO Estimate: Youth Male: % of Male Labour Force Aged 15-24 data was reported at 10.732 % in 2017. This records a decrease from the previous number of 10.792 % for 2016. Somalia SO: Unemployment: Modeled ILO Estimate: Youth Male: % of Male Labour Force Aged 15-24 data is updated yearly, averaging 10.873 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 10.875 % in 1994 and a record low of 10.732 % in 2017. Somalia SO: Unemployment: Modeled ILO Estimate: Youth Male: % of Male Labour Force Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank: Employment and Unemployment. Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.