🌍 This dataset provides global youth unemployment rates for individuals aged 15–24 across all available countries and years, giving a comprehensive view of labor market conditions for young people worldwide.

🔍 Youth unemployment measures young people who are actively looking for work but cannot find a job. According to World Bank standards, students who are not participating in the labor force are not included, while students who are actively job-seeking are counted. Only individuals who are available for work and searching for employment are considered unemployed. This makes the dataset a precise reflection of labor market pressure among young job seekers.

📊 This dataset contains 17,290 rows and 4 columns: Country, CountryCode, Year, and YouthUnemployment. It includes data for all available countries and territories and spans the years 1960–2023. Some values are missing for certain countries and years where data is not available.

💹 Youth unemployment is an important indicator of economic health, social development, and workforce stability. Monitoring these rates helps reveal patterns in youth labor markets, including regional disparities, historical trends, and the effects of economic policies. The dataset allows for cross-country comparisons, time-series analysis, and identification of long-term shifts in youth employment opportunities. It is a valuable resource for researchers, policymakers, educators, and analysts seeking to understand the challenges faced by young populations as they transition from education to the workforce.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Mexico MX: Literacy Rate: Youth: % of People Age 15-24 data was reported at 99.116 % in 2016. This records an increase from the previous number of 98.945 % for 2015. Mexico MX: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 98.382 % from Dec 1980 (Median) to 2016, with 17 observations. The data reached an all-time high of 99.116 % in 2016 and a record low of 91.947 % in 1980. Mexico MX: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics (http://uis.unesco.org/); Weighted average;

This datas real-world trends in children's screen time usage. It includes data on educational, recreational, and total screen time for children aged 5 to 15 years, with breakdowns by gender (Male, Female, Other/Prefer not to say) and day type (Weekday, Weekend). The dataset follows expected behavioral patterns:

Screen time increases with age (~1.5 hours/day at age 5 to 6+ hours/day at age 15).

Recreational screen time dominates, making up 65–80% of total screen time.

Weekend screen time is 20–30% higher than weekdays, with a larger increase for teenagers.

Slight gender-based variations in recreational screen time.

The dataset contains natural variability, ensuring realism, and the sample size decreases slightly with age (e.g., 500 respondents at age 5, 300 at age 15).

This dataset is ideal for data analysis, visualization, and machine learning experiments related to children's digital habits. 🚀

Bangladesh BD: Literacy Rate: Youth Male: % of Males Aged 15-24 data was reported at 94.000 % in 2021. This records an increase from the previous number of 93.000 % for 2020. Bangladesh BD: Literacy Rate: Youth Male: % of Males Aged 15-24 data is updated yearly, averaging 85.500 % from Dec 1981 (Median) to 2021, with 16 observations. The data reached an all-time high of 100.000 % in 2000 and a record low of 44.000 % in 1981. Bangladesh BD: Literacy Rate: Youth Male: % of Males Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Social: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.

Dear Partners,

This month, the Administration for Children and Families (ACF) observed World Day Against Child Labor by spotlighting and encouraging those, who could, to join the Within and Beyond Our Borders: Collective Action to Address Hazardous Child Labor organized by the U.S. Department of Labor (DOL) on June 12, 2023. If you missed it, or would like to rewatch it, you can find it here

.

Since 2018, the DOL has seen a 69 percent increase in children being employed illegally by companies. In the last fiscal year, the department found that 835 companies it investigated had employed more than 3,800 children in violation of labor laws. There has been a 26 percent increase in children employed in hazardous occupations. These numbers tell us that we have work to do as the human services sector to learn more and become engaged in preventing unlawful child labor and supporting youth.

As I have said before, child labor exploitation can disrupt a youth’s health, safety, education, and overall well-being, which are unacceptable consequences for any child. The Administration for Children and Families (ACF) supports a broad network of resources for vulnerable youth. We know that migrant and immigrant youth are especially vulnerable to exploitation, and it is often youth in or exiting the child welfare system who are targeted for various forms of exploitation. Child labor exploitation can impact children and youth across demographics.

On March 24, 2023, the DOL and the U.S. Department of Health and Human Services (HHS) announced a Memorandum of Agreement - PDF

to advance ongoing efforts to address child labor exploitation. In addition, DOL and HHS are collaborating on training and educational materials.

As we expand this work, we know how important our partners throughout the country are in this effort. The Administration for Children and Families (ACF) is committed to addressing the increased presence of child labor exploitation through a variety of actions including equipping partners with materials and educational resources to build knowledge about child labor laws and rights, and remedies. This information is important for our human services sector and the children and families who may be most at risk.

Please join ACF in increasing awareness and distributing resources to address child labor exploitation including the following:

ACF resources may be also useful when working with a youth who has concerns about their safety. This includes the Family and Youth Services Bureau (FYSB)’s program on Runaway and Homeless Youth which provides a hotline for youth, concerned adults, and providers to access resources. At, www.1800runaway.org

, their 24/7 crisis connection allows for calls, texts, live chat, and email to get information and resources.

In addition, ACF’s Office of Trafficking In-Persons (OTIP) is an important resource for identifying and supporting survivors of trafficking. The National Human Trafficking Hotline

provides a 24/7, confidential, multilingual hotline for victims, survivors, and witnesses of human trafficking. While labor exploitation should not be conflated with labor trafficking, in some cases labor exploitation may rise to meet the legal definitions of trafficking. The OTIP website

contains many resources for grantees and communities on labor trafficking.

Again, I hope you will continue to build awareness for yourself, your organization, or your community on child labor exploitation. It takes a whole community effort to support our children and youth.

Most sincerely,

January Contreras

Metadata-only record linking to the original dataset. Open original dataset below.

Users can view and download data regarding youth health behaviors and risk factors from a variety of countries (including the United States). Background The Global School-based Student Health Survey is developed by the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), UNICEF, UNAIDS and UNESCO. The survey is conducted in schools around the world and looks at the health behaviors of students. The information is used by countries to establish priorities and develop programs and by international agencies to make comparisons across countries to gain better understanding of the prevalence and trends of health behaviors.The core questionnaires are designed to gain understanding of the leading causes of mortality and morbidity world wide. The students are asked questions about alcohol and drug use, dietary behaviors, hygiene, mental health, physical activity, protective factors, sexual behaviors, tobacco use and violent behaviors. User Functionality From the website, users can view results by country. Many, but not all, countries have released copies of their questionnaire, fact sheets, full reports and their data. The data is available to download to SAS, Access, SPSS or ASCII. Data Notes The survey participants are between 13 and 15 years old. For some countries, the most recent report is from 2010 and the most recent data set available for download is from 2008. The site does not specify when the data sets will be updated.

Abstract

From December 2009 to March 2010 the World Bank with the help of Moroccan government conducted a study of the country's young people and their engagement in economic and social activities. Researchers from the World Bank's Sustainable Development Sector of the Middle East and North Africa region utilized a mixed-method approach to study factors that impede the economic and social inclusion of Moroccans aged 15 to 29. The Morocco Household and Youth Survey (MHYS) used two survey instruments to gather quantitative data: Household Questionnaire and Youth Questionnaire.

The study used a nationally representative sample of 2,000 households, in which 1,216 households were located in urban areas and 784 households in the rural areas. The Youth Questionnaire was administered to 2,883 young people between the ages of 15 and 29, representing about 90 percent of the youth in the surveyed households. Information was collected on topics such as economic inclusion, community participation, and use of key public services. The survey was able to examine little studied issues relating to youth such as participation in the labor force, intermediation, career choice, perceived job possibilities, use of time, use of recreational and educational activities targeting young people who have completed formal education.

The focus groups discussions supplemented MHYS.

Geographic coverage

National coverage

Analysis unit

• Households,
• Individuals between the ages of 15 and 29.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size for the Household Questionnaire was 2,000 households with 1,216 found in urban locations and 784 in rural locations. The 2,000 households were drawn from the 2004 General Census of Population and Housing. For determining the number of households in urban and rural locations, proportionality of the possible locations was used to ensure representativeness. The proportionality was based off the disaggregation of Morocco into primary units in which there are about 600 households. In the end, 125 primary units were randomly selected, with 76 rural primary units and 49 urban primary units. From these 125 primary units, 16 households were randomly selected giving us the total sample size of 2,000 households.

For the Youth Questionnaire, the sample size was 2,883 individuals between the ages of 15 and 29. These 2,883 individuals came from the selected households in the Household Questionnaire. If there was an individual or individuals between the ages of 15 and 29 living at the selected household, the Youth Questionnaire was administrated. More details on sample design are provided in Appendix 2 in "MHYS Basic Information Document".

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire covers the following topics: Educational Characteristics, Economic Activities in last 12 months, Secondary Economic Activities in last 12 months, Economic Activities in the last 7 days, Unemployment, Health and Social Security, Housing Characteristics and Durables, Agricultural Assets, Climate Change and Shocks in Agriculture,Incidence of Shocks and Household Responses, Assistance from Social Programs, Migration of Household Members, Migration of non-residents, Migration and Climate Change, Decisions on Consumption in the Household, Expenditures on Frequently Consumed Food Items; Less Frequent Non-Food and Food Expenditures Household Consumption expenditures and food source procurement, Expenditure on less frequent non-food and food products,Infrequent Expenditures, Women in Decision Making

Youth Questionnaire includes the following sections: Employment Preferences, Education, Employment during the last 7 days, First Job, Employment History, Entrepreneurship and Independent Farming, Unemployment, Job Search, Job Services Access, Financial Behavior, Participation of Youth in Educational Institutions and in Youth Centers, Participation of Youth in Family, Access of Youth to Recreation and Social Activities, Satisfaction and Communication, and Time Use.

Cleaning operations

The MHYS contains several data files, with each file pertinent to a specific section. For the case in which there are multiple sections per data file, it is because they share similar levels of observations.

The households are identified by the variable "hid" which consists of the region, province, commune, and enumerator area in which the household is located. This allows the household members to remain anonymous yet statistically unique. This is extremely important especially when it comes to merging different datasets.

Merging data sets will depend on which files are being merged. The key to merging the MHYS data files will be to use unique variables.

For the data sets, the "hid" variable will be the unique variable used to perform the merge at household level; "memid" will be the unique variable used to perform the merge at individual level.

The variable "q5" which signifies enumeration area is scrambled to preserve anonymity of sampled households.

The weights are provided in the data file "weights" and can be merged.

Youth & Adult Literacy Rates

Demographics, disparities, and implications

By Eva Murray [source]

About this dataset

This dataset contains data on literacy rates for youth and adults in various regions and countries. The data provides insights on which regions have high or low literacy rates, as well as how literacy rates have changed over time. The dataset can be used to help policy-makers understand where interventions are needed to improve literacy rates

How to use the dataset

• The data can be used to compare literacy rates between different regions and countries, as well as between different age groups within the same region or country.
• To compare literacy rates between different regions, select the 'Region' column from the drop-down menu at the top of the page. To compare literacy rates between different countries, select the 'Country' column from the drop-down menu at the top of the page.
• To compare literacy rates between different age groups, select either the 'Youth (15-24 years)' or 'Adults (15+ years)' option from the 'Age Group' drop-down menu at the top of the page.
• You can also use this data to compare literacy rates between males and females by selecting either th e'Male' or 'Female' option from th eGender drop-down menu at t he top of

Research Ideas

• Measuring the progress of a country's literacy rate over time
• Comparing the literacy rates of different countries
• Comparing the literacy rates of different age groups in a country

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Literacy rates (no pw2).csv | Column name | Description | |:------------------|:--------------------------------------------------------------------------------| | Region | The region the data is from. (String) | | Country | The country the data is from. (String) | | Year | The year the data is from. (Integer) | | Age | The age group the data is from. (String) | | Gender | The gender the data is from. (String) | | Literacy rate | The literacy rate for the given region, country, year, age, and gender. (Float) |

Acknowledgements

If you use this dataset in your research, please credit Eva Murray.

The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.

For further details, please refer to https://datatopics.worldbank.org/world-development-indicators/

2003-2015. Global School dataset. The Global School-based Student Health Survey (GSHS) was developed by the World Health Organization (WHO) in collaboration with the United Nations' UNICEF, UNESCO, and UNAIDS; and with technical assistance from CDC. The GSHS is a school-based survey conducted primarily among students aged 13-17 years in countries around the world. It uses core questionnaire modules that address the leading causes of morbidity and mortality among children and adults worldwide: 1) Alcohol use, 2) dietary behaviors, 3) drug use, 4) hygiene, 5) mental health, 6) physical activity, 7) protective factors, 8) sexual behaviors that contribute to HIV infection, other sexually-transmitted infections, and unintended pregnancy, 9) tobacco use, and 10) violence and unintentional injury. This dataset contains global data from 2003 – 2015. Additional information about the GSHS can be found at https://www.cdc.gov/gshs/index.htm.

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Japan JP: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data was reported at 4.550 % in 2016. This records a decrease from the previous number of 4.710 % for 2015. Japan JP: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data is updated yearly, averaging 5.180 % from Dec 2009 (Median) to 2016, with 7 observations. The data reached an all-time high of 6.120 % in 2009 and a record low of 4.550 % in 2016. Japan JP: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

Jordan JO: Literacy Rate: Youth: % of People Age 15-24 data was reported at 99.106 % in 2012. This records a decrease from the previous number of 99.149 % for 2011. Jordan JO: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 98.975 % from Dec 1979 (Median) to 2012, with 7 observations. The data reached an all-time high of 99.149 % in 2011 and a record low of 90.508 % in 1979. Jordan JO: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Greece GR: Literacy Rate: Youth: % of People Age 15-24 data was reported at 98.695 % in 2011. This records a decrease from the previous number of 99.491 % for 2009. Greece GR: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 98.984 % from Dec 1981 (Median) to 2011, with 7 observations. The data reached an all-time high of 99.562 % in 2007 and a record low of 98.695 % in 2011. Greece GR: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Greece – Table GR.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Overview

Objectives of Global Youth Tobacco Survey:

To determine the level of tobacco use by State/UTs, sex, location of school (urban/rural). To estimate the age of initiation of cigarette and bidi smoking and smokeless tobacco. To estimate the exposure to secondhand smoking (SHS). To estimate the exposure to tobacco advertising

Available Columns in the dataset

1. Use of any form of tobacco, i.e. smoking, smokeless, and any other form of tobacco products;
2. Ever tried or experimented any form of tobacco even once;
3. Use of any form of tobacco in past 30 days;
4. Includes other form of smoking products in addition to cigarette and bidi such as hookah, cigars, cheroots, cigarillos, water pipe, chillum, chutta, dhumti,
5. Use of paan masala together with tobacco was asked directly as one of the categories of smokeless tobacco;
6. Susceptibility to future cigarette use includes those who answered Yes, or maybe to using tobacco products if one of their best friends offered it to them;
7. E-cigarette is part of Electronic Nicotine Delivery System (ENDS) and includes like devices and other emerging products;
8. Stopped using tobacco in past 12 months;
9. Refers to current tobacco users only;
10. Secondhand smoking or passive smoking refers to exposure to other peoples smoking in past 7 days;
11. Refers to schools, hostels, shops, restaurants, movie theatres, public conveyances, gyms, sports arenas, airports, auditorium, hospital building, railway waiting room, public toilets, public offices, educational institutions, libraries, etc.; 12. Refers to playgrounds, sidewalks, entrances to buildings, parks, beaches, bus stops, market places, etc.; #. the value 0.0 represent prevalence of less than 0.05.
12. Refers to source of obtaining tobacco products by current users at the time of last use in past 30 days and the two major sources are given here, therefore, these two figures may not add upto 100% as there are other sources;
13. Includes any form of mass media, fairs, concerts, sporting, community events or social gatherings, tobacco products packages and taught in class;
14. Mass media includes television, radio, internet, billboards, posters, newspapers, magazines, movies, etc.;
15. Social events include sports events, fairs, concerts, community events, social gatherings etc.;
16. Includes any form of media or point of sale;
17. Point of Sale includes any stores, grocery shops, paan shops etc.; 19.Unit of analysis is the school (unweighted);
18. Cigarettes and Other Tobacco Products (Prohibition of Advertisement and Regulation of Trade and Commerce, Production, Supply and Distribution) Act, 2003.

License: Brief of Open Government Data (OGD) License- India

Understanding the factors influencing youth smoking and drug experimentation is essential for shaping effective prevention strategies. This synthetic dataset simulates trends from 2020 to 2024, providing insights into demographic, social, and economic influences on substance use among young individuals.

With approximately 10,000 AI-generated records, this dataset serves as a risk-free and ethically responsible resource for researchers, policymakers, and analysts to explore substance use patterns and their potential causes.

🔍 Key Features: ✔️ Age Groups – Covers a broad spectrum, from 10 to 80 years ✔️ Smoking Prevalence – Modeled insights into smoking engagement among youth ✔️ Drug Experimentation Rates – Simulated trends in drug use patterns ✔️ Socioeconomic Influences – Examines how financial background correlates with substance use ✔️ Peer & Family Influence – Analyzes the role of social circles and family support in youth behavior

📊 Dataset Overview: This dataset is synthetically generated and does not contain real-world data. It is designed for educational purposes, research simulations, and analytical practice in understanding youth substance use trends.

🏢 Columns Description: Person_ID – Unique identifier for each synthetic individual Age – Modeled age group (10–80 years) Gender – Simulated gender representation Socioeconomic_Status – Categorized as Low, Middle, or High Smoking_Status – Modeled likelihood of smoking (Yes/No) Drug_Experimentation – Simulated data on whether the individual has experimented with drugs Family_Influence – Influence level of family support on behavior Peer_Influence – Impact of peer pressure on substance use ⚠️ Disclaimer: This dataset is entirely synthetic and should not be used for real-world policy decisions, medical research, or official reporting. It is intended solely for academic learning, trend analysis, and data science practice.

🔹 Use this dataset to explore trends, develop predictive models, and contribute to meaningful discussions on youth health and substance use prevention! 🌟

Thailand TH: Literacy Rate: Youth: % of People Age 15-24 data was reported at 98.147 % in 2015. This records a decrease from the previous number of 98.314 % for 2013. Thailand TH: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 98.013 % from Dec 1980 (Median) to 2015, with 6 observations. The data reached an all-time high of 98.314 % in 2013 and a record low of 96.598 % in 2010. Thailand TH: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Context

The dataset is published for helping Kiva to make their descions.

Content

These datasets contain the percentage of youth, unemployment and literacy in different countries.

Acknowledgements

This dataset is collected from Wikipedia.

Inspiration

1. Which country needs more help from Kiva?