Among the OECD countries, Canada had the highest proportion of adults with a tertiary education in 2022. About 63 percent of Canadians had achieved a tertiary education in that year. Japan followed with about 56 percent of the population having completed a tertiary education, while in Ireland the share was roughly 54 percent. In India, on the other hand, less than 13 percent of the adult population had completed a tertiary education in 2022.

In 2022, Canada had the highest share of adults with a university degree, at over 60 percent of those between the ages of 25 and 64. India had the smallest share of people with a university degree, at 13 percent of the adult population. University around the world Deciding which university to attend can be a difficult decision for some and in today’s world, people are not left wanting for choice. There are thousands of universities around the world, with the highest number found in India and Indonesia. When picking which school to attend, some look to university rankings, where Harvard University in the United States consistently comes in on top. Moving on up One of the major perks of attending university is that it enables people to move up in the world. Getting a good education is generally seen as a giant step along the path to success and opens up doors for future employment. Future earnings potential can be determined by which university one attends, whether by the prestige of the university or the connections that have been made there. For instance, graduates from the Stanford Graduate School of Business can expect to earn around 250,000 U.S. dollars annually.

Brazil Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Incompleted data was reported at 67.200 % in Mar 2019. This records a decrease from the previous number of 67.400 % for Dec 2018. Brazil Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Incompleted data is updated quarterly, averaging 69.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 71.200 % in Sep 2012 and a record low of 65.700 % in Mar 2017. Brazil Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Incompleted data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

As of 2022, 70 percent of the South Korean population between 25 and 34 had attained a tertiary education, making it the OECD country with the highest proportion of tertiary education graduates. Canada followed with more than two-thirds, while in Japan, the share was around 66 percent. By comparison, roughly 13 percent of South Africans between 25 and 34 had a tertiary education in 2022.

Labour Force Participation Rate: Brazil: by Number of Year Studies: Higher Education: Incompleted data was reported at 73.400 % in Mar 2019. This records a decrease from the previous number of 73.500 % for Dec 2018. Labour Force Participation Rate: Brazil: by Number of Year Studies: Higher Education: Incompleted data is updated quarterly, averaging 73.100 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 75.400 % in Sep 2012 and a record low of 71.600 % in Mar 2014. Labour Force Participation Rate: Brazil: by Number of Year Studies: Higher Education: Incompleted data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Completed data was reported at 82.000 % in Mar 2019. This records a decrease from the previous number of 82.500 % for Dec 2018. Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Completed data is updated quarterly, averaging 82.600 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 84.500 % in Mar 2014 and a record low of 81.500 % in Mar 2016. Labour Force Participation Rate: Northeast: by Number of Year Studies: Higher Education: Completed data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

Goal 4Ensure inclusive and equitable quality education and promote lifelong learning opportunities for allTarget 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and effective learning outcomesIndicator 4.1.1: Proportion of children and young people (a) in grades 2/3; (b) at the end of primary; and (c) at the end of lower secondary achieving at least a minimum proficiency level in (i) reading and (ii) mathematics, by sexSE_TOT_PRFL: Proportion of children and young people achieving a minimum proficiency level in reading and mathematics (%)Indicator 4.1.2: Completion rate (primary education, lower secondary education, upper secondary education)SE_TOT_CPLR: Completion rate, by sex, location, wealth quintile and education level (%)Target 4.2: By 2030, ensure that all girls and boys have access to quality early childhood development, care and pre-primary education so that they are ready for primary educationIndicator 4.2.1: Proportion of children aged 24-59 months who are developmentally on track in health, learning and psychosocial well-being, by sexiSE_DEV_ONTRK: Proportion of children aged 36−59 months who are developmentally on track in at least three of the following domains: literacy-numeracy, physical development, social-emotional development, and learning (% of children aged 36-59 months)Indicator 4.2.2: Participation rate in organized learning (one year before the official primary entry age), by sexSE_PRE_PARTN: Participation rate in organized learning (one year before the official primary entry age), by sex (%)Target 4.3: By 2030, ensure equal access for all women and men to affordable and quality technical, vocational and tertiary education, including universityIndicator 4.3.1: Participation rate of youth and adults in formal and non-formal education and training in the previous 12 months, by sexSE_ADT_EDUCTRN: Participation rate in formal and non-formal education and training, by sex (%)Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurshipIndicator 4.4.1: Proportion of youth and adults with information and communications technology (ICT) skills, by type of skillSE_ADT_ACTS: Proportion of youth and adults with information and communications technology (ICT) skills, by sex and type of skill (%)Target 4.5: By 2030, eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situationsIndicator 4.5.1: Parity indices (female/male, rural/urban, bottom/top wealth quintile and others such as disability status, indigenous peoples and conflict-affected, as data become available) for all education indicators on this list that can be disaggregatedSE_GPI_PTNPRE: Gender parity index for participation rate in organized learning (one year before the official primary entry age), (ratio)SE_GPI_TCAQ: Gender parity index of trained teachers, by education level (ratio)SE_GPI_PART: Gender parity index for participation rate in formal and non-formal education and training (ratio)SE_GPI_ICTS: Gender parity index for youth/adults with information and communications technology (ICT) skills, by type of skill (ratio)SE_IMP_FPOF: Immigration status parity index for achieving at least a fixed level of proficiency in functional skills, by numeracy/literacy skills (ratio)SE_NAP_ACHI: Native parity index for achievement (ratio)SE_LGP_ACHI: Language test parity index for achievement (ratio)SE_TOT_GPI: Gender parity index for achievement (ratio)SE_TOT_SESPI: Low to high socio-economic parity status index for achievement (ratio)SE_TOT_RUPI: Rural to urban parity index for achievement (ratio)SE_ALP_CPLR: Adjusted location parity index for completion rate, by sex, location, wealth quintile and education levelSE_AWP_CPRA: Adjusted wealth parity index for completion rate, by sex, location, wealth quintile and education levelSE_AGP_CPRA: Adjusted gender parity index for completion rate, by sex, location, wealth quintile and education levelTarget 4.6: By 2030, ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracyIndicator 4.6.1: Proportion of population in a given age group achieving at least a fixed level of proficiency in functional (a) literacy and (b) numeracy skills, by sexSE_ADT_FUNS: Proportion of population achieving at least a fixed level of proficiency in functional skills, by sex, age and type of skill (%)Target 4.7: By 2030, ensure that all learners acquire the knowledge and skills needed to promote sustainable development, including, among others, through education for sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of peace and non-violence, global citizenship and appreciation of cultural diversity and of culture’s contribution to sustainable developmentIndicator 4.7.1: Extent to which (i) global citizenship education and (ii) education for sustainable development are mainstreamed in (a) national education policies; (b) curricula; (c) teacher education; and (d) student assessmentTarget 4.a: Build and upgrade education facilities that are child, disability and gender sensitive and provide safe, non-violent, inclusive and effective learning environments for allIndicator 4.a.1: Proportion of schools offering basic services, by type of serviceSE_ACS_CMPTR: Schools with access to computers for pedagogical purposes, by education level (%)SE_ACS_H2O: Schools with access to basic drinking water, by education level (%)SE_ACS_ELECT: Schools with access to electricity, by education level (%)SE_ACC_HNDWSH: Schools with basic handwashing facilities, by education level (%)SE_ACS_INTNT: Schools with access to the internet for pedagogical purposes, by education level (%)SE_ACS_SANIT: Schools with access to access to single-sex basic sanitation, by education level (%)SE_INF_DSBL: Proportion of schools with access to adapted infrastructure and materials for students with disabilities, by education level (%)Target 4.b: By 2020, substantially expand globally the number of scholarships available to developing countries, in particular least developed countries, small island developing States and African countries, for enrolment in higher education, including vocational training and information and communications technology, technical, engineering and scientific programmes, in developed countries and other developing countriesIndicator 4.b.1: Volume of official development assistance flows for scholarships by sector and type of studyDC_TOF_SCHIPSL: Total official flows for scholarships, by recipient countries (millions of constant 2018 United States dollars)Target 4.c: By 2030, substantially increase the supply of qualified teachers, including through international cooperation for teacher training in developing countries, especially least developed countries and small island developing StatesIndicator 4.c.1: Proportion of teachers with the minimum required qualifications, by education leveliSE_TRA_GRDL: Proportion of teachers who have received at least the minimum organized teacher training (e.g. pedagogical training) pre-service or in-service required for teaching at the relevant level in a given country, by sex and education level (%)

The Asia-Pacific region shows significant variations in labor force participation rates (LFPR) among the population aged 15 to 64 years, with North Korea’s LFPR estimated at ** percent and Afghanistan’s at about ** percent in 2024. This stark contrast highlights the diverse economic and social landscapes across the region, influencing workforce engagement. Regional trends and forecasts APAC’s rapidly aging population is putting growing pressure on the labor market, with projections showing a declining labor force participation rate across the region between 2023 and 2050. East Asia, where demographic changes are most pronounced, is expected to see a significant decline in LFPR among those aged 15 to 54 years, while participation among those over 54 years is projected to rise notably during this period. In contrast, South Asia is the only sub-region anticipated to record a modest increase in participation rates for the 25-54 years age group, highlighting a regional divergence in labor force trends Youth engagement in the labor force The labor force participation rates among youth populations vary greatly across Asia-Pacific countries, reflecting diverse economic conditions, education systems, and social factors. For example, North Korea and Australia boast high youth labor force participation rates of more than ** percent for those aged 15 to 24 years, while South Korea's rate for the same age group is considerably lower at around ** percent. In Australia, strong labor market access for students and abundant part-time work opportunities could enable high youth engagement alongside education. Meanwhile, South Korea's strong societal focus on academic achievement and the pursuit of higher education qualifications often leads to prolonged periods of education, which delays young people's entry into the workforce. Moreover, many APAC countries have high NEET (not in education, employment, or training) rates, particularly those in South Asia, underscoring challenges such as skills mismatches and limited job opportunities.

The global labor force participation rate fell by 0.8 percentage points between 2014 and 2024. This is explained by structural changes in low- and middle-income countries, such as more young adults entering higher education. On the contrary, the labor force participation rate fell in high-income countries due to aging populations.

Brazil Labour Force Participation Rate: Southeast: by Number of Year Studies: Higher Education: Completed data was reported at 81.300 % in Mar 2019. This records an increase from the previous number of 81.000 % for Dec 2018. Brazil Labour Force Participation Rate: Southeast: by Number of Year Studies: Higher Education: Completed data is updated quarterly, averaging 82.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 82.800 % in Sep 2012 and a record low of 81.000 % in Dec 2018. Brazil Labour Force Participation Rate: Southeast: by Number of Year Studies: Higher Education: Completed data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

Abstract

Despite the many useful studies on the use of Open Educational Resources (OER) in higher education, most are focused on the activity of students and instructors in the Global North who enjoy comparatively higher levels of economic development, educational provision, policy elaboration, and technological access than those in the Global South – the region where OER is touted as having its potentially greatest impact. This dataset arises from a survey focusing on higher education instructors and students in South America, Sub-Saharan Africa, and South and Southeast Asia. This was a cross-regional survey of 295 instructors at 28 universities in nine countries, Brazil, Chile, Colombia, Ghana, Kenya, South Africa, India, Indonesia, Malaysia. This research seeks to establish a baseline of empirical data for assessing OER awareness and use in the Global South.

The overarching research questions that this study set out to answer are: 1. What proportion of instructors in the Global South have ever used OER? 2. Which variables may account for different OER usage rates between respondents in the Global South?

In order to address these questions, survey responses were correlated against the question (26) of the survey which directly addresses OER usage: "Have you ever used OER that are available in the public domain or has an open license (e.g. Creative Commons) that allows it to be used and/or adapted by others?" A core purpose of the overarching ROER4D project is the development of an empirical baseline of OER and Open Educational Practice (OEP) activity in the Global South. OER itself is a novel concept, and is tied to a broader spectrum of OEP that overlap with, but do not always exactly coincide with, formal OER practice. As such, an investigation into the use, reuse, adaptation, and sharing practices performed by higher education instructors, and the digital infrastructure and foundational literacies that underpin these practices (regardless of their knowledge of formal OER activity) is integral in ascertaining baseline practice. This dataset includes responses by instructors who engage in reuse and sharing activities, irrespective of whether they have consciously used OER in their practice. As such, it offers insights into the practices that exist outside of formally-labelled OER production. Dimension 2 of the survey instrument "Educational Resources" is framed around general practice relating to sharing, use, reuse, creation, and licensing of educational materials, rather than OER per se. Data arising from these responses are to be treated with caution in terms of making inferences around OER, but remain useful in terms of gaining a more informed sense of instructors’ everyday practice. The survey was conducted in four languages (English, Spanish, Portuguese, and Bahasa Melayu); as such, four research instruments were originally produced and four sets of microdata collected. The microdata have been translated into English, and only the English instrument and the aggregated, translated instructor- response microdata is included here. The student-response microdata is not part of this dataset. The dataset is considered to be of interest to OER scholars, practitioners, and policy-makers, as it seeks to provide a useful cross-regional comparison of various aspects of OER adoption.

Geographic coverage

The survey was conducted in nine countries in South America, Sub-Saharan Africa, and South and Southeast Asia.Countries covered were Brazil, Chile, Colombia, Ghana, Kenya, South Africa, India, Indonesia, Malaysia.

Analysis unit

Individuals

Universe

The study engaged instructors in higher education institutions in the nine countries involved in the study.

Kind of data

Qualitative data

Mode of data collection

Face-to-face [f2f]

Response rate

The survey gathered 295 usable responses from instructors.

Brazil Labour Force Participation Rate: North: by Number of Year Studies: Higher Education: Incompleted data was reported at 68.500 % in Mar 2019. This records an increase from the previous number of 67.500 % for Dec 2018. Brazil Labour Force Participation Rate: North: by Number of Year Studies: Higher Education: Incompleted data is updated quarterly, averaging 69.500 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 76.000 % in Jun 2012 and a record low of 66.700 % in Jun 2018. Brazil Labour Force Participation Rate: North: by Number of Year Studies: Higher Education: Incompleted data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

Across all OECD countries included (except for Japan), there was a higher share of women than men among the new first-time higher education students in 2022. This reflects a general trend across developed countries that women tend to reach higher levels of education than that of men.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Education is one of the most powerful instruments for reducing poverty and inequality and lays a foundation for sustained economic growth. The World Bank compiles data on education inputs, participation, efficiency, and outcomes. Data on education are compiled by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics from official responses to surveys and from reports provided by education authorities in each country. Indicators: Adjusted net enrollment rate, Adjusted net intake rate to Grade 1 of primary education, Adolescents out of school, Adult illiterate population, Adult literacy rate, Barro-Lee, Capital expenditure as % of total expenditure in tertiary public institutions, Children out of school, Compulsory education, Cumulative drop-out rate to the last grade of primary education, Current education expenditure, Current expenditure as % of total expenditure in public institutions, Current expenditure as % of total expenditure in tertiary public institutions, DHS, Drop-out rate from Grade 1 of primary education, Drop-out rate from Grade 2 of primary education, Drop-out rate from Grade 3 of primary education, Drop-out rate from Grade 4 of primary education, Educational attainment, Effective transition rate from primary to lower secondary general education, Enrolment in Grade 1 of lower secondary general education, Enrolment in Grade 1 of primary education, Enrolment in Grade 2 of lower secondary general education, Enrolment in Grade 2 of primary education, Enrolment in Grade 3 of lower secondary general education, Enrolment in Grade 3 of primary education, Enrolment in Grade 4 of primary education, Enrolment in Grade 5 of primary education, Enrolment in lower secondary education, Enrolment in lower secondary general, Enrolment in post-secondary non-tertiary education, Enrolment in pre-primary education, Enrolment in primary education, Enrolment in secondary education, Enrolment in secondary general, Enrolment in secondary vocational, Enrolment in tertiary education, Enrolment in upper secondary education, Enrolment in upper secondary general, Enrolment in upper secondary vocational, Expenditure on education not specified by level as % of government expenditure on education, Expenditure on primary education, Expenditure on secondary education, Expenditure on tertiary education, Government expenditure on education, Government expenditure per student, Graduates from tertiary education, Gross enrolment ratio, Gross graduation ratio from lower secondary education, Gross graduation ratio from primary education, Gross intake ratio in first grade of primary education, Gross intake ratio to Grade 1 of lower secondary general education, Gross intake ratio to Grade 1 of primary education, Gross outbound enrolment ratio, Inbound mobility rate, Labor force, Literacy rate, Lower secondary completion rate, Lower secondary school starting age, Net enrolment rate, Net intake rate in grade 1, New entrants to Grade 1 of primary education, New entrants to Grade 1 of primary education with early childhood education experience, Official entrance age to compulsory education, Official entrance age to post-secondary non-tertiary education, Official entrance age to pre-primary education, Official entrance age to upper secondary education, Out-of-school adolescents of lower secondary school age, Outbound mobility ratio, Over-age students, Percentage of enrolment in pre-primary education in private institutions, Percentage of enrolment in tertiary education in private institutions, Percentage of female teachers in lower secondary education who are trained, Percentage of graduates from tertiary education who are female, Percentage of male teachers in lower secondary education who are trained, Percentage of new entrants to Grade 1 of primary education with early childhood education experience, Percentage of repeaters in Grade 1 of lower secondary general education, Percentage of repeaters in Grade 1 of primary education, Percentage of repeaters in Grade 2 of lower secondary general education, Percentage of repeaters in Grade 2 of primary education, Percentage of repeaters in Grade 3 of lower secondary general education, Percentage of repeaters in Grade 3 of primary education, Percentage of repeaters in Grade 4 of primary education, Percentage of repeaters in Grade 5 of primary education, Percentage of repeaters in lower secondary general education, Percentage of repeaters in primary education, Percentage of students in post-secondary non-tertiary education who are female, Percentage of students in pre-primary education who are female, Percentage of students in tertiary ISCED 5 programmes who are female, Percentage of students in tertiary ISCED 6 programmes who are female, Percentage of students in tertiary ISCED 7 programmes who are female, Percentage of students in tertiary ISCED 8 programmes who are female, Percentage of students in tertiary education who are female, Percentage of teachers in lower secondary education who are female, Percentage of teachers in lower secondary education who are trained, Percentage of teachers in primary education who are trained, Percentage of teachers in upper secondary education who are female, Persistence to grade 5, Persistence to last grade of primary, Population, Population ages 0-14, Population ages 15-64, Population of the official entrance age to primary education, Preprimary education, Primary completion rate, Primary education, Primary school starting age, Progression to secondary school, Pupil-teacher ratio, Pupil-teacher ratio in lower secondary education, Pupil-teacher ratio in upper secondary education, Rate of out-of-school adolescents of lower secondary school age, Rate of out-of-school children of primary school age, Repeaters, Repeaters in Grade 1 of lower secondary general education, Repeaters in Grade 1 of primary education, Repeaters in Grade 2 of lower secondary general education, Repeaters in Grade 2 of primary education, Repeaters in Grade 3 of lower secondary general education, Repeaters in Grade 3 of primary education, Repeaters in Grade 4 of primary education, Repeaters in Grade 5 of primary education, Repeaters in lower secondary general education, Repeaters in primary education, Repetition rate in Grade 1 of primary education, Repetition rate in Grade 2 of primary education, Repetition rate in Grade 3 of primary education, Repetition rate in Grade 4 of primary education, Repetition rate in Grade 5 of primary education, School age population, School enrollment, School life expectancy, Secondary education, Share of all students in secondary education enrolled in vocational programmes, Share of all students in tertiary education enrolled in ISCED 5, Share of all students in tertiary education enrolled in ISCED 6, Share of all students in tertiary education enrolled in ISCED 7, Share of all students in tertiary education enrolled in ISCED 8, Share of all students in upper secondary education enrolled in vocational programmes, Share of female students in secondary education enrolled in vocational programmes, Share of female students in tertiary education enrolled in ISCED 7, Share of female students in tertiary education enrolled in ISCED 8, Share of male students in secondary education enrolled in vocational programmes, Share of male students in tertiary education enrolled in ISCED 7, Share of male students in tertiary education enrolled in ISCED 8, Survival rate to Grade 4 of primary education, Survival rate to Grade 5 of primary education, Survival rate to the last grade of lower secondary general education, Survival rate to the last grade of primary education, Teachers in lower secondary education, Teachers in primary education, Teachers in secondary general education, Teachers in secondary vocational education, Teachers in tertiary education programmes, Teachers in upper secondary education, Tertiary education, Theoretical duration of lower secondary education, Theoretical duration of post-secondary non-tertiary education, Theoretical duration of pre-primary education, Theoretical duration of upper secondary education, Total inbound internationally mobile students, Total net enrolment rate, Total outbound internationally mobile tertiary students studying abroad, Trained teachers in lower secondary education, Trained teachers in primary education, Unemployment, Youth illiterate population

The average for 2022 based on 10 countries was 40.16 percent. The highest value was in Singapore: 98.02 percent and the lowest value was in Laos: 13.7 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Participation in non-formal adult education (NFE) is considered an essential part of lifelong learning, aiming to foster the development of individuals and societies. This significance is particularly evident today, given the era of extensive digitalization and disruptive technological advances. Nevertheless, not all adults participate in organized learning and have equal chances. Therefore, this study addresses the absence of up-to-date comparative findings on participation in NFE in the post-COVID-19 world. To this end, we examine current trends in NFE participation in four European countries: Sweden, Germany, the United Kingdom, and the Czech Republic (RQ1), where we explore the impact of key micro (social and behavioral), meso (job-related), and macro-level (country-specific) factors on this participation (RQ2). Our findings indicate that NFE participation remained relatively stable in 2022 compared to 2016, except for Sweden and Germany, which achieved higher participation rates. However, differences in participation between countries are diminishing. Simultaneously, NFE participation is becoming increasingly job-oriented and receives more support from employers. However, it is important to note that inequality in access to NFE persists, as the main predictors of NFE participation, such as learning intentions, educational attainment, economic and occupational status, remain consistent, regardless of the participants’ economic activity and country of birth. This underscores the enduring significance of a key concept behind this study: the willingness to engage in organized NFE exhibits a complex structure with multiple layers.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Brazil Labour Force Participation Rate: Central West: by Number of Year Studies: Higher Education: Incompleted data was reported at 74.600 % in Mar 2019. This stayed constant from the previous number of 74.600 % for Dec 2018. Brazil Labour Force Participation Rate: Central West: by Number of Year Studies: Higher Education: Incompleted data is updated quarterly, averaging 72.300 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 75.300 % in Sep 2017 and a record low of 68.700 % in Jun 2015. Brazil Labour Force Participation Rate: Central West: by Number of Year Studies: Higher Education: Incompleted data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA039: Continuous National Household Sample Survey: Labour Force Participation Rate: by Number of Year Studies. It is the percentage of people at labour force in the week of reference in relation to people at work age.

The average for 2022 based on 126 countries was 94.03 percent. The highest value was in Finland: 144.85 percent and the lowest value was in Burkina Faso: 33.72 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.