NEET Rates Research Articles

Bridging the Gender Gap in NEET Risk: Institutional Influences on NEET Status in Different Age Groups

Utilizing the Survey of Adult Skills from the Program for the International Assessment of Adult Competencies (PIAAC) and the OECD database, this study investigates the role of gender inequality and public social spending in the gender gap in Not in Employment, Education, or Training (NEET) risk across various age cohorts. The research identifies a concentration of female NEETs aged 25 to 34 in nations with more pronounced gender employment gaps, whereas such disparities were not evident among the 15 to 24 age groups. In exploring the role of public social spending as a mitigating factor for the gender-based NEET rate gap, the study underscores that investments in education, labor market activation, and early childhood education serve as key factors in reducing gender discrepancies in the likelihood of NEET status.

NEET youth in central and eastern European countries: a panel model approach

ABSTRACT The purpose of the present study was to examine macro-determinants of the Not Engaged in Employment, Education, or Training Young People (NEET) in Central and Eastern European Countries. Data from 16 countries were collected from Eurostat –, UNESCO – and Word Bank Database 2013–2021 by using the panel data analysis method. Early school leaving rate, vocational education and training enrollment rate, unemployment rate, labour market regulation, gross domestic product, education expenditure and human development index were used for explaining the NEET in selected area. The relationship between variables was analyzed using the Panel Data Methods via Fixed-Effects Model. Therefore, according to the findings of Driscoll and Kraay Estimator – One-Way Fixed Effects Model, gross domestic product, labour market regulation, early school leaving rate, vocational education, and training enrollment rate variables have a high and statistically significant effect on NEET as the dependent variable, while unemployment rate and human development index have a marginal but significant effect on NEET. The findings of the present study showed associations between socio-economic and institutional conditions (labour market regulation) and the NEET rate at the country level and may indicate appropriate policy measures to promote a decrease in the NEET rate.

Using machine learning for NEETs and sustainability studies: Determining best machine learning algorithms

In this study, we apply and compare different algorithms from machine learning to describe and predict NEET rates in 31 European countries in the period from 2005 to 2020. With this aim, we considered eleven indicators describing the socio-economic national context and the level of innovation of the economies. Besides improving knowledge about the use of machine learning algorithms for the description of the NEET phenomenon, we discuss the connections between NEETs and other indicators that connect with other relevant sustainable development goals (SDGs), such as education, the reduction of inequalities, and decent work for everyone. The reduction of NEET rates is the only goal directly addressed to young people, The article underscores the need for evidence-based approaches to measure SDG achievement, especially concerning the heterogeneous NEET population. It emphasizes the importance of machine learning algorithms as a modern methodology for understanding and addressing the NEET phenomenon within the framework of SDGs, considering the complex interrelationships of socio-economic factors contributing to social and economic sustainability.

Outcomes of Comprehensive Service Delivery and Early Interventions in Countering Youth Exclusion

The high rates of young people not in employment, education, or training (NEET) are an international concern. At the core of the European Union’s (EU), policy agenda is the reduction of youth unemployment and the active engagement of as many young people as possible in the workforce. The need for holistic services, interagency collaboration, and early intervention have been highlighted as important measures to reduce the risk of youth becoming NEET and subject to long-term unemployment. However, although highlighted as important, little is known about how these factors affect NEET rates. This study addresses this issue by exploring whether comprehensive service delivery, including holistic and collaborative approaches, and early interventions aimed at preventing youth from disengaging from education or employment, may explain the outcome of local NEET rates. Empirically, this study consists of multiple steps. An initial multilevel regression analysis of all Norwegian municipalities provided the basis for strategically selecting 18 municipalities based on their consistently higher or lower NEET rates than predicted when controlling for individual and structural factors that are shown to impact NEET risk. Semi-structured interviews in these municipalities regarding local work with NEETs provided the data, which were analysed using a fuzzy-set qualitative comparative method (fsQCA). The results suggest that the engagement of public employment and social services (PESS) in early intervention measures aimed at preventing youth from ending up in a NEET situation, combined with either extensive collaboration with other services or a holistic-oriented local (mental) healthcare service, may indeed explain lower NEET rates.

Labor Market Reflections Of Covıd-19 Pandemic: A Global Investigation Specific To Income Groups And Vulnerable Workers

The Covid 19 pandemic, which started in Wuhan, China in November 2019 and then spread rapidly all over the world, caused the death of millions of people, stagnation in the global economy, and created a rare economic conjuncture by creating both demand and supply shocks. The pandemic has affected world economies and deeply affected the labor markets on a global scale. Production in many sectors has decreased significantly, and in some sectors it has come to a standstill. As a result, unemployment rates and employment losses have increased and employment patterns have changed. Main objective of this study is to investigate the effects of the pandemic on labour markets around the world in terms of both income groups and vulnerable labour based on the extensive literature and ILO&IMF database. According to the findings, the macroeconomic structures of the countries have differentiated their levels of being affected by the crisis, while unemployment and employment losses were felt sharply in middle and low-income countries. Moreover, impacts of the pandemic on disadvantaged groups have been harsh, women, youth, migrant and child labor have been affected in different ways by the pandemic. Due to the pandemic, women had difficulty in staying in the labor market, young people were left out of the labor market and NEET rates increased, migrant workers also experienced significant employment losses, the pandemic has also increased child labor globally.

The Importance of a Coordinated Career Guidance System in Addressing the Rural NEETs Issue

A rapidly ageing population, the dual transition, major changes in the job market, and the coronavirus and its effects amplify existing disparities (gender gap, urban-rural cleavages), posing a considerable challenge for peripheral regions. In these circumstances, the labour market integration of young people who are neither in employment nor in education or training (NEET) is becoming increasingly urgent for peripheral regions such as rural areas. Various legislation, policies, and community-based interventions play a significant role in promoting integration. Still, subjective factors such as self-efficacy beliefs affect perceptions of career opportunities and can even prevent some from seizing opportunities. As a result, approaches to tackling the rural NEET issue need to focus on a long-term, sustainable solution. One could be career guidance, which helps individuals take charge of their lives and choose meaningful careers and educational paths. Consequently, our research aimed to identify the conditions in 22 European countries related to career guidance that lead to low rural NEET rates among 25–29-year-olds. Career guidance systems were explored through content analysis of country-specific reports on lifelong guidance systems and then analysed using the fuzzy-set qualitative comparative analysis. The research results draw attention to the importance of coordinated career guidance systems in preventing and (re)integrating NEETs, as it helps make informed, meaningful, and long-term career decisions.

Young people’s literacy, numeracy achievements, and the school-to-work transition: a longitudinal study of regional variation

ABSTRACT We conducted a study on a local scale targeting the relationship of economic capital, cultural capital, young people’s literacy, numeracy achievements, and the school-to-work transition. We investigated whether participation rates by very young children in early childhood education (ECE) may mediate the historical effects of economic and cultural capital. We analysed longitudinal data from a high-quality national database that included information from 103 Italian provinces. We used structural equation modelling (SEM), multi-sample SEM to investigate spatial inequalities, and mediation analyses. Vector Autoregression models were estimated to determine the temporal trend and the relationship occurring between economic capital and ECE. Results indicate that economic capital is associated with young people’s literacy and numeracy achievements and with the NEET rate, with only partial mediation played by the rate of participation in ECE. The association of cultural capital on the NEET rate is near to significance, but it is strongly mediated by participation in ECE. Together, these results imply that the rate of participation in ECE in the Italian provinces may mediate the effect of cultural capital, but only partly that of economic capital.

Ocena zmian komponentów wskaźnika NEET w krajach Unii Europejskiej z zastosowaniem testu T2 Hotellinga

Decision-makers and researchers dealing with labour market and education are largely focused on the NEET rate of young people as an indicator complementary to the unemployment rate. Typically in studies, it is the change in the overall NEET rate of young people that is evaluated, rather than changes in its individual components. The aim of the study presented in this paper is to detect the volume of changes in the components of the NEET rate determined on the basis of socio-demographic and economic features of young people in EU countries, by means of Hotelling’s T2 test for dependent measurements. The study employed multivariate statistical inference, and more specifically, the multiple comparison tests. The analysis covered the years 2019 and 2021, i.e. the year preceding the outbreak of the COVID-19 pandemic and the full year of its duration. The calculations were performed on the data drawn from the Eurostat database. The study demonstrates that the comparison of the NEET youth rate components allows a more detailed assessment of the change in the labout market situation of young people belonging to this category than comparing the overall NEET rates only. For this reason, it would be advisable to apply a multidimensional approach when making decisions concerning labour market policies.

Evaluation of the Labour Market Situation of Young People in EU Countries – The Multiple Regression Approach

The article considers the problems of young people aged 20-24 on the labour market affected by unemployment in European Union countries. Unemployment is one of the most important economic and social problems, which at the same time constitutes one of the biggest measures characterising the condition of the economy. The diversity of the economic situation in EU countries directly affects young people, an individual group of people entering the labour market and have little or no professional experience. At the same time, they are ready to start work, facing great difficulties in entering the market, influenced by socio-economic as well as demographic factors which directly and indirectly affect employment. Considering the above premise, the aim of the article was to identify the determinants of unemployment of young people aged 20-24 in the EU. The study used data from two years: 2010 and 2020, and applied multiple regression. Statistical data were taken from Eurostat databases. The study allowed to examine the dependence of the influence of individual socioeconomic as well as demographic factors on youth unemployment. The study found that the multivariate regression showed that factors related to young people's participation in education and training (including the NEET rate) relative to labour market status, as well as social inclusion, had a significant impact on the unemployment studied. Over the decade, a decrease was seen in unemployment in most EU member states, in as many as 19 countries, while the remaining eight countries showed an increase.

성인으로 이행하는 청년에 대한 한국 사회정책의 특성

This study was conducted by using international comparison approach to explore characteristics of social policy for youth transitioning into adulthood in South Korea. The analytical framework was established in terms of ‘minimum income protection’(‘redistribution of income’) and ‘enabling’ (‘redistribution of opportunity’), based on review of international literature. Looking at South Korea’s position at the international level, The minimum income protection indicators, the accessibility and Adequacy of social assistance benefits, is low, while the vocational schools and training rate and the inactive NEET rate, which are the indicators of ‘enabling’, are at a moderate level and very high, respectively. The‘enabling’ means the low comprehensiveness of youth employment policy. Given that youth in South Korean tend to delay the period of independence, being mostly economically dependent on their parents under strong familialism, it is concluded that their familialization are related to South Korea’s insufficient social policy measures in the institutional context. It is hoped that the results provide a clue to understand the characteristics of social policies for youth in South Korea at a preliminary level, while helping to seek policy alternatives.

Poverty Among Youth-Headed Households in South Africa: Quo Vadis

ABSTRACT In South Africa, youth (15–34 years) are the most vulnerable age group, assuming a large share of unemployment and NEET rates. This has raised concerns of their living standards, which have a great influence on their overall development. Although much has been written on poverty in South Africa, poverty specifically among the youth remains under-researched. This study analyses factors that determine poverty among youth-headed households in South Africa using the 2018 General Household Survey data from Statistics South Africa. Using a binary logistic regression, the paper provides findings and makes recommendations and imperative insights to policy-makers in advancing the socio-economic status of young people.

Macro-Determinants of NEET: An Ecological Study at the Country Level of Analysis for the Period 1997–2020

The aim of the present study was to examine macro-determinants of the Not Engaged in Employment, Education or Training (NEET) rate with the country as the unit of analysis. Data from 40 countries were extracted from the Organisation for Economic Co-operation and Development (OECD) database. Linear mixed models were used to examine associations between the NEET rate and gross domestic product (GDP), population density, life expectancy, social spending, homicide rate, part-time employment, poverty, social inequality (GINI index), and education spending. As part of a sensitivity analysis, the analysis was repeated using open data from the World Bank Group. GDP and social spending were uniquely associated with the NEET rate after controlling for the effects of other factors. Social inequality, poverty, and education spending showed borderline significant associations with the NEET rate. The findings of the present ecological study showed associations between environmentally unfavourable conditions or harshness and the NEET rate at the country level and may inform appropriate policy measures to contain and promote a decrease in the NEET rate.

Analysis of the Composition and Trends in the European Union Labor Market Between 2010 and 2020

This article aims, through research methods such as quantitative and qualitative analysis (empirical and descriptive), as well as comparison and interpretation, to highlight the composition and trends in the EU labor market between 2010-2020, given the link and mutual conditioning between socio-economic phenomena and the labor market, as part of the realities and trends of European social policy. Thus, the aim was to identify the differences between the Member States of the European Union, but also compared to the EU average, by analyzing the performance and the degree of fulfillment of the indicators pre-established by public policies, as specific objectives of social policy, aiming to ensure an adequate and non-discriminatory framework so that all citizens have equal access to resources and opportunities.In order to present the trend in the evolution of employment, we analyzed the indicators regarding the active population, activity rates, employment rate, employed population, unemployment, unemployment rate, inactive population, but also the Job vacancy rate (annual average). Last but not least, we analyzed a delicate issue at the level of some member states of the European Union, highlighting both shortcomings in the transition from the education system to the labor market, as well as shortcomings in terms of employment of a category of population, namely NEET rate.

TO BE YOUNG, ALIENATED AND UNEMPLOYED: SOCIAL IDENTITY, ATTITUDES AND WELL-BEING OF GEORGIA’S NEET YOUTH

Education and employment are essential factors for social inclusion of young people in society, so it is important to study young people who are neither in education or in employment (called NEETs) to determine how they deal with their social status and their mechanisms to integrate into society. This study examines how negatively or positively NEET young people perceive their social status, how NEET status affects young people's attitudes, social identity, or well-being, and whether young people try to escape from the status of NEET. The survey was conducted with 380 young people and in-depth interviews with 12 people. Research shows that the social status of NEET is neither desirable nor appreciated. NEETs are associated with diminished well-being mainly because of their lower life satisfaction. NEET youth scores lower than the general population in life satisfaction, although they have similar level of self-esteem. Research has shown that NEET youth use psychological mechanisms, such as identifying with a positively assessed group, to help young people maintain high self-esteem or use strategies to escape from the NEETs group, get a job, or continue their education. The following factors positively contribute to the desire to leave the NEET group: self-esteem is the most important motivator, followed by social identity, attitudes towards education and employment, and family economic status. The high NEET rate in Georgia suggests that NEETs youth should be a particular target group for interventions to enable their ‘activation’ to integrate into society. Keywords: attitudes towards education, attitudes towards employment, NEET youth, social identity, well-being

Being NEET in Youthspaces of the EU South: A Post-recession Regional Perspective

Youth unemployment and precarity have been expanding in the aftermath of the recent global recession. This article offers a theoretically informed empirical examination of the spatio-temporally uneven expansion of young people ‘Not in Employment, Education or Training’ (NEETs) between 2008 and 2018 in the European Union (EU) South, namely in Italy, Spain, Greece and Cyprus. This article contributes to the growing literature on youth inactivity and marginalization, by focusing on the spatial, rather than just the temporal dimension of youth which marks most relevant studies. The analysis engages with the concept of ‘youthspaces’ to critically analyse the economic, social and political spatialities that determine the dynamic relationship between youth and the labour market, and discuss the persistently high NEET rate in the EU South. Employing a mixed-methods approach, we highlight that gender, class, education and economic growth are key socio-spatial factors that determine the geographically uneven expansion of NEETs across the study regions.

Is there a uniform NEET identity in the European Union?

ABSTRACT During the last decade, the policy efforts aiming to tackle the NEET situation (young people who neither study nor work) have increased dramatically in the European Union. Meanwhile, many studies challenged those policies, showing how they failed due to lack of understanding the NEETs. Thus, we analyse the factors that influence the appearance, modification and elimination of a NEET identity. The results reveal the presence of a shared NEET identity in the countries with high NEET rates, despite the considerable differences in the countries’ and NEETs’ characteristics. The NEET rate stands out as the key factor influencing the NEET identity, showing that this identity depends more on economic cycles than on the specific country or its culture.

The Impact of Education on Youth Employability: The Case of Selected Southeastern European Countries

This paper focuses on the processes of school-to-work transitions in a selected group of countries from South-eastern Europe (SEE), namely: Bosnia and Herzegovina; Croatia; Montenegro; North Macedonia; Serbia; and, Slovenia. Each of these countries display the same roots of development in their educational systems: however, due to their transition and integration processes within the European Union, they implemented different concepts of reforms within their educational systems. In addition, the challenges of youth employability are a common problem for each of the selected countries, and the effectiveness of the processes of school-to-work-transition varies across the countries. By using panel data and multiple linear regression models, this paper estimates the impact of different educational levels on youth employability and changes in the rates of NEET population (aged 15–24) in the selected group of countries over the period 2009 to 2019. The results suggest that the impact of the attained level of education has an ambiguous effect on the rates of youth employment; moreover, the relationship with changes in NEET rates are statistically significant and negative in most of the selected group of countries.

Are Some Canadian Youth NEETer than Others? Examining North-South and Rural-Urban Inequalities in Education, Employment, and Training

A growing body of research studies youth not actively involved in education, employment, or training (NEET). Some recent estimates of NEET place Canadian youth at slightly below the OECD average. At the same time, however, researchers have identified a number of regional barriers that present unique challenges to labour market participation for Canadians residing in northern and rural areas. In this article, we investigate the extent to which regional differences contribute to the labour market inactivity of Canadian youth. Using multiple waves of Statistics Canada’s Youth in Transition Survey (YITS-A), we find that indeed NEET rates differ for youth who reside in northern and southern Canada. Northern, rural youth show significantly higher probabilities of being NEET between ages 20 and 22. Moreover, these regional differences in NEET status continue to have a strong and independent effect, even when accounting for socio-demographic characteristics, parental socio-economic factors, educational experiences, and family structure. These inequalities in early workforce outcomes have important implications for policy-makers, as they seek new ways of bolstering the school to work transitions of northern and rural youth.

Professional and educational activity of youth in the digital economy

The paper is aimed to rank countries similar in terms of selected diagnostic variables: in terms of digital competencies held and variables related to the youth professional activity. The method of descriptive and statistical analysis, including comparative analysis, is used in the study. The paper also uses cluster analysis. The conducted analysis included the empirical material referring to the youth at the age of 15-29 taken from the Eurostat database. The research period is 2011–2019. The analysis by type of educational and professional activity of young people conducted in the EU member countries allowed the identification of four groups of countries, differing in the levels of both the NEET rate (Neither in employment nor in education or training) and the digital skills. The digital skills have been additionally grouped into competences in the field of information, communication, problem-solving and programming skills. The group of countries with the lowest NEET rate proved to include those where young people presented high levels of digital skills in all the dimensions analyzed. The study shows that acquiring digital competencies enables young people to participate in communities and gives them a better chance for professional activity.

Not in education, employment and training status in the early stages of bipolar I disorder with psychotic features.

There is a lack of existing research regarding young people with bipolar I disorder (BD-I) and psychotic features, who are not in education, employment, and training (NEET). Thus, the aims of the study were to: (a) establish rates of NEET at service entry to a specialist early intervention service; (b) delineate premorbid and current variables associated with NEET status at service entry and (c) examine correlates of NEET status at discharge. Medical file audit methodology was utilized to collect information on 118 patients with first episode psychotic mania treated at the Early Psychosis Prevention and Intervention Centre (EPPIC), Melbourne, Australia. NEET status was determined using the modified vocation status index (MVCI). Bivariate and multivariable logistic variables were used to examine relationships between premorbid, service entry and treatment variables, and NEET status at service entry and discharge. The NEET rate was 33.9% at service entry, and 39.2% at discharge. Variables associated with NEET status at service entry were premorbid functioning and polysubstance use. NEET status at service entry was the only significant correlate of NEET status at discharge. When service entry NEET was taken out of the model, substance use during treatment was predictive of NEET status at discharge. NEET status at service entry was related to a history of premorbid decline, and risk factors such as substance use and forensic issues. NEET status can decline during treatment, and utility of vocational intervention programs specifically for BD, in addition to specialist early intervention, needs to be examined.