Fact-checked by Grok 2 weeks ago

Neet

NEET, an acronym for "Not in , , or Training," designates individuals—predominantly aged 15 to 29—who are disengaged from formal , , or vocational training activities. The term emerged in the during the 1980s to describe a growing of disconnected young people amid economic shifts, and it has since been adopted internationally by organizations tracking labor market participation. While NEET status can affect any demographic, it disproportionately impacts those with lower , limited work experience, or health challenges, reflecting deeper structural and personal barriers to integration into productive societal roles. Prevalence of NEETs varies widely by region and economy, with the reporting an average rate of 14% among in member countries as of , down from pre-pandemic peaks but still signaling persistent challenges in youth transitions to adulthood. In the , rates for those aged 15-29 ranged from 5% in the to 19% in in recent , often higher among women due to factors like caregiving roles classified outside formal or work. Globally, the highlights elevated NEET figures in developing economies, where insufficient job creation exacerbates disconnection, contributing to broader social anxieties over prospects. Empirical analyses underscore that NEET periods correlate with long-term scarring effects, including reduced lifetime earnings and heightened vulnerability to . Key risk factors identified in peer-reviewed syntheses include deficient skills, physical or impairments, family , and marital dynamics, with issues—such as or anxiety—emerging as a leading driver of economic inactivity in multiple contexts. NEET youth face elevated odds of adverse outcomes, including a 2.8-fold increase in risk and doubled likelihood of criminal involvement compared to engaged peers, based on meta-analytic evidence from diverse studies. These patterns persist despite interventions like targeted training programs, suggesting that causal pathways often involve intertwined individual agency deficits and systemic disincentives, such as overly generous welfare provisions that may prolong disengagement in some welfare states. Addressing trends demands rigorous evaluation of interventions, prioritizing those grounded in verifiable gains over ideologically driven narratives that downplay .

Definition and Terminology

Core Definition

A , an for "Not in , Employment, or ," refers to an individual who is neither employed nor enrolled in formal or vocational . This status encompasses youth who are unemployed and actively seeking work, as well as those who are inactive—such as discouraged workers not seeking employment—provided they are not participating in any structured learning or skill-building programs. The definition relies on self-reported data from labor force surveys, where employment follows (ILO) standards, including paid work, , or family assistance for at least one hour per week, while and exclude informal or unpaid activities unless formally recognized. The term primarily categorizes young people, with age ranges varying by institution: focuses on ages 15-24 for youth NEET rates, while the extends to 15-29 to capture prolonged disengagement. Unlike narrower metrics like the rate, which requires active job search, the NEET classification highlights broader social disconnection, including those detached from both labor markets and development. This broader scope aids in identifying potential long-term risks such as skill atrophy and dependency, though it may overlap with temporary states like or short-term illness in some national adaptations.

Historical Origins of the Term

The concept underlying the designation emerged in the during the early 1990s, initially termed "Status Zer0" (later stylized as "Status 0") to categorize 16- and 17-year-olds who fell outside standard labor market or al classifications in career services records, ineligible for due to age but disconnected from structured activities. This label highlighted a small —estimated at around 1-2% of the age group—who were neither in full-time , apprenticeships, , nor schemes, often linked to post-compulsory transitions amid rising disconnection. The acronym , expanding to "Not in , , or Training," first appeared in academic and policy discussions in the mid- as a more precise alternative to "Status Zer0," reflecting broader concerns over youth disengagement beyond administrative gaps. It entered official British government lexicon on July 29, 1999, via the Unit's report Bridging the Gap, which analyzed persistent non-participation among 16- to 18-year-olds and advocated targeted interventions, marking the term's shift from descriptive tool to policy metric. This formalization emphasized empirical tracking of at-risk youth, with data showing approximately 7% of 16- to 18-year-olds in fitting the criteria by the late , often concentrated in disadvantaged regions. In various countries, local terms have emerged as equivalents or close analogs to NEET, reflecting similar phenomena of youth disengagement from education and formal employment. For instance, in , particularly and other Spanish-speaking nations, the term ni-ni—short for ni estudia ni trabaja (neither studies nor works)—describes young people outside these spheres, often carrying stronger due to cultural expectations of . This usage parallels NEET in policy discussions but emphasizes involuntary idleness amid economic informality. In Portuguese-speaking contexts like and , analogous expressions such as nem-nem convey the same "neither-nor" detachment. Japan features distinct but interrelated concepts: hikikomori refers to acute social withdrawal, where individuals (predominantly young males) isolate themselves in their residences for extended periods, often six months or more, avoiding social interactions entirely; while overlapping with NEET status due to lack of employment or training, hikikomori is differentiated by its psychological intensity and deviation from societal norms, with estimates suggesting over 1 million cases by 2010. Complementing this, freeter (from freelance + arubaito, or part-time work) denotes young adults voluntarily opting for irregular, low-commitment jobs to evade rigid corporate structures, thus involving partial labor engagement unlike the total exclusion in NEET or hikikomori. These terms highlight cultural variances, with Japanese variants often tied to post-bubble economy pressures and collectivist values. The label itself masks internal heterogeneity, including subgroups such as active job seekers facing barriers, "opportunity explorers" testing informal paths, the "unavailable" (e.g., due to caregiving or ), and the "decommitted" who have disengaged entirely; this diversity challenges its utility as a monolithic indicator, as aggregated statistics may overlook causal distinctions like versus personal withdrawal. Academic critiques argue the category overemphasizes individual failings while homogenizing experiences, potentially inflating perceived without accounting for voluntary choices or temporary states. Internationally, 's application varies, with some studies refining it via longitudinal tracking to distinguish persistent from episodic cases, revealing that up to 20-30% of experience short-term NEET spells globally, per labor organization data.

History

Emergence in the

The category emerged in the amid structural shifts in youth labor market statistics during the late , when reforms to benefit eligibility under the 1988 rendered most individuals under age 18 ineligible for , thereby excluding them from official counts. This policy change, intended to encourage completion and apprenticeships, created a statistical "blind spot" for disengaged youth, prompting analysts to develop alternative metrics for tracking those detached from , employment, or training. The term "" was initially formulated in academic research rather than formal policy, with early references appearing in a study by Istance, Rees, and on disconnection in , , where it described 16- to 18-year-olds outside conventional labor market or educational pathways. This built on prior observations of rising inactivity amid and post-school transitions, but the crystallized the concept for broader application. By the mid-1990s, the label gained traction in policy circles to quantify an estimated 160,000 to 200,000 young people aged 16-18—roughly 7-12% of the cohort—not engaged in productive activities, distinct from the unemployed who actively sought work. Policy recognition accelerated under the government, with the Social Exclusion Unit's 1999 report Bridging the Gap formally elevating NEET as a key indicator of , linking it to risks of long-term dependency and crime. The report estimated 7% of 16- to 18-year-olds as NEET, advocating targeted interventions like the for Young People program launched in 1998, which emphasized work-focused gateways over passive benefits. This framing reflected causal emphases on individual agency deficits alongside economic barriers, though critics later noted potential overemphasis on supply-side factors amid persistent regional disparities in manufacturing decline.

Spread to Other Countries

The NEET framework, developed in the during the late 1990s, disseminated internationally via multilateral organizations focused on labor market analysis. The (OECD) integrated NEET metrics into its comparative youth indicators around the early 2000s, enabling standardized measurement of youth detachment from , , or training across approximately 38 member countries by 2007. This adoption facilitated policy benchmarking, as OECD reports highlighted variations in NEET prevalence tied to national economic structures and education systems, prompting governments to adapt the category for domestic use. Within Europe, the incorporated the NEET concept into its youth employment strategies under the framework launched in 2000, with compiling NEET data from member states to quantify risks of . Countries such as , , and reported NEET shares exceeding the EU average of about 10% for ages 15-24 by the mid-2000s, leading to targeted interventions like programs modeled on examples, though structural rigidities in southern European labor markets amplified the phenomenon beyond initial UK patterns. In , adapted the terminology in the early to address youth labor market deviations from lifetime employment norms, defining it for ages 15-34 excluding those in housework, with government surveys in 2002 estimating 2.4% of this group—roughly 540,000 individuals—as , often overlapping with (irregular workers) and (social recluses). The Japanese of , and established a support by 2004, reflecting causal links to post-bubble and rigid hiring practices that discouraged mid-career entry. Similar uptake occurred in , where the term entered policy lexicon amid rising youth inactivity rates, with the Korea Labor Institute tracking s from 2003 onward to inform vocational reforms. The (ILO) further globalized the indicator by the mid-2000s, applying it beyond nations to developing economies, though definitional variations persisted—such as age cutoffs (typically 15-24) and exclusions for informal work—highlighting the UK's original focus on formal detachment as a baseline for of driven by skill mismatches or discouragement. This diffusion underscored empirical regularities in disengagement linked to globalization's uneven impacts on entry-level , rather than uniform cultural shifts.

Evolution Post-2008 Financial Crisis

The 2008 global financial crisis triggered a sharp rise in rates across countries, as economic contraction led to widespread layoffs in entry-level sectors and reduced hiring for young entrants, amplifying youth-specific vulnerabilities such as limited experience and network effects. rates surged, with many transitioning from job-seeking to inactivity due to prolonged discouragement, pushing aggregate levels higher than pre-crisis baselines. For instance, in the , the rate for 15- to 24-year-olds climbed from approximately 11.5% in 2008 to peaks around 13-15% by 2013-2014, reflecting both cyclical downturns and emerging structural barriers like skill mismatches between education outputs and labor demands. This evolution marked a shift from transient unemployment to more entrenched inactivity, with empirical analyses indicating increased short-term persistence of NEET status post-recession, particularly among males, as initial labor market setbacks reduced future employability through depreciation and scarring effects. In southern European economies like , , and , NEET rates exceeded 20-25% during the sovereign debt phase of the crisis (2010-2015), driven by austerity measures that curtailed jobs and training programs, contrasting with more resilient northern counterparts such as , where rates hovered below 8% due to robust systems. Globally, developing regions experienced parallel spikes, though data gaps limit precision; in the United States, the NEET share for 16- to 24-year-olds rose from 14.5% in 2007 to over 16% by 2010, correlating with a peak of nearly 20% for young men. Recovery trajectories diverged post-2014, with NEET rates declining in many OECD nations amid quantitative easing and labor market rebounds, yet failing to revert to pre-2008 lows in crisis-hit areas, sustaining elevated baselines around 12-13% EU-wide by 2019. Longitudinal evidence highlights causal persistence: individuals entering NEET during the recession faced 10-20% higher odds of extended spells compared to pre-crisis cohorts, attributable to eroded confidence, mental health declines, and mismatched vocational training rather than solely demand shortfalls. Policy interventions, such as expanded apprenticeships in the UK (where NEET peaked at 16.9% in 2011) and EU Youth Guarantee schemes launched in 2013, mitigated some increases but exposed limitations in addressing underlying factors like over-reliance on tertiary education without practical skills alignment. By 2023, lingering effects included intergenerational transmission risks, with post-recession NEET youth more prone to low-wage traps, underscoring the crisis's role in entrenching NEET as a chronic rather than episodic phenomenon.

Prevalence and Statistics

The global NEET rate for aged 15-24 stood at 20.4% in 2023, equivalent to 256 million individuals, according to data from the (ILO). This figure encompasses not only the unemployed but also those detached from and , highlighting broader labor market disengagement beyond traditional metrics, which fell to a 15-year low of 13% (affecting 64.9 million ) in the same year. Regional disparities remain stark, with NEET rates surpassing 25% in , the , and , compared to under 10% in and the Pacific. Post-2008 trends showed an initial surge in populations due to economic contraction and youth labor market entry barriers, with global rates climbing toward 15-20% by the mid-2010s before stabilizing amid uneven recoveries. The exacerbated this, pushing rates upward by 2-5 percentage points in many economies through 2020-2021 via lockdowns and educational disruptions, though by the first quarter of 2024, levels in most countries had reverted to or dipped below pre-pandemic baselines, reflecting labor market rebounds in sectors like services and manufacturing. Nonetheless, persistent structural factors—such as skill mismatches, displacement, and demographic pressures in aging societies—have sustained elevated shares in developing regions, where informal economies fail to absorb youth entrants adequately. Gender imbalances amplify global trends, with female rates roughly double those of males (28% versus 14% in 2023), driven by disproportionate unpaid , early marriage, and discriminatory barriers in low- and middle-income countries. Projections from the ILO indicate potential stagnation or slight increases toward 2025, with an estimated 262 million youth—one in four—potentially disengaged amid rising work-related anxieties reported by 60% of surveyed youth, underscoring the need for targeted interventions beyond cyclical recoveries. In advanced economies tracked by the , NEET rates hover around 10-15%, with transitions from education to work improving marginally; for instance, 54% of 18-24-year-olds remain in education across OECD members as of 2023, yet 19% combine study with employment, signaling partial mitigation through dual pathways.

Regional and National Data

In 2023, the global youth rate stood at 20.4% for individuals aged 15-24, with pronounced gender disparities: 28.1% for females and 13.1% for males. Rates are generally lower in high-income regions like and countries, averaging around 14% for 18-24 year-olds across the latter, due to stronger labor markets and education systems, while higher in low- and middle-income areas such as and , where and limited opportunities prevail. Within the , the NEET rate for 15-29 year-olds averaged 11.0% in 2024, a decline of 4.7 percentage points since 2014, though variations persist across member states. Southern and Eastern European countries report elevated figures, such as at 15.2% and at 19%, attributable to slower economic recovery and youth emigration, whereas Northern states like the (5%) and exhibit rates below the EU's 2030 target of 9%. National data further illustrate disparities, with advanced economies showing resilience post-pandemic while emerging markets face persistent challenges. The following table summarizes selected rates, noting age group differences across sources:
Country/RegionNEET Rate (%)YearAge GroupNotes
5202415-29Lowest in ; strong vocational training integration.
8.0202415-24Reflects cultural emphasis on education and low .
15.2202415-29Above average; linked to regional economic divides.
38.0202415-24Highest among sampled; driven by skills mismatches and .
These figures, drawn from labor force surveys, underscore how NEET prevalence correlates with GDP per capita and education access, though data comparability is limited by methodological variations in inactivity definitions.

Demographic Patterns

Globally, NEET status disproportionately affects young females, with the (ILO) reporting a 2023 rate of 28.1% for females aged 15-24 compared to 13.1% for males, comprising two-thirds of the 256 million total NEET youth. This gender disparity is attributed primarily to burdens on women in low- and middle-income countries, though it narrows in high-income economies where female rates approach or slightly exceed male rates, such as 10.7% versus 10.1% in 2023. NEET rates inversely correlate with educational attainment, remaining elevated among those with low or no formal education; in the , the 2024 rate for 15-29-year-olds with low education levels stood at 12.6%, compared to lower figures for those with medium or high attainment. The ILO notes that significantly reduces NEET risk across income groups, particularly for women in lower-middle and low-income countries, though educated in these regions face higher due to skill-job mismatches.
Region (2023)Total NEET Rate (%)Female Rate (%)Male Rate (%)
Arab States33.246.321.1
26.442.413.0
21.927.016.9
High-Income10.410.710.1
Rural areas exhibit higher NEET prevalence than urban ones globally, driven by limited job and access. By ethnicity and race, patterns vary nationally: in the United States, and youth show elevated rates, with women at the highest among major groups in 2022 data; in the , // youth had a 15.2% rate in recent surveys, exceeding youth; Canadian racialized groups experienced a 2.0 rise in NEET rates for ages 20-29 as of 2025. These disparities often reflect intersecting factors like and socioeconomic barriers rather than inherent group differences.

Causes and Risk Factors

Economic and Structural Causes

Economic downturns represent a primary driver of elevated rates, as youth are disproportionately affected by cyclical during recessions. The 2008 global financial crisis, for instance, led to a marked rise in NEET prevalence across countries, with rates failing to fully recover in many regions even years later due to persistent labor market contraction. In Ireland, the rate surged from 9.9% to 33% between 2008 and 2012, paralleling an increase in the NEET proportion from 10.1%. Such shocks reduce availability, particularly in sectors like and that traditionally absorb young workers, amplifying inactivity among those lacking experience. Structural mismatches between educational outputs and labor market needs further entrench status by hindering smooth transitions from schooling to work. Lower correlates strongly with risk, as without secondary or tertiary qualifications face barriers in accessing formal amid evolving demands. Insufficient creation of decent, high- jobs—especially in middle-income economies—exacerbates this, with global rates holding at 20.4% in despite falling overall , reflecting a of stable positions matching capabilities. Over half of young workers remain in informal worldwide, which offers limited pathways to development or secure careers, perpetuating disconnection from structured training or advancement opportunities. Socioeconomic inequalities and poverty amplify these dynamics, creating intergenerational barriers to labor market participation. Family-level poverty restricts access to quality education and initial work experience, with empirical reviews identifying it as a critical indicator of NEET vulnerability through reduced household resources for training or relocation. In regions with low labor market dynamism, such as parts of East Asia and the Arab States, structural rigidities like limited formal sector expansion sustain higher NEET shares compared to pre-2019 levels, underscoring how entrenched inequalities compound economic exclusion. These factors collectively foster a cycle where initial disadvantages in skills or networks impede re-entry, independent of individual effort.

Social and Cultural Influences

Social structures such as family instability and weakened peer networks elevate the risk of status. Studies indicate that youth from single-parent families or those experiencing early parenthood face significantly higher probabilities of disconnection, with data from 2023 identifying these as key family-level predictors alongside low parental . Disturbed peer relations further compound vulnerability, as evidenced in multicultural cohorts where poor ties correlate with NEET outcomes independent of economic factors. Cultural norms surrounding the transition to adulthood have evolved in many societies, fostering extended periods of emerging adulthood that delay entry into or . This prolongation, marked by deferred milestones like , aligns with higher persistence, particularly in where youth report mismatched self-perceptions of maturity against traditional expectations. In contexts like , individuals explicitly link their status to unachieved adult roles, reflecting broader societal shifts away from early workforce integration. Community-level social dynamics, including geographic isolation and neighborhood disadvantage, reinforce NEET patterns through diminished and normative inactivity. European analyses show that residing in deprived areas doubles NEET likelihood, attributable to localized social environments lacking employment or supportive networks. Rural-urban divides exacerbate this, with rural exhibiting 20% higher disconnection rates tied to cultural insularity and limited opportunities. In select cultural settings, collectivist pressures intersect with social withdrawal, as observed in where societal expectations amplify isolation akin to NEET profiles, blending individual retreat with communal norms against failure. Gender-specific cultural barriers also persist, with entrenched roles in some regions confining women to domestic spheres and inflating female rates despite available . These influences underscore how societal fabrics, beyond pure economics, sustain disconnection by shaping expectations and opportunities.

Individual and Behavioral Factors

Mental health disorders represent a primary individual for status, with longitudinal studies demonstrating that conditions such as , anxiety, (ADHD), disorders, , and during childhood and adolescence strongly predict entry into NEET in young adulthood. Poor not only precedes NEET but also exacerbates it through symptoms like reduced motivation and withdrawal from social and occupational activities, with NEET individuals showing elevated rates of psychiatric disorders, , and substance use problems compared to non-NEET peers. Personality traits further contribute to NEET vulnerability, particularly low —characterized by diminished and for long-term goals—which empirical assessments identify as a key psychological predictor of sustained NEET status among . NEET young adults often exhibit rigid personality structures involving disorganization, , and deficits in emotional regulation and stress tolerance, hindering adaptation to or demands. Associated traits include low , reduced , introversion combined with poor communication skills, and inadequate hope, all of which correlate with prolonged disengagement from productive activities. Behavioral patterns amplify these risks, with adolescent histories of , peer conflicts, and low prosocial behaviors showing consistent links to outcomes in prospective cohort analyses. Risky behaviors, such as use and inadequate mechanisms, alongside low mental , perpetuate cycles of avoidance and failure to engage in or work, independent of structural barriers. These individual-level dynamics underscore how internal psychological and volitional elements, rather than solely external forces, sustain trajectories in many cases.

Consequences and Impacts

Effects on Individuals

Prolonged status is associated with elevated risks of disorders, including , anxiety, and substance use problems, beyond what pre-existing conditions alone explain. Empirical analyses of cohorts show that NEET youth exhibit higher prevalence of concurrent psychological issues, with self-perceptions of failure in work-related domains mediating poorer outcomes. Longitudinal data from British birth cohorts indicate that experiencing NEET periods in early adulthood correlates with increased prescriptions for antidepressants and anti-anxiety medications in later years. NEET individuals report significantly worse self-perceived physical compared to non-NEET peers, with rates of poor or fair health standing at 11.3% among NEETs versus 5.6% among others in adolescent samples. Long-term follow-ups reveal heightened hospitalization risks for physical ailments among those with extended NEET histories, suggesting a where inactivity exacerbates somatic decline. These patterns persist even after controlling for baseline , pointing to inactivity as a causal contributor to diminished and conditions like musculoskeletal . Economically, spells lead to "scarring" effects on career trajectories, including reduced lifetime and persistent barriers to skilled due to skill depreciation and signaling of unreliability. Non-cognitive abilities such as atrophy during inactivity, widening gaps in relative to continuously engaged . Cohort studies confirm that early NEET status predicts adverse labor market attachment into adulthood, with low-skilled individuals facing compounded future unemployment risks. Socially, status fosters isolation and eroded , heightening vulnerability to exclusion and , as evidenced by qualitative and quantitative reviews linking prolonged disconnection to diminished interpersonal networks and . These individual-level harms compound over time, with sustained periods correlating to higher on public support and lower overall well-being metrics.

Broader Societal Costs

The prevalence of status among imposes substantial economic burdens through foregone and output. In the , estimates based on 2008 data indicate that NEETs aged 15-24 contributed to annual economic losses equivalent to approximately 1.5-2.2% of GDP across member states, primarily from reduced labor force participation and associated scarring effects on lifetime earnings. Globally, high NEET rates exacerbate and hinder growth, with each percentage point increase in NEET prevalence linked to measurable declines in national , as disengaged fail to contribute to economic processes. Fiscal costs arise from heightened reliance on public systems and reduced tax revenues. In the , the lifetime fiscal impact per individual entering status at age 16 or 18 exceeds £50,000, encompassing elevated welfare expenditures, lower income tax contributions, and increased demands on health and ; aggregate costs for the cohort of 16-18-year-olds have been projected as low as £22 billion and as high as £77 billion in resource terms. These burdens reflect not only immediate benefit payments but also long-term opportunity costs, with NEET periods correlating to persistent and dependency. For female NEETs, societal costs can reach 1.62-2.49% of GDP in affected economies, exceeding those for males due to compounded effects on family formation and caregiving roles. Social repercussions extend to elevated risks of , deterioration, and community fragmentation. individuals exhibit higher incidences of criminal behavior and , alongside broader societal exclusion that undermines social cohesion and increases public safety expenditures. Post-crisis analyses show s facing entrenched barriers to , amplifying intergenerational transmission of disadvantage and straining networks without corresponding economic offsets. These outcomes underscore causal links between prolonged disengagement and amplified costs, including untreated issues that persist into adulthood.

Policy Responses and Interventions

Approaches in High-Income Countries

In high-income countries, policy responses to populations prioritize activation strategies that integrate vocational training, apprenticeships, and personalized employment services to facilitate transitions into work or . These approaches often feature "youth guarantees" mandating timely offers of jobs, continued schooling, or traineeships, alongside targeted support for barriers such as skills gaps or challenges. Funding typically draws from national budgets and supranational mechanisms, with an emphasis on early intervention to mitigate long-term disconnection. The European Union's Youth Guarantee, implemented since 2013 and reinforced in 2020, requires member states to extend offers of , continued , apprenticeships, or traineeships to individuals aged 15-29 within four months of unemployment or exiting formal . Supported by €22 billion in EU funding from 2021-2027, including €11 billion from the European Social Fund Plus, the scheme allocates at least 12.5% of resources in high-NEET countries toward activation measures and prioritizes vulnerable subgroups like migrants and those with disabilities. Complementary initiatives include the program for disadvantaged NEETs and updated quality frameworks for traineeships to ensure fair conditions and relevance to labor market needs. While NEET rates have declined since implementation—averaging 12.6% in 2019 with a target of 9% by 2030—evaluations note persistent challenges in securing sustainable, quality outcomes beyond initial placements. In the , the government's Get Britain Working of November 2024 outlines a Guarantee providing every 18- to 21-year-old with access to , apprenticeships, or tailored , building on prior schemes like foundation apprenticeships for entry-level skills and a centralized Jobs and Careers for guidance. These measures address a rate of 12.5% (948,000 individuals aged 16-24) as of April-June 2025, up from pre-pandemic lows, amid post-Brexit and economic pressures. Historical programs, such as the now-defunct Kickstart scheme, emphasized subsidized jobs, but current efforts focus on integrating and employer partnerships to boost participation. The employs the term "opportunity youth" or "disconnected youth" for NEET equivalents aged 16-24, with federal programs under the channeling funds into job training, education recovery, and sector-specific skills like or healthcare. , operational since the , serves at-risk by combining GED attainment, vocational certification, and , enrolling thousands annually through grants. Other initiatives, including Performance Partnership Pilots since 2015, allow flexible funding for holistic services like mentoring and housing assistance, while the Reconnecting Youth project compiles evidence on scalable models emphasizing rapid re-engagement. These target structural disconnection affecting over 4.5 million , prioritizing evidence-based practices over universal guarantees. Japan's response, confronting elevated NEET rates among 15-34-year-olds, includes Regional Youth Support Stations established in 2006 for counseling and social reintegration, alongside youth-specific Hello Work employment offices offering job-matching and communication training. The Basic Plan for Working Youth Welfare Measures provides consultations with career advisors and operates around 500 National Homes for transitional housing and skill-building. These address cultural factors like employment precariousness ("freeters") and withdrawal ("hikikomori"), with policies since the early 2000s focusing on non-coercive outreach to counter long-term inactivity affecting over 500,000 youth as of recent estimates. Systematic reviews of interventions in these contexts highlight efficacy in models like Individual Placement and Support (IPS), which integrates treatment with rapid job placement, yielding employment rates of 48-82% in trials from , the , and compared to 8-42% in controls. Intensified training and job-search assistance also boost training uptake (e.g., 46% vs. 35% in ) and school returns, though outcomes vary by subgroup, with stronger results for younger or female participants; broader activation programs show modest impacts without addressing underlying disincentives like dependencies.

Strategies in Developing Regions

In developing regions, strategies to address status among youth prioritize supply-side interventions such as vocational training combined with practical work experience, which have demonstrated positive short-term effects on and in evaluations across countries like , , and . For instance, programs like Peru's Jóvenes Productivos provide career guidance and skills alignment with labor market needs, targeting to facilitate transitions into formal or informal work. Similarly, initiatives offering cash grants, credit access, and business training—such as Uganda's programs—have boosted non-farm and profits, particularly for groups including ex-combatants and women, though impacts often require sustained support to avoid fading after 2-3 years. Demand-side measures focus on job creation in high-potential sectors like , , and green economies, with examples including South Africa's Presidential Employment Initiative, which has generated 1.57 million opportunities since 2021 by incentivizing hiring in informal and . In , interventions emphasizing cognitive, socio-emotional, and technical skills aid school-to-work transitions for young women, who comprise a disproportionate share of NEETs due to unpaid burdens and gender norms. Regional adaptations, such as Thailand's National Economic and Social Development Plan (2023–2027) aiming to re-engage 100,000 NEETs through ecosystem platforms, underscore the value of multidimensional approaches integrating education, matching, and incentives. In and , where rates exceed 20-25% in many areas, public-private partnerships for digital skills enhancement via mobile-first and community-based training address infrastructure gaps and informal sector dominance, promoting in emerging tech roles. Low-cost financial incentives like transport subsidies have improved formal job access in and , while hybrid models in combine public funding with private delivery for scalable outcomes. Overall, evidence from over 100 impact evaluations indicates moderate effectiveness for bundled programs targeting priority groups, but highlights needs for rigorous diagnostics of local economies and long-term monitoring to mitigate effects and ensure .

Evidence of Effectiveness

Systematic reviews of randomized controlled trials and quasi-experimental studies indicate limited high-quality evidence supporting the effectiveness of interventions aimed at re-engaging youth in , , or . A 2017 meta-analysis of three high-quality trials found that intensive multi-component interventions, such as combined vocational , internships, and case management, yielded only a 4% absolute increase in rates compared to controls (95% : 0.0–0.7; 1.04, 95% : 1.00–1.07), a borderline significant effect driven by short-term outcomes. Overall, across 18 reviewed trials, and re-engagement effects were inconsistent, with many programs showing no sustained benefits beyond six months. More recent evaluations highlight modest successes in specific models but underscore persistent challenges. A 2024 systematic review of nine trials (eight RCTs) identified positive effects in five studies, particularly for Individual Placement and Support () approaches, which integrate rapid job placement with ongoing coaching; one trial reported 82% in the IPS group versus 42% in controls. Multi-component programs combining skills , counseling, and temporary work placements showed mixed results for return, with three trials demonstrating improvements, though heterogeneity prevented . Secondary outcomes like and improved in some cases, but drug use and showed negligible changes. Broader analyses of youth programs, including those targeting disadvantaged groups akin to NEETs, reveal that skills training and (e.g., training plus employment subsidies) produce significant positive labor market effects in about 35% of 3,105 estimates, with stronger short-term gains in earnings and when follow-up exceeds one year. However, subsidized and standalone services underperform, and long-term remains rare without mechanisms like participant profiling or provider incentives. A comprehensive review from 2000–2019 concluded no convincing evidence for any specific intervention type, attributing variability to high dropout rates and inadequate addressing of underlying barriers like or motivation. In high-income contexts, structural factors such as systems correlate with lower rates (e.g., Germany's dual model maintains rates below 5%), but causal evidence from targeted interventions remains weak, with many evaluations suffering from small samples, short follow-ups, and selection biases favoring motivated participants. Programs emphasizing , structured routines, and show theoretical promise as common elements, yet empirical validation is lacking, highlighting the need for rigorous, long-term trials to distinguish causal impacts from or Hawthorne effects.

Controversies and Debates

Critiques of Welfare Incentives

Critics argue that generous systems, particularly support without work requirements, create disincentives for young people to seek or , thereby contributing to higher rates among low-skilled . These disincentives arise from "welfare traps," where benefits phase out sharply upon earning income, resulting in high effective marginal tax rates that make low-wage work less attractive than remaining on support. Empirical evidence from illustrates this effect: a 55% increase in maximum payments for childless unmarried individuals at age 25 led to a 2-3% decline in among low-skilled , with benefit take-up rising 10-14%, primarily through transitions from work to and reduced labor market entry. This causal response was concentrated at very low earnings levels, highlighting how benefit generosity can deter initial participation for those with limited skills. Similar patterns emerge in other contexts, such as France's Revenu Minimum d'Insertion (RMI) , where age-based eligibility discontinuities reveal disincentive effects on labor supply, with uneducated single men showing reduced participation when benefits become available. Critics, including economists analyzing budget constraints, contend that such traps are exacerbated for lacking qualifications, as entry-level jobs offer wages barely exceeding benefits, fostering dependency rather than skill-building. Cross-nationally, higher —encompassing lower regulatory burdens and reduced state intervention in labor markets—correlates with lower rates in the , with from 2002-2022 showing consistent reductions across subgroups through mechanisms like eased market entry and promotion. While some aggregate studies link higher public social spending to lower NEET prevalence, particularly via and active labor market expenditures, detractors emphasize that passive and family benefits often yield net disincentives by subsidizing idleness over . For instance, in systems with high replacement rates (benefits as a percentage of prior wages), persists despite spending, as evidenced by structural rigidities in high- European economies compared to more flexible ones. These critiques underscore the need for designs prioritizing work incentives, such as gradual phase-outs or mandatory , to mitigate traps without eliminating support nets. Empirical reforms reducing such disincentives, like those in Denmark's programs for young recipients, have shown potential to boost exits from , though long-term youth-specific data remains limited.

Debates on Personal Responsibility vs.

The debate over status often pits explanations rooted in individual agency and personal choices against those emphasizing structural barriers and systemic deficiencies. Advocates for personal responsibility contend that many young people become due to avoidable decisions, such as early school dropout or failure to acquire marketable skills, which reflect lapses in or effort. For instance, studies highlight that lack of prior work experience and low skill levels are significant predictors of outcomes, suggesting that proactive engagement in or entry-level could mitigate risks. However, empirical analyses challenge simplistic attributions of , finding that youth report comparable levels of to non-NEET peers but encounter entrenched psychological barriers, including issues that precede disengagement. Conversely, systemic failure perspectives attribute NEET prevalence to macroeconomic and institutional shortcomings, such as rates, regional economic disparities, and inadequate educational preparation for labor market demands. Systematic reviews of risk factors consistently identify disadvantaged socioeconomic backgrounds, family , and low parental as strong correlates, with odds ratios indicating up to 2-3 times higher NEET likelihood among those from such environments. Municipal-level data further supports this, showing that a 1% increase in local elevates individual NEET risk by 0.5 percentage points, independent of personal traits. These findings underscore causal pathways from early adversities—like poor schooling access—to prolonged marginalization, though critics of systemic views note that variations in NEET rates across similar economic contexts imply residual roles for individual factors, such as or adaptive behaviors. Resolving the debate requires recognizing the interplay: while structural conditions amplify vulnerabilities (e.g., via health disparities or ), individual-level interventions targeting skill-building and yield measurable reductions in duration, as evidenced by activation programs in contexts like , where both early school leaving (individual) and regional labor shortages (structural) interact as predictors. Academic literature, often institutionally inclined toward structural explanations to justify expansions, may underweight , yet longitudinal data affirm that modifiable personal factors—like completing —halve risks even amid economic pressures. This causal realism highlights that neither extreme fully captures the phenomenon, with evidence favoring multifaceted approaches over monocausal blame.

Measurement and Definitional Challenges

The NEET category encompasses youth who are neither employed nor enrolled in formal education or training, but definitional inconsistencies across international organizations and national contexts complicate uniform application. The International Labour Organization (ILO) and Organisation for Economic Co-operation and Development (OECD) typically apply the term to individuals aged 15-24, calculating the rate as the share of unemployed non-students plus inactive non-students relative to the total youth population. In contrast, Eurostat often extends the age range to 15-29 or focuses on 18-24, reflecting policy emphases on prolonged youth transitions in Europe, which can inflate reported rates by including older cohorts with higher inactivity. These variations hinder cross-national comparisons, as evidenced by differing NEET profiles: for instance, extending to age 29 captures more gender-disaggregated inactivity, such as women in unpaid domestic roles, which comprise a larger share in regions like the Middle East and North Africa. Further challenges arise from "broad" versus "strict" interpretations of the status. A strict definition excludes unemployed individuals who are students, focusing solely on non-students who are jobless or inactive, while broader variants may inadvertently include student-unemployed overlaps, overstating rates by up to 10% or more in countries like and . Across 41 countries analyzed by the ILO, the average discrepancy between these approaches was 1.4 percentage points, underscoring how definitional looseness distorts aggregate statistics. Misconceptions exacerbate this, such as equating NEETs primarily with discouraged workers— who represent only about 9.1% of the group— or conflating the indicator with informal exclusion, which it does not measure, as employed youth (including informal workers reported as such) are excluded regardless. Measurement relies heavily on labor force surveys like the ILO's Labour Force Survey (LFS) or School-to-Work Surveys (SWTS), which demand granular on activity status, but inconsistencies in survey and response rates introduce biases. Formal and are standardly required for non-NEET status, excluding informal apprenticeships or family-based skill acquisition prevalent in developing economies, potentially overcounting NEETs where such activities substitute for formal systems. Activities like compulsory or unpaid caregiving are variably classified— sometimes as or equivalents, other times as inactivity— leading to undercounting in militarized societies or gender-biased overcounting of women in care roles. Data sparsity in low-income countries, where surveys are infrequent or coverage incomplete, further limits reliability, with NEET rates showing wider variance (e.g., 5% in to 43.5% in ) than in high-income contexts. Overall, these factors undermine international comparability, as survey methodologies (e.g., LFS versus SWTS) and cultural reporting norms affect whether marginal activities qualify as "" or "."

References

  1. [1]
    Youth not in employment, education or training (NEET) - OECD
    Youth not in employment, education or training (NEET) refers to the share of young people who are not engaged in any form of employment, formal education, or ...Missing: causes | Show results with:causes
  2. [2]
    Risk Factors of Being a Youth Not in Education, Employment or ...
    The most critical indicators were education level, work experience and skill, physical and mental health, marital status, poverty and social inequalities.
  3. [3]
    Transition from education to work: Where are today's youth? - OECD
    Sep 9, 2025 · In 2024, after several years of recovery after the COVID-19 pandemic, the average NEET rate across OECD countries was 14%, similar to the value ...
  4. [4]
    Statistics on young people neither in employment nor in education ...
    The proportion of 15–29-year-olds in the EU neither in employment nor in education and training in 2024 ranged from 5% in the Netherlands to 19% in Romania.Missing: origin | Show results with:origin<|separator|>
  5. [5]
    Number of youth not in employment, education, or training (NEET) a ...
    Aug 12, 2024 · The report cautions that the continuing high NEET rates and insufficient growth of decent jobs are causing growing anxiety among today's youth, ...Missing: origin | Show results with:origin
  6. [6]
    [PDF] Unravelling the NEET phenomenon: a systematic literature review ...
    Mar 24, 2024 · Our findings highlight that NEET is associated with a higher suicide risk (OR = 2.8, 1.8–3.8), criminal behaviour (OR = 2.06, 1.47–. 2.65), and ...
  7. [7]
    Youth not engaged in education, employment, or training: a discrete ...
    May 27, 2024 · This study identified employment, education, and training service preferences among Upcoming youth. The findings indicate a need to create a service model.
  8. [8]
    Glossary:Young people neither in employment nor in education and ...
    ... NEET, corresponds to the percentage of the population of a given age group and sex who is not employed and not involved in further education or training.
  9. [9]
    Share of youth not in education, employment ... - Glossary | DataBank
    The share of youth not in education, employment or training (also known as “the NEET rate”) conveys the number of young persons not in education, employment or ...Missing: acronym origin
  10. [10]
    [PDF] NEETs: who are they? - European Parliament
    'NEET' is an acronym used to refer to young people who are not in education, employment or training. The expression, which first emerged in the mid-90s in the.Missing: precise | Show results with:precise
  11. [11]
    [PDF] NEETs Young people not in employment, education or training
    Drawing from the Eurostat definition presented earlier, young people are defined as NEET if they ... Source: Eurostat EU-SILC ad-hoc request and Eurofound ...<|separator|>
  12. [12]
    Origins and future of the concept of NEETs in the European policy ...
    Against this background, the term NEET was coined in ... “Literature Review of the Costs of Being 'Not in Education, Employment or Training' at Age 16–18.
  13. [13]
    Full article: New Labour's new deal for socially excluded young people
    In the early-1990s, 'Status Zer0', a term derived from careers-service records, was used in some circles to describe 16- and 17-year-olds outside education ...
  14. [14]
    [PDF] Reducing the number of young people not in employment ... - GOV.UK
    Being not in employment, education or training (NEET) is likely to have clear short- and long-term ... Young people in England not in education, employment or ...Missing: acronym origin
  15. [15]
    NEET | Tropedia | Fandom
    There's also a Mexican version of this trope, called Ni Ni and compared with the Japanese NEET, the Mexican ones are even more socially rejected, due to the ...
  16. [16]
    The NEET and Hikikomori spectrum: Assessing the risks and ... - NIH
    We believe that both NEET and Hikikomori show psychological tendencies that deviate from those governed by mainstream cultural attitudes, values, and behaviors.Missing: variations | Show results with:variations
  17. [17]
    Stagnant Youth: the NEET, freeter, and hikikomori phenomena
    Apr 5, 2015 · NEETs are not in education, employment, or training; freeters have part-time jobs; hikikomori are in seclusion, not leaving their rooms.
  18. [18]
    What heterogeneity hides behind the acronym NEET? - Microfinanza
    NEET means 'Neither in Education, Employment or Training'. It includes Job seekers, Opportunity explorers, the Unavailable, and the Decommitted, showing ...
  19. [19]
    A Critique of the Use of the Neet' Category - ResearchGate
    In OECD countries, the problem of young people not being in education, employment or training (the so-called "NEET") has been frequently raised in the ...
  20. [20]
    A Longitudinal Study of NEET Occurrences among Young Adults in ...
    Oct 26, 2020 · This enables a critical assessment of the quality of the NEET concept as a proxy for measuring young adults at risk of social exclusion.Missing: variations | Show results with:variations
  21. [21]
    Young adults not in education, employment, or training (NEET)
    Oct 8, 2025 · For the purpose of this review, we adopt an inclusive definition of NEET, referring to individuals aged 16-35 who are not engaged in education, ...Missing: statistics causes
  22. [22]
    [DOC] Who-are-the-persistently-NEET-young-people-literature-overview ...
    As was noted in the report, the phenomenon of young people not in education, employment, or training (NEET) is seen as a key indicator in policy, alongside ...
  23. [23]
    (Un)Happy 21st Birthday NEET! A genealogical approach to ...
    Oct 16, 2019 · The term 'NEET' (Not in Education, Employment or Training) in the UK has become a contentious issue for policy makers, youth services ...
  24. [24]
    NEET Policy Rhetoric in the UK and Scotland - PMC - PubMed Central
    Jun 23, 2021 · In 1999, the NEET label was visibly streamlined into policy rhetoric around young people in the UK in the form of the Bridging the Gap report by ...
  25. [25]
    [PDF] NEET: Young people not in education, employment or training
    May 8, 2018 · This report looked at the cohort of pupils who completed Key Stage 4 in 2010/11, and analysed the characteristics of those in this cohort who ...
  26. [26]
    [PDF] NEET Youth in the Aftermath of the Crisis: Challenges and Policies
    This paper presents an overview of the situation of youth in OECD countries since the onset of the financial crisis focusing primarily on describing the ...Missing: adoption terminology
  27. [27]
    Youth Employment in Japan's Economic Recovery: 'Freeters' and ...
    May 6, 2006 · Freeters and NEETs are deviations from the basic school-to-work transition model in Japanese society, in which students become full-time tenured ...
  28. [28]
    (PDF) NEETs' Challenge to Japan: Causes and Remedies
    Aug 5, 2025 · This paper examines the underlying causes of the NEET (Not in Employment, Education or Training) prob- lem in Japan.
  29. [29]
    [PDF] What does NEETs mean and why is the concept so easily ...
    NEETs: Young people not in employment, education or training: Characteristics, costs and policy responses in Europe (Dublin). Eurostat. 2014. “Young people ...
  30. [30]
    [PDF] Youth not in Employment, Education or Training (NEET):
    There are significant differences in the calculation of NEET today, both in terms of age range and the way it is defined (Eurostat, 2022; OECD, 2022;. Turkstat, ...
  31. [31]
    Being a NEET before and after the Great Recession - NIH
    Aug 12, 2021 · Therefore, the aggregate evolution shows an increase in the standard NEET rates in all countries with the Great Recession, followed by a ...
  32. [32]
    Being NEET in Youthspaces of the EU South: A Post-recession ...
    May 6, 2022 · Our analysis reveals that national NEET rates increased post-2008, due to the dire effects of the crisis on the EU southern economies.
  33. [33]
    Millions of US, EU youth are neither working nor learning
    Jan 28, 2016 · The 16-to-24 NEET rate rose again following the early-2000s recession, fell back to 14.5% in 2007, then jumped during the Great Recession. The ...Missing: post- | Show results with:post-
  34. [34]
    NEET: Young People Not in Education, Employment or Training
    Sep 12, 2025 · The proportion of 16-24 year olds who were NEET increased following the 2008 recession and peaked in July-September 2011 when 16.9% of 16-24 ...
  35. [35]
    Global Employment Trends for Youth 2024
    Aug 12, 2024 · Standing at 13 per cent in 2023, the global youth unemployment rate ... NEET rates below 15 per cent. Why are youth anxieties on the rise ...Missing: OECD | Show results with:OECD
  36. [36]
    [PDF] Youth at Work in G20 countries: Progress and policy action in 2023
    By the first quarter of 2024, NEET rates had returned to or fallen below their pre-pandemic levels in most. G20 economies with available quarterly data.
  37. [37]
    Measuring what matters: NEET vs youth unemployment
    Aug 12, 2025 · The ILO estimates that in 2025 around 262 million – or one in four - young people aged between 15 and 24 - are neither employed nor studying: ...
  38. [38]
    Young people neither in employment nor in education - Euronews.com
    Aug 23, 2025 · Two-thirds of European countries have not yet met the 9% target for young people who are neither in employment nor in education or training ...Missing: definition | Show results with:definition
  39. [39]
    Share of youth not in education, employment or training, total (% of ...
    Share of youth not in education, employment or training, total (% of youth population) from The World Bank: Data.
  40. [40]
    None
    Summary of each segment:
  41. [41]
    Are Young Men Falling Behind Young Women? The NEET Rate ...
    Mar 30, 2023 · Within the four ethnicity-race groups, Hispanic men and women have the largest NEET gap (6.4 percentage points); Black men and women have the ...Missing: global | Show results with:global<|separator|>
  42. [42]
    [PDF] Trends in young people not in education, employment or training
    Source: Annual Population Survey from the Office for National Statistics. Black/African/Caribbean young people have the highest NEET rate at. 15.2%, largely ...
  43. [43]
    Youth not in employment, education or training: Recent trends
    May 1, 2025 · The NEET rate rose by 2.0 percentage points among members of racialized groups aged 20 to 29. Among the largest racialized groups, Note Black ...Missing: ethnicity global country
  44. [44]
    Impact of the Great Recession on unemployed and NEET ...
    Aug 7, 2025 · The country's youth unemployment rate rose from 9.9% to 33% over the same time period, while the proportion of NEETs increased from 10.1% in ...
  45. [45]
    [PDF] Risk factors for being NEET among young people
    Risk factors include: education (low attainment, absence), family (single parent, child before 21), health (disability, mental health), and living (social ...
  46. [46]
    Not engaged in education, employment or training (NEET) in an ...
    Mar 23, 2019 · Olsen and colleagues describe the term NEET, and its plural NEETs, as the acronym for 'not in education, employment or training'. The term NEET ...Missing: origin | Show results with:origin
  47. [47]
    “I Don't Feel like an Adult”—Self-Perception of Delayed Transition to ...
    This study aimed to provide a deeper understanding of the self-perception of the transition to adulthood among the Italian NEET.
  48. [48]
    [PDF] Quality of life of NEET youth in comparative perspective - HAL-SHS
    Sep 7, 2023 · Abstract: In this study, we examine the self-reported subjective well-being (SWB) of youth who are. 'not in employment, education or ...<|separator|>
  49. [49]
    Place Matters: Understanding Geographic Influences on Youth Not ...
    Jan 9, 2025 · This systematic review has illuminated the significant impact of geographical factors on the NEET status among young people in Europe.
  50. [50]
    Disconnected Young Adults in the U.S. by Race and Geography
    Aug 15, 2024 · This blog post examines the prevalence of disconnected young adults in the US by disaggregating data by geography and race and ethnicity.
  51. [51]
    [PDF] MODERN HERMITS: HIKIKOMORI - Scholars' Bank
    They suggest that these typically collectivist cultural factors may play a role in the similarities between NEETs and hikikomori. Ishii and Uchida (2016) ...
  52. [52]
    Understanding Young People not in Employment, Education or ...
    Jun 26, 2025 · This study also highlights the adversity young women face as they are excluded from employment and formal education due to the entrenched ...
  53. [53]
    Understanding the influence of mental health on youth NEET status ...
    Jul 17, 2024 · Poor mental health such as attention deficit hyperactive disorder, autism, depression, borderline, and psychosis during childhood and adolescence is strongly ...
  54. [54]
    Beyond the mind: Understanding the influence of mental health on ...
    Jul 17, 2024 · NEET for more than 5 years affected 2.2% of those without psychosis, 35.8% of those with any nonaffective psychotic disorder, and 57.0% of those ...
  55. [55]
    The mental health of young people who are not in education ... - NIH
    Dec 21, 2021 · When disaggregated, NEET was most consistently associated with suicidal behaviours, drug use problems, any psychiatric disorders, cannabis use ...
  56. [56]
    Grit: a psychological predictive factor among NEET youth
    Oct 7, 2024 · Psychopathology may contribute to the likelihood of entering NEET status, may be inversely related to NEET status or may only be related to ...
  57. [57]
    Personality Structure and Self-Regulation in NEET Young Adults
    Oct 10, 2025 · NEET individuals showed a more rigid personality structure, marked by disorganization, impulsivity, and reduced emotional regulation, stress ...
  58. [58]
    Young adults not in education, employment, or training (NEET)
    Oct 8, 2025 · Low mental resilience, poor self-confidence, and a lack of coping skills were additional factors contributing to NEET risk [55, 56, 60]. A ...
  59. [59]
    How Far Are NEET Youth Falling Behind in Their Non-Cognitive ...
    Research on Russian data confirms that introversion as a personality trait, combined with low social activity and underdeveloped communication skills, creates ...
  60. [60]
    Unravelling the NEET phenomenon: a systematic literature review ...
    Mar 24, 2024 · This systematic review and meta-analysis examines the factors contributing to NEET (Not in Education, Employment, or Training) status among youth.
  61. [61]
    Once in NEET, always in NEET? Childhood and adolescent risk ...
    Mar 4, 2024 · Childhood and adolescent risk factors​​ Sex, socioeconomic status of parents (SES), educational level, physical health, negative life events, ...
  62. [62]
    Self-perceptions and mental health in NEET 18-year-olds from ... - NIH
    We compared four types of work-related self-perceptions, as well as vulnerability to mental health and substance abuse problems, among youths not in education, ...
  63. [63]
    Long term health effects of NEET experiences - NIH
    Poor physical health is measured by any admission into hospital and poor mental health is measured by prescription of anti-depressant and anti-anxiety medicine.
  64. [64]
    Health status among NEET adolescents and young adults in the ...
    This study examines the association of NEET status and poor/fair self-reported health status (SRH), among adolescents and young adults in the United States.
  65. [65]
    What are the individual consequences of being NEET? | CEDEFOP
    May 13, 2021 · Additional factors such as low family income, disadvantaged family background, migratory background, disabilities and family responsibilities ...Missing: behavioral | Show results with:behavioral
  66. [66]
    [PDF] The economic cost of the young people not in employment ... - GESIS
    This study is the first providing an estimation of the economic cost of NEETs at European level. The analysis is performed using the 2008 cross-sectional ...Missing: empirical | Show results with:empirical<|separator|>
  67. [67]
    NEET status duration and socio-economic background
    The economic literature and empirical evidence on scarring effects focuses more on the unemployed than on NEETs.
  68. [68]
    Does economic freedom alleviate youth disengagement? An ...
    The empirical findings of this study provide clear and consistent evidence that economic freedom significantly reduces NEET rates among youth aged 15–29 in the ...
  69. [69]
  70. [70]
    [PDF] EXECUTIVE SUMMARY Estimating the life-time cost of NEET: 16-18 ...
    Our lowest estimate of resource costs is just under £22billion a 210 per cent increase on our 2002 estimate. The high estimate is nearly £77billion.
  71. [71]
    Costing the Problem | developmentanalytics
    Being NEET has serious costs for the individual and society. Being NEET has detrimental and long-lasting effects on future employability and future earnings ...
  72. [72]
    Are we failing young people not in employment, education or ... - NIH
    Jan 25, 2017 · In addition to the societal costs of NEETs, there are of course stark effects on the individuals concerned. Social inclusion, health, and ...Missing: empirical | Show results with:empirical
  73. [73]
    Youth employment and social policies - OECD
    The NEET rate measures the share of young people who are not in employment, education, or training. They can be either unemployed (i.e., without a job but ...Missing: adoption terminology
  74. [74]
    Youth employment support - Employment, Social Affairs and Inclusion
    The European Pillar of Social Rights Action Plan includes an objective to decrease the rate of NEETs from 12.6% in 2019 to 9% by 2030 by improving their ...Missing: government UK Japan
  75. [75]
    Programs & Initiatives Working to Reconnect Youth & Prevent ...
    YouthBuild programs give at-risk youth ages 16-24 the opportunity to transform their lives by earning their high school diploma or state-recognized equivalency ...
  76. [76]
    Reconnecting Youth: A Compendium of Programs and Evidence ...
    The Reconnecting Youth project aims to systematically understand what programs and practices are operating in the United States to support these young people.
  77. [77]
    [PDF] Youth Employment and Employment Policies in Japan
    Dec 22, 2022 · In 2006, Regional Youth Support Stations (RYSS) were opened to provide assistance to NEETs, and Hello Work for the youth and Hello Work for new ...
  78. [78]
    Interventions targeting young people not in employment, education ...
    Jun 27, 2024 · I_ All interventions targeting the NEET population, such as group-based or individual counselling, educational and training programs, financial ...
  79. [79]
    [PDF] The evidence is in: How should youth employment programs in low
    Sep 26, 2017 · Youth in many low-income countries are entering the labor force in unprecedented numbers, yet many struggle to secure rewarding livelihoods.
  80. [80]
    None
    ### Summary of Strategies and Policy Areas to Reduce NEET in Developing/Emerging Countries
  81. [81]
    [PDF] Facilitating the School to Work Transition of Young Women
    However, the following provides a description of rigorously tested interventions in the region that were successful in helping young NEET women access ...
  82. [82]
    Strategies for Enhancing Digital Skills among Africa's NEET Youth
    Aug 15, 2025 · This background paper examines the critical issue of how to enhance digital skills among youth who are not in employment, education, ...Missing: rates | Show results with:rates
  83. [83]
    Are we failing young people not in employment, education or ...
    Jan 25, 2017 · Conclusions. There is some evidence that intensive multi-component interventions effectively decrease unemployment amongst NEETs. The quality ...Data Extraction And Quality... · Summary Of Findings · Policy Implications
  84. [84]
    Interventions targeting young people not in employment, education ...
    Jun 27, 2024 · The present systematic review aims to identify, synthesize, and evaluate evidence of effects from interventions targeting youth not in education, employment, ...
  85. [85]
    [PDF] Do Youth Employment Programs Improve Labor Market Outcomes ...
    The analysis looks at the effectiveness of various interventions and the factors that influence program performance including country context, targeted ...
  86. [86]
    Effective interventions for NEETs: a systematic review - Utrecht ...
    However, effective ingredients of interventions include social support, providing structure, and autonomy. More research is needed to determine what types of ...
  87. [87]
    New Evidence on Welfare's Disincentive for the Youth Using ...
    May 14, 2024 · We provide novel evidence on the employment response of the unmarried childless youths to an increase in welfare payments in Denmark.
  88. [88]
    The Effect of Social Benefits on Youth Employment*
    We first discuss how the age discontinuity in the RMI program can be exploited to measure the disincentive effect of this welfare scheme on labor market.
  89. [89]
  90. [90]
    Caught in the trap? Welfare's disincentive and the labor supply of ...
    The evidence we provide is based on large variations in budget constraints. In 1999, unemployed singles aged 25 and over could receive welfare payments of up to ...
  91. [91]
    The Role of the Welfare State for NEETs: Exploring the Association ...
    Sep 22, 2023 · This study explores the role of the welfare state in reducing young people not being in education, employment, or training (NEET)s across 15 ...
  92. [92]
    the effects of mandatory activation programs for young welfare ...
    Feb 16, 2021 · We study the impact of mandatory activation programs for young welfare recipients in the Netherlands. What makes this reform unique is that it clashed head on ...Missing: critiques incentives causing
  93. [93]
    Conditions of youth transition: individual and municipal factors ...
    We examined how individual characteristics and municipal conditions are associated with the NEET rate in Finnish municipalities.
  94. [94]
    Grit: a psychological predictive factor among NEET youth - PMC
    Studies have highlighted that a large proportion of these NEETs were homemakers, and NEET homemakers had less substance use, substance use disorders and ...
  95. [95]
    Individual and Structural Causes of Neet - a Case Study of Austria
    Nov 28, 2016 · First results reveal gender-specific risk factors for becoming NEET including early school leaving, poor health/disabilities, involvement in ...