Consequences, risk factors, and geography of young people not in education, employment or training (NEET)

Chapter 4 Conclusions

As discussed in the introduction to this report, policy makers in Scotland are concerned about the persistently high level of young people who are not in employment, education or training over the past few decades. It is important to conduct research into the phenomenon of NEETs, and to understand the causes and consequences of being NEET. The research findings in this report provide evidence to help target future policy interventions designed to reverse the increase of NEET among young people and to mitigate the often long-term negative effects of NEET experiences.

Key Research findings

In this report we used Scotland's census data and the Scottish Longitudinal Study (SLS) to examine long-term effects, risk factors and geographies of being NEET.

We found evidence that being NEET is associated with several long-term negative outcomes:

Consequences

• The NEET group remains disadvantaged in their educational attainment 10 and 20 years later. More than one in five of NEET young people in 2001 had no qualifications by 2011 compared with only one in twenty five of non-NEETs.
• There is a scarring effect in economic activity. In comparison with their non-NEET peers NEET young people in 2001 were 2.8 times as likely to be unemployed or economically inactive 10 years later.
• The scarring effect is also evident in the occupational positions that NEET young people entered. For example, NEET young people in 2001 were 2.5 times as likely as their non-NEET peers to work in a low status occupation in 2011.
• NEET experiences are associated with a higher risk of poor physical health after 10 and 20 years. The risk for the NEET group was 1.6 - 2.5 times that for the non-NEET group varying with different health outcomes.
• NEET experiences are associated with a higher risk of poor mental health after 10 and 20 years. The risk of depression and anxiety prescription for the NEET group is over 50% higher than that for the non-NEET group.
• Young people who were NEET in 1991 and remained economically inactive in 2001 consistently demonstrated significantly poorer outcomes by 2011 than those who were non-NEET in 1991 and economically active in 2001 and those who were engaged with employment or education in either 1991 or 2001. This suggests that there is a cumulative effect of being out of employment or education on later life chances and this group is the most disadvantaged that need continuing support.
• Young people who changed from NEET status in 1991 to employment or education in 2001 have lower risks of poor life outcomes compared with those who were consistently in disadvantaged positions. However, the negative effect of NEET status in 1991 was not fully discounted by the later engagement of employment or education, indicating the long-lasting detrimental effect of NEET experiences.
• Young people who changed from being non-NEET in 1991 to being economically inactive or unemployed in 2001 have higher risks of poor life outcomes compared with those who were consistently in employment or education. This suggests that economic activity in 2001 is also predictive of later labour market and health outcomes regardless of NEET status in 1991.

We found evidence that being NEET is associated with several demographic and socioeconomic factors:

Risk Factors

• Risk factors are consistent across two cohorts and between males and females.
• Educational qualification is the most important factor. No qualifications increased the risk of being NEET by 6 times for males and 8 times for females in Cohort 3. No qualifications at SCQF level 5 or higher obtained by school stage S4 increase the risk of being NEET by 10 times for males and 7 times for females in Cohort 4.
• Other school factors are important including the proportion of time absent from school and the number of exclusions.
• Two factors are especially important for females: being an unpaid carer for more than 20 hours per week and teenage pregnancy.
• Household factors are also important. Living in a social renting household, living in a family that is not headed by a married couple, living in a household with no employed adults, having a large number of siblings all increased the risk of becoming NEET.
• Local NEET rate is an important factor for both cohorts and genders, with the risk of NEET increasing with local NEET rate.
• A risk score derived from the statistical modelling has potential to identify young people who are at risk of becoming NEET.

Deprived areas are found to have a consistently higher proportion of NEET young people over two decades. The majority of NEET hotspot council areas like Glasgow, West Dunbartonshire, Inverclyde and North Ayrshire display higher than the national average in the proportion of young people who were NEET persistently over the two decades between 1991 and 2011.

These findings provide further evidence that NEET status should be an important policy concern and that young people not in employment, education or training should be a target group in terms of policy intervention.

Policy implications

Our research has a number of policy implications.

• Disengagement from employment and education when young can lead to long-term consequences in employment, occupations and health. The social and economic costs can be considerable not only for individuals but also for society. Tackling the NEET issue remains a policy concern and represents a serious economic and social challenge.
• The NEET problem should be tackled as part of wider strategies for social inclusion because causes of NEET are complex and result from the interplay between many individual, household and local factors.
• Young people who have been disaffected with education are at greatest risk of becoming NEET. Measures to increase school attendance and to boost attainment may help young people to avoid becoming NEET later on.
• School factors also provide potentials for identifying those 'at-risk' and for targeting interventions.
• Being consistently detached from employment, education or training exacerbates the long-term negative effect for NEET young people. Continuing support is needed for people who are excluded persistently from employment or education.
• In addition, area-based interventions and local coordination may be useful as NEET young people appear to be concentrated in more deprived areas and in some councils.

Future research

The research outlined in this report provides well-validated, robust estimates of risk factors for and the long-term consequences of not being in education, employment or training at ages 16-19. At this point, the available data does not include some important risk factors, some factors are not found in administrative data but might be available to careers guidance officers such as the personality of a young person and whether they are influenced by their peers. Others might in future become available to the SLS such as crime and justice data. The risk score developed here could be improved if it were supplemented with such extra information using retrospective data and/or prospective data. For example, this might show that young people with a police record should always be considered as being in the highest risk category or that the presence of a good role model should move a young person down one risk category regardless of any other data. The risk score would therefore evolve and improve with use. More subtle processes whereby some young people with the same 'up-stream' risk factors do not become NEET in youth might require more detailed qualitative research into the complex set of factors implicated in a child's development. Future research might therefore build on the findings in this report to investigate the pre-school, school and career pathways of those 'at risk' and explore how different trajectories are associated with individual characteristics, family backgrounds, and socioeconomic structures in the local labour market. This might help to identify the most effective interventions and the points at which they should be applied.

Evaluation of policies that may impact NEET in youth is clearly important given our and others' findings on the long-term negative consequences on young people. The benefit of establishing a valid national dataset for examining outcomes in youth, is that it will allow the investigation of differential outcomes that may result from different policies or interventions as they are enacted across the country. This then provides the opportunity to explore the impact of different policies within a 'quasi-experimental' context. Analysis could examine similar groups of young people who have or have not been exposed to the intervention, with exposure being dependent on their geographical location and not on a characteristic that may be related to the risk of them being NEET in youth. Because the dataset used in this report can examine the NEET context over the last 20 years, it is also possible to use it to examine historic spatial or temporal differences in approaches.

Linking other administrative records to the SLS will extend the range of issues that can be examined. For example, linking individuals' work lives data from The Department of Work and Pensions to the SLS may be very useful in tracing peoples movement into and out of the labour market. Other administrative data sources - for example training schemes for the NEET group or unemployed people in general - are also crucial and, if linked to the SLS, will be a powerful source to evaluate a policy intervention. So a more general aim, to support research in this area, should be linking new datasets into the SLS. In addition, it would also be possible to look more closely at specific subgroups. For example, those who were NEET but who then go on to relatively advantaged occupations or risk factors for those NEET and economically inactive 10 years later.