Predictors of becoming not in education, employment or training: a dynamic comparison of the direct and indirect determinants

This paper uses a dynamic latent factor model to investigate the determinants of not in education, employment or training (NEET) status among adolescents in the United Kingdom. We bring together within one framework various determinants of NEET status, such as educational achievements, non-cognitive skills, family socio-economic factors, aspirations, mental health and local labour market conditions. We model the educational progress over multiple periods through the life of the young person, up to the completion of compulsory schooling. By taking into account this progression, we can determine the direct and indirect impacts of different determinants of NEET status, and the stage in the life of the young person at which each determinant is important. Our findings suggest that cognitive ability (as measured by educational achievements) remains the key predictor of NEET status. Further, while a range of individual and family factors determines NEET status, the impact of most of these factors is largely indirect, through ability formation and not necessarily direct. To gauge the relative contributions of various determinants, we conduct simulations to predict the probability of the young person being NEET under different scenarios and assumptions. The exercise indicates that the effects of aspirations of the young person, their school engagement, and the local youth unemployment rate on the likelihood of the young person being NEET are as large as boosting their cognitive skills.