The effect of crime in the community on becoming not in education, employment or training (NEET) at 18-19 years in England

The increasing number of young people who are inactive and not engaged in education, employment or training (NEETs) in the UK over the last years bears severe implications both for individual young people and for the society. This study explores the processes underlying the effects of neighborhood context on young people who experience NEET status. It relies on quantitative data from a nationally representative study, the Longitudinal Study of Young People in England (LSYPE), linked with the seven decomposed English Indices of Deprivation.\ud \ud Drawing on previous sociological theories this study puts forward an original theoretical framework, the Ecological Model of Neighbourhood Effects that proposes four pathways\ud that mediate the direct effect of neighbourhoods on young people: \ud a) individual characteristics and attitudes; \ud b) parental characteristics and relationships; \ud c) school experiences and attitudes to schooling, and; \ud d) social epidemics.\ud \ud Potential causal pathways between neighbourhood context and individual outcomes are explored on a first strand of analysis by employing a logistic regression model. The\ud results show that there is a higher probability for young people who live in high Crime Score areas to become NEETs in comparison to those who live in areas with low Crime\ud Score after controlling for individual, family, school and peer group characteristics.\ud \ud On a second strand of analysis, I employ counterfactual models, propensity score matching and sensitivity analysis. The findings suggest that when two groups of children with\ud identical observed characteristics at the age 13/14 experience di↵erent neighbourhood contexts, those who grow up in high Crime Score areas are more likely to become\ud NEETs in comparison to those who grow up in low Crime Score areas. Unobserved characteristics though indicate the presence of selection bias that could alter the inferences\ud drawn about neighbourhood effects.\u