Disentangling the importance of individual, family and neighbourhood factors on educational outcomes using sibling data

The family in which people are born has a strong influence on individual life outcomes, including educational and occupational outcomes. There is a voluminous body of work analysing social inequalities in educational outcomes but most of this research relies on individual survey data which contain only limited information about the family of origin and no or limited information about the areas where they live. This work is likely to underestimate the full extent to which family of origin matters for young people's education since many family characteristics are unobserved and they may confound the effect of family and neighbourhood.
This PhD project will adopt a sibling design to disentangle the effects of individual factors (e.g. gender, age, ethnicity), shared family factors (including all measured and unmeasured characteristics shared by siblings at birth and during their upbringing) and contextual factors (characteristics of the family's area of residence) on young people's educational outcomes. The project will exploit a new, unique sibling data set which links information from three administrative data sources (the Scottish Longitudinal Study, Vital Events birth data and ScotXed data) and contains longitudinal information on exam results and school curriculum choices as well as geographical mobility.
The study will require the use of advanced statistical methods, i.e. longitudinal data analysis and the latest developments in multilevel spatial data analysis. It will also require an understanding of how to work with sensitive and complex linked data from administrative sources. The student will receive training on data security and different aspects of working with sensitive data.
The PhD will provide an excellent opportunity for the student to work with a unique data set, to acquire advanced statistical skills and to produce and present impactful research to policy makers and school practitioners. The student will join a vibrant community of quantitative social scientists in the Advanced Quantitative Research in Education Hub and have access to training provided through the Q-Step centre, the Research Training Centre and the Centre for Statistics in the University of Edinburgh, as well as training provided by the ESRC National Centre for Research Methods.