Abstract
AbstractThis article models the migration flows of international students who have graduated from master's and doctoral programmes in UK universities. Previously, access to sufficient data from the Destination of Leavers from Higher Education (DLHE) data set on the destinations of higher education (HE) international students has been difficult, despite the fact that international student numbers have grown substantially. Two 1‐year extracts from the DLHE data set were analysed (2013/2014 and 2014/2015) using cross‐classified multilevel modelling in order to estimate influences on ‘stay rate’: the likelihood of highly skilled graduates remaining in the United Kingdom for work after graduation. The home domicile and the UK higher education institution (HEI) attended for study were modelled as random effects that allowed the variance in stay rate to be partitioned between the student, higher levels of domicile and HEI attended. Variance at the domicile level was estimated to be 1.67 times greater than variance at HEI level, indicating that home country is a better predictor of stay rates than the HEI attended. The cross‐classified model was a better fit to data than simpler, two‐level hierarchical models (students nested in domicile or students nested in HEI attended). A number of student, domicile‐ and HEI‐level factors were added to the models. At HEI level, attending a Russell Group university and university location outside London were factors that led to significantly lower likelihood of graduates staying in the United Kingdom for work. At the domicile level, none of four factors (GDP, unemployment rates, English language and commonwealth affiliation) were significant in predicting stay rates.
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