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This article models migration of international postgraduate students graduated from UK universities. Destinations of Leavers from Higher Education dataset was analysed (2013/14, 2014/15) using cross-classified multilevel modelling in order to estimate influences on “stay-rate”: the likelihood of highly-skilled graduates remaining in UK for work after graduation. The home domicile and HEI attended were modelled as random effects that allowed variance in stay-rate to be partitioned between student, higher-levels of domicile and HEI. Results indicate that gender, subject area and level of study have significant influence on student employment destination. Cross-classified model provided a better fit to data than simpler two-level models. At domicile-level, none of four factors (GDP, unemployment rates, English language and Commonwealth affiliation) were significant in predicting stay-rate.
Meng Zhan, University of Southampton
Martin Dyke, University of Southampton
Christopher Downey, University of Southampton