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International postgraduate students' labour mobility in the United Kingdom: A cross‐classified multilevel analysis

International postgraduate students' labour mobility in the United Kingdom: A cross‐classified multilevel analysis
International postgraduate students' labour mobility in the United Kingdom: A cross‐classified multilevel analysis
This 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.
cross-classified multilevel logistic modelling, international student migration, labour mobility, postgraduate students, stay rate, the United Kingdom
1544-8444
1-15
Zhan, Meng
f5791df1-c09b-429b-9f1b-9a341fc73f2d
Downey, Christopher
bb95b259-2e31-401b-8edf-78e8d76bfb8c
Dyke, Martin
5a5dbd02-39c5-41e0-ba89-a55f61c9cb39
Zhan, Meng
f5791df1-c09b-429b-9f1b-9a341fc73f2d
Downey, Christopher
bb95b259-2e31-401b-8edf-78e8d76bfb8c
Dyke, Martin
5a5dbd02-39c5-41e0-ba89-a55f61c9cb39

Zhan, Meng, Downey, Christopher and Dyke, Martin (2020) International postgraduate students' labour mobility in the United Kingdom: A cross‐classified multilevel analysis. Population, Space and Place, e2381, 1-15. (doi:10.1002/psp.2381).

Record type: Article

Abstract

This 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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Zhan et al Population Place and Space 2020 - Version of Record
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More information

Accepted/In Press date: 13 August 2020
e-pub ahead of print date: 28 August 2020
Keywords: cross-classified multilevel logistic modelling, international student migration, labour mobility, postgraduate students, stay rate, the United Kingdom

Identifiers

Local EPrints ID: 444354
URI: http://eprints.soton.ac.uk/id/eprint/444354
ISSN: 1544-8444
PURE UUID: d787c351-f731-4ba6-a270-9fdc3bd01a01
ORCID for Christopher Downey: ORCID iD orcid.org/0000-0002-6094-0534

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Date deposited: 14 Oct 2020 16:30
Last modified: 28 Apr 2022 01:57

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Contributors

Author: Meng Zhan
Author: Martin Dyke

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