by Tej Nathwani
As SRHE noted in their summary of the theme of the 2022 conference, one of the current areas of discussion is the relationship between student mobility and outcomes. For example, the Institute for Fiscal Studies (IFS) have used the Longitudinal Education Outcomes dataset to explore trends in graduate mobility and earnings in England. While mobility is correlated with individual destinations, there are also wider macroeconomic consequences resulting from the extent to which graduates move around the country.
In a separate paper by the Resolution Foundation and the Centre for Economic Performance, researchers at the two organisations highlighted how one of the key factors that explains variations in productivity across areas are human capital levels – measured by the share of graduates in the locality. Hence, while providers can help with widening participation and upskilling the labour force in our most deprived regions, the full benefits of this for the vicinity may only be realised if those individuals who study in higher education choose not to move out of the area or region. One of the consequences of this is that providers are increasingly working with employers to try and ensure graduates can utilise their skills in the local economy (for example at Sheffield Hallam).
Given the state of the UK economy and the role mobility may have on individuals and growth, this is a topic that will remain salient in forthcoming years. However, even before we think about the association between mobility and outcomes, the first question to consider is how data might help us to better understand the extent to which graduates move for study and/or work. Historically, exploration of graduate movements has been at a regional level, which has become less relevant and valuable at a time when interest also lies in inequalities within regions, as well as between them. This blog will thus focus on a new marker HESA has generated to help our users gain more detailed insights into mobility.
The current problem
Patterns of regional migration and the categorisation of graduates into different groups based on this was first explored by Prospects back in the mid-2000s. One of the limitations of using such an aggregated level of geography, however, is that Wales, Scotland and Northern Ireland are all classified as individual regions. This means we are unable to examine what mobility is like within these nations. To see the drawbacks for investigating mobility in England using region, consider the neighbouring areas of Bradford and Leeds – both of which are within Yorkshire and The Humber. As the ONS regional economic activity data illustrates, there has been a divergence in the economic performance of these two places over the last twenty years. Hence, a graduate originally from Bradford who studies at the local university, but then moves for work to Leeds would be allocated to the same group in a regional analysis as one who initially lives, studies and is then employed in Bradford. With the graduate share being a key factor in understanding the differences in economic performance between areas, the possibility of distinguishing between graduates who remain in areas of low economic activity and those who move out of such localities for work is growing in importance.
A potential solution
HESA collect the postcode at which the individual resides prior to starting higher education and also request similar data from the graduate in the Graduate Outcomes survey regarding their location of employment (if they don’t know the postcode for their employment location, we ask the graduate to provide the town/city/area in which they work). There is therefore the potential to map these postcodes to local authority data (and their equivalents in Scotland and Northern Ireland). Using local authority of residence/work and region of study, we have created a mobility marker consisting of the following seven categories:
- Stays in same region for study and finds work in the same local authority as original location of residence
- Returns to the same local authority for work as original location of residence, having left region/country for study
- Stays in same region for study, but finds work in different local authority (in the same region) to original location of residence
- Returns to a different local authority (of the same region) for work when compared with original location of residence, having moved region/country for study
- Moved region/country for work, but did not move region for study
- Moved region/country for study, but did not then move region/country again for work
- Moved region/country for study and then moved region/country again for work (with the region/country being different to their original region/country of residence)
Going back to our original example of the two graduates from Bradford (one who moves for work and one who doesn’t), this new classification ensures they are no longer placed in the same group. Rather, one is allocated to category A, while the other is assigned to C. Such distinctions will help improve our awareness of overall patterns of mobility across time.
Our initial exploration into mobility and job quality suggests that migrating for employment is correlated with graduates finding a role that fits better with their career plans. With similar findings on the benefits of moving for work from a salary perspective also being reported by the IFS, this could potentially leave those aiming to reduce disparities in economic performance between areas with a conundrum. Policies aiming to upskill the labour force in more deprived areas and help reduce spatial inequalities require these individuals to remain in such neighbourhoods. Yet current evidence suggests that moving for work is associated with more positive outcomes for these people. Given the relevance to policy aims, as we continue to collect increasing amount of data on graduates through our annual Graduate Outcomes survey, we shall be exploring the potential to map how mobility differs by area (eg by investigating whether we have adequate sample size at more granular levels of geography). If this does prove feasible, this will help end users with ascertaining the extent to which localities with lower output are gaining/losing graduates.
High levels of inequality and poor growth are two key concerns for the UK economy. We hope that the development of new measures on deprivation and graduate mobility can help the higher education sector with tackling these issues and assist providers in capturing the wider impact they are making in society.
Feedback on our mobility marker is most welcome. Please send these to email@example.com.
To learn more about Graduate Outcomes, visit www.graduateoutcomes.ac.uk or view the latest national level official statistics.
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Tej Nathwani is a Principal Researcher (Economist) at HESA, which is now part of Jisc.