Using administrative data sources to better understand student migration and circular travel patterns

Main Article Content

Rebecca Spilsbury

Abstract

The ONS is transforming the way we produce migration statistics, to better meet our users’ needs. We are currently progressing a transformation programme to put administrative data at the core of our evidence on international migration.


We currently use the International Passenger Survey (IPS) to produce estimates of international migration to and from the UK. Our new analysis of circular patterns of movement using Home Office administrative data clearly demonstrates the complexity of the travel patterns we see in the data. Looking at individuals who arrived in the UK on non-visit visas and their travel patterns for the following two-year period, we were able to identify a range of circular journeys into and out of the country.


There is therefore potential to produce statistics on circular migration in future, so we are exploring how we can do this using linked administrative data.


Main Aim



  • To analyse circular travel patterns and see how these migrants may fit into our traditional definitions of international migrants

  • To obtain the most common visa types, travel patterns, nationality and length of stay.

  • To produce counts of potential circular migrants.


We have analysed a three-year extract of Home Office Exit Checks data to identify circular patterns of movement for non-EU nationals whose journey started on a non-visit visa.


We published our first outputs in January 2019, where we categorised people by how frequently they travelled, length of stay and demographic information. Since then we have investigated short-term circular journeys and determined common visa types, counts and travel patterns.


Circular migrants are not a homogenous group as they have wide-ranging travel patterns. The results from this exploratory analysis have provided evidence of short-term migrant travel patterns which will aid our understanding of these migrant movement types.

The ONS is transforming the way we produce migration statistics, to better meet our users’ needs. We are currently progressing a transformation programme to put administrative data at the core of our evidence on international migration.

We currently use the International Passenger Survey (IPS) to produce estimates of international migration to and from the UK. Our new analysis of circular patterns of movement using Home Office administrative data clearly demonstrates the complexity of the travel patterns we see in the data. Looking at individuals who arrived in the UK on non-visit visas and their travel patterns for the following two-year period, we were able to identify a range of circular journeys into and out of the country.

There is therefore potential to produce statistics on circular migration in future, so we are exploring how we can do this using linked administrative data.

Main aims:

  • To analyse circular travel patterns and see how these migrants may fit into our traditional definitions of international migrants
  • To obtain the most common visa types, travel patterns, nationality and length of stay.
  • To produce counts of potential circular migrants.

We have analysed a three-year extract of Home Office Exit Checks data to identify circular patterns of movement for non-EU nationals whose journey started on a non-visit visa.

We published our first outputs in January 2019, where we categorised people by how frequently they travelled, length of stay and demographic information. Since then we have investigated short-term circular journeys and determined common visa types, counts and travel patterns.

Circular migrants are not a homogenous group as they have wide-ranging travel patterns. The results from this exploratory analysis have provided evidence of short-term migrant travel patterns which will aid our understanding of these migrant movement types.

Article Details

How to Cite
Spilsbury, R. (2019) “Using administrative data sources to better understand student migration and circular travel patterns”, International Journal of Population Data Science, 4(3). doi: 10.23889/ijpds.v4i3.1249.