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Updated: Sep 9, 2025

A Cost Effective and Adaptable Scratch Migration Assay
Published on: June 30, 2020
Tools for collecting information on irregular migration estimates and indicators
Carlos Vargas-Silva1, Arjen Leerkes2, Denis Kierans1
1Centre on Migration, Policy and Society, University of Oxford, Oxford, England, OX2 6QS, UK.
Abstract:
This paper discusses the tools used to collect quantitative data related to irregular migration stocks and flows of the Measuring Irregular Migration and Related Policies (MIrreM) project. The ultimate goal of this exercise was to construct two databases that provide an inventory and a critical appraisal of estimates and indicators related to irregular migration in the countries covered by MIrreM (12 EU member states, the UK, Canada, the USA and five transit countries). The databases contain estimates on the size and characteristics of the irregular migrant population in a given country and the changes in that population, with one database focussing on irregular migrant stocks and the other on flows. The flows database also contains an inventory of other indicators of irregular migration (e.g. border apprehensions). MirreM is a follow-up project to the Clandestino project which covered the period 2000-2007. MIrreM covers the period 2008 to 2023. MIrreM guidelines were adjusted from those developed by the Clandestino project to maintain some consistency across projects, but also to account for changes across the different periods and overall purposes of the projects. In addition, the approach to assessing the quality of estimates and indicators was refined, notably by explicitly distinguishing between statistical indicators, on the one hand, and estimates, on the other, developing different assessment criteria, and collecting information on the use of these data in policymaking. Beyond the immediate purpose of guiding data collection and analysis within the MIrreM project, these tools may also be useful for other researchers working on comparable topics characterised by a lack of robust research-driven data, hard-to-reach target groups and limited and imperfect administrative data.
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