Towards the More Effective Use of Irregular Migration Data in Policymaking
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Highlights
Data to measure irregular migration are inconsistent, hard to access, and can have collection bias. Better standards and data literacy are vital for sound policymaking.
- Most irregular migration data are collected as a byproduct of enforcement, creating gaps in population-level information; visa overstayers, trafficking victims, children of irregular migrants, and people in secondary movement are routinely undercounted.
- Inconsistent definitions of ‘irregular migrant’ across EU Member States limit comparability over time and across countries, and missing metadata increases the risk of misinterpretation and misuse.
- Data access is constrained by unclear legal frameworks, noninteroperable systems, and informal sharing practices that leave many potential users unable to retrieve or analyse existing datasets.
- There are ways to strengthen local data collection, separate data collection from enforcement, harmonise definitions, improve interoperability with safeguards, and build data literacy among policymakers.
Across Europe, concerns about irregular migration have dominated media headlines and shaped recent elections. Discussions of and policymaking related to irregular migration are often a numbers game, fueled by the latest estimates of changing migration trends and migrant populations. Data on irregular migration also influence decision-making, advocacy, and strategic and operational planning of a wide range of governmental and nongovernmental actors.
But despite playing such important roles, data on irregular migration are often inadequate—either lacking altogether, uneven, or difficult to access. This has consequences for policymakers, service providers, and other stakeholders that would benefit from better access to reliable data.
This MPI Europe policy brief explores obstacles that hinder the effective collection and use of irregular migration data, how this affects policymakers and other actors, and potential avenues for strengthening the evidence base. This study, which is part of the Measuring Irregular Migration and Related Policies (MIrreM) project, draws on insights shared in workshops and interviews by policymakers, subject matter experts, NGO representatives, and other stakeholders.
Table of Contents
1 Introduction
2 Challenges to Effective Data Practices
A. Data Gaps and Collection Bias
B. Unclear or Inconsistent Definitions and a Lack of Data Literacy
C. Obstacles to Data Access and Sharing
D. Data Non-Usage and Underusage
3 Learning from Best Practices and Innovations in Irregular Migration Data
4 Final Reflections
