Repository of Practices

Primary GCM Objectives

GCM Guiding Principles*

*All practices are to uphold the ten guiding principles of the GCM. This practice particularly exemplifies these listed principles.

Sustainable Development Goals (SDGs)

Dates

2020 - 2023

Type of practice

Measuring/Data collection

Geographic scope

Regions:

Europe

Summary

The QuantMig Migration Estimates Explorer is an online database of harmonised migration estimates for Europe developed within the QuantMig project (www.quantmig.eu). The estimates are based on data from the origin and destination countries, as well as the relevant metadata and expert assessment of various dimensions of data quality.

The Explorer provides harmonised probabilistic estimates of migration flows among 32 countries in the European Union (EU), the United Kingdom, the European Free Trade Association (EFTA), and North Macedonia, as well as to and from the rest of the world, based on publicly-available Eurostat data on migration, and covariate information from a range of other published sources. All estimates have been produced by using a dedicated statistical model, following a Bayesian hierarchical approach, and as such include selected measures of uncertainty. The estimated migration flows relate to long-term migrants (for 12 months or longer), as defined in the EC Regulation 862/2007 on migration and asylum statistics. The estimates update and expand the ones created in the project Integrated Modelling of European Migration (IMEM), funded in 2009-12 by NORFACE.

Estimated flows can be presented by country of origin, country of destination, age, sex, and the region of birth, for years 2009 to 2019, also including the original IMEM estimates for 2002 to 2008. The IMEM methodology is described in: J Raymer, A Wiśniowski, JJ Forster, PWF Smith and J Bijak (2013) Integrated Modelling of European Migration. Journal of the American Statistical Association, 108(503), 801-819 (DOI: 10.1080/01621459.2013.789435).

The estimation methodology and instructions for using the QuantMig Migration Estimates Explorer are respectively available from: G Aristotelous, PWF Smith and J Bijak (2022) Technical report: Estimation methodology, Deliverable D6.3, and M Potancoková, J Sadler, J Bijak, M González-Leonardo and A Soto-Nishimura (2023) Documentation of QuantMig Web Tools for Data and Simulation, Deliverable D10.4 (Section 3).

Disclaimer: This practice has been funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 870299 QuantMig: Quantifying Migration Scenarios for Better Policy. This document reflects the authors' views and the Research Executive Agency of the European Commission are not responsible for any use that may be made of the information it contains.

Organizations

Main Implementing Organization(s)

University of Southampton

Partner/Donor Organizations

University of Continued Education Krems

International Institute for Applied Systems Analysis

Max Planck Society – Population Europe

Netherlands Interdisciplinary Demographic Institute

Peace Research Institute

University of Oslo

European Union

Benefit and Impact

The QuantMig Migration Estimates Explorer updates and streamlines earlier work on providing harmonized migration estimates for Europe (the Integrated Model of European Migration, IMEM), including flows into and out of the 32 European countries under consideration, thus enhancing, updating and strengthening the evidence base on European migration in the first two decades of the 21st century. This resource is intended to provide foundations for further research and policy analysis, which will be of substantive interest in many migration-related areas. Breakdowns by age, sex or region of birth enable a more fine-tuned analysis at the level of individual flows than has been possible before. The work is based on cutting-edge statistical methodology, which is providing a very flexible and versatile framework for reconciling various migration data sources and their quality assessment.

Several dimensions of the database have become integrated into the Human Migration Database (HMigD) project, which is currently under development at the Max Planck Institute for Demographic Research in Rostock – for a Beta version, see M Dańko (2024) HMigD I App: The Human Migration Database I App. Version 3.1.1, February 2024. Rostock: Max Planck Institute for Demographic Research. Online resource: https://maciej-jan-danko.shinyapps.io/HMigD_Shiny_App_I (access on 7 April 2024).

Key Lessons

Information on migration contained in multiple data sources is insufficient to provide reliable assessment of the true flows and needs supplementing with expert assessment of data quality aspects. Expert-based information is still uncertain but largely (at least weakly) informative, especially about undercounting in official migration data.

Since the implementation of EC Regulation 862/2007 on migration and asylum statistics, data comparability across Europe has generally improved, but completeness and availability have not, with notable gaps in reporting, including Germany.

Information from experts and meta-information on data quality, coupled with available statistics on migration flows across Europe, enable the application of a very flexible modelling framework offered by the IMEM model, which produces probabilistic estimates of migration flows with measures of uncertainty. Estimates for 2009–19 are available from www.quantmig.eu.

(After: White Paper on Migration Uncertainty, https://bit.ly/migration-uncertainty)

Recommendations(if the practice is to be replicated)

For an assessment of migration data quality, expert knowledge is very useful, but it needs to be triangulated with data of known provenance – ideally coming from different data collection systems, whose features can, in this way, be assessed more thoroughly.

Despite some progress since the adoption of EC Regulation 862/2007, migration data and metadata availability across Europe needs further improvement. Barriers to improving quality and fuller harmonisation of definitions across the EU need to be particularly examined.

The uncertainty of the harmonised migration estimates can be large, but is reducible, so this is an area worth investing in at the European level and with partner countries. Approaches used for estimation can rely on ‘mirror statistics’ as well as new data sources, if the latter can be used together with traditional data that has better known features.

(After: White Paper on Migration Uncertainty, https://bit.ly/migration-uncertainty)

Innovation

The QuantMig Migration Estimates Explorer utilizes cutting-edge statistical methodology for reconciling data on migration flows from both the origin and destination countries, mediated by the assessment of several relative quality aspects of these data. The Explorer integrates the past efforts in that area (original IMEM estimates for 2002–2008) and the underlying statistical approach has already spurred methodological development in the current work on the Human Migration Database (HMigD), described above, which, once implemented, will become a vehicle to ensure the sustainability of the broader thread of research on the used of hierarchical Bayesian models in estimating migration.
In addition, the methodology underpinning the database is scalable, with the estimates mainly subject to availability of appropriate input data on bilateral flows, which at the moment are mostly available for more economically developed countries and regions, such as Europe. Regarding the impact of COVID-19: the last year of the estimates is 2019, so still before the pandemic – this criterion does not therefore apply.

Additional Resources

QuantMig Migration Estimates Explorer

Additional Images

Date submitted:

15 July 2024

Disclaimer: The content of this practice reflects the views of the implementers and does not necessarily reflect the views of the United Nations, the United Nations Network on Migration, and its members.