Modeling International Migration Flows by Integrating Multiple Data Sources

Emanuele Del Fava , Max Planck Institute for Demographic Research (MPIDR)
Arkadiusz Wisniowski, University of Manchester
Emilio Zagheni, Max Planck Institute for demographic Research

Migration has become a significant source of population change at the global level, with broad societal implications. Although understanding the drivers of migration is critical to enact effective policies, theoretical advances in the study of migration processes have been limited by lack of data on flows of migrants or by their fragmented nature. In this paper, we build on existing Bayesian modelling strategies to develop a statistical framework for integrating different types of data on migration flows. We offer estimates, and associated measures of uncertainty, for both immigration flows and emigration flows among European countries, obtained from combining administrative and household survey data from 2002 to 2015. Substantively, we document the historical impact of the EU enlargement on migration flows. Methodologically, our approach improves over the Integrated Modeling of European Union (IMEM) framework and is flexible enough to be further extended to incorporate new data sources, like social media, in order to evaluate recent migration trends within a robust statistical framework.

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 Presented in Session 33. Methods for Migration Research