Modeling international migration flows by integrating multiple data sources

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 enacting effective policies, theoretical advances in the study of migration processes have been limited by the lack of data on flows of migrants, or by the fragmented nature of these data. In this work, we build on existing probabilistic modeling strategies to develop a statistical framework for integrating different types of data on migration flows. We offer estimates, as well as associated measures of uncertainty, for inflows and outflows among 31 European countries, by combining administrative and household survey data from 2002 to 2022. Methodologically, we demonstrate the added value of survey data when there is lack of administrative data or they show poor quality. Additionally, we examine how the free movement of workers in Europe, resulting from the historical EU enlargement, has impacted migration flows. The paper is accompanied by a shiny app that includes underlying data, metadata, and allows flexible presenting of the results.