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yildiz-et-al-2024-integrating-traditional-and-social-media-data-to-predict-bilateral-migrant-stocks-in-the-european.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/106292 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/106292 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/106292 archive 353 disk0/00/01/97/52 2024-05-29 11:40:22 2024-05-29 11:40:22 2024-05-29 11:40:22 article show 1 Yildiz D. 2175 0000-0001-6192-0634 Wiśniowski A. Abel G. 1966 0000-0002-4893-5687 Weber I. Zagheni E. Gendronneau C. Hoorens S. pub POPJUS MDM MIG Although up-to-date information on the nature and extent of migration within the European Union (EU) is important for policymaking, timely and reliable statistics on the number of EU citizens residing in or moving across other member states are difficult to obtain. In this paper, we develop a statistical model that integrates data on EU migrant stocks using traditional sources such as census, population registers and Labour Force Survey, with novel data sources, primarily from the Facebook Advertising Platform. Findings suggest that combining different data sources provides near real-time estimates that can serve as early warnings about shifts in EU mobility patterns. Estimated migrant stocks match relatively well to the observed data, despite some overestimation of smaller migrant populations and underestimation for larger migrant populations in Germany and the United Kingdom. In addition, the model estimates missing stocks for migrant corridors and years where no data are available, offering timely now-casted estimates. 2024-05-29 published Wiley doi:10.1177/01979183241249969 2960 3136 public International Migration Review TRUE 01979183 Future Migration Scenarios for Europe (FUME, H2020 870649) yes info:eu-repo/grantAgreement/EC/H2020/870649/EU//FUME info:eu-repo/semantics/article info:eu-repo/semantics/openAccess