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.

中文翻译：

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整合传统和社交媒体数据来预测欧盟双边移民存量


尽管有关欧盟 (EU) 内部移民性质和范围的最新信息对于政策制定很重要，但很难获得有关居住或跨过其他成员国的欧盟公民数量的及时、可靠的统计数据。在本文中，我们开发了一个统计模型，将使用人口普查、人口登记和劳动力调查等传统来源的欧盟移民存量数据与主要来自 Facebook 广告平台的新颖数据源相结合。研究结果表明，结合不同的数据源可以提供近乎实时的估计，可以作为欧盟流动模式转变的早期预警。尽管德国和英国对较小移民人口的估计较高，而对较大移民人口的估计较低，但估计的移民存量与观测数据吻合较好。此外，该模型还估算了移民走廊和没有可用数据的年份的缺失种群，从而提供了及时的现预测值。