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The aim of this study was to develop a methodological tool to 'nowcast' migrant stocks by using real-time data from the Facebook Marketing Application Programming Interface (API) and official migration data from EU member states and states in the United States. To meet this aim, RAND researchers collected real-time data that could provide estimates of migrant stocks in the countries of interest from the Facebook Marketing API, along with migrant-stocks data from official sources from 2010 onwards, and developed a Bayesian model capable of combining the Facebook and official migration data to nowcast stocks of migrants in EU member states and US states. The model developed in this study is capable of producing near real-time nowcasts for each source of official statistics, which can serve as an early-warning system to anticipate 'shock events' and rapid migration trends that would otherwise be captured too late or not at all by official migration data sources. This tool therefore enables decision-makers to make informed, evidence-based policy decisions in the rapidly changing social policy sphere of international migration. The study also provides a useful example of how to combine 'big data' with traditional data to improve measurement and estimation which can be applied to other social and demographic phenomena. Suggestions for future work include continued data collection activities to extend the temporal overlap between Facebook data and official migration statistics, nowcasting migrant stocks for demographic subgroups, and exploring alternative specifications for the Bayesian model to improve the accuracy of the nowcasts.