Replication data for: Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020

Data and code for performing analyses and plotting figures for "Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020" The code and data can also be found at https://github.com/MPIDR/Global-flows-and-rates-of-international-mig...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Theile, Tom, Akbaritabar, Aliakbar, Zagheni, Emilio
Format: Dataset
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Data and code for performing analyses and plotting figures for "Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020" The code and data can also be found at https://github.com/MPIDR/Global-flows-and-rates-of-international-migration-of-scholars/ Abstract: A lack of comprehensive migration data is a major barrier for understanding the causes and consequences of migration processes, including for specific groups like high-skilled migrants. We leverage large-scale bibliometric data from Scopus and OpenAlex to trace the global movements of scholars. Based on our empirical validations, we develop pre-processing steps and offer best practices for the measurement and identification of migration events. We have prepared a publicly accessible dataset that shows a high level of correlation between the counts of scholars in Scopus and OpenAlex for most countries. Although OpenAlex has more extensive coverage of non-Western countries, the highest correlations with Scopus are observed in Western countries. We share aggregated yearly estimates of international migration rates and of bilateral flows for 210 countries and areas worldwide for the period 1998-2020 and describe the data structure and usage notes. We expect that the publicly shared dataset will enable researchers to further study the causes and the consequences of migration of scholars to forecast the future mobility of global academic talent.
DOI:10.5281/zenodo.11145734