Laboratory

Migration and Mobility

At a Glance Projects Publications Team

Research Area

High-Skilled Migration

Migration is often modeled as a single, unified process, yet this assumption obscures a fundamental reality: Migration is inherently heterogeneous, comprising distinct flows driven by different root causes, including labor market dynamics, educational opportunities, conflict, policy environments, and social networks. Treating these diverse processes as analytically equivalent limits the explanatory power of migration research. In contrast, fields such as mortality research have long benefited from systematic classification frameworks like the International Classification of Diseases, which enable researchers to distinguish between causes, and to thereby develop more precise empirical and theoretical insights. Migration research lacks an equivalent structure due in part to persistent data limitations that hinder the identification and measurement of specific migration processes.

This absence of such a structure has important consequences. When heterogeneous migration flows are aggregated, the mechanisms that drive them become blurred, complicating both empirical inference and theory development. As a result, existing models often capture correlations without adequately reflecting the underlying causal processes, limiting their interpretability and predictive capacity. Advancing the field therefore requires a more systematic effort to identify and categorize migration according to its causes. By isolating different types of migration flows, researchers can more effectively link empirical patterns to theoretical mechanisms, enabling more robust, theory-informed explanations of migration. Such an approach is essential for moving beyond descriptive accounts and toward a more analytically rigorous and cumulatively advancing science of human mobility.

One of the most consequential domains within this broader agenda is high-skilled migration. The movement of highly educated individuals is a cornerstone of modern economies, driving innovation, productivity, and global knowledge exchange. Its scale and significance continue to grow, with profound implications for economic development, labor markets, and inequality. However, despite its importance, high-skilled migration remains surprisingly difficult to measure and understand using traditional data sources, which are often incomplete, outdated, or poorly suited to capturing dynamic mobility processes.

This research area confronts these limitations directly by leveraging the transformative potential of digital trace data. Two domains, in particular, have opened up unprecedented opportunities. First, the migration of scholars can now be systematically analyzed using large-scale bibliometric data from sources such as Scopus. Building on these data, we have developed the Scholarly Migration Database, a unique global resource that tracks the mobility of scientists through changes in their institutional affiliations over time. This database enables both fine-grained longitudinal analyses and aggregate flow estimates, at global and subnational levels, covering more than two decades. It has already generated novel insights into the relationship between economic development and academic mobility, revealed persistent gender disparities, quantified the impact of major shocks such as Brexit on scientific migration, and shed new light on the links between internal and international migration.

Second, digital trace data from professional platforms like LinkedIn allow us to move beyond academia and capture the broader dynamics of high-skilled labor migration. These data provide us with rare access to information not only on observed mobility, but also on migration intentions, which in turn enables us to measure country attractiveness and to compare scholars’ aspirations with their realized moves. This represents a critical step toward understanding migration as a decision-making process, rather than as a purely observed outcome.

By systematically integrating novel digital trace data with rigorous methodological frameworks, this research agenda goes beyond merely addressing empirical limitations. It establishes the basis for developing a fundamentally improved, cause-oriented understanding of migration, thereby enabling the identification and separation of distinct migration processes and linking observed patterns more directly to their underlying mechanisms. In doing so, this research advances a broader goal of developing a more precise and theoretically grounded science of human mobility.

Projects of this Research Area