Migration has become a prominent research theme in geography and regional science and it has been approached from various methodological angles. Nonetheless, a common missing element in most migration studies is the lack of awareness of the overall network topology, which characterizes migration flows. Although gravity models focus on spatial interaction—in this case migration—between pairs of origins and destinations, they do not provide insights into the topology of a migration network. We employ network analysis to address such systemic research questions, in particular: how centralized or dispersed are migration flows and how does this structure evolve over time? And, how is migration activity clustered between specific countries, and if it is clustered, do such patterns change over time? Going a step further than exploratory network analysis, in this paper we estimate international migration models for OECD countries based on a dual approach: gravity models estimated using conventional econometric approaches such as panel data regressions and network-based regression techniques such as multivariate regression quadratic assignment procedures. The empirical results reveal not only the determinants of international migration among OECD countries, but also the value of blending network analysis with more conventional analytic methods. <br> <b>Keywords:</b> immigration, gravity model, complex networks, community detection, MRQAP
