A Model of Dynamic Flows: Explaining Turkey's Interprovincial Migration

The flow of resources across nodes over time (e.g., migration, financial transfers, peer-to-peer interactions) is a common phenomenon in sociology. Standard statistical methods are inadequate to model such interdependent flows. We propose a hierarchical Dirichlet-multinomial regression model and a Bayesian estimation method. We apply the model to analyze 25,632,876 migration instances that took place between Turkey's 81 provinces from 2009 to 2018. We then discuss the methodological and substantive implications of our results. Methodologically, we demonstrate the predictive advantage of our model compared to its most common alternative in migration research, the gravity model. We also discuss our model in the context of other approaches, mostly developed in the social networks literature. Substantively, we find that population, economic prosperity, the spatial and political distance between the origin and destination, the strength of the AKP (Justice and Development Party) in a province, and the network characteristics of the provinces are important predictors of migration, whereas the proportion of ethnic minority Kurds in a province has no positive association with in- and out-migration.