Network Dependency in Migration Flows

The contribution of this paper is to analyse the role of network interdependencies in a dynamic panel data model for German internal migration fl ows since re-unifi cation. So far, a capacious account of spatial patterns in German migration data is still missing in the empirical literature. In the context of this paper, network dependencies are associated with correlations of migration fl ows strictly attributable to proximate fl ows in geographic space. Using the neoclassical migration model, we start from its aspatial specifi cation and show by means of residual testing that network dependency eff ects are highly present. We then construct spatial weighting matrices for our system of interregional fl ow data and apply spatial regression techniques to properly handle the underlying space-time interrelations. Besides spatial extensions to the Blundell-Bond (1998) system GMM estimator in form of the commonly known spatial lag and unconstrained spatial Durbin model, we also apply system GMM to spatially fi ltered variables. Finally, combining both approaches to a mixed spatial fi lteringregression specifi cation shows a remarkably good performance in terms of capturing spatial dependence in our migration equation and at the same time qualify the model to pass essential IV diagnostic tests. The basic message for future research is that space-time dynamics is highly relevant for modelling German internal migration fl ows. JEL Classifi cation: R23, C31, C33