Modelling emergent structures in mobility

Abstract

It is increasingly common to study mobility and migration of individuals between social and physical locations as networks in which locations are nodes connected by mobile individuals. This conceptualisation as mobility networks facilitates the analysis of how individuals influence one another in their mobility destinations. Technically, this amounts to analysing interdependence between individuals' mobility paths. A recently proposed framework allows the statistical modelling of these social processes and, therefore, dependence in mobility, combining features of Exponential Random Graph Models (ERGMs) and classic log-linear models. However, insufficient attention was paid to how such models should be specified in a principled, theoretically informed way. In this study, we apply statistical theory to propose model specifications that can be used to analyse emergent structures in mobility. We first reformulate the model under analysis as a multinomial logit with dependent observations. Subsequently, we show how to specify models that (i) are based on clear dependence assumptions on the individual level, that (ii) have a clear individual level interpretation, and that (iii) avoid (near-)degeneracy, a common problem for models with dependent observations.

This work is joint work with Per Block.