Models for emergent structures in mobility: Specification and individual-level interpretation

It is increasingly common to study mobility and migration of individuals between social and physicallocations as networks in which locations are nodes connected by mobile people. This conceptualisationas mobility networks facilitates the analysis of how individuals influence one another in their mobilitydestinations. Technically, this amounts to analysing interdependence between individuals’ mobilitypaths. A recently proposed framework – the endogenous log-linear model (ELMo) – allows the statisticalmodelling of these social processes and, therefore, dependence in mobility, combining insights from exponentialrandom graph models (ERGMs) and log-linear models. However, little attention was paid tohow such models should be specified in a principled, theoretically informed way. In this study, we applystatistical theory to propose model specifications that can be used to analyse emergent structures in mobility.We first reformulate the model under analysis as a conditional multinomial logit with dependentobservations. Subsequently, we show how to specify models that (i) are based on clear dependence assumptionson 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. We end with an exampleapplication pertaining to the mobility of computer science faculty between university departments.