Models for emergent structures in mobility: Specification and individual-level interpretation
Marion Hoffman and
Per Block
No 8nkfj_v1, SocArXiv from Center for Open Science
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 people. 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 – the endogenous log-linear model (ELMo) – allows the statistical modelling of these social processes and, therefore, dependence in mobility, combining insights from exponential random graph models (ERGMs) and log-linear models. However, little 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 conditional 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. We end with an example application pertaining to the mobility of computer science faculty between university departments.
Date: 2026-01-06
References: Add references at CitEc
Citations:
Downloads: (external link)
https://osf.io/download/695c1a1db1b267ebca8a6805/
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:8nkfj_v1
DOI: 10.31219/osf.io/8nkfj_v1
Access Statistics for this paper
More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().