MOMA: Multiscale network modelling of migration flows in Austria
MOMA is a WWTF funded projected with aims to exploit a unique combination of datasets of individual-level migration events in Austria with high-resolution socioeconomic maps to reveal the nationwide multiscale, hierarchical internal flow of people over a period of more than two decades, together with its latent social and economic correlates.
Using state-of-the-art data science methodology, we will combine longitudinal neighborhood-level relocation information with individualized data on income, employment, and demographic factors (e.g. ethnicity, gender, nationality, marital status).
Together with customized inferential network science methods, we will construct a higher-order dynamic generative model able to identify the most relevant spatial and temporal patterns and dynamics of internal migration, and establish their underlying causal structures.
Our goal is to answer the questions:
How does social segregation and social mobility interact with internal and international migration?
How migration interweaves with urban and business development?
By answering these questions, our data-driven analysis will allow for the assessment of the impact of policy interventions on the dynamics of social mobility, segregation, urbanization, immigration, and socioeconomic development.