Multilayer Network Analysis of European Regional Flows
arXiv:2412.09178 · doi:10.3390/e27090978
Abstract
In Regional Economics, the attractiveness of regions for capital, migrants, tourists, and other kinds of flows is a relevant topic. Usually, studies in this field explore single flows, characterizing the dimensions of territorial attractiveness separately, rarely considering the interwoven effect of flows. Here, we investigate attractiveness from a multi-dimensional perspective (i.e., dealing with different flows), asking how various types of regional flows collectively shape the attractiveness dynamics of European regions. We analyze eight distinct flow types across NUTS2 regions from 2010 to 2018, employing a multilayer network approach. Notably, the multilayer approach unveils insights that would be missed in single-layer analyses. Community detection reveals complex structures that demonstrate the cohesive power of national borders and the existence of strong cross-border ties in specific regions. Our study contributes to a more nuanced understanding of regional attractiveness, with implications for targeted policy interventions in regional development and European cohesion.
Main: 29 pages, 10 figures, 4 tables. Supplementary: 18 pages, 10 figures, 10 tables
References in corpus (12)
- Statistical mechanics of complex networks
- Multilayer Networks
- The structure and dynamics of multilayer networks
- Spatial Networks
- Diffusion dynamics on multiplex networks
- The map equation
- The Statistical Physics of Real-World Networks
- MuxViz: A Tool for Multilayer Analysis and Visualization of Networks
- Multiscale Dynamic Human Mobility Flow Dataset in the U.S. during the COVID-19 Epidemic
- Unbiased sampling of network ensembles
- Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
- A faster horse on a safer trail: generalized inference for the efficient reconstruction of weighted networks