Multilayer Network Analysis of European Regional Flows

TL;DR

This study uses multilayer network analysis to examine how different types of regional flows collectively influence the attractiveness of European regions, revealing complex community structures and cross-border ties.

Contribution

It introduces a multilayer network approach to analyze multiple regional flows simultaneously, uncovering insights missed by single-flow analyses.

Findings

Multilayer analysis reveals complex community structures.

National borders influence regional flow communities.

Cross-border ties are significant in certain regions.

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.