Can Regional Infrastructure Predict Its Economic Resilience? Limited Evidence from Spatial Modelling

This study examines whether regional infrastructure can predict economic resilience in European regions, focusing on resistance, recovery, and reorientation during the COVID-19 crisis. While infrastructure is widely recognized as a key factor influencing regional resilience, its explicit role has been underexplored in the European context. Using a comprehensive literature review and spatial econometric models applied to NUTS-2 level data from 2017 to 2024, we investigate the direct and spatial spillover effects of various infrastructure types—transportation, healthcare, tourism, education, and digital access—on regional resilience outcomes. We apply OLS and four spatial models (SEM, SLX, SDEM, SDM) under 29 spatial weighting matrices to account for spatial autocorrelation. Results show that motorway density, early school leaving, and healthcare infrastructure in neighbouring regions significantly affect resistance. For recovery, railway density and GDP per capita emerge as key predictors, with notable spatial spillovers. Reorientation is shaped by population structure, railway density, and tourism infrastructure, with both positive and negative spatial dynamics observed. The findings underscore the importance of infrastructure not only in isolation but also within regional systems, revealing complex interdependencies. We conclude that policymakers must consider spatial externalities and coordinate infrastructure investments to enhance regional economic resilience across interconnected Europe.