Abstract Regional economies are increasingly exposed to volatility and prolonged shocks, yet the role of intersectoral linkages and their spatial interdependencies in shaping adjustment remains underexplored. This study analyses the evolution and spatial structure of inter-industrial dependencies across Greek NUTS-2 regions during 2008–2018, a period of deep recession and uneven recovery. Using regional input-output models, the analysis estimates sectoral output multipliers to identify key drivers of economy-wide effects and to trace their evolution over time. Spatial diagnostics detect clustering patterns in multiplier dynamics, while correlation and spatial correlation analyses explore the relationship between structural change and regional gross value added performance. Results indicate that the crisis was associated with a modest weakening of overall inter-industrial linkages, alongside a reconfiguration of production structures. The industry sector emerged as the dominant source of multiplier effects, while construction and finance experienced a substantial decline in network importance. Information and communication maintained relatively steady multiplier strength, suggesting their growing role within regional production systems. Spatial analysis indicates persistent industrial polarization and sector-specific clustering, pointing to path-dependent and geographically uneven adjustment processes. Correlation analysis shows weak associations between multiplier growth and own-region economic performance, but positive relationships with neighbouring regions’ growth, underscoring the importance of spatial spillovers. By integrating production-network and spatial perspectives, the proposed analytical framework offers a diagnostic tool for assessing regional economic restructuring and supports the design of place-based resilience policies that explicitly account for intersectoral linkages and cross-regional spillover mechanisms.

Abstract The present study explores students’ decisions to either relocate or commute to their place of study depending on the availability of student tickets. By leveraging regional variations in the coverage of these subsidized public transport tickets, we explore whether their availability decreases students’ likelihood of moving. We investigate how the importance of subsidized tickets changes with commuting time and how their relevance varies based on students’ financial resources, social backgrounds, and risk attitudes. To do so, we use the MESARAS 2013 (Mobility, Expectations, Self-Assessment, and Risk Attitude of Students) survey, which queries university entrants in the field of economics at seven German universities. We link locational identifiers from the survey with the Google Distance Matrix API to assess commuting times and regional administrative data. Our logistic regression models suggest that the availability of student tickets may decrease the likelihood of moving. The association appears to be less pronounced as commuting time increases and seems to depend on parental academic status as well as students’ budget. Thus, our study offers three contributions: First, we provide policy-relevant evidence on the importance of affordable public transportation. Second, we address (social) inequalities in the moving versus commuting decision. Third, we demonstrate how accurate spatial modeling of commuting times and integration of survey data with external data sources benefits socio-spatial analysis.

Abstract The conceptualisation of gentrification and its relationship to displacement remains highly contested within urban studies, which is also reflected in divergent methodological approaches. While there are integrated methodologies which combine measures for both phenomena and allow to estimate the effect of gentrification on the extent of displacement, there is a lack of quantitative approaches which are capable of revealing how neighbourhood upgrading is related to individual displacement specifically. This article addresses this gap by introducing a sequential research design that combines the spatial analysis of socio-economic and real estate upgrading processes at neighbourhood level with a survey-based analysis of displacement. The combination of spatial analysis and tailored primary survey enables us to precisely determine the factors behind displacement at the individual level and distinguish between different forms of (gentrification-related) displacement in systematically selected neighbourhoods. In turn, these displacement processes can be contextualised within differentiated upgrading patterns at neighbourhood level. Thus, the approach bridges the gap between relevant dimensions and scales of gentrification and helps to elucidate their substantive relationship. The methodology is illustrated using the example of the city of Nuremberg, Germany. The displacement survey was conducted in three case study neighbourhoods identified through a systematic, data-driven selection strategy.

Abstract In this paper, we analyse the influence of interregional trade on regional economic growth, adopting balance-of-payments constrained regional growth model. To do this, we extend the model theoretically by incorporating interregional trade relations and then make an empirical application to Spanish regions for the period 1996–2018. The results obtained from the empirical application show that the restriction would not have limited economic growth in the case of Spanish regions. We therefore evaluate the possibility that there may be interregional fiscal and financial flows that make the persistence of internal trade imbalances possible in the long term and that the restriction on growth does not work. To verify this explanation, we test whether the differences between real and constrained growth can be explained by proxy variables of both types of flows. The conclusion is that fiscal flows could explain this difference, indicating that they might exert a compensatory effect that counteracts the restriction of the balance.

Abstract While promoting the well-being of people is the ultimate goal of all EU social and economic policies, research in this area has been mainly limited to income-based measures of well-being, such as GDP per capita, especially at the regional level. Therefore, this study aims to go beyond income-based measures and examine the spatial distribution and drivers of objective well-being in European regions. To achieve this, a unique panel dataset is created by integrating regional data on objective well-being (based on the EU-Social Progress Index), economic growth, industrial clusters and knowledge structure, covering 165 NUTS-2 regions from 11 EU countries (between 2011 and 2018). Based on dynamic panel regressions using a system generalized method of moments (GMM) approach, it is shown that the economic growth promotes the objective well-being in regions. Evidence is also found that the industrial structure within regions is an additional driver. Regions with a diverse industrial cluster portfolio are more likely to have high objective well-being. However, this influence is negatively moderated by the strength of the industrial clusters, which possibly refers to size-related negative externalities. Besides the economic effects, industrial cluster structures can therefore also influence the objective well-being in regions. To promote regional well-being, regional policies should support a diverse industrial cluster portfolio rather than a regional cluster structure that is overly specialized in relatively few large industries.

Scholarly work in economic geography and regional science has recently seen a renewed interest in spatial inequalities, driven significantly by the debate on left-behind places and the resulting geographies of discontent. The plight of left-behind places calls for new place-based policy responses that address the specific challenges of these regions but that at the same time address grand societal challenges such as climate change, biodiversity loss, or pollution with synthetic chemicals. Despite growing attention among economic geographers and regional scientists to either green or inclusive regional development approaches, how to reconcile environmental sustainability and social inclusiveness in highly challenged left-behind places remains poorly understood. This editorial reflects on and critically discusses the literature on left-behind places and distils unifying conceptual characteristics of left-behindness. We argue that left-behindness is a temporal, relational, multidimensional, discursive, but not deterministic concept. The non-determinism of left-behindness opens up different choices for actors to shape regional futures. Imagining and negotiating these futures involves dealing with difficult potential trade-offs between environmental sustainability and social inclusiveness, some of which are explored by the articles in this special issue.