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on Economic Geography |
| By: | Álvarez, Inmaculada C.; Barbero, Javier; Orea, Luis; Rodríguez-Pose, Andrés |
| Abstract: | Most studies of institutional quality and regional growth assume uniform effects across territories. However, this may mask crucial regional heterogeneity, with direct policy implications. We use a latent class framework applied to 230 EU regions over 2009-2017 to identify institution-driven regional parameter groups, and to examine both average effects and catching-up effects associated with changes in the institutional environment. We demonstrate that institutional quality generates highly variable returns to investment in physical capital and innovation. Nordic and Central European regions show highest returns to physical capital and R&D investment, whereas less-developed regions benefit most from education spending. Crucially, we find that improving government quality not only raises average returns but also promotes territorial cohesion. By contrast, regional autonomy shows limited impact on returns. Our findings challenge the one-size-fits-all approach to cohesion policy and indicate that cohesion policy should explicitly promote institutional improvements in addition to capital deployment. |
| Keywords: | institutional quality; European funds; investment; regional development |
| JEL: | E61 H54 R11 |
| Date: | 2025–12–24 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130747 |
| By: | Borsekova, Kamila; Korony, Samuel; Rodríguez-Pose, Andrés; Styk, Michal; Westlund, Hans |
| Abstract: | The importance of institutions and innovation for regional development is well established. How these two factors interact under different historical legacies and urban-regional contexts remains, however, insufficiently understood. This paper identifies which combinations of institutional and innovation indicators most effectively classify regions into distinct developmental archetypes, revealing critical thresholds that redirect regional trajectories. Employing decision-tree analysis on 233 EU NUTS-2 regions, we analyse 15 indicators spanning institutional quality, technological readiness, business sophistication, and innovation. This methodology uncovers non-linear relationships that traditional approaches cannot capture. The findings demonstrate that institutional quality acts as a necessary condition for innovation-led growth. High-performing regions, predominantly in Western and Northern Europe, benefit from robust institutions and strong innovation outputs. Many lower-performing regions, particularly in Central and Eastern Europe, exhibit innovation potential but are constrained by governance deficits. By integrating institutional and innovation indicators within a single analytical framework, we underscore how addressing governance and innovation in tandem can result in balanced and sustainable growth across Europe. |
| Keywords: | regional development; institutions; innovation; decision tree modelling; regional competitiveness |
| JEL: | J1 |
| Date: | 2026–02–28 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130741 |
| By: | Buyukyazici, Duygu; Coll-Martínez, Eva |
| Abstract: | This study provides the first conceptual and empirical framework to evaluate the cultural and creative industries’ (CCIs) skill composition by utilising the revealed skill requirements method. First, it identifies the most important skills within and across the CCIs. Second, it maps their spatial distribution and links them to the stage-sensitive regional specialisation of the CCIs. Finally, it formalises a framework to assess the specialisation potential patterns. Moving beyond a generic treatment of the CCIs, this study develops a comprehensive, bottom-up approach to regional CCIs policy, focusing on place-specific capabilities and untapped potential of regions by comparing their skill endowments with observed CCIs’ specialisation patterns. |
| Keywords: | complexity; creativity; cultural and creative industries; human capital; regional specialisation; skill relatedness |
| JEL: | B52 J24 R11 |
| Date: | 2026–01–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130094 |
| By: | Quintana Pablo; Herrera-Gomez Marcos |
| Abstract: | Identifying regions that are both spatially contiguous and internally homogeneous remains a core challenge in spatial analysis and regional economics, especially with the increasing complexity of modern datasets. These limitations are particularly problematic when working with socioeconomic data that evolve over time. This paper presents a novel methodology for spatio-temporal regionalization—Spatial Deep Embedded Clustering (SDEC)—which integrates deep learning with spatially constrained clustering to effectively process time series data. The approach uses autoencoders to capture hidden temporal patterns and reduce dimensionality before clustering, ensuring that both spatial contiguity and temporal coherence are maintained. Through Monte Carlo simulations, we show that SDEC significantly outperforms traditional methods in capturing complex temporal patterns while preserving spatial structure. Using empirical examples, we demonstrate that the proposed framework provides a robust, scalable, and data-driven tool for researchers and policymakers working in public health, urban planning, and regional economic analysis. |
| JEL: | C1 C4 C45 C63 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:aep:anales:4831 |
| By: | Talassino, Mauricio Rodrigo; Nicolini, Esteban; Aráoz, María Florencia |
| Abstract: | This paper has two main contributions. The first one is to present a new data set with 360 consistent local geographic units (CLGU henceforth) defined by matching the departments of each population census in Argentina between 1895 and 2022; this structure generates a traceable and transparent connection between the ways in which the information is presented in each census and, hence, it can be a crucial tool to combine information on socioeconomic dimensions across time. The second contribution is the estimation of local indicators of economic activity (LIEA henceforth) for Argentina for 1895 and 1960 and, using the 360 CLGUs, a completely novel exploration of spatialchanges of economic activity and local economic growth in Argentina in the first half of the twentieth century. |
| Keywords: | Regional inequalit; Regional growth; Argentina |
| JEL: | N1 N9 O4 R1 |
| Date: | 2026–01–09 |
| URL: | https://d.repec.org/n?u=RePEc:cte:whrepe:48819 |
| By: | Yolanda de Llanos (Department of Economics, Universidad de Extremadura, Spain); Luisa Alamá-Sabater (Department of Economics and IIDL, Universitat Jaume I, Castellón, Spain); Miguel Ángel Márquez (Department of Economics, Universidad de Extremadura, Spain); Emili Tortosa-Ausina (IVIE, Valencia and IIDL and Department of Economics, Universitat Jaume I, Castellón, Spain) |
| Abstract: | This paper examines the concept of left-behind places through the lens of neoendogenous development, with special attention to the role of the social economy in enhancing territorial resilience. Focusing on the Autonomous Community of Extremadura (Spain) as a representative regional case, it investigates the bidirectional relationship between population dynamics and employment using a simultaneous equations model that captures the spatial interdependencies among rural, urban and semi-urban municipalities. The findings highlight that employment growth drives population growth (supporting the idea that people follow jobs) while no evidence is found for the reverse. Local factors such as age structure, foreign population, income per capita and the presence of cooperatives also play a significant role in shaping these dynamics. Notably, the presence of social economy entities has a positive effect on both population and employment growth. The results suggest several policy pathways to mitigate depopulation: promoting employment in urban and intermediate areas, improving rural accessibility, and strengthening the social economy as a key strategy to foster sustainable local development. |
| Keywords: | depopulation, left-behind places, neo-endogenous development, rural, social economy |
| JEL: | C3 O18 O21 R1 R23 R3 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:jau:wpaper:2026/03 |
| By: | Yuji HONJO; Arito ONO; Daisuke TSURUTA |
| Abstract: | This study examines how regional financial development influences new firm creation and growth in Japan. Using prefecture–year panel data from 2007 to 2023, we distinguish between regional equity and debt capital, proxied by the number of investment limited partnerships and bank branches, respectively. We find that regions with greater equity capital have more newly founded firms and initial public offerings, and provide suggestive evidence of stronger sales growth among young firms (firms within five years of establishment), whereas regional debt capital has no significant effect. Moreover, regional equity capital is associated with higher employment shares of medium- and large-sized young firms and lower shares of small ones, implying that regional equity capital promotes a compositional shift in new firm creation toward larger entrants. These findings are robust to potential endogeneity concerns and to alternative measures of financial development. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:26005 |
| By: | Fritsch, Michael; Greve, Maria; Wyrwich, Michael (University of Groningen) |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:gro:rugfeb:2025010-i&o |
| By: | Boczon, Marta (Department of Economics, Copenhagen Business School); Severgnini, Battista (Department of Economics, Copenhagen Business School) |
| Abstract: | This paper studies how regional economic conditions, birth timing, and institutional rules shape talent allocation into high-risk/high-reward payoff structure occupations. Using rich data on English-born professional footballers and exploiting exogenous variation from European Structural Funds in the United Kingdom (1990–2000), we show that improved local conditions reduced the share of summer-born children, who are disadvantaged by age-based cutoffs in youth academies but exhibit higher underlying talent. Although regional income per capita did not significantly change, fertility timing shifted, shrinking this high-potential group: players born after the intervention exhibit lower peak market values, reflecting how economic and institutional factors can misallocate talent. |
| Keywords: | Talent allocation; Early-life conditions; Birth-timing; Professional sports |
| JEL: | J13 J24 R11 Z22 |
| Date: | 2026–01–12 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:cbsnow:2026_002 |
| By: | Evgenidis Anastasios; Fasianos Apostolos; Papapanagiotou George; Lazarou Nicholas Joseph (European Commission - JRC) |
| Abstract: | Recent advances in Artificial Intelligence (AI) and the growing role of these technologies in enhancing productivity have attracted significant research and policy attention, yet the determinants of AI innovation remain relatively understudied. This study contributes to this emerging literature by examining the role of public R&D spending in fostering AI-related innovation across EU regions. Our analysis draws on bibliographic information from all patents registered at the European Patent Office (EPO) between 1980 and 2023. Using textual analysis of patent abstracts, we identify the share of AI patents among total patents and construct a novel dataset that allocates AI patents to NUTS-2 regions based on inventor addresses. This regional mapping enables us to assess the impact of public R&D funding on AI innovation while addressing endogeneity concerns by instrumenting regional public R&D spending with national defence-related R&D expenditure. The results show that public R&D plays a significant role in driving AI innovation: a 1% increase in public R&D spending raises AI patent output by approximately 0.27%. These findings speak directly to Europe’s innovation policy framework, providing evidence that public investment remains a powerful lever for stimulating AI development. They also reinforce the rationale for sustained funding under Horizon Europe, the Digital Europe Programme, and national innovation strategies aimed at building technological and reducing regional disparities in AI advancement. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:termod:202512 |