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on Economic Geography |
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Issue of 2025–11–03
seven papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Francesco Molica; Francesco Cappellano; Teemu Makkonen |
| Abstract: | Since a few years, the international economic system has been experiencing growing fragmentation and uncertainty. However, research on Regional Innovation Systems (RIS) has yet to comprehensively engage with this phenomenon, despite its (spatial) significance. The paper contributes to addressing this gap, in particular by exploring the potential implications for RIS arising from the decline and disruptions of international knowledge flows associated with economic de-globalization. The study seeks to define a theoretical approach grounded in evolutionary geography to assess this trend. It applies such perspective to three types of RIS—metropolitan, old industrial, and peripheral—across five analytical dimensions that capture the structural and relational factors shaping RIS exposure and resilience to de-globalization. The discussion highlights that, in the face of knowledge and technological disruptions arising from international instability, metropolitan RIS may leverage their diversified knowledge bases, dense institutional frameworks, and strong global connectivity to successfully reconfigure external linkages; old industrial RIS may follow mixed trajectories, with the risk of deepening economic and policy lock-ins; while peripheral RIS—due to their reliance on external knowledge sources and limited endogenous innovation capacity—emerge as the most vulnerable. |
| Keywords: | De-globalization; Knowledge flows; Regional innovation system; Resilience |
| Date: | 2025–10–22 |
| URL: | https://d.repec.org/n?u=RePEc:ict:wpaper:2013/395461 |
| By: | Raian Kudashev (DEM, Université du Luxembourg); Pierre M. Picard (DEM, Université du Luxembourg) |
| Abstract: | This paper studies the effects of congestion relief in a spatial general equilibrium model of Luxembourg and its cross-border commuting zone. Using traffic speed data, we apply a difference-in-differences design on Luxembourgs highways to measure congestion severity and identify choke points. We then simulate counterfactual scenarios where highway speeds are set to free-flow levels and track the resulting changes in output, welfare, and fiscal revenues. Economic output rises in Luxembourg City and Esch, while other cities lose production but gain in resident welfare. For residents of Luxembourg City, we estimate a short-run welfare loss of €1, 140 per person per year, which becomes a welfare gain of €3, 490 in the long run after population reallocation. When accounting for migration from the outside economy, the welfare effect in Luxembourg City turns negative at €8, 110 per person per year. The elimination of congestion induces a fiscal gain of €2.50 billion per year in the short run, €1.18 billion in the long run, and €7.04 billion when accounting for migration inflows. |
| Keywords: | "Road congestion, cross-border employment, land prices, taxes, quantitative spatial economics." |
| JEL: | H73 R13 R14 R23 R31 R41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:luc:wpaper:25-17 |
| By: | Priscila Espinosa (Department of Applied Economics, Universitat de València, Spain); Priscila Espinosa; Maria Teresa Balaguer-Coll (Department of Finance and Accounting, Universitat Jaume I, Castellón, Spain); José Manuel Pavía (Department of Applied Economics, Universitat de València, Valencia, Spain); Emili Tortosa-Ausina (IVIE, Valencia and IIDL and Department of Economics, Universitat Jaume I, Castellón, Spain) |
| Abstract: | The floods that struck the Valencian region (Spain) in October 2024 illustrate how climate change is intensifying extreme weather events in Mediterranean floodprone areas, challenging regional economic resilience. This disaster, which resulted in numerous fatalities and extensive infrastructure damage, disrupted supply chains across a region already vulnerable due to decades of urban and industrial development in the area. Drawing on regional economic resilience theory and recovery curve methodologies, we present an ex ante framework for rapidly assessing climate disaster impacts on regional economic growth. Our approach combines sectoral recovery dynamics with worker-level impact data to update GDP growth forecasts in real-time, addressing a critical gap in disaster response capabilities for increasingly climate-vulnerable regions. Applied to the Valencia floods, our methodology reveals differential sectoral resilience patterns: while construction demonstrates rapid recovery due to reconstruction demand, agriculture shows prolonged vulnerability reflecting the sector’s exposure to climate risks. Compared to pre-flood forecasts, results indicate economic contractions of up to 0.2 percentage points in 2024 and 2025, followed by a policy-supported rebound adding 0.3 percentage points to growth in 2026. The analysis underscores how government intervention fundamentally shapes postdisaster economic trajectories in flood-prone regions. Beyond providing immediate impact assessment, this framework offers a generalisable tool for enhancing climate resilience planning in Mediterranean and other climatevulnerable territories, enabling policymakers to rapidly adjust economic forecasts and recovery strategies as extreme weather events become more frequent and severe under climate change. |
| Keywords: | macroeconomic forecasting; GDP growth; natural disasters; recovery curves; regional economic resilience |
| JEL: | Q54 R11 H84 C53 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:jau:wpaper:2025/10 |
| By: | Filippo De Feo (Institut für Mathematik, Technische Universität Berlin); Giorgio Fabbri (Université Grenoble Alpes; INRAE); Silvia Faggian (Ca’ Foscari University of Venice); Giuseppe Freni (Parthenope University of Naples) |
| Abstract: | We study optimal and strategic extraction of a renewable resource that is distributed over a network, migrates mass-conservingly across nodes, and evolves under nonlinear (concave) growth. A subset of nodes hosts extractors while the remaining nodes serve as reserves. We analyze a centralized planner and a noncooperative game with stationary Markov strategies. The migration operator transports shadow values along the network so that Perron–Frobenius geometry governs long-run spatial allocations, while nonlinear growth couples aggregate biomass with its spatial distribution and bounds global dynamics. For three canonical growth families, logistic, power, and log-type saturating laws, under related unilities, we derive closed-form value functions and feedback rules for the planner and construct a symmetric Markov equilibrium on strongly connected networks. To our knowledge, this is the first paper to obtain explicit policies for spatial resource extraction with nonlinear growth and, a fortiori, closed-form Markov equilibria, on general networks. |
| Keywords: | Harvesting, spatial models, differential games, nature reserves |
| JEL: | Q20 Q28 R11 C73 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2025:22 |
| By: | Fanze Kong; Jiayi Sun; Shuangquan Xie |
| Abstract: | One of the most significant findings in the study of spatial Solow-Swan models is the emergence of economic agglomeration, in which economic activities concentrate in specific regions. Such agglomeration provides a fundamental mechanism driving the spatial patterns of urbanization, labor migration, productivity growth, and resource allocation. In this paper, we consider the one-dimensional spatial Solow-Swan model with capital-induced labor migration, which captures the dynamic interaction between labor and capital through migration and accumulation. Focusing on the regime of sufficiently small capital diffusivity, we first construct an interior spike (spiky economic agglomeration) quasi-equilibrium. Next, we perform the linear stability of the corresponding spike equilibrium by using a hybrid asymptotic and numerical method. We show that a single interior spike remains stable for small reaction-time constants but undergoes a Hopf bifurcation when the constant is sufficiently large, leading to oscillations in spike height (economic fluctuation). Finally, we derive a differential-algebraic system to capture the slow drift motion of quasi-equilibrium (core-periphery shift). Numerical simulations are carried out to support our theoretical studies and reveal some intriguing yet unexplained dynamics. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.19204 |
| By: | Benoit, Florence (European Commission, Directorate-General for Research and Innovation); Di Girolamo, Valentina (European Commission, Directorate-General for Research and Innovation); Diodato, Dario (European Commission, Directorate-General for Research and Innovation); Canton, Erik (European Commission, Directorate-General for Research and Innovation); Ravet, Julien (European Commission, Directorate-General for Research and Innovation) |
| Abstract: | In today’s economy, knowledge represents a critical resource for long-term economic growth (Romer, 1990). Knowledge tends to accumulate in densely populated areas, where geographical proximity facilitates spillovers, rapid idea diffusion, and the recombination of capabilities. This localised concentration can further be enriched by global knowledge flows through collaborations and networks. Through this process, economies can obtain a set of capabilities that form the basis for the development of unique technological assets (Storper & Venables, 2004). These unique assets, which are difficult to replicate, become the cornerstone of a sustainable competitive advantage and contribute significantly to long-term economic development and resilience. |
| JEL: | O32 O52 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:eug:wpaper:ki-01-25-015-en-n |
| By: | Önnerfors, Martin |
| Abstract: | This paper describes the methodology for geocoding historical Swedish census data from 1878-1950, developed as part of the research project "Cities and Socioeconomic Segregation in the Long Term, 1880-2017." While Sweden's historical demographic data is renowned for its quality and coverage, geocoding this data presents unique challenges that cannot be solved using modern geocoding APIs. The primary obstacles include temporal changes in address-coordinate relationships, street relocations, and the complete disappearance of spatial units through demolition and redevelopment. Historical Swedish census data varies in geographic precision, ranging from village-level information in rural areas to property-level detail in urban centers like Stockholm. The paper proposes a solution based on constructing a "canonical" historical address and property database that incorporates temporal dimensions, allowing for accurate matching at specific time points. This database is compiled from multiple sources and validated against georeferenced historical city maps. The methodology addresses the distinction between property-level (block name and number) and address-level (street name and house number) geocoding, with property coordinates proving more temporally stable. Manual data collection and quality assurance are essential components of the process, particularly for areas subject to major urban redevelopment such as Stockholm's Klara neighborhood. This approach enables accurate geocoding of historical census data while maintaining spatial precision appropriate for demographic analysis of urban segregation patterns over more than a century. |
| Date: | 2025–10–22 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:bfn24_v1 |