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on Economic Geography |
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Issue of 2025–08–18
nine papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Ikeda, Kiyohiro; Kogure, Yosuke; Aizawa, Hiroki; Takayama, Yuki |
| Abstract: | This paper investigates how international trade competition influences cross-country migration by using a general equilibrium model of economic geography. We employ a global--local system to represent local places grouped into countries, which collectively form a global network. Through the place-to-country reduction analysis proposed herein, the governing equation at the place level are reduced to a country-level equation that efficiently describes each country’s trade environment. We model and analyze international trade competition---including trade liberalization and protectionism---among the UK, France, and Germany, using the Helpman (1998) model. The recommended strategies for the UK and the EU include reducing domestic transportation costs, while tariffs and retaliatory tariffs act as a double-edged sword, potentially enhancing or undermining their trade positions. |
| Keywords: | Brexit, economic geography model, global--local system, hierarchical spatial economy, reduction analysis, tariffs, trade liberalization, trade strategy. |
| JEL: | F15 F22 R12 |
| Date: | 2025–08–09 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125691 |
| By: | Eric Donald; Masao Fukui; Yuhei Miyauchi |
| Abstract: | How do regional productivity shocks or transportation infrastructure improvements affect aggregate welfare? In a general class of spatial equilibrium models, we provide a formula for aggregate welfare changes, decomposed into terms associated with (i) technology (Fogel 1964, Hulten 1978), (ii) spatial dispersion of marginal utility, (iii) fiscal externalities, (iv) technological externalities, and (v) redistribution. We further use this decomposition to derive a general formula for optimal spatial transfers and show that, whenever optimal transfers are in place, the technology term alone captures the aggregate welfare effects of technological shocks. We apply our framework to study welfare gains from improving the US highway network. We find that changes in the spatial dispersion of marginal utility are as important as technological externalities in accounting for the deviations from the Fogel-Hulten benchmark to assess welfare gains. |
| JEL: | E0 F0 R0 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34075 |
| By: | Pablo Quintana (UNCuyo); Marcos Herrera-Gómez (CIANECO/CONICET/Universidad Nacional de Río Cuarto) |
| 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. |
| Keywords: | Spatial clustering, Spatial Data Science, Spatio-temporal Classification, Territorial analysis. |
| JEL: | C23 C45 C63 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:aoz:wpaper:368 |
| By: | Tatsuru Kikuchi |
| Abstract: | This paper develops the first comprehensive theoretical and empirical framework for analyzing AI-driven spatial distribution dynamics in metropolitan areas undergoing demographic transition. We extend New Economic Geography by formalizing five novel AI-specific mechanisms: algorithmic learning spillovers, digital infrastructure returns, virtual agglomeration effects, AI-human complementarity, and network externalities. Using Tokyo as our empirical laboratory, we implement rigorous causal identification through five complementary econometric strategies and develop machine learning predictions across 27 future scenarios spanning 2024-2050. Our theoretical framework generates six testable hypotheses, all receiving strong empirical support. The causal analysis reveals that AI implementation increases agglomeration concentration by 4.2-5.2 percentage points, with heterogeneous effects across industries: high AI-readiness sectors experience 8.4 percentage point increases, while low AI-readiness sectors show 1.2 percentage point gains. Machine learning predictions demonstrate that aggressive AI adoption can offset 60-80\% of aging-related productivity declines. We provide a strategic three-phase policy framework for managing AI-driven spatial transformation while promoting inclusive development. The integrated approach establishes a new paradigm for analyzing technology-driven spatial change with global applications for aging societies. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.19911 |
| By: | Rodríguez-Pose, Andrés; Sandu, Alexandra |
| Abstract: | In this paper we investigate what determines access to banking in Central and Eastern Europe (CEE). The research uses different waves of the OeNB Euro Survey – covering over 91, 000 individuals during the period 2012–2020 – and pooled and multilevel logit models to analyse how the interplay of trust in institutions, socio-economic attributes and geographic contexts shapes access to bank accounts, savings deposits and loans across 10 CEE countries. The findings reveal significant disparities in banking inclusion across products: while institutional trust enhances access to current accounts and savings deposits, its impact on loans is weaker. Socio-economic factors and geographical contexts, particularly at the local NUTS3 level, also matter enormously for financial inclusion. National and local economic conditions are key in shaping variations in financial inclusion/exclusion across CEE. |
| Keywords: | banking access; institutional trust; financial inclusion; Central and Eastern Europe; multilevel analysis |
| JEL: | G21 O16 R11 |
| Date: | 2025–07–28 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:128413 |
| By: | Dennis Egger; Benjamin Faber; Ming Li; Wei Lin |
| Abstract: | We combine a new collection of microdata from China with a natural policy experiment to investigate the extent to which reductions in rural-urban migration barriers affect flows of trade and investments between cities and the countryside. We find that increases in worker eligibility for urban residence registration (Hukou) across origin-destination pairs increase rural-urban exports, imports, capital inflows and outflows, both in terms of bilateral transaction values and the number of unique buyer-seller matches. To quantify the implications at the regional level, we interpret these estimates through the lens of a spatial equilibrium model in which migrants can reduce buyer-seller matching frictions. We find that a 10% increase in a rural county's migration market access on average leads to a 1.5% increase in the county's trade market access and a 2% increase in investment market access. In the context of China's recent Hukou reforms, we find that these knock-on effects on market integration were on average larger among the urban destinations compared to the rural origins, reinforcing incentives for rural-urban migration. |
| JEL: | F63 O12 R11 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34098 |
| By: | Karsten Mau; Mingzhi (Jimmy) Xu; Yawen Zheng |
| Abstract: | We evaluate how access to international transport infrastructure promotes trade and economic development. Exploiting the gradual unfolding of transcontinental rail freight connections between China and Europe, our empirical findings indicate increasing exports from connected cities, with positive spillovers to neighboring cities and other indicators economic activity. Not all products and cities are equally responsive to new rail export opportunities. We set up a multi-sector heterogeneous firms model with a rich specification of trade costs, in which firms optimize trade costs by choosing alternative transportation modes and routes. Leveraging a unique data set on trade flows between Chinese cities, we calibrate our model to discuss local welfare effects, relying on sufficient statistics that quantify changes in city-level trade costs. We also highlight significant spatial distributional effects of trade infrastructure development. |
| Keywords: | transport infrastructure, trade, regional development, China |
| JEL: | F14 F15 R11 R41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12027 |
| By: | Fraske, Tim |
| Abstract: | The concept of Reallabore (real-world laboratories) has undergone remarkable semantic evolution in Germany - rooted in the experimental turn in social sciences, shaped in sustainability research, and culminating in national innovation policy. This paper frames Reallabore as a travelling concept: a term that shifts in meaning as it moves across institutional, disciplinary, and political contexts. Drawing on perspectives from economic geography, it traces four distinct phases in the evolution of the term, highlighting the tensions and strategic translations that have shaped its development. Understanding such conceptual trajectories is key to interpreting the performative power of innovation discourse in regional policymaking. |
| Keywords: | Economic geography, travelling concept, real-world laboratory, innovation policy, experimental governance |
| JEL: | O31 O38 R11 R58 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:322478 |
| By: | Surender Raj Vanniya Perumal; Mark Thissen; Marleen de Ruiter; Elco E. Koks |
| Abstract: | Disasters often impact supply chains, leading to cascading effects across regions. While unaffected regions may attempt to compensate, their ability is constrained by their available production capacity and logistical constraints between regions. This study introduces a Multi-Regional Impact Assessment (MRIA) model to evaluate the regional and macroeconomic consequences of disasters, capturing regional post-disaster trade dynamics and logistical constraints. Our findings emphasize that enhancing production capacity alone is inadequate; regional trade flexibility must also be improved to mitigate disaster impacts. At the regional level, disaster-affected areas experience severe negative impacts, whereas larger, export-oriented regions benefit from increased production activity. Additionally, we propose a sectoral criticality assessment alongside the more common sensitivity and incremental disruption analysis, which effectively identifies sectors with low redundancy while accounting for the potential for regional substitution in a post-disaster scenario. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.00510 |