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on Economic Geography |
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Issue of 2025–11–24
nine papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Kikuchi, Tatsuru |
| Abstract: | This paper develops a unified theoretical and empirical framework for analyzing treatment effects that propagate through both spatial proximity and network connections. Building on the continuous functional approach in \citet{kikuchi2024dynamical} and the Navier-Stokes foundation in \citet{kikuchi2024navier}, I introduce network channels as continuous internal degrees of freedom, deriving both spatial diffusion and network contagion from common first principles rooted in conservation laws and stochastic processes. The framework resolves three fundamental challenges in modern econometrics: how spatial and network effects interact (the mixed effect), how treatment effects evolve in general equilibrium, and how network structure affects system fragility. I show that the mixed spatial-network effect emerges naturally at second order in perturbation theory, creating synergistic amplification when geographic proximity and network similarity align. The theoretical analysis yields three main contributions. First, I derive explicit expressions for the mixed effect functional, showing it equals the mutual information between spatial and network coordinates—a purely information-theoretic measure with no free parameters. Second, I extend the analysis to general equilibrium, proving that endogenous price and employment adjustments amplify partial equilibrium estimates by factors between 1.8 and 2.5 depending on market structure. Third, I connect network structure to system fragility through entropy production rates, providing operational measures of how consolidation affects shock dissipation speeds and cascade probabilities. The empirical application uses county-level wage data (2018-2023) to analyze minimum wage spillovers across 3, 142 U.S. counties and 274 industry classifications. Four main findings emerge. First, the mixed spatial-network effect accounts for 40 percent of total treatment propagation, with point estimate 0.043 (s.e. 0.008), statistically significant and economically large. This implies retail workers in Nevada counties near the California border experience wage increases 43 percent larger than the sum of pure spatial spillover (from proximity alone) and pure network effect (from industry connections) would predict. Second, spatial decay parameters increase from 0.01 per mile for pure geographic spillovers to 0.02 when network effects are included, demonstrating that networks concentrate rather than disperse spatial impacts. Third, general equilibrium amplification factors range from 1.8 (dispersed markets) to 2.5 (concentrated markets), implying substantial bias in partial equilibrium policy evaluation. Fourth, entropy-based fragility measures predict out-of-sample shock propagation with $R^2 = 0.67$, outperforming standard network centrality metrics ($R^2 = 0.43$). These findings have direct policy implications. Minimum wage policies should account for network amplification: optimal state-level minimum wages are 15-20 percent lower when accounting for general equilibrium feedbacks through supply chains and labor mobility networks. Financial regulation should monitor entropy production rates as early warning indicators: systems approaching critical fragility thresholds (entropy production declining by more than 30 percent) require preemptive intervention before cascades materialize. Regional development policies should leverage spatial-network synergies: infrastructure investments yield highest returns in regions with strong geographic clustering and dense economic networks. |
| Keywords: | Spatial treatment effects, network economics, general equilibrium, continuous functionals, diffusion processes, entropy production, mixed effects, system fragility, minimum wage, labor markets |
| JEL: | C14 C21 C31 C51 D04 E24 I38 R12 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126723 |
| By: | Alessandro Borin; Francesco Paolo Conteduca; Fabrizio Leone; Michele Mancini; Patrick Zoi |
| Abstract: | This paper examines how international trade shocks transmit through domestic supply chains, shaping local economic vulnerabilities. Using detailed firm-to-firm domestic and foreign transaction data, we quantify the direct and indirect exposure of Italian labor markets to two major sources of external risk: imports from China and exports to the United States. We quantify the importance of firms’ domestic and foreign linkages for overall exposure and highlight the critical role of wholesalers and top trading firms within the domestic network in shaping tails risks. Pronounced local disparities in exposure reveal that aggregate trade statistics conceal substantial and uneven regional vulnerabilities. |
| Keywords: | global value chains, local labor markets, trade shocks, firm-to-firm linkages, geopolitical fragmentation, production network |
| JEL: | F14 R12 L14 F61 R15 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12271 |
| By: | Mohamed Zahidi (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar)); Sara Ousghir (UCD - Université Chouaib Doukkali); Hajar Makry (UCD - Université Chouaib Doukkali); Ayoub Kassimi (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar)) |
| Abstract: | Numerous studies have focused on the relationship between proximitymainly geographical -and business innovation in a given territory (Chesbrough, 2003; Laursen & Salter, 2006; Mongo, 2013). The objective of our research is to study the link between the proximity of all forms and start-ups' level of innovation in the Casablanca-Settat region of Morocco by applying structural equation modelling (PLS-SEM) using the Smart PLS 3.3.9 software. Moreover, a structural model is proposed that can be used to assess the level of innovation in organizations based on their internal capacities (human, financial, and technical capital) and the logic of proximity established within their local and global environment. To verify our hypotheses, the proposed model is tested on a sample of 98 Moroccan start-ups, relying on the mixed methodology of the hypothetico- |
| Keywords: | proximity, innovation, internal capabilities, Moroccan start-ups, PLS-SEM approach |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05243699 |
| By: | Ioramashvili, Carolin |
| Abstract: | The successful implementation of industrial strategies relies on high-quality evidence of interventions that work. Yet, there is a lack of such evidence, particularly for local and regional economic policy. While policymakers at all levels of government express a strong desire for better evidence, limited research has addressed the question of why more resources are not devoted to producing better evidence. This article identifies barriers to more and better evaluation of industrial and economic policy more generally. This is a pertinent question in the UK context as a new industrial strategy is launched, while local government is undergoing a reorganisation with new powers for economic policy being devolved. The article makes two contributions. First, it argues that evaluation and evidence should be treated as a public good that will be underprovided without deliberate investment. Second, the lack of a strong ecosystem for evaluation at the local level is identified, which could act as a flexible resource to improve evaluation capacity and capability and support the use of existing evidence. Implications for the design of incentives and institutions for evaluation are considered. |
| Keywords: | evaluation; devolution; industrial policy; institutions; local economic growth policy; local government |
| JEL: | R14 J01 |
| Date: | 2025–10–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130096 |
| By: | Kikuchi, Tatsuru |
| Abstract: | This paper develops a dual-channel framework for analyzing technology diffusion that integrates spatial decay mechanisms from continuous functional analysis with network contagion dynamics from spectral graph theory. Building on \citet{kikuchi2024navier} and \citet{kikuchi2024dynamical}, which establish Navier-Stokes-based approaches to spatial treatment effects and financial network fragility, we demonstrate that technology adoption spreads simultaneously through both geographic proximity and supply chain connections. Using comprehensive data on six technologies adopted by 500 firms over 2010-2023, we document three key findings. First, technology adoption exhibits strong exponential geographic decay with spatial decay rate $\kappa \approx 0.043$ per kilometer, implying a spatial boundary of $d^* \approx 69$ kilometers beyond which spillovers are negligible (R-squared = 0.99). Second, supply chain connections create technology-specific networks whose algebraic connectivity ($\lambda_2$) increases 300-380 percent as adoption spreads, with correlation between $\lambda_2$ and adoption exceeding 0.95 across all technologies. Third, traditional difference-in-differences methods that ignore spatial and network structure exhibit 61 percent bias in estimated treatment effects. An event study around COVID-19 reveals that network fragility increased 24.5 percent post-shock, amplifying treatment effects through supply chain spillovers in a manner analogous to financial contagion documented in \citet{kikuchi2024dynamical}. Our framework provides micro-foundations for technology policy: interventions have spatial reach of 69 kilometers and network amplification factor of 10.8, requiring coordinated geographic and supply chain targeting for optimal effectiveness. |
| Keywords: | Technology diffusion, Supply chain networks, Spatial treatment effects, Network contagion, Navier-Stokes dynamics, Spectral graph theory |
| JEL: | C31 D85 L14 O33 R11 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126724 |
| By: | Kikuchi, Tatsuru |
| Abstract: | This paper develops a unified theoretical framework for detecting and estimating boundaries in treatment effects across both spatial and temporal dimensions. We formalize the concept of treatment effect boundaries as structural parameters characterizing regime transitions where causal effects cease to operate. Building on reaction-diffusion models of information propagation, we establish conditions under which spatial and temporal boundaries share common dynamics governed by diffusion parameters $(\delta, \lambda)$, yielding the testable prediction $d^*/\tau^* = 3.32\lambda\sqrt{\delta}$ for standard detection thresholds. We derive formal identification results under staggered treatment adoption and develop a three-stage estimation procedure implementable with standard panel data. Monte Carlo simulations demonstrate excellent finite-sample performance, with boundary estimates achieving RMSE below 10\% in realistic configurations. We apply the framework to two empirical settings: EU broadband diffusion (2006-2021) and US wildfire economic impacts (2017-2022). The broadband application reveals a scope limitation --- our framework assumes depreciation dynamics and fails when effects exhibit increasing returns through network externalities. The wildfire application provides strong validation: estimated boundaries satisfy $d^* = 198$ km and $\tau^* = 2.7$ years, with the empirical ratio (72.5) exactly matching the theoretical prediction $3.32\lambda\sqrt{\delta} = 72.5$. The framework provides practical tools for detecting when localized treatments become systemic and identifying critical thresholds for policy intervention. |
| Keywords: | Difference-in-Differences, Spatial Spillovers, Treatment Effect Heterogeneity, Diffusion Equations, Atmospheric Dispersion, Boundary Detection |
| JEL: | C21 C23 Q53 R11 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126732 |
| By: | Brugiavini, Agar; Di Cataldo, Marco; Romani, Giulia |
| Abstract: | The spatial concentration of knowledge-intensive activities can generate multiplicative effects at the local level. This paper examines how employment growth in knowledge-intensive and tradable sectors affects wage, days worked, and internal migration of non-tradable workers in Italy. We leverage matched employer-employee data (2005–2019) to track individuals across jobs and locations. Our empirical strategy combines a two-step estimation with a shift-share instrument to disentangle the roles of worker sorting and local spillovers. We find that knowledge sector expansion increases the number of days worked locally and attracts non-tradable workers. It also raises nominal wages, but only when sorting is not accounted for, suggesting selective inflows of more productive workers into knowledge hubs. However, rising local living costs offset nominal wage gains, leading to lower real wages. |
| Keywords: | labour demand shocks; knowledge economy; local spillovers; sorting; Italy |
| JEL: | J23 J61 R12 R23 |
| Date: | 2025–12–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130106 |
| By: | Rongjun Ao; Ling Zhong; Jing Chen; Xiaojing Li; Xiaoqi Zhou |
| Abstract: | While prior research has emphasized the path-dependent nature of occupational systems, it has paid limited attention to how local industrial structures contribute to occupational change. To address this gap, this study examines how regional occupational evolution is shaped by two distinct mechanisms: (1) path-dependent skill and knowledge transfer, whereby new occupations emerge through the recombination of existing occupational structures; and (2) industry-driven task reconfiguration, through which industrial upgrading reshapes the demand for occupations. To operationalize these dynamics, the concept of industry–occupation cross-relatedness is introduced, capturing the proximity between new occupations and a region’s existing industrial portfolio. Drawing on panel data from 241 Chinese cities between 2000 and 2015, the study estimates the effects of both occupational relatedness and cross-relatedness on new occupation specialization. The results reveal that both mechanisms significantly promote occupational evolution, yet they tend to function as substitutes rather than complements. Furthermore, their effects differ across skill levels: high-skilled occupations are more responsive to industrial transformation, low-skilled occupations to occupational pathways, while medium-skilled occupations exhibit relatively weak responsiveness to both. These findings underscore the importance of structural conditions and skill heterogeneity in shaping regional patterns of occupational change. |
| Keywords: | Occupational Evolution; Path Dependence; Chinese Cities; Industry-Occupation Cross-Relatedness; Skill Heterogeneity |
| JEL: | R11 O14 N95 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2534 |
| By: | Alfonso Diez-Minguela (Universitat de València, Valencia (Spain)); Francisco J. Goerlich (Universitat de València & IVIE, Valencia (Spain)); Rafael González Val (Universidad de Zaragoza, Zaragoza (Spain)); Daniel A. Tirado-Fabregat (Universitat de València, Valencia (Spain)) |
| Abstract: | This study presents a novel methodology for constructing a historical population grid, ESGRID1887, that sheds light on the spatial distribution of Spain’s population in the late nineteenth century. The grid is compared, at a granular and temporally consistent scale, with population settlement patterns revealed by the most recent population grid produced by EUROSTAT (GEOSTAT2021). ESGRID1887 uses data from the Nomenclátor of Spain (1887) and cadastral records to distribute the population reported in the 1887 Spanish Census across 1 km² cells. Unlike analyses based on administrative units (municipalities), this fine-grained approach highlights the historical significance of dispersed settlement across large areas of the Atlantic, Cantabrian, and Mediterranean peripheries, as well as in several mountainous regions of the peninsula in 1887. Moreover, the comparison with GEOSTAT2021 reveals that although the populated area increased from 21.6% of the territory in 1887 to 26.4% in 2021, this modest expansion resulted from two opposing dynamics: sprawl and depopulation. One third of the cells occupied in 2021 were uninhabited in 1887, while one third of those inhabited in 1887 are now uninhabited. The new evidence presented in this article thus reveals an additional dimension of the long-term depopulation process affecting a substantial part of Spain—the emptying of the territory—which has not previously been examined from a historical perspective. |
| Keywords: | Digital Humanities, Historical Grids, Depopulation, Geography, Spain |
| JEL: | J11 N33 N01 R11 R23 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:ahe:dtaehe:2505 |