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on Network Economics |
| By: | Kikuchi, Tatsuru |
| Abstract: | This paper develops a continuous functional framework for analyzing contagion dynamics in financial networks, extending the Navier-Stokes-based approach to network-structured spatial processes. We model financial distress propagation as a diffusion process on weighted networks, deriving a network diffusion equation from first principles that predicts contagion decay depends on the network's algebraic connectivity through the relation $\kappa = \sqrt{\lambda_2/D}$, where $\lambda_2$ is the second-smallest eigenvalue of the graph Laplacian and $D$ is the diffusion coefficient. Applying this framework to European banking data from the EBA stress tests (2018, 2021, 2023), we estimate interbank exposure networks using maximum entropy methods and track the evolution of systemic risk through the COVID-19 crisis. Our key finding is that network connectivity declined by 45\% from 2018 to 2023, implying a 26\% reduction in the contagion decay parameter. Difference-in-differences analysis reveals this structural change was driven by regulatory-induced deleveraging of systemically important banks, which experienced differential asset reductions of 17\% relative to smaller institutions. The networks exhibit lognormal rather than scale-free degree distributions, suggesting greater resilience than previously assumed in the literature. Extensive robustness checks across parametric and non-parametric estimation methods confirm declining systemic risk, with cross-method correlations exceeding 0.95. These findings demonstrate that post-COVID-19 regulatory reforms effectively reduced network interconnectedness and systemic vulnerability in the European banking system. |
| Keywords: | Financial networks, systemic risk, contagion dynamics, network diffusion, algebraic connectivity, Navier-Stokes equations, maximum entropy estimation, European banking |
| JEL: | C45 D85 G21 G28 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126729 |
| 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: | Valerio Dionisi |
| Abstract: | Complementarities in intermediate inputs trigger the even transmission of asymmetric shocks in production networks. This paper linearly captures these complementarities through shared inter-sectoral trade relationships, and makes two novel contributions to the understanding of networked economies. First, it introduces a theoretical framework that distinguishes between factor input demand and factor input supply network distances, measuring economic distance between sectors based on common upstream sellers or downstream buyers. These horizontal interdependencies determine how sector-specific shocks transmit horizontally across the network, complementing and balancing the standard vertical (Leontief inverse) mechanism. Second, using sector-level U.S. employment data, the paper provides empirical evidence that positive employment shocks in closely demand- or supply-connected sectors are attenuated, whereas larger distances generate employment comovement. Together, these two contributions reveal that the horizontal geometry of a production network plays a critical role in understanding how sectoral interactions propagate micro-originated shocks in an Input-Output economy. |
| Keywords: | Input-Output economy, production networks, network distance, horizontal transmission, sectoral comovement, tools for policy design |
| JEL: | C67 D57 E32 F16 L14 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:mib:wpaper:559 |
| By: | Pasquale Accardo (University of Bath); Adriano Amati (Università Ca' Foscari Venezia); Giovanni Mastrobuoni (Collegio Carlo Alberto; University of Turin; University of Essex) |
| Abstract: | This study uses a unique longitudinal data set on daily museum visits in Northern Italy to investigate how social networks influence leisure consumption. Based on detailed administrative records of museum cardholders, we use repeated joint visits to build a dynamic network of peers. We identify peer effects that exploit exogenous variation in membership prices generated by age-based discounts. We find robust evidence of peer spillovers in both museum attendance and membership renewal, primarily driven by a preference for shared experiences. These results underscore the role of social interactions in shaping leisure demand and support the view that social networks can amplify individual behavior. More broadly, our findings contribute to the understanding of peer dynamics in settings where consumption is inherently social. |
| Date: | 2025–09–25 |
| URL: | https://d.repec.org/n?u=RePEc:eid:wpaper:58192 |
| 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: | Kikuchi, Tatsuru |
| Abstract: | This paper develops and empirically implements a continuous functional framework for analyzing systemic risk in financial networks, building on the dynamic spatial treatment effect methodology established in \citet{kikuchi2024dynamical}. We extend the Navier-Stokes-based approach from \citet{kikuchi2024navier} to characterize contagion dynamics in the European banking system through the spectral properties of network evolution operators. Using high-quality bilateral exposure data from the European Banking Authority Transparency Exercise (2014-2023), we estimate the causal impact of the COVID-19 pandemic on network fragility using spatial difference-in-differences methods adapted from \citet{kikuchi2024dynamical}. Our empirical analysis reveals that COVID-19 elevated network fragility, measured by the algebraic connectivity $\lambda_2$ of the system Laplacian, by 26.9\% above pre-pandemic levels (95\% CI: [7.4\%, 46.5\%], p$ |
| Keywords: | inancial networks, Systemic risk, Navier-Stokes dynamics, Spatial treatment effects, Network contagion, Banking regulation, COVID-19 |
| JEL: | C31 C63 E44 G01 G21 G28 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126721 |
| By: | Charlie Joyez (Université Côte d'Azur, CNRS, GREDEG, France) |
| Abstract: | We study how COVID-19 a ected the ownership co-location network of French multinationals over 2012-2022. Using INSEE's LiFi, we build annual country-industry co-location networks and assess robustness via topology (density, centralization, assortativity, clustering) and edge survival (Weighted Jaccard). We then test for post-shock shifts in the determinants of dyadic co-location with MRQAP. Three results emerge. First, the network's core is robust: topology shows no discontinuity and centrality persists. Second, adaptation is continuous at the margin: around one-third of edges rewire, concentrated in the periphery while core ties endure. Third, after 2020 the determinants of tie weights change, with a reduced role for gravity-like factors and greater cross-sector rebalancing. Thus the system is structurally robust with active peripheral adjustment. Rather than strict resilience in the sense of a return to the pre-COVID configuration, we observe durable strategic reweighting. |
| Keywords: | Global Value Chain, Multinational Firms, Location Choices, Weighted Directed Networks |
| JEL: | F02 F23 F60 C4 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:gre:wpaper:2025-46 |
| By: | Kikuchi, Tatsuru |
| Abstract: | The 2008 financial crisis exposed fundamental vulnerabilities in interconnected banking systems, yet existing frameworks fail to integrate spatial propagation with network contagion mechanisms. This paper develops a unified spatial-network framework to analyze systemic risk dynamics, revealing three critical findings that challenge conventional wisdom. First, banking consolidation paradoxically increased systemic fragility: while bank numbers declined 47.3 \% from 2007 to 2023, network fragility measured by algebraic connectivity rose 315.8 \%, demonstrating that interconnectedness intensity dominates institutional count. Second, financial contagion propagates globally with negligible spatial decay (boundary d* = 47, 474 km), contrasting sharply with localized technology diffusion (d* = 69 km)—a scale difference of 688 times. Third, traditional difference-in-differences methods overestimate crisis impacts by 73.2 \% when ignoring network structure, producing severely biased policy assessments. Using bilateral exposure data from 156 institutions across 28 countries (2007-2023) and employing spectral analysis of network Laplacian operators combined with spatial difference-in-differences identification, we document that crisis effects amplified over time rather than dissipating, increasing fragility 68.4 \% above pre-crisis levels with persistent effects through 2023. The consolidation paradox exhibits near-perfect correlation (r = 0.97) between coupling strength and systemic vulnerability, validating theoretical predictions from continuous spatial dynamics. Policy simulations demonstrate network-targeted capital requirements achieve 11.3x amplification effects versus uniform regulations. These findings establish that accurate systemic risk assessment and macroprudential policy design require explicit incorporation of both spatial propagation and network topology. |
| Keywords: | Financial networks, Systemic risk, Spatial treatment effects, Network contagion, 2008 Financial Crisis, Consolidation paradox |
| JEL: | C31 C63 E44 G01 G21 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126725 |
| By: | Yun Young Gwak |
| Abstract: | Distinguishing between sector-specific and aggregate shocks and assessing their contributions to inflation are vital for informed policy. This paper quantifies cross-sectoral spillovers in U.S. consumer price inflation using a factor-adjusted network approach that jointly models aggregate factors and sectoral network propagation. Using disaggregated personal consumption expenditure data across 26 sectors from 1959-2024, the model employs Lasso nuclear-norm regularization to estimate high-dimensional VARs while controlling for aggregate influences. Cross-sectoral spillovers account for roughly two-fifths of total price variation--more than twice the share attributable to aggregate factors--and are systematically mismeasured in conventional models: factor models understate spillovers by absorbing network transmission into common components, while VARs without factors overstate them by conflating comovement with propagation. The spillover structure is highly granular, dominated by large consumer-facing sectors such as food, furnishings, and services, with gasoline exerting more moderate but persistent effects. Spillovers propagate mainly through backward production linkages and scale with sector size, indicating that large downstream sectors play a disproportionate role in transmitting sector-specific shocks across the price network. The findings underscore the need for integrating sectoral networks and aggregate factors in modeling inflation dynamics and policy design. |
| Keywords: | sectoral spillovers, network connectedness, inflation, cross-sectoral transmission |
| JEL: | C32 C38 E31 E32 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2025-63 |
| By: | Tatsuru Kikuchi |
| Abstract: | The 2008 financial crisis exposed fundamental vulnerabilities in interconnected banking systems, yet existing frameworks fail to integrate spatial propagation with network contagion mechanisms. This paper develops a unified spatial-network framework to analyze systemic risk dynamics, revealing three critical findings that challenge conventional wisdom. First, banking consolidation paradoxically increased systemic fragility: while bank numbers declined 47.3% from 2007 to 2023, network fragility measured by algebraic connectivity rose 315.8%, demonstrating that interconnectedness intensity dominates institutional count. Second, financial contagion propagates globally with negligible spatial decay (boundary d* = 47, 474 km), contrasting sharply with localized technology diffusion (d* = 69 km)--a scale difference of 688 times. Third, traditional difference-in-differences methods overestimate crisis impacts by 73.2% when ignoring network structure, producing severely biased policy assessments. Using bilateral exposure data from 156 institutions across 28 countries (2007-2023) and employing spectral analysis of network Laplacian operators combined with spatial difference-in-differences identification, we document that crisis effects amplified over time rather than dissipating, increasing fragility 68.4% above pre-crisis levels with persistent effects through 2023. The consolidation paradox exhibits near-perfect correlation (R = 0.97) between coupling strength and systemic vulnerability, validating theoretical predictions from continuous spatial dynamics. Policy simulations demonstrate network-targeted capital requirements achieve 11.3x amplification effects versus uniform regulations. These findings establish that accurate systemic risk assessment and macroprudential policy design require explicit incorporation of both spatial propagation and network topology. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.08602 |
| 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: | Matthew L. Elliott; Matthew O. Jackson |
| Abstract: | We introduce a parsimonious multi-sector model of international production and use it to study the impact of a disruption in the production of some goods propagates to other goods and consumers, and how that impact depends on the goods' positions in, and overall structure of, the production network. We show that the short-run impact of a disruption can be dramatically larger than the long-run impact. The short-run disruption depends on the value of all of the final goods whose supply chains involve a disrupted good, while by contrast the long-run disruption depends only on the cost of the disrupted goods. We use the model to show how increased complexity of supply chains leads to increased fragility in terms of the probability and expected short-run size of a disruption. We also show how decreased transportation costs can lead to increased specialization in production, lowering the chances for disruption but increasing the impact conditional upon disruption. We use the model to characterize the power that a country has over others via diversions of its production as well as quotas on imports and exports. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.03660 |
| By: | Kikuchi, Tatsuru |
| Abstract: | Spatial econometrics lacks principled methods for measuring minimum wage spillovers. Existing approaches assume arbitrary functional forms without theoretical justification, preventing researchers from answering basic questions: How far do effects reach? Through which channels? At what speed? This paper derives spatial treatment effects from first principles using Navier-Stokes equations. Three theoretical predictions emerge and are validated empirically. First, treatment boundaries exhibit self-similar scaling, growing proportional to the square root of elapsed time as predicted by diffusion theory (estimated exponent: 0.500, standard error: 0.001). Second, spatial weights follow Modified Bessel K-zero functions, the exact Green's function solution to the two-dimensional Helmholtz equation. This theoretically-derived specification fits observed spillover patterns substantially better than exponential, Gaussian, or power-law alternatives commonly assumed in applied work (R-squared: 0.99 versus 0.35). Third, network consolidation paradoxically increases rather than dampens wage volatility during stress periods, with consolidation-volatility correlation rising from near-zero to positive 0.0067 following COVID-19. Using 64, 421 county-quarter observations from 2018 to 2023, I estimate characteristic spillover distance of 100 miles with cumulative effects reaching 0.44 log points over four quarters. Economic network linkages dominate geographic proximity by factor of eight, demonstrating that institutional connections matter more than physical distance. Spatial decay parameters increased 27 percent during COVID-19 (from 0.0155 to 0.0196), shrinking effective spillover radius from 65 to 51 miles and confirming time-varying dynamics predicted by perturbation theory. The framework provides concrete policy guidance. Regional minimum wage coordination should encompass 100-mile radius under normal conditions, contracting to 65 miles during crises. For Japan's minimum wage reform targeting 1, 500 yen per hour by 2030, spillovers from Tokyo will substantially affect surrounding prefectures within 160 kilometers. Self-similar scaling implies effects reach half of final magnitude within one year but continue expanding indefinitely, requiring multi-year coordination frameworks. |
| Keywords: | Spatial wage spillovers, Self-similar scaling, Network fragility, Modified Bessel functions, Minimum wage policy, Japan |
| JEL: | C21 D85 J31 J38 R23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126722 |
| By: | Liping Tang; Michiko Ogaku |
| Abstract: | We study linguistic indirectness when speakers attend to social ties. Social ties are modeled by a graph, and conferences are the sets of nodes that hear a message. Conference worth is a distance polynomial on the graph; allocations are given by the Myerson value of the conference-restricted worth, which yields the bargaining-power components for each participant. Aggregating these components gives an effective bias that, via a Partition-Threshold rule, pins down the number of equilibrium message partitions in a cheap talk game. Results: (i) among trees, stars maximize worth, leading to weakly fewer equilibrium partitions; (ii) on stars, we derive closed-form effective biases, with a witness-hub marginal effect of adding leaves changing sign at $\delta^{\ast}=0.6$; (iii) for two stars joined by one link, two-star (hub-hub) vs big-star (hub-leaf) precision flips at 8/15 for the same number of nodes; private leaf-leaf conferences are most informative. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.07961 |