Network Economics http://lists.repec.org/mailman/listinfo/nep-net Network Economics 2026-06-22 When market boundaries weaken: Network reconfiguration and regime-dependent cross-asset spillovers https://d.repec.org/n?u=RePEc:arx:papers:2605.30442&r=&r=net Cryptocurrencies are increasingly adopted as investment assets, making their interactions with traditional financial markets central to cross-asset diversification and systemic risk. This paper studies the integration of cryptocurrencies, fiat currencies, and S&P500 equities using a balanced panel of 381 assets from October 2017 to February 2024. We combine rolling correlation networks, consensus-based community detection, market-specific and system-wide Turbulence Indices, and VAR-based connectedness analysis to examine how market stress, network topology, and shock transmission co-evolve across regimes. The results show that cross-asset integration is episodic. In normal periods, the three asset classes remain relatively segmented, whereas under stress, local clustering increases, modular separation weakens, and communities become more compositionally mixed across asset classes. Connectedness analysis further shows that regime shifts alter the structure of transmission rather than simply increasing spillover magnitudes. In high-turbulence states, fiat-market turbulence becomes the main propagation channel, while network clustering and modularity become more involved in forecast-uncertainty transmission. These findings support the interpretation of network topology as an emergent, state-dependent amplification channel rather than a persistent exogenous driver of turbulence. The results highlight the need for regime-aware risk monitoring, since full-sample connectedness estimates can understate the coupling that arises when diversification benefits are most vulnerable. Ruixue Jing Luis Enrique Correa Rocha 2026-05 Predicting Shock Propagation and Uncovering Heterogeneity with Graph Neural Networks https://d.repec.org/n?u=RePEc:eti:dpaper:26045&r=&r=net Recent research has made substantial progress in studying shock propagation through inter-firm transaction networks, and empirical studies have directly documented firm-level shock propagation. Despite these advances in both theory and empirics, no method has yet been established to accurately predict the effects of large-scale future shocks, such as natural disasters, financial crises, or pandemics. A central challenge is the heterogeneity inherent in firms and transaction relationships, which makes it difficult to identify which firms are important for shock propagation and which links amplify it. To address this issue, this study uses firm-level data and a graph neural network (GNN) to predict firm growth rates with a model that explicitly incorporates network structure. In particular, by analyzing the trained GNN model, we quantitatively identify the firms and transaction links that are important for shock propagation. Using the global financial crisis, specifically the sharp decline in exports, as a case study, we show that incorporating network structure significantly improves predictive performance and enables us to identify specific firms and links that are important for propagation. Yoshiyuki ARATA 2026-05 GDP-Driven Structural and Dynamical Heterogeneity in the Synchronization of Chaotic Macroeconomic Networks https://d.repec.org/n?u=RePEc:arx:papers:2605.21806&r=&r=net We investigate the emergence of synchronization in a network of coupled chaotic macroeconomic systems. Each node represents an economy characterized by three key variables savings, gross domestic product (GDP), and foreign capital inflows. These economies interact or are connected through a fitness-based probability that depends on the potential GDP of each node. This formulation allows both structural heterogeneity, arising from uneven network connectivity, and dynamical heterogeneity, due to differences in local parameters, to be explored within a unified framework. Using both numerical simulations and a mean-field approximation, by varying the coupling strength and the degree of heterogeneity of both network topology and dynamical behavior of the nodes, we analyze synchronization transitions. Our results show that the mean-field approach accurately captures the collective dynamics in homogeneous and fully connected networks even with heterogeneity within the intrinsic dynamic of the nodes but fails when strong heterogeneity in the structure of the network is introduced. In heterogeneous networks, the system exhibits partial synchronization and on--off intermittency, where coherent phases of global synchronization alternate with abrupt desynchronization bursts. The distribution of laminar phase durations follows a power-law scaling, consistent with theoretical predictions for intermittent synchronization. From an economic perspective, these results suggest that global business cycle synchronization is inherently fragile: strong integration can promote temporary coordination among economies, but structural and dynamical disparities inevitably lead to intermittent breakdowns of collective behavior. Thierry Njougouo Fernando Fagundes Ferreira Diego Garlaschelli 2026-05 Two-scale topological momentum and persistence of stress regimes in correlation networks: evidence from equity markets https://d.repec.org/n?u=RePEc:pra:mprapa:129341&r=&r=net We apply persistent homology to the time-varying correlation network of 49 Fama –French industry portfolios (1976–2026) to study synchronization transitions associated with market stress. Vietoris–Rips filtrations on rolling Mantegna distance matrices capture one-dimensional homological cycles (H1) that are associated with intransitive triples of sectors—configurations where two pairwise correlations are strong while the third remains relatively weak. The analysis reveals a two-scale topological structure:stress episodes amplify intransitivity among the most strongly correlated industries while dissolving it among weakly and moderately correlated ones. Because static topological indicators are highly collinear with average correlation, we shift attention to the momentum of topological reorganization. Using strict temporal separation and moving-block bootstrap validation, we find that the standardized rate of change in the persistence-weighted mean cycle birth parameter provides information beyond standard synchronization metrics, improving forecasts of stress onset. Decomposing cycles into sectoral triples maps abstract topology onto interpretable sectoral linkages. The method avoids look-ahead bias and applies to other domains with time-varying correlation networks. Yagufarov, Ruslan persistent homology, topological data analysis, financial correlation networks, market stress, synchronization transitions, Vietoris-Rips filtration, Fama-French industry portfolios, out-of-sample forecasting, regime detection, systemic risk 2026-05-31 Merit or networks? What decides where research is published https://d.repec.org/n?u=RePEc:arx:papers:2606.03763&r=&r=net Does scientific publishing reward the quality of ideas or the advantage of connections? The question is universal to prestige-driven science, yet it has resisted decades of study because a paper's quality could not be gauged ahead of its publication fate without using that fate as the yardstick. We break this constraint by measuring a paper's idea quality directly from its text, before publication, using a discipline-trained LLM evaluator that scores the idea without seeing author names or outcomes. Using economics as a case study, we combine this text-legible idea-quality score with an execution-quality rubric, a connection index, an author-ability index, and an off-the-shelf language-model text score to estimate a five-input production function for journal placement across 6, 208 economics working papers. The inputs are not rivals but a sequence along the ladder of prestige. Execution sets a meritocratic floor and is the largest input overall. Text-legible idea quality grades the rungs in between. Connections set a favoritism ceiling that bites mainly near the apex, the most selective journals. Connections work through two additive channels: connected authors write papers that score higher, and at equal scores their papers are still more likely to place better. Yet this advantage is bounded. Connections raise the odds of every rung without making the apex the typical outcome for ordinary ideas, and even the highest-scoring papers face real friction reaching the visible journal ladder. The result nests, rather than chooses between, the meritocracy and network accounts of how science is published. Ning Li 2026-06 When social networks polarize: On the number of clusters in the Hegselmann–Krause model https://d.repec.org/n?u=RePEc:hal:journl:hal-05611642&r=&r=net In the present paper, we study opinion dynamics in a social network, where individuals only listen to those with opinion not farther away than a given threshold from their own opinion (known as bounded confidence models, proposed by Hegselmann and Krause). It is well known that in bounded confidence models consensus does not always exist, and that agents split in clusters (polarization), with convergence to consensus in each cluster. We are precisely interested in the effect of bounded confidence on polarization in the network. Our main focus concerns the formation of clusters and their number, as well as its non-monotonicity with respect to the value of the threshold. First, a framework with a finite number of agents is considered. We study analytically disintegration of various types of opinion chains (clusters), and investigate by simulation the likelihood of chains of a certain length and their disintegration. Next, we examine the (non-)monotonicity of the number of clusters with respect to the threshold for a given initial vector of opinions and in expectation. Finally, we analyse in a formal way the formation of clusters in a model with a continuum of agents. Wout de Vos Michel Grabisch Agnieszka Rusinowska Opinion dynamics, Polarization, Clusters, Bounded confidence, Non-monotonicity, Network formation, Continuous opinion 2026-05 Geopolitical Rivalry Reshapes Global Innovation Networks https://d.repec.org/n?u=RePEc:rif:briefs:182&r=&r=net Abstract Geopolitical tensions have increasingly extended to the development of strategic technologies. In particular, technological rivalry between the United States and China has reshaped firms’ international innovation networks and the organization of research and development activities. Patent data from leading 5G firms indicate that the effects of geopolitical fragmentation are strongest among firms whose innovation networks were previously highly integrated across geopolitical blocs. In these firms, the increase in geopolitical fragmentation is associated with a reduction of approximately 2.1 percentage points in the likelihood of collaboration between cross-block inventors, equivalent to roughly one quarter of the average level of collaboration. Geopolitical fragmentation also reduces inventor team diversity and the participation of inventors from rival geopolitical blocs. The effects were the broadest among Chinese firms. The findings suggest that geopolitical rivalry affects not only trade, investment, and technology transfer but also innovation networks through which new technologies are developed. In strategic industries such as 5G, geopolitical fragmentation may narrow the channels of international knowledge exchange and reshape the structure of global innovation networks. Koski, Heli 5G, Geopolitical fragmentation, Innovation networks, Crossborder collaboration, Patents 2026-06-09 Recurrence as a Governance Signal: Diagnostic Network Metrics for Public Procurement Oversight in Greece https://d.repec.org/n?u=RePEc:hel:greese:219&r=&r=net This study examines what recurring buyer–supplier relationships in Greek public procurement reveal about routinised contracting behaviour. Drawing on contract award data from Greece's Central Electronic Registry of Public Contracts (KIMDIS, 2018–2025), it models procurement as a temporally evolving bipartite network across twelve domains, generating seven year-pair predictions. Three interpretable network signals — Historical Frequency, Preferential Attachment, and an adapted Adamic–Adar index — capture routinised continuity, structural concentration, and context-bound repetition. Predictability varies systematically across domains (AUC 0.80–0.96), with feature importance shifting from history-driven to structurally diverse recurrence over time. Authority-level analysis reveals extreme within-domain heterogeneity (vendor diversity 1–300+, HHI 0.008–1.0), demonstrating that uniform oversight thresholds are structurally inappropriate. The framework suggests differentiated governance responses — contestability reviews, dependency audits, and specification reform — and can be integrated into Greece's existing digital procurement infrastructure. Results are robust across three negative sampling specifications. Ioannis G. Fountoukidis Eleni L. Dafli Ioannis E. Antoniou Nikos C. Varsakelis public procurement, organisational routines, governance diagnostics, contestability, Greece 2026-05 Mitigation of spatial economic impact propagation of highway disruptions by redundant networks https://d.repec.org/n?u=RePEc:arx:papers:2606.00614&r=&r=net The damage to transportation infrastructure caused by disasters can indirectly lead to economic damage through economic interdependence, even in areas that are not directly affected. However, even when transportation routes are interrupted by a disaster, the damage can be mitigated if alternative routes are secured. Rural areas with low-density transportation networks are more vulnerable to traffic disruptions in a disaster. This study develops a method for evaluating the effectiveness of redundant transportation networks in mitigating economic vulnerability in the event of a disaster. Our methodology combines inter-regional road network connectivity with a spatial computable general equilibrium (SCGE) model. We apply the method to road disruption scenarios in the Chugoku region of Japan, which has a system of parallel highways. The affected areas are in close geographical proximity to many rural areas and have strong economic interdependencies with them. Several counterfactual simulations depicted the situation without the alternative road and the disaster. We evaluate the transportation impacts, measured by changes in travel time, and the economic impacts, measured by negative benefits, respectively. The results suggest that the economic vulnerability reduction effect is more far-reaching than the transportation impacts. Tomoki Ishikura 2026-05 Ownership Networks and Economic Power in the Italian Energy Sector https://d.repec.org/n?u=RePEc:arx:papers:2605.25555&r=&r=net The energy sector is a cornerstone of national strategic autonomy, yet its increasing financialization has transformed ownership structures into complex networked configurations. This paper investigates the distribution of economic power in the Italian energy sector by introducing two sector-level extensions of the Network Power framework: the Aggregate Network Power Index (A-NPI) and the Aggregate Network Power Flow (A-NPF). Unlike traditional macro-level measures, these indices aggregate firm-level control and influence into a systemic framework that accounts for the relative economic weight of each operator. Applying this framework to the Italian case reveals a "Governance Paradox": while the State retains formal majority ownership, the sector's deepening reliance on global capital markets and the pervasive presence of common ownership by transnational institutional investors have progressively hollowed out public strategic direction. The results show that capital centralization enables global financial actors to internalize sectoral competition, fostering a regime of tacit strategic convergence in the management of critical infrastructure. This configuration challenges European strategic autonomy, raising questions about the adequacy of traditional Foreign Direct Investment (FDI) screening and antitrust tools in addressing the systemic influence exerted through networked ownership structures. Andrea Pannone Francesco Giancaterini Tiziano Bacaloni Andrea Bernardini Alessio Abeltino 2026-05 Laços entre cooperativas: um estudo sobre a prática e impacto do uso de administradores em comum https://d.repec.org/n?u=RePEc:pra:mprapa:128965&r=&r=net The connections between organizations, through their main decision-making bodies, create links known as Board Interlocking, with effects that extend beyond the operational sphere. Based on Social Network Analysis and interviews, this study investigates these connections and their implications in cooperatives in Southern Brazil. The motivations for the phenomenon were compared with the reasons traditionally presented in the literature, and real cases are transcribed to demonstrate worrying impacts on governance and democratic equity in cooperatives. The results confirmed the existence of interconnections in cooperatives and demonstrated their use as part of a controversial strategy for maintaining political and institutional power. Schneider, Alexandre Marcelo Carbonai, Davide Board Interlocking; Governance; Conflict of interest; Cooperativism; Leadership 2025-11-23