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on Network Economics |
| By: | Matteo Bizzarri (Università di Napoli Federico II, Napoli, Italy); Fernando Vega-Redondo (The Chinese University of Hong Kong, Hong Kong) |
| Abstract: | We quantify a parsimonious model of oligopolistic competition with common ownership in input–output networks. Using Spanish data on demand, ownership, and input–output linkages, we estimate the overall welfare effect of common ownership. Input–output linkages introduce a theoretical channel through which common ownership could improve welfare. We find that this channel exists but is not strong enough to offset the reduction in competition: common ownership has a negative welfare effect, though weaker than in the absence of input–output linkages. Finally, we introduce a parameterized ownership separation to compute a firm-level index of the anti-competitiveness of common ownership. |
| Keywords: | production networks, network games, common ownership, oligopoly |
| JEL: | D43 D57 D85 L13 L16 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:net:wpaper:25-05 |
| By: | Edouard Schaal; Mathieu Taschereau-Dumouchel |
| Abstract: | We study how time-to-build and delivery lags affect the propagation of sectoral and aggregate shocks in an economy with input-output linkages. Time-to-build significantly contributes to the persistence of shocks, with highly heterogeneous effects across sectors. We analyze delay shocks and demonstrate that bottlenecks can be identified by the product of a sector’s supplier and buyer centralities. Shocks propagate asynchronously through the network, generating endogenous fluctuations via an echo effect. These fluctuations arise due to the presence of loops in the network. We show that the Fourier spectrum of sectoral and aggregate output can be predicted from the durations and weights of the network’s dominant cycles. Sectoral comovements are complex and can be decomposed into the network’s dominant walks. |
| JEL: | C67 D57 D85 E23 E32 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:upf:upfgen:1901 |
| By: | Jaeho Choi; Jaewon Kim; Seyoung Chung; Chae-shick Chung; Yoonsoo Lee |
| Abstract: | This study examines the relationship between Federal Open Market Committee (FOMC) announcements and financial market network structure through spectral graph theory. Using hypergraph networks constructed from S\&P 100 stocks around FOMC announcement dates (2011--2024), we employ the Fiedler value -- the second eigenvalue of the hypergraph Laplacian -- to measure changes in market connectivity and systemic stability. Our event study methodology reveals that FOMC announcements significantly alter network structure across multiple time horizons. Analysis of policy tone, classified using natural language processing, reveals heterogeneous effects: hawkish announcements induce network fragmentation at short horizons ($k=6$) followed by reconsolidation at medium horizons ($k=14$), while neutral statements show limited immediate impact but exhibit delayed fragmentation. These findings suggest that monetary policy communication affects market architecture through a network structural transmission, with effects varying by announcement timing and policy stance. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.02705 |
| By: | Hwang, Joon; Alam, Nurul; Shenk, Mary K (The Pennsylvania State University) |
| Abstract: | Throughout human evolutionary history, individuals have faced two fundamental challenges under uncertainty: deciding whether to take risks and managing risks through cooperation. While both risk-taking and social risk management have been widely studied, less attention has been given to how these two processes are linked—specifically, how risk-taking itself may be shaped by social networks. We test the "social capital buffer" hypothesis, which posits that greater social connectedness promotes risk-taking by buffering against negative outcomes. Analyzing social networks and risk preferences among 140 individuals in rural Bangladesh whose livelihoods range from farming to wage labor and small-scale trade, we identify distinct pathways through which social capital influences risk preference. Highly clustered individuals in financial support networks exhibit greater risk preference, suggesting that clustering facilitates risk-taking by ensuring resource circulation within a tight-knit group. In contrast, individuals with more support-receiving ties in material support networks are more risk-averse, indicating that material support functions as informal social insurance reducing reliance on risky decisions. Finally, reciprocity in material support networks promotes risk-taking only among wealthier individuals, highlighting how individual economic resources interact with social capital to shape risk-taking. These findings reveal that social capital does not uniformly promote or constrain risk-taking but serves distinct adaptive functions based on network structure, economic conditions, and resource types, balancing risk-taking and risk-avoidance to help individuals successfully navigate uncertainty. |
| Date: | 2025–09–27 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:bxt8g_v1 |
| By: | Silvia Faggian (Ca’ Foscari University of Venice); Dominika Machowska (University of Warsaw); Agnieszka Wiszniewska-Matyszkiel (University of Warsaw) |
| Abstract: | This paper investigates the formation of stable coalitions in a differential game of resource extraction where players' resource deposits are interdependent and spatial relations between them are represented as a network. The network structure allows heterogeneity in the spatial distribution of extractable resources. We introduce a new framework for cooperative extraction in which, in addition to side payments, extraction rights can also be shared. The main contribution is the identification of conditions under which partial coalitions with more than three players can be stable, and under which the grand coalition can also be stable. Illustrative examples of such games are provided. |
| Keywords: | resource extraction, network, the tragedy of the commons, cooperation, partial cooperation, stability of coalitions |
| JEL: | C61 C71 C72 C73 D85 Q20 Q21 Q30 Q32 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2025:18 |
| By: | Evan Heus; Rick Bookstaber; Dhruv Sharma |
| Abstract: | Large Language Models (LLMs) struggle with the complex, multi-modal, and network-native data underlying financial risk. Standard Retrieval-Augmented Generation (RAG) oversimplifies relationships, while specialist models are costly and static. We address this gap with an LLM-centric agent framework for supply chain risk analysis. Our core contribution is to exploit the inherent duality between networks and knowledge graphs (KG). We treat the supply chain network as a KG, allowing us to use structural network science principles for retrieval. A graph traverser, guided by network centrality scores, efficiently extracts the most economically salient risk paths. An agentic architecture orchestrates this graph retrieval alongside data from numerical factor tables and news streams. Crucially, it employs novel ``context shells'' -- descriptive templates that embed raw figures in natural language -- to make quantitative data fully intelligible to the LLM. This lightweight approach enables the model to generate concise, explainable, and context-rich risk narratives in real-time without costly fine-tuning or a dedicated graph database. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.01115 |
| By: | Luca Lazzaro; Manuel S. Mariani; Ren\'e Algesheimer; Radu Tanase |
| Abstract: | Faced with uncertainty in decision making, individuals often turn to their social networks to inform their decisions. In consequence, these networks become central to how new products and behaviors spread. A key structural feature of networks is the presence of long ties, which connect individuals who share few mutual contacts. Under what conditions do long ties facilitate or hinder diffusion? The literature provides conflicting results, largely due to differing assumptions about individual decision-making. We reinvestigate the role of long ties by experimentally measuring adoption decisions under social influence for products with uncertain payoffs and embedding these decisions in network simulations. At the individual level, we find that higher payoff uncertainty increases the average reliance on social influence. However, personal traits such as risk preferences and attitudes toward uncertainty lead to substantial heterogeneity in how individuals respond to social influence. At the collective level, the observed individual heterogeneity ensures that long ties consistently promote diffusion, but their positive effect weakens as uncertainty increases. Our results reveal that the effect of long ties is not determined by whether the aggregate process is a simple or complex contagion, but by the extent of heterogeneity in how individuals respond to social influence. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.04785 |
| By: | Anh Do; Sharat Ganapati; Woan Foong Wong; Oren Ziv |
| Abstract: | The majority of global trade moves by sea through hub-and-spoke shipping networks. We investigate the returns to being a hub country by analyzing how transshipment activity shapes trade and supply chains. We show that most US imports especially from smaller origin countries are transshipped via key hubs, and transshipment is positively correlated with the hubs product-level trade. Leveraging the indirect shipping network structure to construct an instrument, we find that transshipment increases hubs imports from origins for which they facilitate trade and exports of downstream goods, highlighting their central role in shaping modern global trade and supply chain dynamics. |
| Keywords: | trade costs, scale, hubs, transport costs, transportation networks, international trade, shipping |
| JEL: | F10 F13 F14 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12187 |
| By: | Arthur Charpentier; Philipp Ratz |
| Abstract: | Over the past decade alternatives to traditional insurance and banking have grown in popularity. The desire to encourage local participation has lead products such as peer-to-peer insurance, reciprocal contracts, and decentralized finance platforms to increasingly rely on network structures to redistribute risk among participants. In this paper, we develop a comprehensive framework for linear risk sharing (LRS), where random losses are reallocated through nonnegative linear operators which can accommodate a wide range of networks. Building on the theory of stochastic and doubly stochastic matrices, we establish conditions under which constraints such as budget balance, fairness, and diversification are guaranteed. The convex order framework allows us to compare different allocations rigorously, highlighting variance reduction and majorization as natural consequences of doubly stochastic mixing. We then extend the analysis to network-based sharing, showing how their topology shapes risk outcomes in complete, star, ring, random, and scale-free graphs. A second layer of randomness, where the sharing matrix itself is random, is introduced via Erd\H{o}s--R\'enyi and preferential-attachment networks, connecting risk-sharing properties to degree distributions. Finally, we study convex combinations of identity and network-induced operators, capturing the trade-off between self-retention and diversification. Our results provide design principles for fair and efficient peer-to-peer insurance and network-based risk pooling, combining mathematical soundness with economic interpretability. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.21411 |