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on Network Economics |
| By: | Maria Bigoni (University of Bologna); Gabriele Camera (Economic Science Institute, Chapman University); Edoardo Gallo (University of Cambridge) |
| Abstract: | Globalization offers unparalleled opportunities to expand welfare through cooperation across large networks of unrelated individuals. Social exclusion – permanent or temporary – and monetary exchange are institutions that in theory can incentivize cooperation. In an experiment, we evaluate their relative performance and interaction in anonymous networks of different sizes. Permanent social exclusion (ostracism) reduces long-run economic potential by leading to sparse networks. Monetary exchange and temporary social exclusion perform similarly well in small networks. In large networks, however, monetary exchange is the only institution that promotes full cooperation by crowding out ostracism and keeping the network complete. An insight is that monetary systems outperform social exclusion mechanisms in promoting cooperation in globalized social and economic networks. |
| Keywords: | cooperation, experiment, money, network, social exclusion |
| JEL: | C92 E40 D85 C73 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:chu:wpaper:25-06 |
| By: | Julia Gonzalez |
| Abstract: | This paper examines whether deforestation-related import regulations reshape the global trade network of forest-risk commodities such as soy, palm oil, timber, and paper. While existing research has focused on trade volumes and environmental outcomes, the structural effects of such policies on trade architecture remain underexplored. Using UN Comtrade data from 2004 to 2024 and a newly compiled dataset of import regulations, this study models global trade as a network of countries linked by bilateral flows. It applies a Difference-in-Differences framework to estimate how policy exposure affects country-level centrality, combined with community detection and modular realignment metrics to track changes in trade bloc configurations. Results show modest structural shifts. Treated importers often experience increased eigenvector centrality and reduced out-degree, especially under certification and market-based policies. However, effects are generally small and not consistently significant across all specifications. Modular realignment analysis reveals that only a few policies lead to measurable changes in trade community structure. The findings suggest that deforestation-related trade regulations can influence the architecture of global trade networks, but their structural impact depends heavily on policy design and enforcement. This paper contributes a novel network perspective to the literature on environmental trade governance. |
| Keywords: | Deforestation, Network Analysis, Modular Realignment, Global Supply Chain. |
| JEL: | E01 E16 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:ise:remwps:wp03872025 |
| By: | Lijun Wu; Dong Hao; Zhiyi Fan |
| Abstract: | Graph Neural Networks (GNNs) have achieved outstanding performance across a wide range of graph-related tasks. However, their "black-box" nature poses significant challenges to their explainability, and existing methods often fail to effectively capture the intricate interaction patterns among nodes within the network. In this work, we propose a novel explainability framework, GraphEXT, which leverages cooperative game theory and the concept of social externalities. GraphEXT partitions graph nodes into coalitions, decomposing the original graph into independent subgraphs. By integrating graph structure as an externality and incorporating the Shapley value under externalities, GraphEXT quantifies node importance through their marginal contributions to GNN predictions as the nodes transition between coalitions. Unlike traditional Shapley value-based methods that primarily focus on node attributes, our GraphEXT places greater emphasis on the interactions among nodes and the impact of structural changes on GNN predictions. Experimental studies on both synthetic and real-world datasets show that GraphEXT outperforms existing baseline methods in terms of fidelity across diverse GNN architectures , significantly enhancing the explainability of GNN models. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.17848 |
| By: | Marco Civico; François Grin; François Vaillancourt |
| Abstract: | This paper addresses language dynamics with simulations using an agent-based model (ABM). This model explores language dynamics within a social network. Simulation techniques aim to provide a formalized representation of how factors like language adoption, social influence, economic incentives, and language policies interact, impacting language preferences and fluency over time and, through them, the spread of a language. The ABM developed for this study focuses on complex interactions between agents within a dynamic system. Agents, representing entities that vary according to their level of aggregation (individuals, groups, countries), are endowed with specific linguistic attributes and engage in interactions (communication) guided by predefined rules. A pivotal aspect of our modelling framework is the incorporation of network analysis, where relationships among agents are structured as a network, allowing us to leverage network metrics and measures. The network’s dynamic evolution reflects changing inter-agent connections. By combining ABM with network analysis, we gain a nuanced understanding of emergent behaviours and system dynamics, offering insights that extend beyond traditional modelling approaches. This integrative approach proves instrumental in capturing intricate relationships and shedding light on the underlying mechanisms governing complex systems and provides an analytical framework that can be combined with data from sociolinguistic observation. Ce texte aborde la dynamique linguistique au moyen de simulations basées sur un modèle à base d’agents (MBA). Ce modèle étudie la dynamique linguistique au sein d'un réseau social. Les techniques de simulation visent à fournir une représentation formalisée de l'interaction de facteurs tels que l'adoption d'une langue, l'influence sociale, les incitations économiques et les politiques linguistiques, impactant ainsi l'évolution au fil du temps des préférences linguistiques et de la compétence linguistique et, par conséquent, de la diffusion d'une langue. Le MBA développé pour cette étude se concentre sur les interactions complexes entre agents au sein d'un système dynamique. Les agents, représentant des entités associés à divers niveaux d’agrégation (individus, groupes, pays), sont dotés d'attributs linguistiques spécifiques et interagissent (communication) selon des règles prédéfinies. Un aspect essentiel de notre démarche est l'intégration de relations entre agents structurées en réseau, ce qui nous permet d'exploiter les métriques et les indicateurs de celui-ci. L'évolution dynamique du réseau reflète l'évolution des connexions inter-agents. En combinant MMA et analyse de réseau, nous acquérons une compréhension fine des comportements émergents et de la dynamique du système, offrant des perspectives qui dépassent les approches traditionnelles de modélisation. Cette démarche intégrative s’avère essentielle pour saisir les relations complexes et mettre en lumière les mécanismes sous-jacents qui régissent les systèmes complexes, et elle fournit un cadre analytique qui peut être combiné avec des données issues de l’observation sociolinguistique. |
| Keywords: | Sociolinguistics, Networks, Language dynamics, Agent-based Modelling, Sociolinguistique, Réseaux, Modélisation à base d’agents, Dynamique linguistique |
| JEL: | C63 F15 Z13 |
| Date: | 2025–07–28 |
| URL: | https://d.repec.org/n?u=RePEc:cir:cirwor:2025s-23 |
| By: | Roy Cerqueti (GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome]); Raffaele Mattera (Università degli studi della Campania "Luigi Vanvitelli" = University of the Study of Campania Luigi Vanvitelli); Saverio Storani (UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome], GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement) |
| Abstract: | This paper develops a class of complex network-based models whose interconnected nodes are commodities. We assume that the considered commodities are linked on the ground of the similarities of risk profiles and correlations of their returns. In this framework, we explore the resilience of the networks — i.e., their ability to absorb exogenous microscopic shocks. To this aim, we assume that high levels of resilience are associated with small variations of the community structure of the network when an exogenous shock occurs — hence, assuming that the stability of the networked commodities is measured through the maintenance of their connection levels. Shocks are conceptualized as impulsive modifications of the links among the considered commodities. The employed methodological instrument is the clustering coefficient, which is a nodal centrality measure describing the way the adjacent of the nodes are mutually connected. The theoretical proposal is empirically tested over a large set of commodities of different nature. |
| Keywords: | Resilience, Commodity market, Network modeling |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05109120 |
| By: | Roberto Esposti (Department of Economics and Social Sciences, Universita' Politecnica delle Marche (UNIVPM)) |
| Abstract: | This paper investigates the interdependence among prices in the commodity and natural resource market segment. The analysis is performed using a large dataset made of about 50 commodity prices observed with monthly frequency over a period of almost half a century (1980-2024). These different commodities are clustered in five groups (energy, metals, agriculture, food, other raw materials) in order to discriminate the interdependence within and between groups. The adopted method consists in building a Commodity Price Network (CPN) defined via Granger causality tests. These tests are performed with two alternative empirical strategies: pairwise VAR models estimation (pairwise Granger Causality) and sparse VAR models estimation (sparse VAR Granger Causality). Both price levels and price first differences are considered in order to take the possible non-stationarity or price series into account. Network analysis is performed on the different networks obtained using these alternative series and modelling approaches. Results suggest relevant differences across series and methods but some solid results also emerges, particularly pointing to a generalized interdependence that still assigns a central role to some metals and agricultural products. |
| Keywords: | Commodity Prices, Price Interdependence, Granger Causality, Network Analysis, Sparse VAR Models. |
| JEL: | C32 Q02 O13 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:anc:wpaper:498 |
| By: | Roy Cerqueti (GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome]); Giovanna Ferraro (Università degli Studi di Roma Tor Vergata [Roma, Italia] = University of Rome Tor Vergata [Rome, Italy] = Université de Rome Tor Vergata [Rome, Italie]); Raffaele Mattera (UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome]); Saverio Storani (GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement, UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome]) |
| Abstract: | This paper faces the relevant task of assessing the integration of European countries when dealing with three paradigmatic socio-environmental themes: Circular Economy (CE), Energy Transition (ET), and Social Justice (SJ). Specifically, we aim to explore whether a similar behavior in facing one of the considered aspects is mirrored by similarity in the others. We move from a dataset composed of five variables for CE, two for ET, and three for SJ, representing yearly data for the quinquennium 2016-2020 and European countries. We build a multilayer network based on the ten variables having countries as nodes. Each layer/variable has weighted links based on countries' similarity. Inter-layer links are created through a community detection exercise over the individual layers. This approach allows us to evaluate analogies, leading to the assessment of intra-and inter-layer policy integration. We find a relatively low level of integration at the European level and a high sensitivity to the number of detected communities, thus revealing the role of countries' heterogeneity in driving integration. |
| Keywords: | Circular economy, Energy transition, Social justice, European countries, Multilayer networks, Clustering procedures |
| Date: | 2025–01–22 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05109264 |
| By: | Ina Hajdini; Saten Kumar; Samreen Malik; Jordan J. Norris; Mathieu Pedemonte |
| Abstract: | In a randomized control trial of customer-supplier firm pairs in New Zealand, we treat with information one firm in a pair and analyze the treatment's effects on the expectations and actions of both the directly treated firms (direct effect) and connected firms that did not directly receive information (spillover effect). The direct and spillover effects on expectations and actions are significant and of comparable magnitude. Higher expected future real GDP growth increases prices and employment, while greater uncertainty about it reduces prices, investment, and employment. We show that spillover effects on the connected firms' expectations are driven by inter-firm communication, as opposed to observable actions. This matters as we find communication to be symmetric upstream vs downstream, while propagation via actions is asymmetric. We embed inter-firm communication along the supply chain in a New Keynesian pricing problem and discuss implications for the transmission of aggregate uncertainty to prices and inflation. |
| Keywords: | communication; firms; macroeconomic expectations; networks; spillovers |
| JEL: | D8 E3 E4 E5 L14 |
| Date: | 2025–08–04 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedcwq:101377 |