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on Network Economics |
| By: | Guo, F.; Choi, S.; Goyal, S.; Moisan, F. |
| Abstract: | Social networks shape individual behavior, and public policy increasingly leverages networks to enhance effectiveness. It is therefore important to understand how individuals behave in network interactions. This paper uses lab experiments to examine behavior in games on networks involving strategic substitutes and strategic complements. Theory suggests that an individual’s choice is proportional to their (Bonacich) centrality. Our experiments, however, find that while choices increase with centrality, the relationship is weaker than predicted. The total action levels individuals choose and the total payoff they achieve are higher than the Nash outcomes in some cases while lower in others. We find that these results can be coherently explained by individuals’ behavioral attenuation: they have incomplete adjustments to the strategic differences across network positions, exhibiting a bias toward generally high-payoff choices in complex networks—even when these choices are not optimal for their specific network positions. |
| Keywords: | Centrality, Behavioural Biases, Networks |
| JEL: | C92 D83 D85 Z13 |
| Date: | 2024–12–31 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camjip:2433 |
| By: | Xiaopeng Wang; Chengyi Tu; Shuhao Chen; Sicheng Wang; Ying Fan; Samir Suweis; Paolo D'Odorico |
| Abstract: | As the global population and the per capita demand for resource intensive diets continues to grow, the corresponding increase in food demand challenges the global food system, enhancing its reliance on trade. Most previous research typically constructed either unweighted networks or weighted solely by tonnage to represent food trade, and focused on bilateral trade relationships between pairs of countries. This study investigates the properties of global food trade constructed in terms of total food calories associated with all the main food products exchanged along each trade link (edge of the food trade network). Utilizing data from the Food and Agriculture Organization between 1986 and 2022, we construct a directed, weighted network of net caloric flows between countries. This approach highlights the importance of considering nutritional value in discussions of food security and trade policies, offering a more holistic view of global food trade dynamics. Our analysis reveals significant heterogeneity in trade patterns, with certain countries emerging as major exporters or importers of food calories. Moreover, we employ network measures, including network connectivity, network heterogeneity, network modularity, and node correlation similarity, to elucidate the structural dynamics of global net food calorie trade networks that are relevant to the stability and resilience of the global food system. Our work provides a more nuanced understanding of global food trade dynamics, emphasizing the need for comprehensive strategies to enhance the resilience and sustainability of food trade networks. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.18856 |
| By: | Dimitri Sarkiss Tatoyan (CRJ-CCJ - Centre de recherches sur le Japon - CCJ - Chine, Corée, Japon - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - UPCité - Université Paris Cité); Aleksandra Kobiljski (CRJ-CCJ - Centre de recherches sur le Japon - CCJ - Chine, Corée, Japon - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - UPCité - Université Paris Cité); Hiroki Yamashita (Institut d'Études Politiques [IEP] - Paris); Éric Mermet (TSE-R - TSE-R Toulouse School of Economics – Recherche - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | The 1445 Toll Register is the only surviving medieval customs register in Japan. As such, it is a precious window into Japan's medieval commercial revolution. While well studied using traditional methods, this article is the first attempt to submit this source to social network analysis (SNA) methods. It highlights the potential of statistical, spatial and network analysis, producing visualizations which nuance our understanding of the role of commercial agents in the medieval maritime trade. Starting from visualizing the overall network, this article probes into the legwork of a commodity network, much of which passed through the hands of the commercial agents. Our analysis also reveals that a group of 32 actors, who in the register appear to have been principally commercial agents, were in fact also shipmasters. A community detection method allows us to open up new avenues of understanding maritime trade clusters, while geospatial data visualization point to a historically irregular absence which requires further research. |
| Keywords: | medieval studies, 15th century, medieval Japan, maritime trade, commerical agents, shipmasters, commodification |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04870442 |
| By: | Lehdonvirta, Vili; Wu, Boxi; Hawkins, Zoe |
| Abstract: | U.S. and Chinese technology companies dominate digital networks. What explains the extent to which third countries attach to U.S. versus Chinese network hubs? The answer matters, because both governments have demonstrated the ability to “weaponize” their hubs to advance their security interests. We synthesize three hypothetical explanations for third countries' network hub attachment from previous qualitative literature: 1) network hub attachment is a product of economic forces; 2) network hub attachment is determined by rivaling great powers coaxing and coercing third countries to attach to their hubs over their rival’s; and 3) network hub attachment results from third-country governments’ strategic policy choices. In the first quantitative study on the topic, we assess these explanations with original data on the global geography of U.S. and Chinese -owned hyperscale cloud infrastructures. Based on the findings, we argue that third countries or “spoke states” enjoy agency in bipolar networks which they did not have in unipolar networks, and that their strategic interests in combination with economic forces shape the topology of geographically distributed bipolar networks more so than great-power rivalry. Our model contributes to the weaponized interdependence framework which predicted the rise of alternative hubs but lacked a model of bipolar network topology. |
| Date: | 2025–01–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:6s7dn |
| By: | Vanya Georgieva |
| Abstract: | Industrial policy has gained popularity in recent years and across all regions and income levels. Consequently, it is increasingly important to understand how governments choose the sectors they target. This analysis explores the role of domestic production networks in sector targeting, while controlling for other sector and global value chain characteristics. Combining datasets on industrial policy (Global Trade Alert) and input-output linkages (ICIO, OECD) provides novel insight into the network features of industrial policy. In particular, a sector’s ‘centrality’—i.e., its degree of connectedness - within the domestic production network is an important and significant predictor of sector intervention. The results indicate that industrial policy is used differently across regions, income groups, time periods, and types of policy tools. Notably, emerging economies tend to target more central sectors, while advanced economies target less central ones, on average. However, there has been a global shift toward more central sectors over time. Lastly, subsidies are deployed on more central sectors, while tariffs are used on less central ones. |
| Keywords: | Industrial Policy; Trade Policy; Subsidies; Global Value Chains; Production Networks; Spillovers |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/023 |
| By: | Bailey, N.; Ditzen, J.; Holly, S. |
| Abstract: | We analyse asymmetric spatial or network dynamics in a panel framework by first distinguishing them from stronger common effects. We eliminate pervasive influences by means of a de-factoring model and then uncover the weaker cross-sectional structures by identifying units with significant residual bivariate correlation. In order to assess the effect on a given unit i from shocks to ‘neighbouring’ units, we make use of spatial econometric techniques. Given that the effects of these shocks can be directional, i.e. depend on factors such as a city’s distance from other cities and their relative sizes appropriately defined, we measure network dependencies in terms of partial correlations instead. For this, we employ GMM and use the information in a regularised version of the residual correlation matrix to identify instruments which comply with the required relevance and exclusion restrictions for instrumentation. For the jth variable in the equation for the ith unit we select elements in the jth column of this correlation matrix that represent units that are correlated with the jth variable but are not correlated with the ith variable. Translating into the terminology of the spatial or networks literature, we focus on the effects of each unit’s neighbours’ neighbours that are not their neighbours. This approach is consistent with estimating a variant of a gravity model of idiosyncratic shocks to variables such as house prices. |
| Keywords: | Spatial interconnections, housing, multiple testing, networks |
| JEL: | C21 C23 |
| Date: | 2025–01–10 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2501 |
| By: | Mahdi Salahshour; Amirahmad Shafiee; Mojtaba Tefagh |
| Abstract: | The Lightning Network (LN) has emerged as a second-layer solution to Bitcoin's scalability challenges. The rise of Payment Channel Networks (PCNs) and their specific mechanisms incentivize individuals to join the network for profit-making opportunities. According to the latest statistics, the total value locked within the Lightning Network is approximately \$500 million. Meanwhile, joining the LN with the profit-making incentives presents several obstacles, as it involves solving a complex combinatorial problem that encompasses both discrete and continuous control variables related to node selection and resource allocation, respectively. Current research inadequately captures the critical role of resource allocation and lacks realistic simulations of the LN routing mechanism. In this paper, we propose a Deep Reinforcement Learning (DRL) framework, enhanced by the power of transformers, to address the Joint Combinatorial Node Selection and Resource Allocation (JCNSRA) problem. We have improved upon an existing environment by introducing modules that enhance its routing mechanism, thereby narrowing the gap with the actual LN routing system and ensuring compatibility with the JCNSRA problem. We compare our model against several baselines and heuristics, demonstrating its superior performance across various settings. Additionally, we address concerns regarding centralization in the LN by deploying our agent within the network and monitoring the centrality measures of the evolved graph. Our findings suggest not only an absence of conflict between LN's decentralization goals and individuals' revenue-maximization incentives but also a positive association between the two. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.17353 |
| By: | Rentschler, Johannes |
| Abstract: | Intermodal transportation refers to the movement of goods in one and the same loading unit, which uses successively two or more modes—such as rail, road, and maritime—without handling the goods themselves in changing modes. This approach capitalizes on the strengths of each transportation mode, optimizing efficiency, cost-effectiveness, and environmental sustainability. This dissertation investigates continental intermodal transportation in Europe. It thereby focuses on the configuration of intermodal transportation networks and the transformative impact of digitalization. The European intermodal transportation market, characterized by diverse actors, varying laws, and non-standardized processes, presents distinctive challenges. These differences necessitate tailored approaches to address unique circumstances effectively. Given this complexity, multiple research methodologies on different planning levels are employed to systematically explore the structural configuration of transportation networks and the impact of digitalization. Qualitative methods, such as case studies and expert interviews, complement quantitative models by providing contextual and experiential insights and practical knowledge from industry professionals and stakeholders. Case studies are particularly suitable for analyzing the European intermodal transportation market. They allow for in-depth exploration of specific contexts, capturing nuances that broader methods might miss, providing a nuanced understanding of intermodal transportation systems, and helping to develop actionable solutions. The main body of this dissertation is based on five research papers. The first two papers investigate the structural configuration of intermodal transportation networks and its impact on overall system performance. By integrating strategic hub location and tactical service network design models, the research provides deeper insights into network structure, leading to optimized configurations that enhance efficiency and reduce costs. A case study involving a German intermodal operator demonstrates that this integration leads to more realistic and efficient network designs, considering economies of scale and density. In the third paper, the feasibility and benefits of continental intermodal transportation as a possible solution for connecting Asia and Europe are studied. The qualitative analysis of the Trans-Caspian Corridor through interviews with logistics companies and political authorities revealed the intricate geopolitical and strategic challenges influencing the corridor's development.The fourth paper focuses on ETA forecasts in the pre-and post-haulage of intermodal transportation. Digitalization and real-time data significantly improve operational processes in intermodal transportation by enhancing visibility and enabling dynamic adjustments to routing and scheduling. A simulation study shows that ETA forecasts lead to an average cost reduction of 7%. The fifth paper investigates how digitalization drives the evolution of intermodal transportation towards synchromodal transportation, where different transportation modes are seamlessly integrated, providing flexible and adaptive real-time solutions. The integration of digital technologies such as IoT, blockchain, and AI further supports this transition, offering advanced tools for real-time monitoring, data analytics, and decision-making. The findings of this dissertation contribute to both academic knowledge and practical applications, providing valuable insights for policymakers, industry stakeholders, and researchers in the field of intermodal transportation. |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:152591 |
| By: | Thiago Christiano Silva; Paulo Victor Berri Wilhelm; Solange Maria Guerra |
| Abstract: | This paper examines the causal impact of extreme climate events—intense rains, floods, and flash floods—on the supply chain. We map the Brazilian supply network in a unique and comprehensive way using proprietary granular data on over 1.7 billion inter-firm payments composed of fast payments (Pix), boletos (invoices), and wire transfers (TEDs). Our analysis reveals that supply shocks follow extreme climate events, with outside-the-affected-area customers reducing payments to affected suppliers by up to 8% in the immediate aftermath, compared to unaffected ones within the same industry. We document significant heterogeneities across sectors, with some affected suppliers in agriculture experiencing reductions in payments nearing 20%, five times greater than the average. Leveraging granular data on borrower-lender credit relationships from banking institutions in Brazil, we find affected firms experience increased indebtedness post-disaster, especially in credit types related to immediate liquidity needs. We observe a remarkable ability of the supply chain to adapt to these shocks: outsidethe- affected-area firms are often able to replace affected partners with low friction. However, some sectors, such as construction, face substantial difficulties. In this industry, consumers exhibit a substitution friction of approximately 10 p.p. This demonstrates how indirect effects can amplify the direct impacts of extreme climate events on the supply chain. While overall resilience is crucial for maintaining operability, directly affected firms are likely to experience a permanent loss of market share as unaffected firm counterparts shift their economic transactions away from them, leading to harmful consequences in areas affected by extreme climate events. Our research may support policymakers in designing strategies to aid affected firms in restoring market share and mitigating frictions in sectors less prone to partner replacement. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:bcb:wpaper:613 |