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on Network Economics |
| By: | Matthew J. Lindquist (Stockholm University); Eleonora Patacchini (Cornell University); Michael Vlassopoulos (University of Southampton); Yves Zenou (Monash University) |
| Date: | 2024–12–06 |
| URL: | https://d.repec.org/n?u=RePEc:ifs:ifsewp:24/56 |
| By: | Fafchamps, Marcel (Stanford University); Islam, Asadul (Monash University); Pakrashi, Debayan (Indian Institute of Technology Kanpur); Tommasi, Denni (University of Bologna) |
| Abstract: | We conduct a clustered randomized controlled trial across 180 villages in Uttar Pradesh, India, to promote the take-up of a savings commitment product newly introduced to our study population. A random subset of participants was targeted through our promotional campaign to test whether the product's diffusion among untargeted participants operates primarily through information sharing or through persuasion by incentivized target participants. If social learning is the main channel of diffusion, we would expect higher sign-up and take-up rates in information villages compared to persuasion villages. Conversely, if persuasion is the primary channel, sign-up and take-up rates should be higher in persuasion villages. Our findings consistently favor the persuasion channel, as sign-up and take-up rates were higher in the persuasion treatment, even without increased financial literacy or knowledge about the product. Information alone had a negligible impact on take-up, while the combined treatment achieved the highest sign-up and conversion rates, suggesting that information complements persuasion by enhancing its effectiveness. These results highlight the importance of incentivized persuasion in promoting product take-up and suggest that, in certain contexts, direct information-sharing may be less effective than previously assumed. |
| Keywords: | diffusion, social networks, savings, financial inclusion, information, persuasion |
| JEL: | O16 D14 G21 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17555 |
| By: | Luca Colombo (ESC [Rennes] - ESC Rennes School of Business); Paola Labrecciosa; Agnieszka Rusinowska (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | We take a novel approach based on differential games to the study of criminal networks. We extend the static crime network game (Ballester et al., 2006, 2010) to a dynamic setting where criminal activities negatively impact the accumulation of total wealth in the economy. We derive a Markov Feedback Equilibrium and show that, unlike in the static crime network game, the vector of equilibrium crime rates is not necessarily proportional to the vector of Bonacich centralities. Next, we conduct a comparative dynamic analysis with respect to the network size, the network density, and the marginal expected punishment, finding results in contrast with those arising in the static crime network game. We also shed light on a novel issue in the network theory literature, i.e., the existence of a voracity effect. Finally, we study the problem of identifying the optimal target in the population of criminals when the planner's objective is to minimize aggregate crime at each point in time. Our analysis shows that the key player in the dynamic and the static setting may differ, and that the key player in the dynamic setting may change over time. |
| Keywords: | Differential games, Markov equilibrium, Criminal networks, Bonacich centrality, Key player |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:cesptp:hal-04850675 |
| By: | Fetzer, Thiemo (Warwick University & University of Bonn); Lambert, Peter John (London School of Economics and Political Science); Feld, Bennet (London School of Economics and Political Science); Garg, Prashant (Imperial College London) |
| Abstract: | This paper leverages generative AI to build a network structure over 5, 000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step build-prune approach using an ensemble of prompt-tuned generative AI classifications. The build step provides an initial distribution of edge predictions, the ‘prune’ step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade. |
| Keywords: | Supply-Chain Network Analysis ; Large Language Models ; On-shoring ; industrial policy ; Trade wars ; Econometrics-of-LLMs JEL Codes: F14 ; F23 ; L16 ; F52 ; O25 ; N74 ; C81 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1528 |
| By: | Daeyoung Jeong; Tongseok Lim; Euncheol Shin |
| Abstract: | In various contexts, such as learning, social distancing behavior, and financial contagion, economic agents' decisions are interdependent and can be represented as a network. This paper investigates how a decision maker (DM) can design an optimal intervention while addressing uncertainty in the network structure. The DM's problem is modeled as a zero-sum game against an adversarial player, referred to as "Nature, " whose objective is to disrupt the DM's goals by reconfiguring the network into its most disadvantageous state. Using the principle of duality, we derive the DM's unique robust intervention strategy and identify the corresponding unique worst-case network structure determined by Nature. This framework provides insights into robust decision-making under network uncertainty, balancing the DM's objectives with Nature's adversarial actions. Moreover, we explore the costs of robustness and highlight the significance of higher-order uncertainties. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.00235 |
| By: | Yicheng Wang (The University of Hong Kong - Department of Mathematics; Southern University of Science and Technology.); Didier Sornette (Risks-X, Southern University of Science and Technology (SUSTech); Swiss Finance Institute); Ke Wu (Southern University of Science and Technology); Sandro Claudio Lera (Southern University of Science and Technology; MIT Connection Science) |
| Abstract: | Instabilities in socio-economic complex systems have long been modeled using Ising-like network interaction models that require fine-tuning to a critical threshold. Recent findings indicate that instabilities can emerge even in sub-critical regimes, provided the network topology is sufficiently non-normal. However, the process by which non-normal networks form is less well understood and has been considered largely decoupled from the dynamics of agents interacting on the network. We show that feedback mechanisms between individual agents and macroscopic quantities such as prices induce feedback loops that cause the network topology to self-organize towards non-normal configurations. The interactions between traders on their dynamically evolving influence network make non-normal networks and financial bubbles intrinsic properties of the financial market dynamics, acting as attractors in the sense of a dynamical system. Through agent-based simulations, we demonstrate that noise traders form a complex network of mutual influences driven by traders’ visibility and success. These dynamics self-organize towards non-normal network topologies that enhance return autocorrelation, increase volatility, and contribute to the formation of financial bubbles, which in turn make the topology more non-normal. We analyze the social trading platform eToro to demonstrate that such feedback mechanisms are active on social trading platforms. Our model thus highlights the increased vulnerability of social systems to instabilities in the presence of global-scale communications. |
| Keywords: | Financial bubbles, Agent-based model, Socio-economic networks, Self-organization, Sub-criticality, Non-normality |
| JEL: | C63 C46 C53 G17 G41 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2477 |
| By: | Seiya Hirano |
| Abstract: | This paper studies the relationship between optimal dynamic pricing for network goods and the coordination of consumers' adoption decisions. We show that based on risk dominance criterion, consumers face the risk of coordination failure, and introductory pricing is optimal if the risk is higher in period~1 without network. We find that under threshold coordination, the impact of price on the network size varies according to consumer beliefs. In pessimistic (optimistic) threshold coordination, the network size expands (shrinks) as the price increases. Lowering (Raising) the price in period~2 implies a smaller network size, so introductory (skim) pricing is optimal. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1267 |
| By: | Wei Li; Yi-Lun Du; Nan Su; Konrad Tywoniuk; Kyle Godbey; Horst St\"ocker |
| Abstract: | Community detection, also known as graph partitioning, is a well-known NP-hard combinatorial optimization problem with applications in diverse fields such as complex network theory, transportation, and smart power grids. The problem's solution space grows drastically with the number of vertices and subgroups, making efficient algorithms crucial. In recent years, quantum computing has emerged as a promising approach to tackling NP-hard problems. This study explores the use of a quantum-inspired algorithm, Simulated Bifurcation (SB), for community detection. Modularity is employed as both the objective function and a metric to evaluate the solutions. The community detection problem is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling seamless integration with the SB algorithm. Experimental results demonstrate that SB effectively identifies community structures in benchmark networks such as Zachary's Karate Club and the IEEE 33-bus system. Remarkably, SB achieved the highest modularity, matching the performance of Fujitsu's Digital Annealer, while surpassing results obtained from two quantum machines, D-Wave and IBM. These findings highlight the potential of Simulated Bifurcation as a powerful tool for solving community detection problems. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.00075 |
| By: | Gert Bijnens (Economics and Research Department, National Bank of Belgium); Mariano Montoya (KU Leuven, Department of Economics); Stijn Vanormelingen (KU Leuven, Department of Economics) |
| Abstract: | This paper estimates how the impact of a natural disaster propagates through the production network. More precisely, we look at the excessive rainfall in the summer of 2021 that caused large areas to be severely flooded in Belgium. We first look at the direct effects on firms active in the flooded areas and find substantial negative effects on sales and employment. Next, we investigate how these shocks propagate through the network, thereby differentiating explicitly between upstream and downstream linkages. Our results show that the floods had a strong negative impact on the performance of firms active in the area. In terms of the supply chain effects, we find negative and persistent effects on sales for firms with upstream exposure. |
| Keywords: | : Flooding, climate change, firms, production network |
| JEL: | D57 L25 Q54 R11 L14 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbb:reswpp:202410-466 |
| By: | Ralf Martin (Imperial College Business School, CEP, CEPR and World Bank-IFC); Mirabelle Muûls (Economics and Research Department, National Bank of Belgium); Thomas Stoerk (Economics and Research Department, National Bank of Belgium) |
| Abstract: | Carbon markets are a central instrument to decarbonise our economies and mitigate the impacts of climate change. Within the European Union, carbon pricing to date has primarily targeted electricity generation and greenhouse gas-intensive industries, and regulatory focus has typically been confined to a subset of firms. This paper explores how the carbon price confronting regulated firms not only shapes their own operations and investment choices but also exerts influence on other entities within their customer and supplier network, even in the absence of direct carbon pricing of these suppliers or clients. Such influence could manifest through alterations in production processes, products and prices, market structures and innovation. Leveraging a distinctive dataset for Belgium, this research investigates the impact of the EU’s carbon price on lowcarbon innovation, supply-chain dynamics, and energy economic activity throughout the Belgian economy’s production network. |
| Keywords: | Emissions pricing, production network, clean innovation |
| JEL: | Q58 Q55 L14 H23 F18 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbb:reswpp:202410-467 |
| By: | Zhesheng Qiu; Yicheng Wang; Le Xu; Francesco Zanetti |
| Abstract: | This paper studies the design of monetary policy in small open economies with domestic and cross-border production networks and nominal rigidities. The monetary policy that closes the domestic output gap is nearly optimal and is implemented by stabilizing the aggregate inflation index that weights sectoral inflation according to the sector’s roles as a supplier of inputs and a net exporter of products within the international production networks. To close the output gap, monetary policy should assign large weights to inflation in sectors with small direct or indirect (i.e., via the downstream sectors) import shares and failing to account for the cross-border production networks overemphasizes inflation in sectors that export intensively directly and indirectly (i.e., via the downstream sectors). We validate our theoretical results using the World Input-Output Database and show that the monetary policy that closes the output gap outperforms alternative policies that abstract from the openness of the economy or the input-output linkages |
| Date: | 2025–01–06 |
| URL: | https://d.repec.org/n?u=RePEc:oxf:wpaper:1064 |
| By: | Okan Akarsu; Emrehan Aktug; Huzeyfe Torun |
| Abstract: | We explore the spillover impact of zombie firms in Türkiye by exploiting a rich administrative dataset that contains firm-level information on balance sheets, inter-firm sales, employment, and firm-bank level credit records. We document four key facts regarding zombie dynamics: (i) Leveraging matched firm-bank level credit registry data, we highlight the presence of an evergreening motive, leading to a misallocation of credit away from productive firms. At the same time, healthy firms in zombie-dense networks face reduced credit access. (ii) Zombie firms, which are on average less productive than nonzombie firms, impede investment and employment opportunities at healthier firms. Nonzombie firms operating in sectors with a high prevalence of zombie firms experience lower sales, assets, and productivity. (iii) Incorporating B2B sales data structured similarly to firm-level input-output data, our study reveals that firms with stronger upstream or downstream zombie connections tend to exhibit reduced sales, investment, and employment compared to firms without any zombie connections. (iv) A higher number of zombie connections leads to significant reductions in markups, value-added, productivity, and EBIT margins due to the cascading effects on production technology, shifting it toward lower value-added. Additionally, a higher share of zombies in the upstream sector reduces input costs for firms due to excess production. |
| Keywords: | Zombie firms, Firm dynamics, Evergreening, Credits |
| JEL: | E12 E24 E31 E52 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:tcb:wpaper:2414 |
| By: | Deepa Dhume Datta; Robert J. Vigfusson |
| Abstract: | Relative to diversity, inclusion is much harder to measure. We measure inclusion of women in economics using novel data on coauthoring relationships among Federal Reserve Board economists. Individual coauthoring relationships are voluntary, yet inclusion in coauthoring networks can be central to research productivity and career success. We document gender affinity in coauthoring, with individuals up to 34 percent more likely to have a same-gender coauthor in the data relative to what would be predicted by random assignment. Because women account for under 30 percent of Federal Reserve Board economists, gender affinity in coauthoring relationships may reduce research opportunities for women relative to their men peers. Whereas commonality of research interests is not sufficient to explain observed gender affinity in coauthoring, we find that paper outcomes may encourage gender affinity, in that papers authored by only men are more downloaded and more likely to be published than papers by mixed-gender teams. Gender affinity may contribute to the gender gap in authoring as well: women make up only 23 percent of authors in the later part of our sample, about 4 percentage points below their share of the economist population. We estimate that reducing gender affinity by men could eliminate between 1.5 to 3 percentage points of the gender gap in observed research output by women. Our findings on gender affinity in coauthoring provide an empirical assessment of the state of inclusivity in economics. |
| Keywords: | Central banks; Coauthoring networks; Diversity; Gender affinity; Inclusion; Leaky pipeline |
| JEL: | A14 J16 E58 |
| Date: | 2024–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2024-91 |
| By: | INOUE Hiroyasu; TODO Yasuyuki |
| Abstract: | This study examines how positive and negative news about firms affects their stock prices and, moreover, how it affects stock prices of the firms' suppliers and clients, using a large sample of publicly listed firms around the world and another of Japanese listed firms. The level of positiveness and negativeness of each news article is determined by FinBERT, a natural language processing model fine-tuned specifically for financial information. Supply chains of firms across the world are identified mostly by financial statements, while those of Japanese firms are taken from large-scale firm-level surveys. We find that positive news increases the change rate of stock prices of firms mentioned in the news before its disclosure, most likely because of diffusion of information through private channels. Positive news also raises stock prices of the firms' suppliers and clients before its disclosure, confirming propagation of market values through supply chains. In addition, we generally find a larger post-news effect on stock prices of the mentioned firms and their suppliers and clients than the pre-news effect. The positive difference between the post- and pre-news effects can be considered as the net effect of the disclosure of positive news, controlling for information diffusion through private channels. However, the post-news effect on suppliers and clients in Japan is smaller than the pre-news effect, which is the opposite result to non-domestic firms from around the world. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:24077 |
| By: | Sen, A. |
| Abstract: | I examine the recent productivity growth slowdown and the emergence of digital technologies through the lens of production networks. Digital technologies are increasingly embedded in intermediate inputs, and digital-intensive sectors, often key producers of intermediate and capital goods, amplify the positive effects of these technologies across industries. I show that the slowdown in computer-specific technical change has contributed to the decline in aggregate productivity growth, particularly in digital-intensive service industries, with these effects spreading through the economy via intersectoral linkages. My estimates suggest that this accounts for around 45–55% of the productivity growth slowdown in both the UK and the US since the mid-2000s. I attribute this slowdown largely to structural changes within the computers industry, especially the rising value-added intensity of the sector. In general, production in digital technology-producing industries is characterized by perfect complementarity, explaining the waning effects of digital technologies on aggregate productivity since the mid-2000s. In light of these findings, I take a pessimistic view on the future of productivity growth. |
| Keywords: | digitalization, productivity, production networks, investment-specific technical change |
| JEL: | O30 O33 D57 O47 L86 L23 |
| Date: | 2024–12–13 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2472 |
| By: | Alabrese, Eleonora (University of Bath, CAGE and SAFE); Capozza, Francesco (WZB Berlin, BSoE, and CESifo); Garg, Prashant (Imperial College London) |
| Abstract: | As social media is increasingly popular, we examine the reputational costs of its increased centrality among academics. Analyzing posts of 98, 000 scientists on Twitter (2016-2022) reveals substantial and varied political discourse. We assess the impact of such online political expression with online experiments on a representative sample of 3, 700 U.S. respondents and 135 journalists who rate vignettes of synthetic academic profiles with varied political affiliations. Politically neutral scientists are viewed as the most credible. Strikingly, on both the 'left' and 'right' sides of politically neutral, there is a monotonic penalty for scientists displaying political affiliations: the stronger their posts, the less credible their profile and research are perceived, and the lower the public's willingness to read their content, especially among oppositely aligned respondents. A survey of 128 scientists shows awareness of this penalty and a consensus on avoiding political expression outside their expertise. |
| Keywords: | Social Media, Scientists’ Credibility, Polarization, Online Experiment JEL Classification: A11, C93, D72, D83, D91, I23, Z10, Z13 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:cge:wacage:735 |