nep-net New Economics Papers
on Network Economics
Issue of 2023‒06‒26
twelve papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Commodity-specific triads in the Dutch inter-industry production network By Marzio Di Vece; Frank P. Pijpers; Diego Garlaschelli
  2. Unions and key players in network games with conflicts and spillovers By Mauleon, Ana; Nanumyan, Mariam; Schopohl, Simon; Vannetelbosch, Vincent
  3. Local Farsightedness in Network Formation By de Callatay, Pierre; Mauleon, Ana; Vannetelbosch, Vincent
  4. Network Topology in Decentralized Finance By Saengchote, K; Castro-Iragorri, C
  5. Exploring resource seeking in a scientific collaboration network and its effect on scientists' knowledge creation. By Karine Revet; Isabel Maria Bodas-Freitas; Barthélemy Chollet; Pablo D’Este
  6. A global perspective on the social structure of science By Aliakbar Akbaritabar; Andrés F. Castro Torres; Vincent Larivière
  7. Coworker Networks and the Labor Market Outcomes of Displaced Workers: Evidence from Portugal By Jose Garcia-Louzao; Marta Silva
  8. Resilience of Japanese Multinational Enterprises' Production Networks during the COVID-19 Pandemic By LICHENG, Liang
  9. Generalised Gately Values of Cooperative Games By Gilles, Robert P.; Mallozzi, Lina
  10. First Generation College Students and Peer Effects By Kofoed, Michael S.; Jones, Todd R.
  11. Social Interactions with Endogenous Group Formation By Shuyang Sheng; Xiaoting Sun
  12. Gated Deeper Models are Effective Factor Learners By Jingjing Guo

  1. By: Marzio Di Vece; Frank P. Pijpers; Diego Garlaschelli
    Abstract: Triadic motifs are the smallest building blocks of higher-order interactions in complex networks and can be detected as over-occurrences with respect to null models with only pair-wise interactions. Recently, the motif structure of production networks has attracted attention in light of its possible role in the propagation of economic shocks. However, its characterization at the level of individual commodities is still poorly understood. Here we analyse both binary and weighted triadic motifs in the Dutch inter-industry production network disaggregated at the level of 187 commodity groups, using data from Statistics Netherlands. We introduce appropriate null models that filter out node heterogeneity and the strong effects of link reciprocity and find that, while the aggregate network that overlays all products is characterized by a multitude of triadic motifs, most single-product layers feature no significant motif, and roughly 80% of the layers feature only two motifs or less. This result paves the way for identifying a simple "triadic fingerprint" of each commodity and for reconstructing most product-specific networks from partial information in a pairwise fashion by controlling for their reciprocity structure. We discuss how these results can help statistical bureaus identify fine-grained information in structural analyses of interest for policymakers.
    Date: 2023–05
  2. By: Mauleon, Ana (Université catholique de Louvain, LIDAM/CORE, Belgium); Nanumyan, Mariam; Schopohl, Simon (Université catholique de Louvain, LIDAM/CORE, Belgium); Vannetelbosch, Vincent (Université catholique de Louvain, LIDAM/CORE, Belgium)
    Abstract: We study network games with social and private dissonance where each player in the network exerts some costly efforts. We allow for cooperative behavior in the sense that players may belong to unions and members of each union choose their efforts by maximizing the joint utility of the union. Each player not only benefits from the aggregate effort and efforts of network neighbors are strategic complements, but also suffers disutility when her effort differs from her neighbors’ efforts or is inconsistent with her ideal effort. We characterize the unique Nash equilibrium of the network game with unions and we define a union intercentrality measure for finding the key player whose removal has the highest impact on the aggregate effort level. In addition, we explore the role of unions in fostering effort levels and we consider two alternative policies: the key addition to an existing union (the player who increases the most the aggregate effort by joining the union) and the key union that generates the highest total effort. Finally, we investigate the stability of unions.
    Keywords: Social networks ; peer effects ; key players ; unions ; social and private dissonance
    JEL: A14 C72 D85 L14
    Date: 2023–04–27
  3. By: de Callatay, Pierre (Université catholique de Louvain, LIDAM/CORE, Belgium); Mauleon, Ana (Université catholique de Louvain, LIDAM/CORE, Belgium); Vannetelbosch, Vincent (Université catholique de Louvain, LIDAM/CORE, Belgium)
    Abstract: We propose the concept of local-k farsighted consistent network for analysing network formation games where players only consider a limited number of feasible networks. A network g is said to be local-k farsightedly consistent if, for any network g' within the distance-k neighbourhood of g, either g is not defeated by g' , or g defeats g' . We show that if the utility function is (componentwise) egalitarian or satisfies reversibility or excludes externalities across components, then local-k farsightedness is more likely to be a good proxy for what would happen when players have full knowledge of all feasible networks.
    Keywords: Networks ; local farsightedness ; stability
    JEL: A14 C70 D20
    Date: 2023–01–20
  4. By: Saengchote, K; Castro-Iragorri, C
    Abstract: The composability and anonymity of participants in Decentralized Finance pose significant challenges in understanding their interactions and the buildup of risk within the network. We map the interconnections among decentralized finance protocols using transactions among contracts and addresses, explore singlelayer and multiplex network properties and quantify the financial exposure of the most critical nodes. We observe scale-free properties similar to traditional financial networks, but the inclusion of user interactions and the influence of externally owned accounts yield distinct network characteristics. Furthermore, centrality measures and high-frequency metrics provide insights into systemically important participants and at-risk protocols, necessitating further research to develop robust risk measures. By identifying potential vulnerabilities and developing appropriate risk management strategies, the stakeholders can help ensure the stability and safety of decentralized finance as a viable alternative to traditional financial systems.
    Keywords: Blockchain; composability; networks
    JEL: G20 D85 D53 L14
    Date: 2023–06–07
  5. By: Karine Revet; Isabel Maria Bodas-Freitas; Barthélemy Chollet; Pablo D’Este
    Abstract: Scientists display heterogeneous profiles regarding the focus of their knowledge production activities, their collaboration strategies and their outcomes. Despite increasing interests on research collaboration, little is known about how scientists mobilize their research network. In their knowledge creation efforts, scientists collaborate with colleagues from both academia and industry. These collaborations, leading or not to co-authorship, allow scientists to access to a number of research resources. The objective of this study is to explore whether and how knowledge production across the four Stokes’ quadrants (different focus on fundamental understandings and on immediate industrial and social application) is associated with specific modes of mobilizing research resources. This study examines empirically the relationship between scientific knowledge production, research resources and collaboration networks, using bibliometric and survey data on 116 scientists active in biotechnology in the Netherlands. Our results suggest that different knowledge creation objectives and outcomes are associated with particular ways of activating the network, and mobilize it to access specific research resources.
    Keywords: Knowledge creation, Scientific networks, University-Industry collaboration, Resources, Contributions
    JEL: M10 O30
    Date: 2023
  6. By: Aliakbar Akbaritabar (Max Planck Institute for Demographic Research, Rostock, Germany); Andrés F. Castro Torres (Max Planck Institute for Demographic Research, Rostock, Germany); Vincent Larivière
    Abstract: We reconstruct the career-long productivity, impact, (inter)national collaboration, and (inter)national mobility trajectory of 8.2 million scientists worldwide. We study the interrelationships among four well-established bibliometric claims about academics’ productivity, collaboration, mobility, and visibility. Scrutinizing these claims is only possible with a global perspective simultaneously considering influential bibliometric variables alongside collaboration among scientists. We use Multiple Correspondence Analysis with a combination of 12 widely-used bibliometric variables. We further analyze the networks of collaboration among these authors in the form of a bipartite co-authorship network and detect densely collaborating communities using Constant Potts Model. We found that the claims of literature on increased productivity, collaboration, and mobility are principally driven by a small fraction of influential scientists (top 10%). We find a hierarchically clustered structure with a small top class, and large middle and bottom classes. Investigating the composition of communities of collaboration networks in terms of these top-to-bottom classes and the academic age distribution shows that those at the top succeed by collaborating with a varying group of authors from other classes and age groups. Nevertheless, they are benefiting disproportionately to a much higher degree from this collaboration and its outcome in form of impact and citations.
    Keywords: World, inequality, science
    JEL: J1 Z0
    Date: 2023
  7. By: Jose Garcia-Louzao; Marta Silva
    Abstract: The use of social contacts in the labor market is widespread. This paper investigates the impact of personal connections on hiring probabilities and re-employment outcomes of displaced workers in Portugal. We rely on rich matched employer-employee data to define personal connections that arise from interactions at the workplace. Our empirical strategy exploits firm closures to select workers who are exogenously forced to search for a new job and leverages variation across displaced workers with direct connections to prospective employers. The hiring analysis indicates that displaced workers with a direct link to a firm through a former coworker are three times more likely to be hired compared to workers displaced from the same closing event who lack such a tie. However, we find that the effect varies according to the type of connection as well as firms’ similarity. Finally, we show that successful displaced workers with a connection in the hiring firm have higher entry-level wages and enjoy greater job security although these advantages disappear over time.
    Keywords: job displacement, coworker networks, re-employment
    JEL: J23 J63 L14
    Date: 2023
  8. By: LICHENG, Liang
    Abstract: We use COVID-19 as an exogenous shock to analyze the impact of Covid-19 pandemic on Japanese multinational affiliates’ performance, determining that the pandemic adversely impacted performance in general, but severe disruptions did not last longer than one year. The COVID-19 shock also affected global transaction networks, and affiliates’ total sales were severely affected by procurement challenges. Regarding heterogeneous effects, affiliates actively engaged in trade experienced worse conditions than localoriented firms. Finally, we explore whether and which local backward linkages could mitigate such shocks, concluding that affiliates’ local procurement from companies beyond only Japanese firms could gain resilience.
    Keywords: COVID-19, Multinational enterprises (MNEs), Affiliates, International production network, Resilience
    JEL: F14 F23
    Date: 2023–06
  9. By: Gilles, Robert P.; Mallozzi, Lina
    Abstract: We investigate Gately's solution concept for cooperative games with transferable utilities. Gately's conception is a bargaining solution and minimises the maximal quantified 'propensity to disrupt' the negotiation of the players over the allocation of the generated collective payoffs. Gately's solution concept is well-defined for a broad class of games. We consider a generalisation based on a parameter-based quantification of the propensity to disrupt. Furthermore, we investigate the relationship of these generalised Gately values with the Core. Gately's solution is in the Core for all regular 3-player games. We identify precise conditions under which generalised Gately values are Core imputations for arbitrary regular cooperative games. We devise an axiomatisation of the Gately value for the class of regular cooperative games. We conclude the paper with an application of the Gately value to the measurement of power in hierarchical social networks.
    Keywords: Cooperative TU-game, sharing values, Gately point, Core
    JEL: C71
    Date: 2022
  10. By: Kofoed, Michael S. (U.S. Military Academy, West Point); Jones, Todd R. (Mississippi State University)
    Abstract: Higher education policymakers are concerned about the success of first-generation college students. In this study, we investigate one potential factor that may influence outcomes: first-generation students' peers. To mitigate common biases that may arise when estimating peer effects, we leverage the assignment of roommates at The United States Military Academy (West Point). We do not find evidence that being exposed to a roommate(s) with a one standard deviation higher English SAT score impacts first-semester English grades for first-generation students. Our findings for math are inconclusive, with at best suggestive evidence of a small, positive effect.
    Keywords: peer effects, roommates, first generation college students
    JEL: I21 I26 H41
    Date: 2023–05
  11. By: Shuyang Sheng; Xiaoting Sun
    Abstract: This paper explores the identification and estimation of social interaction models with endogenous group formation. We characterize group formation using a two-sided many-to-one matching model, where individuals select groups based on their preferences, while groups rank individuals according to their qualifications, accepting the most qualified until reaching capacities. The selection into groups leads to a bias in standard estimates of peer effects, which is difficult to correct for due to equilibrium effects. We employ the limiting approximation of a market as the market size grows large to simplify the selection bias. Assuming exchangeable unobservables, we can express the selection bias of an individual as a group-invariant nonparametric function of her preference and qualification indices. In addition to the selection correction, we show that the excluded variables in group formation can serve as instruments to tackle the reflection problem. We propose semiparametric distribution-free estimators that are root-n consistent and asymptotically normal.
    Date: 2023–06
  12. By: Jingjing Guo
    Abstract: Precisely forecasting the excess returns of an asset (e.g., Tesla stock) is beneficial to all investors. However, the unpredictability of market dynamics, influenced by human behaviors, makes this a challenging task. In prior research, researcher have manually crafted among of factors as signals to guide their investing process. In contrast, this paper view this problem in a different perspective that we align deep learning model to combine those human designed factors to predict the trend of excess returns. To this end, we present a 5-layer deep neural network that generates more meaningful factors in a 2048-dimensional space. Modern network design techniques are utilized to enhance robustness training and reduce overfitting. Additionally, we propose a gated network that dynamically filters out noise-learned features, resulting in improved performance. We evaluate our model over 2, 000 stocks from the China market with their recent three years records. The experimental results show that the proposed gated activation layer and the deep neural network could effectively overcome the problem. Specifically, the proposed gated activation layer and deep neural network contribute to the superior performance of our model. In summary, the proposed model exhibits promising results and could potentially benefit investors seeking to optimize their investment strategies.
    Date: 2023–05

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