nep-net New Economics Papers
on Network Economics
Issue of 2023‒06‒12
thirteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links By Daron Acemoglu; Asuman Ozdaglar; Sarath Pattathil
  2. Contagion in Debt and Collateral Markets By Jin-Wook Chang; Grace Chuan
  3. Firm-level production networks: what do we (really) know? By Lafond, François; Astudillo-Estévez, Pablo; Bacilieri, Andrea; Borsos, András
  4. It's Not Who You Know—It's Who Knows You: Employee Social Capital and Firm Performance By DuckKi Cho; Lyungmae Choi; Jessie Jiaxu Wang
  5. Exploring resource seeking in a scientific collaboration network and its effect on scientists' knowledge creation By Revet, Karine; Bodas-Freitas, Isabel Maria; Chollet, Barthélemy; D'Este, Pablo
  6. Influencing Opinion Networks - Optimization and Games By de Vos, Wout; Borm, Peter; Hamers, Herbert
  7. Inflation and GDP Dynamics in Production Networks: A Sufficient Statistics Approach By Hassan Afrouzi; Saroj Bhattarai
  8. Peer effects in deposit markets By Cramer, Kim Fe; Koont, Naz
  9. Female Neighbors, Test Scores, and Careers By Sofoklis Goulas; Rigissa Megalokonomou; Yi Zhang
  10. The public investment multiplier in a production network By Alessandro Peri; Omar Rachedi; Iacopo Varotto
  11. Financial Crises and the Global Supply Network: Evidence from Multinational Enterprises By Sergi Basco; Giulia Felice; Bruno Merlevede; Martí Mestieri
  12. Monitoring Banks’ Exposure to Nonbanks: The Network of Interconnections Matters By Nicola Cetorelli; Mattia Landoni; Lina Lu
  13. Deep learning of Value at Risk through generative neural network models : the case of the Variational Auto Encoder By Pierre Brugière; Gabriel Turinici

  1. By: Daron Acemoglu; Asuman Ozdaglar; Sarath Pattathil
    Abstract: Adaptation to dynamic conditions requires a certain degree of diversity. If all agents take the best current action, learning that the underlying state has changed and behavior should adapt will be slower. Diversity is harder to maintain when there is fast communication between agents, because they tend to find out and pursue the best action rapidly. We explore these issues using a model of (Bayesian) learning over a social network. Agents learn rapidly from and may also have incentives to coordinate with others to whom they are connected via strong links. We show, however, that when the underlying environment changes sufficiently rapidly, any network consisting of just strong links will do only a little better than random choice in the long run. In contrast, networks combining strong and weak links, whereby the latter type of links transmit information only slowly, can achieve much higher long-run average payoffs. The best social networks are those that combine a large fraction of agents into a strongly-connected component, while still maintaining a sufficient number of smaller communities that make diverse choices and communicate with this component via weak links.
    Date: 2023–04
  2. By: Jin-Wook Chang; Grace Chuan
    Abstract: This paper investigates contagion in financial networks through both debt and collateral markets. We find that the role of collateral is mitigating counterparty exposures and reducing contagion but has a phase transition property. Contagion can change dramatically depending on the amount of collateral relative to the debt exposures. When there is an abundance of collateral (leverage is low), then collateral can fully cover debt exposures, and the network structure does not matter. When there is an adequate amount of collateral (leverage is moderate), then collateral can mitigate counterparty contagion, and having more links in the network reduces contagion, as interlinkages act as a diversifying mechanism. When collateral is not enough (leverage is high) and agents in the network are too interconnected, then the collateral price can plummet to zero and the whole network can collapse. Therefore, we show the importance of the interaction between the level of collateral and interconnectedness across agents. The model also provides the minimum collateral-to-debt ratio (haircut) to attain a robust macroprudential state for a given network structure and aggregate state.
    Keywords: Collateral; Financial network; Fire sale; Systemic risk
    JEL: D49 D53 G01 G21 G33
    Date: 2023–04–11
  3. By: Lafond, François; Astudillo-Estévez, Pablo; Bacilieri, Andrea; Borsos, András
    Abstract: Are standard production network properties similar across all available datasets, and if not, why? We provide benchmark results from two administrative datasets (Ecuador and Hungary), which are exceptional in that there is no reporting threshold. We compare these networks to a leading commercial dataset (FactSet) and published results on national firm-level production networks. Administrative datasets with no reporting thresholds have remarkably similar quantitative properties, while a number of important properties are biased in datasets with missing data.
    Keywords: Production networks, input-output analysis, firm-level data.
    JEL: C80 D57 L14
    Date: 2023–05
  4. By: DuckKi Cho; Lyungmae Choi; Jessie Jiaxu Wang
    Abstract: We show that the social capital embedded in employees' networks contributes to firm performance. Using novel, individual-level network data, we measure a firm's social capital derived from employees' connections with external stakeholders. Our directed network data allow for differentiating those connections that know the employee and those that the employee knows. Results show that firms with more employee social capital perform better; the positive effect stems primarily from employees being known by others. We provide causal evidence exploiting the enactment of a government regulation that imparted a negative shock to networking with specific sectors and provide evidence on the mechanisms.
    Keywords: Social capital; Social networks; Labor and finance
    JEL: G30 G41 L14
    Date: 2023–04–13
  5. By: Revet, Karine; Bodas-Freitas, Isabel Maria; Chollet, Barthélemy; D'Este, Pablo
    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 Stokesâ 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.
    JEL: M10 O30
    Date: 2023–05–25
  6. By: de Vos, Wout (Tilburg University, School of Economics and Management); Borm, Peter (Tilburg University, School of Economics and Management); Hamers, Herbert (Tilburg University, School of Economics and Management)
    Date: 2023
  7. By: Hassan Afrouzi; Saroj Bhattarai
    Abstract: We derive closed-form solutions and sufficient statistics for inflation and GDP dynamics in multi-sector New Keynesian economies with arbitrary input-output linkages. Analytically, we decompose how production linkages (1) amplify the persistence of inflation and GDP responses to monetary and sectoral shocks and (2) increase the pass-through of sectoral shocks to aggregate inflation. Quantitatively, we confirm the significant role of production networks in shock propagation, emphasizing the disproportionate effects of sectors with large input-output adjusted price stickiness: The three sectors with the highest contribution to the persistence of aggregate inflation have consumption shares of around zero but explain 16% of monetary non-neutrality.
    JEL: C67 E32 E52
    Date: 2023–05
  8. By: Cramer, Kim Fe; Koont, Naz
    Abstract: We provide first empirical evidence that consumer peer effects matter for banks' deposit demand. Using a novel measure that depicts for each county how exposed peers are to a specific bank in a given year, we tightly identify the causal effect of peer exposure on deposit demand through a fixed effects identification strategy. We address key empirical challenges such as time-invariant homophily. We find that a one percent increase in a bank's peer exposure leads to a 0.05 percent increase in deposit market share. This effect has become stronger over time with the rise of the internet and social media, which facilitate cross-county communication. Peer exposure is especially relevant for smaller banks and customers that have access to the internet.
    Keywords: deposit demand; peer effects; banking
    JEL: G21
    Date: 2021–09–25
  9. By: Sofoklis Goulas (Hoover Institution, Stanford University); Rigissa Megalokonomou (Department of Economics, Monash University); Yi Zhang (School of Economics, University of Queensland)
    Abstract: How much does your neighbor impact your test scores and career? In this paper, we examine how an observable characteristic of same-age neighbors—their gender—affects a variety of high school and university outcomes. We exploit randomness in the gender composition of local cohorts at birth from one year to the next. Using new administrative data for the universe of students in consecutive cohorts in Greece, we find that a higher share of female neighbors improves both male and female students’ high school and university outcomes. We also find that female students are more likely to enroll in STEM degrees and target more lucrative occupations when they are exposed to a higher share of female neighbors. We collect rich qualitative geographic data on communal spaces (e.g., churches, libraries, parks, Scouts and sports fields) to understand whether access to spaces of social interaction drives neighbor effects. We find that communal facilities amplify neighbor effects among females.
    Keywords: neighbor gender peer effects, cohort-to-cohort random variat, birth gender composition, geodata, STEM university degrees
    JEL: J16
    Date: 2023–05
  10. By: Alessandro Peri (Banco de España); Omar Rachedi (Banco de España); Iacopo Varotto (Banco de España)
    Abstract: Aggregate and sectoral effects of public investment crucially depend on the interaction between the output elasticity to public capital and input-output linkages. We identify this dependence through the lens of a New Keynesian production network. This setting doubles the socially optimal amount of public capital relative to the average one-sector economy, leading to a substantial amplification of the public investment multiplier. We also document novel sectoral implications of public investment. Although public investment is concentrated in far fewer sectors than public consumption, its effects are relatively more evenly distributed across industries. We validate this model implication in the data.
    Keywords: sectoral heterogeneity, input-output matrix, public capital
    JEL: E31 E32 E52
    Date: 2023–03
  11. By: Sergi Basco; Giulia Felice; Bruno Merlevede; Martí Mestieri
    Abstract: This paper empirically examines the effects of financial crises on the organization of production of multinational enterprises. We construct a panel of European multinational networks from 2003 through 2015. We use as a financial shock the increase in risk premia between August 2007 and July 2012 and build a multinational-specific shock based on the network structure before the shock. Multinationals facing a larger financial shock perform worse in terms of revenue, employment, and growth in the number of affiliates. Lower growth in the number of affiliates operates through a negative effect on domestic and foreign affiliates, and is concentrated in affiliates in a vertical relationship with the parent. These effects built up slowly over time. Negative effects are driven by multinationals with initially more leveraged parents, who reduce relatively more the number of foreign affiliates. These findings lend support to the hypothesis of financial frictions shaping multinational activity.
    JEL: F14 F23 F44 L22 L23
    Date: 2023–05
  12. By: Nicola Cetorelli; Mattia Landoni; Lina Lu
    Abstract: The first post in this series discussed the potential exposure of banks to the open-end funds sector, by virtue of commonalities in asset holdings that expose banks to balance sheet losses in the event of an asset fire sale by these funds. In this post, we summarize the findings reported in a recent paper of ours, in which we expand the analysis to consider a broad cross section of non-bank financial institution (NBFI) segments. We unveil an innovative monitoring insight: the network of interconnections across NBFI segments and banks matters. For example, certain nonbank institutions may not have a meaningful asset overlap with banks, but their fire sales could nevertheless represent a vulnerability for banks because their assets overlap closely with other NBFIs that banks are substantially exposed to.
    Keywords: nonbank financial institutions (NBFIs); fire sale; network; monitoring
    JEL: G1 G2
    Date: 2023–04–18
  13. By: Pierre Brugière (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique); Gabriel Turinici (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We present in this paper a method to compute, using generative neural networks, an estimator of the "Value at Risk" for a nancial asset. The method uses a Variational Auto Encoder with a 'energy' (a.k.a. Radon- Sobolev) kernel. The result behaves according to intuition and is in line with more classical methods.
    Date: 2023–04–24

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