nep-net New Economics Papers
on Network Economics
Issue of 2021‒04‒12
eleven papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Are close-knit networks good for employment? By María Paz Espinosa; Jaromír Kovárík
  2. Games on Endogenous Networks By Benjamin Golub; Evan Sadler
  3. Efficient Effort Equilibrium in Cooperation with Pairwise Cost Reduction By García-Martínez, Jose A.; Mayor-Serra, Antonio J.; Meca, Ana
  4. Innovation Diffusion and Physician Networks: Keyhole Surgery for Cancer in the English NHS By Eliana Barrenho; Eric Gautier; Marisa Miraldo; Carol Propper; Christiern Rose
  5. Artificial intelligence applied to bailout decisions in financial systemic risk management By Daniele Petrone; Neofytos Rodosthenous; Vito Latora
  6. Homophily, Peer Effects, and Dishonesty By Liza Charroin; Bernard Fortin; Marie Claire Villeval
  7. Changing Gender Attitudes: The Long-Run Effects of Early Exposure to Female Classmates By Garcia-Brazales, Javier
  8. Optimal Intervention in Economic Networks using Influence Maximization Methods By Ariah Klages-Mundt; Andreea Minca
  9. Identification of Peer Effects using Panel Data By Marisa Miraldo; Carol Propper; Christiern Rose
  10. Sectoral slowdowns in the UK: Evidence from transmission probabilities and economic linkages By Eva Janssens; Robin Lumsdaine
  11. Shifting Coalitions within the Youth Climate Movement in the US By Fisher, Dana R; Nasrin, Sohana

  1. By: María Paz Espinosa (Universidad del País Vasco); Jaromír Kovárík (Universidad del País Vasco)
    Abstract: How do short network cycles–the building component of close-knit network neighborhoods–affect diffusion? We study this issue in labor markets by explicitly modeling the flow of information about vacancies in social networks. We show that short network cycles induce stochastic affiliation in the transmission of job information, generating diffusion inefficiencies with important short- and long-run micro- and macroeconomic consequences. Short network cycles affect employment and inequality patterns within and across networked societies. In particular, they organize employment probabilities in the sense of the first-order stochastic dominance. People in close-knit neighborhoods and dense networks exhibit worse labor-market outcomes. Since dense, overlapping neighborhoods is one aspect of strong relationships, this uncovers an alternative mechanism behind the strength of weak ties (Granovetter, 1973). Moreover, short network cycles reinforce spatial and temporal correlations in employment status, shaping labor-market transition rates and aggregate employment fluctuations.
    Keywords: (stochastic) affiliation, clustering, inequality, information transmission, labor markets, network cycles, networks, unemployment, wages.
    JEL: A14 D85 J60 J30
    Date: 2021
  2. By: Benjamin Golub; Evan Sadler
    Abstract: We study network games in which players both create spillovers for one another and choose with whom to associate. The endogenous outcomes include both the strategic actions (e.g., effort levels) and the network in which spillovers occur. We introduce a framework and two solution concepts that extend standard approaches -- Nash equilibrium in actions and pairwise (Nash) stability in links. Our main results show that under suitable monotonicity assumptions on incentives, stable networks take simple forms. Our central conditions concern whether actions and links are strategic complements or substitutes, as well as whether links create positive or negative payoff spillovers. We apply our model to understand the consequences of competition for status, to microfound matching models that assume clique formation, and to interpret empirical findings that highlight unintended consequences of group design.
    Date: 2021–02
  3. By: García-Martínez, Jose A.; Mayor-Serra, Antonio J.; Meca, Ana
    Abstract: There are multiple situations in which bilateral interaction between agents results in considerable cost reductions. Such interaction can occur in settings where agents are interested in sharing resources, knowledge or infrastructures. Their common purpose is to obtain individual advantages, e.g. by reducing their respective individual costs. Achieving this pairwise cooperation often requires the agents involved to make some level of effort. It is natural to think that the amount by which one agent could reduce the costs of the other may depend on how much effort the latter exerts. In the first stage, agents decide how much effort they are to exert, which has a direct impact on their pairwise cost reductions. We model this first stage as a non-cooperative game, in which agents determine the level of pairwise effort to reduce the cost of their partners. In the second stage, agents engage in a bilateral interaction between independent partners. We study this bilateral cooperation as a cooperative game in which agents reduce each other's costs as a result of cooperation, so that the total reduction in the cost of each agent in a coalition is the sum of the reductions generated by the rest of the members of that coalition. In the non-cooperative game that precedes cooperation with pairwise cost reduction, the agents anticipate the cost allocation that results from the cooperative game in the second stage by incorporating the effect of the effort exerted into their cost functions. Based on this model, we explore the costs, benefits, and challenges associated with setting up a pairwise effort network. We identify a family of cost allocations with weighted pairwise reduction which are always feasible in the cooperative game and contain the Shapley value. We show that there are always cost allocations with weighted pairwise reductions that generate an optimal level of efficient effort and provide a procedure for finding the efficient effort equilibrium.
    Keywords: Allocation, Cost models, Efficiency, Game Theory
    JEL: C71 C72
    Date: 2020–12–15
  4. By: Eliana Barrenho (Paris and Imperial College Business School.); Eric Gautier (Toulouse School of Economics); Marisa Miraldo (Imperial College Business School,); Carol Propper (Imperial College Business School); Christiern Rose (School of Economics, University of Queensland, Brisbane, Australia)
    Abstract: We examine the effect of a physician network on medical innovation using novel matched patient-physician-hospital panel data. The data include every relevant physician and all patients in the English NHS for 15 years and physicians’ workplace histories for more than 20. The dynamic network arising from physician mobility between hospitals over time allows us to separate unobserved physician and hospital heterogeneity from the effect of the network. We build on standard peer-effects models by adding cumulative peer behaviour and allow for particularly influential physicians (‘key players’), whose identities we estimate. We find positive effects of peer innovation take-up, number of peers, and proximity in the network to both pioneers of the innovation and key players. Counterfactual estimates suggest that early intervention targeting young, connected physicians with early take-up can significantly increase aggregate take-up.
    Keywords: Innovation, medical practice, networks, peer-effects
    Date: 2020–12–03
  5. By: Daniele Petrone; Neofytos Rodosthenous; Vito Latora
    Abstract: We describe the bailout of banks by governments as a Markov Decision Process (MDP) where the actions are equity investments. The underlying dynamics is derived from the network of financial institutions linked by mutual exposures, and the negative rewards are associated to the banks' default. Each node represents a bank and is associated to a probability of default per unit time (PD) that depends on its capital and is increased by the default of neighbouring nodes. Governments can control the systemic risk of the network by providing additional capital to the banks, lowering their PD at the expense of an increased exposure in case of their failure. Considering the network of European global systemically important institutions, we find the optimal investment policy that solves the MDP, providing direct indications to governments and regulators on the best way of action to limit the effects of financial crises.
    Date: 2021–02
  6. By: Liza Charroin (Sorbonne Economic Centre, University of Paris 1); Bernard Fortin (Economics Department, Laval University, Québec, CIRPÉE, and CIRANO, Canada. IZA, Bonn, Germany); Marie Claire Villeval (Univ Lyon, CNRS, GATE UMR 5824, 93 Chemin des Mouilles, F-69130, Ecully, France. IZA, Bonn, Germany)
    Abstract: If individuals tend to behave like their peers, is it because of conformity, that is, the preference of people to align behavior with the behavior of their peers; homophily, that is, the tendency of people to bond with similar others; or both? We address this question in the context of an ethical dilemma. Using a peer effect model allowing for homophily, we designed a real-effort laboratory experiment in which individuals could misreport their performance to earn more. Our results reveal a preference for conformity and for homophily in the selection of peers, but only among participants who were cheating in isolation. The size of peer effects is similar when identical peers were randomly assigned and when they were selected by individuals. We thus jointly reject the presence of a self-selection bias in the peer effect estimates and of a link strength effect.
    Keywords: Peer Effects, Homophily, Dishonesty, Self-Selection Bias, Experiment
    JEL: C92 D83 D85 D91
    Date: 2021
  7. By: Garcia-Brazales, Javier
    Abstract: Identity norms are an important cause of inequalities and talent misallocation. I lever- age a unique opportunity to observe students exogenously allocated to classes across a close-to-nationally-representative set of Vietnamese schools to show that more exposure to female peers during childhood causally decreases the extent of agreement with tradi- tional gender roles in the long-run. This shift in attitudes is accompanied by changes in actual behavior: employing friendship nominations I find that male children have more female friends and spend more time with them outside school. Moreover, both their intensive and extensive margin contributions to home production increase in the short- and the long-run. These results are novel in the attitudes formation and in the long- term effects of peers literature and are important in informing optimal class allocation. Academic spillovers from female classmates are much weaker.
    Keywords: Long-term Peer Effects,Gender Roles,Attitudes Formation
    JEL: I24 I25 J16
    Date: 2021
  8. By: Ariah Klages-Mundt; Andreea Minca
    Abstract: We consider optimal intervention in the Elliott-Golub-Jackson network model and show that it can be transformed into an influence maximization problem, interpreted as the reverse of a default cascade. Our analysis of the optimal intervention problem extends well-established targeting results to the economic network setting, which requires additional theoretical steps. We prove several results about optimal intervention: it is NP-hard and additionally hard to approximate to a constant factor in polynomial time. In turn, we show that randomizing failure thresholds leads to a version of the problem which is monotone submodular, for which existing powerful approximations in polynomial time can be applied. In addition to optimal intervention, we also show practical consequences of our analysis to other economic network problems: (1) it is computationally hard to calculate expected values in the economic network, and (2) influence maximization algorithms can enable efficient importance sampling and stress testing of large failure scenarios. We illustrate our results on a network of firms connected through input-output linkages inferred from the World Input Output Database.
    Date: 2021–02
  9. By: Marisa Miraldo (Imperial College Business School,); Carol Propper (Imperial College Business School); Christiern Rose (School of Economics, University of Queensland, Brisbane, Australia)
    Abstract: This paper provides new identification results for panel data models with contextual and endogenous peer effects. Contextual effects operate through individuals’ time-invariant unobserved heterogeneity. Identification hinges on a conditional mean restriction requiring exogenous mobility of individuals between groups over time. Some networks governing peer interactions preclude identification. For these cases we propose additional conditional variance restrictions. We conduct a Monte-Carlo experiment to evaluate the performance of our method and apply it to surgeon-hospital-year data to study take-up of minimally invasive surgery. A standard deviation increase in the average time-invariant unobserved heterogeneity of other surgeons in the same hospital leads to a 0.12 standard deviation increase in take-up. The effect is equally due to endogenous and contextual effects.
    Keywords: Peer effects, panel data, networks, identification, innovation, healthcare
    Date: 2020–12–03
  10. By: Eva Janssens (University of Amsterdam); Robin Lumsdaine (Erasmus University Rotterdam)
    Abstract: This paper studies shock transmission across macroeconomic sectors in the UK, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of shocks to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of shock transmission between them. The combination of both approaches reveals the Monetary Financial Institutions sector's role as shock absorber, and identifies the most important channels of shock transmission. The inferential discrepancies between network data and the actual spillovers highlight the contribution of the proposed methodology.
    Keywords: Flow of Funds, contagion, epidemiology, intersectoral networks, Gibbs sampling, Bayesian priors
    JEL: E37 E32 E01 G01
    Date: 2021–04–05
  11. By: Fisher, Dana R; Nasrin, Sohana
    Abstract: How has the youth climate movement in the US grown since the Climate Strikes began and in what ways did it change as it grew? This article takes advantage of a unique dataset that includes surveys from activists who organized the nationally coordinated climate strikes in the US that began with Fridays for Future in spring 2019. Building on the research on alliance building and strategic coalitions, this article analyzes how the patterns of participation changed over the period of the study. We employ social network analysis to map the affiliation networks among the organizers of these events to assess the coalitions of groups involved and the shifting organizational landscape. Our analysis does not provide evidence that groups spanned the boundaries across movements, nor does it show that identity played a role in coalition building in this movement. Instead, by mapping out the coalition of organizations within this movement and how connections among them change over time, we see clear evidence that this youth-led movement was reoriented by adult-led organizations. Our article concludes by considering how these findings suggest the future trajectory of the youth climate movement and its role in a ‘new climate politics’ in America.
    Date: 2021–04–07

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