nep-net New Economics Papers
on Network Economics
Issue of 2021‒11‒29
eight papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Leaders in Juvenile Crime By Díaz, Carlos; Patacchini, Eleonora; Verdier, Thierry; Zenou, Yves
  2. Education Transmission and Network Formation By Boucher, Vincent; Del Bello, Carlo L.; Panebianco, Fabrizio; Verdier, Thierry; Zenou, Yves
  3. DEEDP DIVING INTO THE S&P 350 EUROPE INDEX NETWORK ANS ITS REACTION TO COVID-19 By Ariana Paola Cortés à ngel; Mustafa Hakan Eratalay
  4. Central Limit Theory for Models of Strategic Network Formation By Konrad Menzel
  5. Asymptotic in a class of network models with sub-Gamma perturbations By Jiaxin Guo; Haoyu Wei; Xiaoyu Lei; Jing Luo
  6. Intermediation and Voluntary Exposure to Counterparty Risk By Maryam Farboodi
  7. Birds of a Feather: Life Cycle Social Externalities, Heterogeneous Beliefs, and Development Bias By Young-Chul Kim; Glenn C. Loury
  8. The Heterogeneous Impact of Referrals on Labor Market Outcomes By Benjamin Lester; David A. Rivers; Giorgio Topa

  1. By: Díaz, Carlos (Catholic University of Uruguay); Patacchini, Eleonora (Cornell University); Verdier, Thierry (Paris School of Economics); Zenou, Yves (Monash University)
    Abstract: This paper presents a new theory of crime where leaders transmit a crime technology and act as a role model for other criminals. We show that, in equilibrium, an individual's crime effort and criminal decisions depend on the geodesic distance to the leader in his or her network of social contacts. By using data on friendship networks among U.S. high-school students, we structurally estimate the model and find evidence supporting its predictions. In particular, by using a definition of a criminal leader that is exogenous to the network formation of friendship links, we find that the longer is the distance to the leader, the lower is the criminal activity of the delinquents and the less likely they are to become criminals. We finally perform a counterfactual experiment that reveals that a policy that removes all criminal leaders from a school can, on average, reduce criminal activity by about 20% and the individual probability of becoming a criminal by 10%.
    Keywords: crime leaders, social distance, criminal decisions, closeness centrality
    JEL: C31 D85 K42
    Date: 2021–10
  2. By: Boucher, Vincent (Université Laval); Del Bello, Carlo L. (Paris School of Economics); Panebianco, Fabrizio (Bocconi University); Verdier, Thierry (Paris School of Economics); Zenou, Yves (Monash University)
    Abstract: We propose a model of intergenerational transmission of education wherein children belong to either highly educated or low-educated families. Children choose the intensity of their social activities while parents decide how much educational effort to exert. Using data on adolescents in the United States, we structurally estimate this model and find that, on average, children's homophily acts as a complement to the educational effort of highly educated parents but as a substitute for the educational effort of low-educated parents. We also perform some counterfactual policy simulations. We find that policies that subsidize kids' socialization efforts can backfire for low-educated students because they tend to increase their interactions with other low-educated students (i.e., homophily), which reduces the education effort of their parents and, thus, their chance of becoming educated. On the contrary, policies that increase heterophily by favoring friendship links between kids from different education backgrounds can be effective in reducing the education gap between them.
    Keywords: social networks, education, homophily, cultural transmission
    JEL: D85 I21 Z13
    Date: 2021–10
  3. By: Ariana Paola Cortés à ngel; Mustafa Hakan Eratalay
    Abstract: In this paper, we analyse the dynamic partial correlation network of the constituent stocks of S&P Europe 350. We focus on global parameters such as radius, which is rarely used in financial networks literature, and also the diameter and distance parameters. The first two parameters are useful for deducing the force that economic instability should exert to trigger a cascade effect on the network. With these global parameters, we hone the boundaries of the strength that a shock should exert to trigger a cascade effect. In addition, we analysed the homophilic profiles, which is quite new in financial networks literature. We found highly homophilic relationships among companies, considering firms by country and industry. We also calculate the local parameters such as degree, closeness, betweenness, eigenvector, and harmonic centralities to gauge the importance of the companies regarding different aspects, such as the strength of the relationships with their neighbourhood and their location in the network. Finally, we analysed a network substructure by introducing the skeleton concept of a dynamic network. This subnetwork allowed us to study the stability of relations among constituents and detect a significant increase in these stable connections during the Covid-19 pandemic.
    Keywords: Financial Networks, Centralities, Homophily, Multivariate GARCH, Networks Connectivity, Gaussian graphical model, Covid-19
    Date: 2021
  4. By: Konrad Menzel
    Abstract: We provide asymptotic approximations to the distribution of statistics that are obtained from network data for limiting sequences that let the number of nodes (agents) in the network grow large. Network formation is permitted to be strategic in that agents' incentives for link formation may depend on the ego and alter's positions in that endogenous network. Our framework does not limit the strength of these interaction effects, but assumes that the network is sparse. We show that the model can be approximated by a sampling experiment in which subnetworks are generated independently from a common equilibrium distribution, and any dependence across subnetworks is captured by state variables at the level of the entire network. Under many-player asymptotics, the leading term of the approximation error to the limiting model established in Menzel (2015b) is shown to be Gaussian, with an asymptotic bias and variance that can be estimated consistently from a single network.
    Date: 2021–11
  5. By: Jiaxin Guo; Haoyu Wei; Xiaoyu Lei; Jing Luo
    Abstract: For the differential privacy under the sub-Gamma noise, we derive the asymptotic properties of a class of network models with binary values with a general link function. In this paper, we release the degree sequences of the binary networks under a general noisy mechanism with the discrete Laplace mechanism as a special case. We establish the asymptotic result including both consistency and asymptotically normality of the parameter estimator when the number of parameters goes to infinity in a class of network models. Simulations and a real data example are provided to illustrate asymptotic results.
    Date: 2021–11
  6. By: Maryam Farboodi
    Abstract: I study a model of the financial sector in which intermediation among debt financed banks gives rise to an endogenous core-periphery network – few highly interconnected and many sparsely connected banks. Endogenous intermediation generates excessive systemic risk in the financial network. Financial institutions have incentives to capture intermediation spreads through strategic borrowing and lending decisions. By doing so, they tilt the division of surplus along an intermediation chain in their favor, while at the same time reducing aggregate surplus. The network is inefficient relative to a constrained efficient benchmark since banks who make risky investments “overconnect”, exposing themselves to excessive counterparty risk, while banks who mainly provide funding end up with too few connections.
    JEL: D85 G20 G21
    Date: 2021–11
  7. By: Young-Chul Kim (Department of Economics, Sogang University, Korea); Glenn C. Loury (Department of Economics, Brown University, USA)
    Abstract: This study models how social networks that span an individual’s entire life cycle affect human capital acquisition and subsequent employment outcomes. Early-life social affiliations can affect the cost of human capital, while later-life connections can affect the earnings derived from previously acquired human capital. The dynamic interactions between early-life network-mediated investments and later-life networkmediated returns give rise to multiple, fully consistent, rational expectations equilibria. These self-fulling expectations imply development bias, wherein heterogeneous beliefs about the future persistently generate unequal outcomes among social groups. When the model is applied to a country’s development cycle, the theoretical findings suggest that, while between-group inequality can reduce economic growth in a mature economy, it may increase growth in an economy in the initial stages of its development. Relevant historical examples of between-group dynamics are discussed extensively.
    Keywords: Group Inequality, Social Externality, Development Bias, Expectation Trap
    JEL: I30 J15 Z13
    Date: 2021
  8. By: Benjamin Lester; David A. Rivers; Giorgio Topa
    Abstract: We document a new set of facts regarding the impact of referrals on labor market outcomes. Our results highlight the importance of distinguishing between different types of referrals—those from family and friends and those from business contacts—and different occupations. Then we develop an on-the-job search model that incorporates referrals and calibrate the model to key moments in the data. The calibrated model yields new insights into the roles played by different types of referrals in the match formation process and provides quantitative estimates of the effects of referrals on employment, earnings, output, and inequality.
    Keywords: Labor Markets; Referrals; Networks; Search Theory; Asymmetric Information
    JEL: E42 E43 E44 E52 E58
    Date: 2021–10–26

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