nep-net New Economics Papers
on Network Economics
Issue of 2021‒05‒31
twelve papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. A Structural Model of Business Card Exchange Networks By Juan Nelson Mart\'inez Dahbura; Shota Komatsu; Takanori Nishida; Angelo Mele
  2. Pandemic Control in ECON-EPI Networks By Azzimonti, Marina; Fogli, Alessandra; Perri, Fabrizio; Ponder, Mark
  3. Collaboration in Bipartite Networks, with an Application to Coauthorship Networks By Hsieh, Chih-Sheng; König, Michael; Liu, Xiaodong; Zimmermann, Christian
  4. A Graphical Lasso Approach to Estimating Network Connections: The Case of U.S. Lawmakers By Battaglini, Marco; Crawford, Forrest; Patacchini, Eleonora; Peng, Sida
  5. Identification and Estimation of a Partially Linear Regression Model using Network Data: Inference and an Application to Network Peer Effects By Eric Auerbach
  6. Education Transmission and Network Formation By Boucher, Vincent; Del Bello, Carlo; Panebianco, Fabrizio; Verdier, Thierry; Zenou, Yves
  7. Preaching to Social Media: Turkey’s Friday Khutbas and Their Effects on Twitter By Ozan Aksoy
  8. Survey methods for estimating the size of weak-tie personal networks By Feehan, Dennis; Son, Vo Hai; Abdul-Quader, Abu
  9. Field Distance and Quality in Economists’ Collaborations By Ali Sina Onder; Sascha Schweitzer; Hakan Yilmazkuday
  10. Get Rich or Fail Your Exam Tryin': Gender, Socioeconomic Status and Spillover Effects of Blended Learning By Mehic, Adrian; Olofsson, Charlotta
  11. Commuting and internet traffic congestion By Berliant, Marcus
  12. Social entrepreneurs as change makers: expanding public service networks for social innovation By Anne Hansen; Lars Fuglsang; Faïz Gallouj; Ada Scupola

  1. By: Juan Nelson Mart\'inez Dahbura; Shota Komatsu; Takanori Nishida; Angelo Mele
    Abstract: Social and professional networks affect labor market dynamics, knowledge diffusion and new business creation. To understand the determinants of how these networks are formed in the first place, we analyze a unique dataset of business cards exchanges among a sample of over 240,000 users of the multi-platform contact management and professional social networking tool for individuals Eight. We develop a structural model of network formation with strategic interactions, and we estimate users' payoffs that depend on the composition of business relationships, as well as indirect business interactions. We allow heterogeneity of users in both observable and unobservable characteristics to affect how relationships form and are maintained. The model's stationary equilibrium delivers a likelihood that is a mixture of exponential random graph models that we can characterize in closed-form. We overcome several econometric and computational challenges in estimation, by exploiting a two-step estimation procedure, variational approximations and minorization-maximization methods. Our algorithm is scalable, highly parallelizable and makes efficient use of computer memory to allow estimation in massive networks. We show that users payoffs display homophily in several dimensions, e.g. location; furthermore, users unobservable characteristics also display homophily.
    Date: 2021–05
  2. By: Azzimonti, Marina; Fogli, Alessandra; Perri, Fabrizio; Ponder, Mark
    Abstract: We develop an ECON-EPI network model to evaluate policies designed to improve health and economic outcomes during a pandemic. Relative to the standard epidemiological SIR set-up, we explicitly model social contacts among individuals and allow for heterogeneity in their number and stability. In addition, we embed the network in a structural economic model describing how contacts generate economic activity. We calibrate it to the New York metro area during the 2020 COVID-19 crisis and show three main results. First, the ECON-EPI network implies patterns of infections that better match the data compared to the standard SIR. The switching during the early phase of the pandemic from unstable to stable contacts is crucial for this result. Second, the model suggests the design of smart policies that reduce infections and at the same time boost economic activity. Third, the model shows that re-opening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.
    Keywords: Complex Networks; COVID-19; epidemiology; SIR; social distance
    JEL: D85 E23 E65 I18
    Date: 2020–08
  3. By: Hsieh, Chih-Sheng; König, Michael; Liu, Xiaodong; Zimmermann, Christian
    Abstract: This paper studies the impact of collaboration on research output. First, we build a micro-founded model for scientific knowledge production, where collaboration between researchers is represented by a bipartite network. The equilibrium of the game incorporates both the complementarity effect between collaborating researchers and the substitutability effect between concurrent projects of the same researcher. Next, we develop a Bayesian MCMC procedure to estimate the structural parameters, taking into account the endogenous matching of researchers and projects. Finally, we illustrate the empirical relevance of the model by analyzing the coauthorship network of economists registered in the RePEc Author Service.
    Keywords: bipartite networks; coauthorship networks; economics of science; research collaboration; Spillovers
    JEL: C31 C72 D85 L14
    Date: 2020–08
  4. By: Battaglini, Marco; Crawford, Forrest; Patacchini, Eleonora; Peng, Sida
    Abstract: Abstract In this paper, we propose a new approach to the estimation of social networks and we apply it to the estimation of productivity spillovers in the U.S. Congress. Social networks such as the social connections among lawmakers are not generally directly observed, they can be recovered only using the observable outcomes that they contribute to determine (such as, for example, the legislators' effectiveness). Moreover, they are typically stable for relatively short periods of time, thus generating only short panels of observations. Our estimator has three appealing properties that allows it to work in these environments. First, it is constructed for "small" asymptotic, thus requiring only short panels of observations. Second, it requires relatively nonrestrictive sparsity assumptions for identification, thus being applicable to dense networks with (potentially) star shaped connections. Third, it allows for heterogeneous common shocks across subnetworks. The application to the U.S. Congress gives us new insights about the nature of social interactions among lawmakers. We estimate a significant decrease over time in the importance of productivity spillovers among individual lawmakers, compensated by an increase in the party level common shock over time. This suggests that the rise of partisanship is not affecting only the ideological position of legislators when they vote, but more generally how lawmakers collaborate in the U.S. Congress.
    Keywords: Graphical Lasso; Legislatures; Social Networks
    Date: 2020–07
  5. By: Eric Auerbach
    Abstract: This paper provides additional results relevant to the setting, model, and estimators of Auerbach (2019a). Section 1 contains results about the large sample properties of the estimators from Section 2 of Auerbach (2019a). Section 2 considers some extensions to the model. Section 3 provides an application to estimating network peer effects. Section 4 shows the results from some simulations.
    Date: 2021–05
  6. By: Boucher, Vincent; Del Bello, Carlo; Panebianco, Fabrizio; Verdier, Thierry; Zenou, Yves
    Abstract: We propose a model of intergenerational transmission of education wherein children belong to either high-educated or low-educated families. Children choose the intensity of their social activities, while parents decide how much educational effort to exert. We characterize the equilibrium and show the conditions under which cultural substitution or complementarity emerges. Using data on adolescents in the United States, we structurally estimate our model and find that, on average, children's homophily acts as a complement to the educational effort of high-educated parents but as a substitute for the educational effort of low-educated parents. We also perform some policy simulations. We find that policies that subsidize social interactions can backfire for low-educated students because they tend to increase their interactions with other low-educated students, which reduce the education effort of their parents and, thus, their chance of becoming educated.
    Keywords: Education; Social Networks
    JEL: D85 I21 Z13
    Date: 2020–07
  7. By: Ozan Aksoy (Centre for Quantitative Social Sciences in the Social Research Institute, University College London)
    Abstract: In this study I analyse through machine learning the content of all Friday khutbas (sermons) read to millions of citizens in thousands of Mosques of Turkey since 2015. I focus on six non-religious and recurrent topics that feature in the sermons, namely business, family, nationalism, health, trust, and patience. I demonstrate that the content of the sermons responds strongly to events of national importance. I then link the Friday sermons with ~4.8 million tweets on these topics to study whether and how the content of sermons affects social media behaviour. I find generally large effects of the sermons on tweets, but there is also heterogeneity by topic. It is strongest for nationalism, patience, and health and weakest for business. Overall, these results show that religious institutions in Turkey are influential in shaping the public’s social media content and that this influence is mainly prevalent on salient issues. More generally, these results show that mass offline religious activity can have strong effects on social media behaviour
    Keywords: text-as-data analysis, computational social science, social media, religion, Islam, Turkey
    JEL: C63 N35 Z12
    Date: 2021–05–01
  8. By: Feehan, Dennis; Son, Vo Hai; Abdul-Quader, Abu
    Abstract: Researchers increasingly use *aggregate relational data* to learn about the size and distribution of survey respondents' weak-tie personal networks. Aggregate relational data are collected by asking questions about respondents' connectedness to many different groups (e.g., "How many teachers do you know?"). This approach can be powerful but, to make use of aggregate relational data, researchers must locate external information about the size of each of these groups from a census or from administrative records (e.g., the number of teachers in the population). This need for external information makes aggregate relational data difficult or impossible to collect in many settings. Here, we show that relatively simple modifications can overcome this need for external data, significantly increasing the flexibility of the method and weakening key assumptions required by the associated estimators. Our methods are appropriate for using a sample survey to study the size and distribution of weak-tie network connections. Our methods can also be used as part of the network scale-up method to estimate the size of hidden populations. We illustrate our approach with two empirical studies: a large simulation study, and original household survey data collected in Hanoi, Vietnam.
    Date: 2021–05–19
  9. By: Ali Sina Onder (University of Portsmouth); Sascha Schweitzer (University of Bayreuth); Hakan Yilmazkuday (Florida International University)
    Abstract: We analyze economics PhDs’ collaborations in peer-reviewed journals from 1990 to 2014 and investigate such collaborations’ quality in relation to each co-author’s research quality, field and specialization. We find that a greater overlap between co-authors’ previous research fields is significantly related to a greater publication success of co-authors’ joint work and this is robust to alternative specifications. Co-authors that engage in a distant collaboration are significantly more likely to have a large research overlap, but this significance is lost when co-authors’ social networks are accounted for. High quality collaboration is more likely to emerge as a result of an interaction between specialists and generalists with overlapping fields of expertise. Regarding interactions across subfields of economics (interdisciplinarity), it is more likely conducted by co-authors who already have interdisciplinary portfolios, than by co-authors who are specialized or starred in different subfields.
    Keywords: Collaboration; Distance; Team Formation; Research Productivity; Fields of Economics; Stratification; Specialization
    JEL: A11 A14 I23
    Date: 2021–05–19
  10. By: Mehic, Adrian (Department of Economics, Lund University); Olofsson, Charlotta (Department of Economics, Lund University)
    Abstract: We evaluate a natural experiment at a Swedish university, in which students were randomized to either taking all their courses online, or to have some courses online and some on campus (blended learning). Our setting creates two groups for the online courses: One group with no access to campus whatsoever, and one group treated with campus classes in parallel, but unrelated, courses. We show that campus access in parallel courses improved academic performance in online courses only among female students with affluent parents. Detailed individual-level survey data suggests that there was no relationship between social status and adverse mental health amid the COVID-19 pandemic. Instead, by estimating each student's network position, linked with administrative data on parental income, we show that female students with wealthy parents have significantly less constrained social networks, enabling them to utilize scarcely available campus time to communicate with classmates more efficiently.
    Keywords: COVID-19; blended learning; online education; social networks
    JEL: I23 I28 J16 Z13
    Date: 2021–05–13
  11. By: Berliant, Marcus
    Abstract: We examine the fine microstructure of commuting in a game-theoretic setting with a continuum of commuters. Commuters' home and work locations can be heterogeneous. A commuter transport network is exogenous. Traffic speed is determined by link capacity and by local congestion at a time and place along a link, where local congestion at a time and place is endogenous. The model can be reinterpreted to apply to congestion on the internet. We find sufficient conditions for existence of equilibrium, that multiple equilibria are ubiquitous, and that the welfare properties of morning and evening commute equilibria differ on a generalization of a directed tree.
    Keywords: Commuting; Internet traffic; Congestion externality; Efficient Nash equilibrium
    JEL: L86 R41
    Date: 2021–05–24
  12. By: Anne Hansen (Roskilde Universitet [Roskilde]); Lars Fuglsang (Roskilde Universitet [Roskilde]); Faïz Gallouj (CLERSE - Centre Lillois d’Études et de Recherches Sociologiques et Économiques - UMR 8019 - Université de Lille - CNRS - Centre National de la Recherche Scientifique); Ada Scupola (Roskilde Universitet [Roskilde])
    Abstract: Social innovation, in the context of public innovation, has gained increased attention in the literature, and is approached relative to the third sector, to social enterprises, or as practices initiated by the public sector. However, the interplay among these actors in enabling social innovation is still underexplored. Therefore, the article investigates the role of social entrepreneurs from outside the public sector in enabling public sector innovation networks. Since social innovation is inherently relational, four cases demonstrating how social entrepreneurs have pushed the boundaries of public sector services, and hence expanded public innovation networks, are analysed.
    Keywords: public service innovation,social innovation,social entrepreneurs,innovation networks
    Date: 2021

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