nep-net New Economics Papers
on Network Economics
Issue of 2021‒05‒17
sixteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Gender and Collaboration By Ductor, Lorenzo; Goyal, Sanjeev; Prummer, Anja
  2. Ethnic Mixing in Early Childhood By Boucher, Vincent; Tumen, Semih; Vlassopoulos, Michael; Wahba, Jackline; Zenou, Yves
  3. Exploring the Antecedents of Consumer Confidence through Semantic Network Analysis of Online News By A. Fronzetti Colladon; F. Grippa; B. Guardabascio; F. Ravazzolo
  4. Perceived Competition in Networks By Bochet, Olivier; Faure, Mathieu; Long, Yan; Zenou, Yves
  5. An Estimable Model of Production Interactions in Endogenous Networks By De Giorgi, Giacomo; Pellizzari, Michele; Rodríguez Barraquer, Tomás
  6. Innovation Diffusion and Physician Networks: Keyhole Surgery for Cancer in the English NHS By Barrenho, Eliana; Gautier, Eric; Miraldo, Marisa; Propper, Carol; Rose, Christiern
  7. O-Ring Production Networks By Demir, Banu; Fieler, Cecilia; Xu, Yi (Daniel); Yang, Kelly Kaili
  8. Tax Planning Knowledge Diffusion via the Labor Market By John M. Barrios; John Gallemore
  9. Social Finance By Kuchler, Theresa; Ströbel, Johannes
  10. A model of inter-organizational network formation By Gaonkar, Shweta; Mele, Angelo
  11. A connections model with decreasing returns link-formation technology By Olaizola, Norma; Valenciano, Federico
  12. Social Distancing During a Pandemic - The Role of Friends By Bailey, Michael; Johnston, Drew; Koenen, Martin; Kuchler, Theresa; Russel, Dominic; Ströbel, Johannes
  13. Efficient Peer Effects Estimators with Random Group Effects By Guido M. Kuersteiner; Ingmar R. Prucha; Ying Zeng
  14. The Local Approach to Causal Inference under Network Interference By Eric Auerbach; Max Tabord-Meehan
  15. Keynesian Production Networks and the Covid-19 Crisis: A Simple Benchmark By Baqaee, David Rezza; Farhi, Emmanuel
  16. Using social network analysis to prevent money laundering By A. Fronzetti Colladon; E. Remondi

  1. By: Ductor, Lorenzo; Goyal, Sanjeev; Prummer, Anja
    Abstract: We connect gender disparities in research output and collaboration patterns in economics. We first document large gender gaps in research output. These gaps persist across 50 years despite a significant increase in the fraction of women in economics during that time. We further show that output differences are closely related to differences in the co-authorship networks of men and women: women have fewer collaborators, collaborate more often with the same co-authors, and a higher fraction of their co-authors collaborate with each other. Taking into account co-authorship networks reduces the gender output gap by 18%.
    Date: 2021–01
  2. By: Boucher, Vincent; Tumen, Semih; Vlassopoulos, Michael; Wahba, Jackline; Zenou, Yves
    Abstract: The social integration of minority groups is a major policy challenge for many countries. This paper addresses this issue in the context of an early childhood program conducted in Turkey aimed at preparing 5-year-old native and Syrian refugee children for elementary school. We randomly assign children to groups with varying ethnic composition and examine whether random exposure to non-coethnic children over a period of 2 months affects interethnic friendship formation and language acquisition. We find that exposure to children of the other ethnicity leads to an increase in the formation of interethnic friendships, especially for Turkish children, while the Turkish language skills of Syrian children are better developed in classes with a larger presence of Turkish children. To explain the empirical patterns, we develop a model of friendship formation with two key mechanisms: preference bias for forming coethnic links, and congestion in the friendship formation process. Structural estimation of the model suggests that interethnic contact: (i) reduces the share of own-ethnicity friends, and (ii) has a non-monotonic effect on the bias toward forming own-ethnicity friendships beyond what would be expected given the size of the group (inbreeding homophily). The latter finding implies that increased exposure of minority children to non-coethnic children can lead to more in-group bias in friendship formation, relative to when the two ethnic shares are more balanced. Finally, counterfactual analysis indicates that improvement in the language skills of Syrian children can offset more than half of the effect that ethnic bias has on friendship formation patterns.
    Keywords: contact theory; Refugees; Social Cohesion; Social Networks
    JEL: J15 J18 Z13
    Date: 2020–12
  3. By: A. Fronzetti Colladon; F. Grippa; B. Guardabascio; F. Ravazzolo
    Abstract: This article studies the impact of online news on social and economic consumer perceptions through the application of semantic network analysis. Using almost 1.3 million online articles on Italian media covering a period of four years, we assessed the incremental predictive power of economic-related keywords on the Consumer Confidence Index. We transformed news into networks of co-occurring words and calculated the semantic importance of specific keywords, to see if words appearing in the articles could anticipate consumers' judgements about the economic situation. Results show that economic-related keywords have a stronger predictive power if we consider the current households and national situation, while their predictive power is less significant with regards to expectations about the future. Our indicator of semantic importance offers a complementary approach to estimate consumer confidence, lessening the limitations of traditional survey-based methods.
    Date: 2021–05
  4. By: Bochet, Olivier; Faure, Mathieu; Long, Yan; Zenou, Yves
    Abstract: Agents compete for the same resources and are only aware of their direct neighbors in a network. We propose a new equilibrium concept, referred to as peer-consistent equilibrium (PCE). In a PCE, each agent chooses an effort level that maximizes her subjective perceived utility and the effort levels of all individuals in the network need to be consistent. We develop an algorithm that breaks the network into communities. We use this decomposition to completely characterize peer-consistent equilibria by identifying which sets of agents can be active in equilibrium. An agent is active if she either belongs to a strong community or if few agents are aware of her existence. We show that there is a unique stable PCE. We provide a microfoundation of eigenvector centrality, since, in any stable PCE, agents' effort levels are proportional to their eigenvector centrality in the network.
    Keywords: eigenvector centrality; policies; Social Networks
    JEL: C72 D85
    Date: 2020–12
  5. By: De Giorgi, Giacomo; Pellizzari, Michele; Rodríguez Barraquer, Tomás
    Abstract: We propose a model where forward-looking agents first decide to form links with each other and, then, engage in a production activity jointly with their linked peers. Exogenous linking opportunities facilitate the creation of network connections and the return to productive effort varies with the personal attributes of the connected agents. We apply our model to a purposely built dataset of college students containing information on the endogeneous networks of study partners linked with administrative records on the students' characteristics and academic performance. Identification relies upon the random assignment of students to classrooms, which generates exogenous opportunities for socialisation. Using the estimated structural parameters, we investigate the implications of two counterfactual experiments, one where students are streamed into classes by ability and one with single-sex classes.
    Keywords: counterfactual; Education; estimation; networks; Production
    JEL: C15 C63 C73 D85 E23 I23
    Date: 2020–11
  6. By: Barrenho, Eliana; Gautier, Eric; Miraldo, Marisa; Propper, Carol; Rose, Christiern
    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
  7. By: Demir, Banu; Fieler, Cecilia; Xu, Yi (Daniel); Yang, Kelly Kaili
    Abstract: We study a production network where quality choices are interconnected across firms. High-quality firms are skill intensive and trade more with other high-quality firms. Using data from Turkish firms, we document strong assortative matching of skills in the production network. A firm-specific export demand shock from a rich country increases the firm's skill intensity and shifts the firm toward skill-intensive domestic partners. We develop a quantitative model with heterogeneous firms, endogenous quality choices, and network formation. An economy-wide export demand shock of 5 percent induces exporters and non-exporters to upgrade quality, raising the average wage by 1.2 percent. This effect is about nine times the effect in a special case of the model with no interconnection of quality choices.
    JEL: F14 L14 O30
    Date: 2021–01
  8. By: John M. Barrios; John Gallemore
    Abstract: We examine the extent to which the labor market facilitates the diffusion of tax planning knowledge across firms. Using a novel dataset of tax department employee movements between S&P 1500 firms, we find that firms experience an increase in their tax planning after hiring a tax employee from a tax aggressive firm. This finding is robust to various research designs and specifications. Consistent with tax planning knowledge driving this result, we find that the tax planning benefit of hiring an employee from a tax aggressive firm is stronger when the employee has more tax experience and is hired into a senior tax department role, and when the hiring firm likely had less tax planning knowledge prior to the hire. Further tests suggest that tax planning knowledge is highly specific in nature: the increase in tax avoidance is larger when the hiring and former firms are similar (i.e., operating in the same sector or having similar foreign operations), and firms are more likely to hire tax department employees from firms with similar characteristics. Our study documents the first-order role of the labor market in the diffusion of tax planning knowledge across firms, and suggests that tax department human capital is a central determinant of tax planning outcomes.
    JEL: H25 H26 J20 J24 J4 J44 J60
    Date: 2021–05
  9. By: Kuchler, Theresa; Ströbel, Johannes
    Abstract: We review an empirical literature that studies the role of social interactions in driving economic and financial decision making. We first summarize recent work that documents an important role of social interactions in explaining household decisions in housing and mortgage markets. This evidence shows, for example, that there are large peer effects in mortgage refinancing decisions and that individuals' beliefs about the attractiveness of housing market investments are affected by the recent house price experiences of their friends. We also summarize the evidence that social interactions affect the stock market investments of both retail and professional investors as well as household financial decisions such as retirement savings, borrowing, and default. Along the way, we describe a number of easily accessible recent data sets for the study of social interactions in finance, including the "Social Connectedness Index,'' which measures the frequency of Facebook friendship links across geographic regions. We conclude by outlining several promising directions for further research in the field of "social finance.''
    Date: 2020–12
  10. By: Gaonkar, Shweta; Mele, Angelo (Johns Hopkins University)
    Abstract: How do inter-organizational networks emerge? Accounting for interdependence among ties while studying tie formation is one of the key challenges in this area of research. We address this challenge using an equilibrium framework where firms' decisions to form links with other firms are modeled as a strategic game. In this game, firms weigh the costs and benefits of establishing a relationship with other firms and form ties if their net payoffs are positive. We characterize the equilibrium networks as exponential random graphs (ERGM), and we estimate the firms' payoffs using a Bayesian approach. To demonstrate the usefulness of our approach, we apply the framework to a co-investment network of venture capital firms in the medical device industry. The equilibrium framework allows researchers to draw economic interpretation from parameter estimates of the ERGM Model. We learn that firms rely on their joint partners (transitivity) and prefer to form ties with firms similar to themselves (homophily). These results hold after controlling for the interdependence among ties. Another, critical advantage of a structural approach is that it allows us to simulate the effects of economic shocks or policy counterfactuals. We test two such policy shocks, namely, firm entry and regulatory change. We show how new firms' entry or a regulatory shock of minimum capital requirements increase the co-investment network's density and clustering.
    Date: 2021–05–05
  11. By: Olaizola, Norma; Valenciano, Federico
    Abstract: We study a connections model where the strength of a link depends on the amount invested in it and is determined by an increasing strictly concave function. The revenue from investments in links is the information that the nodes receive through the network. First, the structures of efficient networks are characterized, and conditions for optimal investments constrained to supporting a given network are obtained. Second, assuming that links are the result of investments by the node-players involved, there is the question of stability. We introduce and characterize a notion of marginal equilibrium weaker than that of Nash equilibrium, and identify different marginally stable structures. Efficiency and stability are shown to be incompatible, but partial subsidizing is shown to be able to bridge the gap.
    Keywords: Networks, Connections model, Decreasing returns, Efficiency, Stability.
    JEL: A14 C72 D85
    Date: 2020–10–28
  12. By: Bailey, Michael; Johnston, Drew; Koenen, Martin; Kuchler, Theresa; Russel, Dominic; Ströbel, Johannes
    Abstract: We explore how social network exposure to COVID-19 cases shapes individuals' social distancing behavior during the early months of the ongoing pandemic. We work with de-identified data from Facebook to show that U.S. users whose friends live in areas with worse coronavirus outbreaks reduce their mobility more than otherwise similar users whose friends live in areas with smaller outbreaks. The effects are quantitatively large: a one standard deviation increase in friend-exposure to COVID-19 cases early in the pandemic results in a 1.2 percentage point increase in the probability that an individual stays home on a given day. As the pandemic progresses, changes in friend-exposure drive changes in social distancing behavior. Given the evolving nature and geography of the pandemic --- and hence friend-exposure --- these results rule out many alternative explanations for the observed relationships. We also analyze data on public posts and membership in groups advocating to "reopen" the economy to show that our findings can be explained by friend-exposure raising awareness about the risks of the disease and inducing individuals to participate in mitigating public health behavior.
    Keywords: COVID-19; peer effects; Social distancing; Social Networks
    JEL: I0
    Date: 2020–12
  13. By: Guido M. Kuersteiner; Ingmar R. Prucha; Ying Zeng
    Abstract: We study linear peer effects models where peers interact in groups, individual's outcomes are linear in the group mean outcome and characteristics, and group effects are random. Our specification is motivated by the moment conditions imposed in Graham 2008. We show that these moment conditions can be cast in terms of a linear random group effects model and lead to a class of GMM estimators that are generally identified as long as there is sufficient variation in group size. We also show that our class of GMM estimators contains a Quasi Maximum Likelihood estimator (QMLE) for the random group effects model, as well as the Wald estimator of Graham 2008 and the within estimator of Lee 2007 as special cases. Our identification results extend insights in Graham 2008 that show how assumptions about random group effects as well as variation in group size can be used to overcome the reflection problem in identifying peer effects. Our QMLE and GMM estimators can easily be augmented with additional covariates and are valid in situations with a large but finite number of different group sizes. Because our estimators are general moment based procedures, using instruments other than binary group indicators in estimation is straight forward. Monte-Carlo simulations show that the bias of the QMLE estimator decreases with the number of groups and the variation in group size, and increases with group size. We also prove the consistency and asymptotic normality of the estimator under reasonable assumptions.
    Date: 2021–05
  14. By: Eric Auerbach; Max Tabord-Meehan
    Abstract: We propose a new unified framework for causal inference when outcomes depend on how agents are linked in a social or economic network. Such network interference describes a large literature on treatment spillovers, social interactions, social learning, information diffusion, social capital formation, and more. Our approach works by first characterizing how an agent is linked in the network using the configuration of other agents and connections nearby as measured by path distance. The impact of a policy or treatment assignment is then learned by pooling outcome data across similarly configured agents. In the paper, we propose a new nonparametric modeling approach and consider two applications to causal inference. The first application is to testing policy irrelevance/no treatment effects. The second application is to estimating policy effects/treatment response. We conclude by evaluating the finite-sample properties of our estimation and inference procedures via simulation.
    Date: 2021–05
  15. By: Baqaee, David Rezza; Farhi, Emmanuel
    Abstract: How do supply and demand shocks, like the ones caused by Covid-19, interact with complex production networks? In this note, we consider a stripped-down version of the model presented in Baqaee and Farhi (2020). Despite its simplicity, the model we present allows for an arbitrary input-output network, complementarities in both consumption and production, incomplete markets, downward nominal wage rigidity, and a zero-lower bound on interest rates. Nevertheless, despite allowing for these realistic ingredients, this model has a very stark property: namely, factor income shares at the initial equilibrium are global sufficient statistics for the input-output network. This irrelevance result clarifies what assumptions must be broken if the production network is to play a role in shock propagation.
    Keywords: complementarities; COVID-19; Downward wage rigidity; irrelevance; production networks; Supply Chains
    JEL: E0 E1 E4
    Date: 2021–01
  16. By: A. Fronzetti Colladon; E. Remondi
    Abstract: This research explores the opportunities for the application of network analytic techniques to prevent money laundering. We worked on real world data by analyzing the central database of a factoring company, mainly operating in Italy, over a period of 19 months. This database contained the financial operations linked to the factoring business, together with other useful information about the company clients. We propose a new approach to sort and map relational data and present predictive models, based on network metrics, to assess risk profiles of clients involved in the factoring business. We find that risk profiles can be predicted by using social network metrics. In our dataset, the most dangerous social actors deal with bigger or more frequent financial operations; they are more peripheral in the transactions network; they mediate transactions across different economic sectors and operate in riskier countries or Italian regions. Finally, to spot potential clusters of criminals, we propose a visual analysis of the tacit links existing among different companies who share the same owner or representative. Our findings show the importance of using a network-based approach when looking for suspicious financial operations and potential criminals.
    Date: 2021–05

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