nep-net New Economics Papers
on Network Economics
Issue of 2021‒05‒24
eighteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Binary Outcomes and Linear Interactions By Boucher, Vincent; Bramoullé, Yann
  2. Key Sectors in Endogeneous Growth By Huang, Jingong; Zenou, Yves
  3. When a coauthor joins an editorial board By Lorenzo Ductor; Bauke Visser
  4. Production and financial networks in interplay: Crisis evidence from supplier-customer and credit registers By Jiménez, Gabriel; Kenan, Huremovic; Moral-Benito, Enrique; Peydró, José Luis; Vega-Redondo, Fernando
  5. Abstentions and Social Networks in Congress By Battaglini, Marco; Leone Sciabolazza, Valerio; Patacchini, Eleonora
  6. On the optimal control of interbank contagion in the euro area banking system By Fukker, Gábor; Kok, Christoffer
  7. Efficiency and stability in the connections model with heterogeneous node By Olaizola, Norma; Valenciano, Federico
  8. Stock Market Spillovers via the Global Production Network: Transmission of U.S. Monetary Policy By di Giovanni, Julian; Hale, Galina B
  9. Multi-Level Parallel Production Networks By Antonio Peyrache; Maria C. A. Silva
  10. Deep Graph Convolutional Reinforcement Learning for Financial Portfolio Management -- DeepPocket By Farzan Soleymani; Eric Paquet
  11. Social Externalities and Economic Analysis By Fleurbaey, Marc; Kanbur, Ravi; Viney, Brody
  12. Learning Financial Network with Focally Sparse Structure By Victor Chernozhukov; Chen Huang; Weining Wang
  13. The Impact of Peers on Academic Performance: Theory and Evidence from a Natural Experiment By Diego Carrasco-Novoa; Sandro D´ıez-Amigo; Shino Takayama
  14. Industrial Clusters, Networks and Resilience to the Covid-19 Shock in China By Dai, Ruochen; Mookherjee, Dilip; Quan, Yingyue; Zhang, Xiaobo
  15. Changes in mobility and socioeconomic conditions in Bogotá city during the COVID-19 outbreak By Marcos Deuñas; Mercedes Campi; Luis Olmos
  16. Using social network and semantic analysis to analyze online travel forums and forecast tourism demand By A Fronzetti Colladon; B Guardabascio; R Innarella
  17. Network Centrality and Managerial Market Timing Ability By Evgeniou, Theodoros; Peress, Joël; Vermaelen, Theo; Yue, Ling
  18. Social Networks and Job Referrals in Recruitment By Marie Lalanne

  1. By: Boucher, Vincent; Bramoullé, Yann
    Abstract: Heckman and MaCurdy (1985) first showed that binary outcomes are compatible with linear econometric models of interactions. This key insight was unduly discarded by the literature on the econometrics of games. We consider general models of linear interactions in binary outcomes that nest linear models of peer effects in networks and linear models of entry games. We characterize when these models are well defined. Errors must have a specific discrete structure. We then analyze the models' game-theoretic microfoundations. Under complete information and linear utilities, we characterize the preference shocks under which the linear model of interactions forms a Nash equilibrium of the game. Under incomplete information and independence, we show that the linear model of interactions forms a Bayes-Nash equilibrium if and only if preference shocks are iid and uniformly distributed. We also obtain conditions for uniqueness. Finally, we propose two simple consistent estimators. We revisit the empirical analyses of teenage smoking and peer effects of Lee, Li, and Lin (2014) and of entry into airline markets of Ciliberto and Tamer (2009). Our reanalyses showcase the main interests of the linear framework and suggest that the estimations in these two studies suffer from endogeneity problems.
    Keywords: Binary Outcomes; Econometrics of Games; Linear Probability Model; peer effects
    Date: 2020–11
  2. By: Huang, Jingong; Zenou, Yves
    Abstract: This paper develops a multi-sector endogenous growth model that includes an innovation network, which captures intrasectoral as well as heterogeneous intersectoral knowledge flows. We analyze the importance of sectors (nodes) and directed knowledge linkages (edges) in the innovation network by their contribution to the growth of knowledge in this economy. We show that the growth rate of knowledge is equal to the spectral radius of the innovation network. We also demonstrate that a sector's importance to growth (``key sectors'') is related to its positions in both the downstream and upstream technology network. Finally, the importance of a knowledge linkage is characterized by both the upstream centrality of its source sector, the downstream centrality of its target sector and the strength of knowledge flows from the source sector to the target sector.
    Keywords: Endogenous Growth; innovation networks; Key players
    JEL: D85 E2 O4
    Date: 2020–09
  3. By: Lorenzo Ductor (University of Granada); Bauke Visser (Erasmus University Rotterdam)
    Abstract: Using novel and large-scale data at the individual level, we find that an author publishes more articles when a coauthor joins an editorial board, both in the "coauthor's'" journal and in other journals. This effect is larger, the less experienced the author is, and disappears quickly once the coauthor leaves the journal's board. Of the hypotheses that we consider to explain these patterns, the signalling hypothesis is a strong contender. It argues that the temporary increase in status of the coauthor improves the plight of the author as it improves the inference that editorial boards make about the author's underlying quality. Only the favoritism hypothesis can explain that, especially at journals with low board turnover, articles published during a coauthor's stint on the editorial board receive less citations than articles published during other years.
    Keywords: editorial boards, networks, collaboration, coauthor
    JEL: A11 A14 D71 I26 J44 O30
    Date: 2021–05–17
  4. By: Jiménez, Gabriel; Kenan, Huremovic; Moral-Benito, Enrique; Peydró, José Luis; Vega-Redondo, Fernando
    Abstract: We show that bank shocks originating in the financial sector propagate upstream and downstream along the production network and triple the impact of direct bank shocks. Our identification relies on the universe of both supplier-customer transactions and bank loans in Spain, a standard operationalization of credit-supply shocks during the 2008-09 global crisis, and the proposed theoretical framework. The impact on real effects is strong, and similarly so, when considering: (i) direct bank shocks to firms versus first-order interim contagion; (ii) first-order versus higher-order network effects; (iii) downstream versus upstream propagation; (iv) firm-specific versus economy-wide shocks. Market concentration amplifies these effects.
    Keywords: credit supply; networks; real effects of finance; shock propagation; Supply Chains
    JEL: D85 E44 E51 G01 G21
    Date: 2020–09
  5. By: Battaglini, Marco; Leone Sciabolazza, Valerio; Patacchini, Eleonora
    Abstract: We study the extent to which personal connections among legislators influence abstentions in the U.S. Congress. Our analysis is conducted by observing representatives' abstention for the universe of roll call votes held on bills in the 109th-113th Congresses. Our results show that a legislator's propensity to abstain increases when the majority of his or her alumni connections abstains, even after controlling for other well-known predictors of abstention choices and a vast set of fixed effects. We further reveal that a legislator is more prone to abstain than to take sides when the demands from personal connections conflict with those of the legislator's party.
    Keywords: abstention; alumni networks; Social Networks; U.S. Congress
    JEL: D72 D85
    Date: 2020–09
  6. By: Fukker, Gábor; Kok, Christoffer
    Abstract: In this paper we present a methodology of model-based calibration of additional capital needed in an interconnected financial system to minimize potential contagion losses. Building on ideas from combinatorial optimization tailored to controlling contagion in case of complete information about an interbank network, we augment the model with three plausible types of fire sale mechanisms. We then demonstrate the power of the methodology on the euro area banking system based on a network of 373 banks. On the basis of an exogenous shock leading to defaults of some banks in the network, we find that the contagion losses and the policy authority's ability to control them depend on the assumed fire sale mechanism and the fiscal budget constraint that may or may not restrain the policy authorities from infusing money to halt the contagion. The modelling framework could be used both as a crisis management tool to help inform decisions on capital/liquidity infusions in the context of resolutions and precautionary recapitalisations or as a crisis prevention tool to help calibrate capital buffer requirements to address systemic risks due to interconnectedness. JEL Classification: C61, D85, G01, G18, G21, G28, L14
    Keywords: contagion, fire sales, interbank networks, macroprudential policy, optimal control, stress testing
    Date: 2021–05
  7. By: Olaizola, Norma; Valenciano, Federico
    Abstract: This paper studies the connections model (Jackson and Wolinsky, 1996) when nodes may have different values. It is shown that efficiency is reached by a strongly hierarchical structure that we call strong NSG-networks: Nested Split Graph networks where the hierarchy or ranking of nodes inherent in any such network is consistent with the rank of nodes according to their value, perhaps leaving some of the nodes with the lowest values disconnected. A simple algorithm is provided for calculating these efficient networks. We also introduce a natural extension of pairwise stability assuming that players are allowed to agree on how the cost of each link is split and prove that stability in this sense for connected strong NSG-networks entails efficiency.
    Keywords: Networks, Connections model, Heterogeneity, Efficiency, Stability.
    JEL: A14 C72 D85
    Date: 2021–05–17
  8. By: di Giovanni, Julian; Hale, Galina B
    Abstract: We quantify the role of global production linkages in explaining spillovers of U.S. monetary policy shocks to stock returns of 54 sectors in 26 countries. We first present a conceptual framework based on a standard open-economy production network model that delivers a spillover pattern consistent with a spatial autoregression (SAR) process. We then use the SAR model to decompose the overall impact of U.S. monetary policy on stock returns into a direct and a network effect. We find that up to 80% of the total impact of U.S. monetary policy shocks on average country-sector stock returns are due to the network effect of global production linkages. We further show that U.S. monetary policy shocks have a direct impact predominantly on U.S. sectors and then propagate to the rest of the world through the global production network. Our results are robust to controlling for correlates of the global financial cycle, foreign monetary policy shocks, and to changes in variable definitions and empirical specifications.
    Keywords: asset prices; global production network; monetary policy shocks
    JEL: F10 F36 G15
    Date: 2020–10
  9. By: Antonio Peyrache (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia); Maria C. A. Silva (CEGE - Católica Porto Business School,)
    Abstract: Network Data Envelopment Analysis (DEA) has become a largely researched topic in the DEA literature. In this paper we consider one of the simplest network models: Parallel Network DEA models. We briefly review a large body of literature that relates to these network models. Then we proceed to discuss existing models and point out some of their pitfalls. Finally, we propose an approach that attempts to solve these pitfalls, recognising that when one computes a decision making unit (DMU) efficiency score and want to decompose it into the divisional/process efficiencies there is a component of allocative inefficiency. We develop our models at three levels of aggregation: the sub-unit (production division/process), the DMU (firm) and the industry. For each level we measure the inefficiency using the directional distance function and we relate the different levels to each other by proposing a decomposition into exhaustive and mutually exclusive components. We illustrate the application of our models to the case of Portuguese hospitals and we also propose avenues for future research, since most of the topics addressed in this paper are not only related to Parallel network models but to general network structures.
    Keywords: Data Envelopment Analysis; Multi-Level Networks; Parallel Networks; Directional Distance Function; Efficiency.
    Date: 2021–02
  10. By: Farzan Soleymani; Eric Paquet
    Abstract: Portfolio management aims at maximizing the return on investment while minimizing risk by continuously reallocating the assets forming the portfolio. These assets are not independent but correlated during a short time period. A graph convolutional reinforcement learning framework called DeepPocket is proposed whose objective is to exploit the time-varying interrelations between financial instruments. These interrelations are represented by a graph whose nodes correspond to the financial instruments while the edges correspond to a pair-wise correlation function in between assets. DeepPocket consists of a restricted, stacked autoencoder for feature extraction, a convolutional network to collect underlying local information shared among financial instruments, and an actor-critic reinforcement learning agent. The actor-critic structure contains two convolutional networks in which the actor learns and enforces an investment policy which is, in turn, evaluated by the critic in order to determine the best course of action by constantly reallocating the various portfolio assets to optimize the expected return on investment. The agent is initially trained offline with online stochastic batching on historical data. As new data become available, it is trained online with a passive concept drift approach to handle unexpected changes in their distributions. DeepPocket is evaluated against five real-life datasets over three distinct investment periods, including during the Covid-19 crisis, and clearly outperformed market indexes.
    Date: 2021–05
  11. By: Fleurbaey, Marc; Kanbur, Ravi; Viney, Brody
    Abstract: This paper considers and assesses the concept of social externalities through human interdependence, in relation to the economic analysis of externalities in the tradition of Pigou and Arrow, including the analysis of the commons. It argues that there are limits to economic analysis. Our proposal is to enlarge the perspective and start thinking about a broader framework in which any pattern of influence of an agent or a group of agents over a third party, which is not mediated by any economic, social, or psychological mechanism guaranteeing the alignment of the marginal net private benefit with marginal net social benefit, can be attached the "externality" label and be scrutinized for the likely negative consequences that result from the divergence. These consequences may be significant given the many interactions between the social and economic realms, and the scope for spillovers and feedback loops to emerge. The paper also establishes a tentative and probably incomplete list of possible internalizing mechanisms for externalities under this broader framework, which includes: pricing and monetary incentives; altruism and solidarity; moral norms; reciprocity and mutual monitoring; centralized cooperative decision-making; and merger. There are clear reasons why the pricing mechanism is not appropriate in some cases. A more difficult question to answer is what factors determine which of the mechanisms is the appropriate one to rely on in a given sphere of relations and activities. The object of the paper is to encourage research and contributions from all the relevant disciplines of social sciences on the pervasive human interdependence that the notion of social externalities tries to capture.
    Keywords: Commons; Ethical Principles; Externalities; Human Interdependence; Internalizing Mechanisms; Social Externalities
    JEL: A12 A13 B31 D02 D62 D63 H23
    Date: 2020–08
  12. By: Victor Chernozhukov; Chen Huang; Weining Wang
    Abstract: This paper studies the estimation of network connectedness with focally sparse structure. We try to uncover the network effect with a flexible sparse deviation from a predetermined adjacency matrix. To be more specific, the sparse deviation structure can be regarded as latent or misspecified linkages. To obtain high-quality estimator for parameters of interest, we propose to use a double regularized high-dimensional generalized method of moments (GMM) framework. Moreover, this framework also facilitates us to conduct the inference. Theoretical results on consistency and asymptotic normality are provided with accounting for general spatial and temporal dependency of the underlying data generating processes. Simulations demonstrate good performance of our proposed procedure. Finally, we apply the methodology to study the spatial network effect of stock returns.
    Date: 2021–05
  13. By: Diego Carrasco-Novoa (School of Economics, University of Queensland, Brisbane, Australia); Sandro D´ıez-Amigo (Department of Economics, Massachusetts Institute of Technology); Shino Takayama (School of Economics, University of Queensland, Brisbane, Australia)
    Abstract: We introduce a flexible theoretical framework to model the mechanics of peer effects in education. Then we take advantage of a natural experiment in order to illustrate how the proposed model can be used to gain additional empirical insights from reduced-form econometric analysis. Leveraging the exogenous variation in peer characteristics generated by the random assignment of freshman college students to their first semester class groups, we observe a negative impact on academic performance of secondary schoolmate presence and concentration in the first semester college classroom, suggesting that in the study context socialization was in overall terms distractive, and that the group structure increased socialization for all students. We also find some evidence of a negative impact of higher average admission scores on academic performance, suggesting that in the study context the direct positive impact of peer mean ability on academic performance was more than eclipsed by the negative effect of higher peer mean ability on self-confidence. Observed peer effects generally persist throughout the duration of undergraduate studies.
    Date: 2021–04–29
  14. By: Dai, Ruochen; Mookherjee, Dilip; Quan, Yingyue; Zhang, Xiaobo
    Abstract: We examine how exposure of Chinese firms to the Covid-19 shock varied with a cluster index (measuring spatial agglomeration of firms in related industries) at the county level. Two data sources are used: entry flows of newly registered firms in the entire country, and an entrepreneur survey regarding operation of existing firms. Both show greater resilience in counties with a higher cluster index, after controlling for industry dummies and local infection rates, besides county and time dummies in the entry data. Reliance of clusters on informal entrepreneur hometown networks and closer proximity to suppliers and customers help explain these findings.
    Keywords: China; Clusters; COVID-19; firms; Social Networks
    JEL: D31 I3 J12 J16
    Date: 2020–10
  15. By: Marcos Deuñas (Universidad de Bogotá Jorge Tadeo Lozano); Mercedes Campi (Universidad de Buenos Aires/CONICET); Luis Olmos (University of California)
    Abstract: We analyze mobility changes following the implementation of containment measures aimed at mitigating the spread of COVID-19 in Bogot ´a, Colombia. We characterize the mobility network before and during the pandemic and analyze its evolution and changes between January and July 2020. We then link the observed mobility changes to socioeconomic conditions, estimating a gravity model to assess the e?ect of socioeconomic conditions on mobility flows. We observe an overall reduction in mobility trends, but the overall connectivity between di?erent areas of the city remains after the lockdown, reflecting the mobility network’s resilience. We find that the responses to lockdown policies depend on socioeconomic conditions. Before the pandemic, the population with better socioeconomic conditions shows higher mobility flows. Since the lockdown, mobility presents a general decrease, but the population with worse socioeconomic conditions shows lower decreases in mobility flows. We conclude deriving policy implications.
    Keywords: Mobility networks Poverty; Informality Socioeconomic strata COVID-19
    Date: 2020–11
  16. By: A Fronzetti Colladon; B Guardabascio; R Innarella
    Abstract: Forecasting tourism demand has important implications for both policy makers and companies operating in the tourism industry. In this research, we applied methods and tools of social network and semantic analysis to study user-generated content retrieved from online communities which interacted on the TripAdvisor travel forum. We analyzed the forums of 7 major European capital cities, over a period of 10 years, collecting more than 2,660,000 posts, written by about 147,000 users. We present a new methodology of analysis of tourism-related big data and a set of variables which could be integrated into traditional forecasting models. We implemented Factor Augmented Autoregressive and Bridge models with social network and semantic variables which often led to a better forecasting performance than univariate models and models based on Google Trend data. Forum language complexity and the centralization of the communication network, i.e. the presence of eminent contributors, were the variables that contributed more to the forecasting of international airport arrivals.
    Date: 2021–05
  17. By: Evgeniou, Theodoros; Peress, Joël; Vermaelen, Theo; Yue, Ling
    Abstract: We document that long-run excess returns following announcements of share buyback authorizations and insider purchases are a U-shape function of firm centrality in the input-output trade flow network. These results conform to a model of investors endowed with a large but finite capacity for analyzing firms. Additional links weaken insiders' informational advantage in peripheral firms (simple firms whose cash flows depend on few economic links) provided investors' capacity is large enough, but eventually amplify that advantage in central firms (firms with many links) due to investors' limited capacity. These findings shed light on the sources of managerial market timing ability.
    Keywords: Buybacks; insider trading; Market Efficiency; market timing; Network centrality
    JEL: G32 O32
    Date: 2020–09
  18. By: Marie Lalanne
    Abstract: This paper investigates whether using recommendations for recruitment reduce information asymmetries or allow the exchange of favors in the labor market of board directors. I use data on all directors of large listed US companies between 2004 and 2008. These are linked with extensive information on their social networks and detailed information on the referrals underpinning new independent board appointments. Compared to non-connected new directors, connected directors are 14% more likely to be referred by current board members with whom they share employment history. Predictions of a theoretical model allow me to further discriminate between information provision and favoritism in the use of such referrals for recruitment. Results show that referrals help select directors with higher ability, in particular the type of ability that is partially observed at the time of hiring.
    Keywords: social networks, job referrals, recruitment, board appointments, asymmetric information.
    JEL: M51 J44 D82
    Date: 2021

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