nep-net New Economics Papers
on Network Economics
Issue of 2020‒02‒10
fourteen papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Targeting in social networks with anonymized information By Francis Bloch; Shaden Shabayek
  2. Modeling Economic Networks with Firm-to-Firm Wire Transfers By Thiago C. Silva; Diego R. Amancio; Benjamin M. Tabak
  3. A game of hide and seek in networks By Francis Bloch; Bhaskar Dutta; Marcin Dziubinski
  4. Private debt renegotiation and financial institutions' network By Christophe GODLEWSKI; Bulat SANDITOV
  5. Network VAR models to Measure Financial Contagion By Daniel Felix Ahelegbey; Paolo Giudici; Shatha Qamhieh Hashem
  6. The digital layer: How innovative firms relate on the web By Krüger, Miriam; Kinne, Jan; Lenz, David; Resch, Bernd
  7. The network paradigm as a modeling tool in regional economy: the case of interregional commuting in Greece By Dimitrios Tsiotas; Labros Sdrolias; Dimitrios Belias
  8. Peer Effects in Academic Research: Senders and Receivers By Clément Bosquet; Pierre-Philippe Combes; Emeric Henry; Thierry Mayer
  9. Measuring the Input Rank in Global Supply Networks By Armando Rungi; Loredana Fattorini; Kenan Huremovic
  10. Reciprocal Lending Relationships Between Financial Conglomerates: Evidence from the Mexican Repo Market By Cañon, C; Flórez, J.H; Gómez, K
  11. Monetary Dynamics in a Network Economy By Antoine Mandel; Vipin Veetil
  12. Segregation with Social Linkages: Evaluating Schelling's Model with Networked Individuals By Roy Cerqueti; Luca De Benedictis; Valerio Leone Sciabolazza
  13. Anti-conformism in the threshold model of collective behavior By Michel Grabisch; Fen Li
  14. Knowledge Graphs for Innovation Ecosystems By Alberto Tejero; Victor Rodriguez-Doncel; Ivan Pau

  1. By: Francis Bloch; Shaden Shabayek
    Abstract: This paper studies whether a planner who only has information about the network topology can discriminate among agents according to their network position. The planner proposes a simple menu of contracts, one for each location, in order to maximize total welfare, and agents choose among the menu. This mechanism is immune to deviations by single agents, and to deviations by groups of agents of sizes 2, 3 and 4 if side-payments are ruled out. However, if compensations are allowed, groups of agents may have an incentive to jointly deviate from the optimal contract in order to exploit other agents. We identify network topologies for which the optimal contract is group incentive compatible with transfers: undirected networks and regular oriented trees, and network topologies for which the planner must assign uniform quantities: single root and nested neighborhoods directed networks.
    Date: 2020–01
  2. By: Thiago C. Silva; Diego R. Amancio; Benjamin M. Tabak
    Abstract: We study a novel economic network comprised of wire transfers (electronic payment transactions) among the universe of firms in Brazil (6.2 million firms). We construct a directed and weighted network in which vertices represent cities and edges connote pairwise economic dependence between cities. Each city (vertex) represents the collection of all firms within that city. Edge weights are modeled by the total amount of wire transfers that arise due to business transactions between firms localized at different cities. The rationale is that the more they transact with each other, the more dependent they become in the economic sense. We find a high degree of economic integration among cities in the trade network, which is consistent with the high degree of specialization found across Brazilian cities. We are able to identify which cities have a dominant role in the entire supply chain process using centrality network measures. We find that the trade network has a disassortative mixing pattern, which is consistent with the power-law shape of the firm size distribution in Brazil. After the Brazilian recession in 2014, we find that the disassortativity becomes even stronger as a result of the death of many small firms and the consequent concentration of economic flows on large firms. Our results suggest that recessions have a large impact on the trade network with meaningful and heterogeneous economic consequences across municipalities.
    Date: 2020–01
  3. By: Francis Bloch; Bhaskar Dutta; Marcin Dziubinski
    Abstract: We propose and study a strategic model of hiding in a network, where the network designer chooses the links and his position in the network facing the seeker who inspects and disrupts the network. We characterize optimal networks for the hider, as well as equilibrium hiding and seeking strategies on these networks. We show that optimal networks are either equivalent to cycles or variants of a core-periphery networks where every node in the periphery is connected to a single node in the core.
    Date: 2020–01
  4. By: Christophe GODLEWSKI (LaRGE Research Center, Université de Strasbourg); Bulat SANDITOV (Université Paris-Saclay, Univ Evry, IMT-BS, LITEM)
    Abstract: We study the influence of financial institutions’ network on private debt renegotiation outside of distress. Lenders with a network-central position have access to superior private information, are more experienced and trustworthy and have a greater reputational capital. Using a large sample of more than 10.000 loans issued in 25 European countries we find that network-central lenders have a significant influence on the renegotiation process. Such lenders increase the likelihood of renegotiation, the number of renegotiation rounds, and the number of amendments to the loan agreement. Our findings survive multiple robustness checks and confirm that access to superior information, greater experience, reputation, and trust encourages private debt renegotiation.
    Keywords: financial contracts, bank loan, renegotiation, syndicated lending, social network analysis, lender network, lender centrality.
    JEL: G21 G24 G32 G34
    Date: 2020
  5. By: Daniel Felix Ahelegbey (Università di Pavia); Paolo Giudici (Università di Pavia); Shatha Qamhieh Hashem (An-Najah National University)
    Abstract: Financial contagion among countries can arise from different channels, the most important of which are financial markets and bank lending. The paper aims to build an econometric network approach to understand the extent to which contagion spillovers (from one country to another) arise from financial markets, from bank lending, or from both. To achieve this aim we consider a model specification strategy which combines Vector Autoregressive models with network models. The paper contributes to the contagion literature with a model that can consider bank exposures and financial market prices, jointly and not only separately. From an empirical viewpoint, our results show that both bilateral exposures and market prices act as contagion channels in the transmission of shocks arising from a country to international financial markets. While the impact of the former is more stable in time, the latter is more volatile and reacts to a wider variety of events.
    Keywords: Financial Contagion,Network Models,VAR,Bank Lending,Financial Markets
    JEL: C01 C32 G01 G12 G21
    Date: 2020–01
  6. By: Krüger, Miriam; Kinne, Jan; Lenz, David; Resch, Bernd
    Abstract: In this paper, we introduce the concept of a Digital Layer to empirically investigate inter-firm relations at any geographical scale of analysis. The Digital Layer is created from large-scale, structured web scraping of firm websites, their textual content and the hyperlinks among them. Using text-based machine learning models, we show that this Digital Layer can be used to derive meaningful characteristics for the over seven million firm-to-firm relations, which we analyze in this case study of 500,000 firms based in Germany. Among others, we explore three dimensions of relational proximity: (1) Cognitive proximity is measured by the similarity between firms' website texts. (2) Organizational proximity is measured by classifying the nature of the firms' relationships (business vs. non-business) using a text-based machine learning classification model. (3) Geographical proximity is calculated using the exact geographic location of the firms. Finally, we use these variables to explore the differences between innovative and non-innovative firms with regard to their location and relations within the Digital Layer. The firm-level innovation indicators in this study come from traditional sources (survey and patent data) and from a novel deep learning-based approach that harnesses firm website texts. We find that, after controlling for a range of firm-level characteristics, innovative firms compared to non-innovative firms maintain more numerous relationships and that their partners are more innovative than partners of non-innovative firms. Innovative firms are located in dense areas and still maintain relationships that are geographically farther away. Their partners share a common knowledge base and their relationships are business-focused. We conclude that the Digital Layer is a suitable and highly cost-efficient method to conduct large-scale analyses of firm networks that are not constrained to specific sectors, regions, or a particular geographical level of analysis. As such, our approach complements other relational datasets like patents or survey data nicely.
    Keywords: Web Mining,Innovation,Proximity,Network,Natural Language Processing
    JEL: O30 R10 C80
    Date: 2020
  7. By: Dimitrios Tsiotas; Labros Sdrolias; Dimitrios Belias
    Abstract: Network Science is an emerging discipline using the network paradigm to model communication systems as pair-sets of interconnected nodes and their linkages (edges). This paper applies this paradigm to study an interacting system in regional economy consisting of daily road transportation flows for labor purposes, the so-called commuting phenomenon. In particular, the commuting system in Greece including 39 non-insular prefectures is modeled into a complex network and it is studied using measures and methods of complex network analysis and empirical techniques. The study aims to detect the structural characteristics of the Greek interregional commuting network (GCN) and to interpret how this network is related to the regional development. The analysis highlights the effect of the spatial constraints in the structure of the GCN, it provides insights about the major road transport projects constructed the last decade, and it outlines a populationcontrolled (gravity) pattern of commuting, illustrating that high-populated regions attract larger volumes of the commuting activity, which consequently affects their productivity. Overall, this paper highlights the effectiveness of complex network analysis in the modeling of systems of regional economy, such as the systems of spatial interaction and the transportation networks, and it promotes the use of the network paradigm to the regional research.
    Date: 2020–01
  8. By: Clément Bosquet (Spatial Economic Research Center); Pierre-Philippe Combes (Département d'économie); Emeric Henry (Département d'économie); Thierry Mayer (Département d'économie)
    Abstract: Using an instrument based on a national contest in France determining researchers’ location, we find evidence of peer effects in academia, when focusing on precise groups of senders (producing the spillovers) and receivers (benefiting from the spillovers), defined based on field of specialisation, gender and age. These peer effects are shown to exist even outside formal co-authorship relationships. Furthermore, the match between the characteristics of senders and receivers plays a critical role. In particular, men benefit a lot from peer effects provided by men, while all other types of gender combinations produce spillovers twice as small.
    Keywords: Economics of Science; Peer Effects; Research Productivity; Gender Publication Gap
    JEL: I23 J16 J24
    Date: 2019–11
  9. By: Armando Rungi; Loredana Fattorini; Kenan Huremovic
    Abstract: In this paper, we introduce the Input Rank as a measure to study the organization of global supply networks at the firm level. We model the case of a firm that needs assessing the technological relevance of each direct and indirect supplier on a network-like production function with labor and intermediate inputs. In our framework, an input is technologically more relevant if a shock on that upstream market can hit harder the marginal costs of a downstream buyer, considering the topology of the supply structure. A higher labor intensity at each stage buffers the transmission of upstream shocks in the network. In addition, we provide for the possibility that producers have limited knowledge of inputs in the supply network, hence they can underestimate the relevance of more distant inputs. After applications, the Input Rank returns a matrix of technological centralities that order any direct or indirect input for a representative firm in any output industry. We compute the Input Rank on U.S. and world input-output tables. Finally, we test how it correlates with choices of vertical integration made by 20,489 U.S. parent companies controlling 154,836 affiliates worldwide. We find that a higher Input Rank is positively associated with higher odds that that input is vertically integrated, relatively more when final demand is elastic. A supplier's Input Rank remains a significant predictor of a firm's decision to integrate even after controlling for the relative positions on upstreamness(downstreamness) segments.
    Date: 2020–01
  10. By: Cañon, C; Flórez, J.H; Gómez, K
    Abstract: This paper examines the reciprocal lending between Financial Conglomerates in the repo market to better understand both what motivates powerful firms to engage in this type of contemporaneous crossfunding relationships, and, on the other hand, some of the implications that such reciprocal transactions may entail for the agents involved and for the market as a whole. In particular, in terms of the implications we focus on two dimensions: first, the potential effects that reciprocal lending has on the market power of FCs and the competitiveness of the repo market for mutual funds and second, the potential implications that frequent and stable reciprocal lending can have in terms of the industry’s systemic risk. Using transaction-level data from the Mexican repo market, we show that reciprocal lending between financial conglomerates is mutually beneficial as it reduces search costs for borrowers and mitigates credit risk concerns for lenders. Further, we find that reciprocal lending favors market concentration of the repo lending in a few powerful funds and increases fund market power. Finally, we find that reciprocal lending also leads to centrality within the financial network and increases the dependence between the parties involved. Interestingly, a higher intensity of reciprocal lending can harmful, but this does not necessarily deteriorates financial stability.
    Keywords: Reciprocal lending, collateralized money market, repo, banks, mutual funds, assetmanagers, market power, financial stability
    JEL: G01 G11 G21 G23 G28 L16 L22 L4
    Date: 2020–02–03
  11. By: Antoine Mandel (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Panthéon-Sorbonne, PSE - Paris School of Economics); Vipin Veetil (IIT Madras - Indian Institute of Technology Madras)
    Abstract: We develop a tractable model of out-of-equilibrium dynamics in a general equilibrium economy with cash-in-advance constraints. The dynamics emerge from local interactions between firms governed by the production network underlying the economy. We analytically characterise the influence of network structure on the propagation of monetary shocks. In the long run, the model converges to general equilibrium and the quantity theory of money holds. In the short run, monetary shocks propagate upstream via nominal demand changes and downstream via real supply changes. Lags in the evolution of supply and demand at the micro level can give rise to arbitrary dynamics of the distribution of prices. Our model explains the long standing Price Puzzle: a temporary rise in the price level in response to monetary contractions. The Price Puzzle emerges under two assumptions about downstream firms: they are disproportionally affected by monetary contractions and they account for a sufficiently small share of the wage bill. Empirical evidence supports the two assumptions for the US economy. Our model calibrated to the US economy using a data set of more than fifty thousand firms generates the empirically observed magnitude of the price level rise after monetary contractions.
    Abstract: Nous proposons un modèle de la dynamique hors-équilibre dans une économie en réseau où les agents sont soumis à des contraintes financières. Nous étudions la propagation des chocs de politique monétaire dans ce cadre. Nous démontrons notamment que le "price puzzle" émerge dans ce cadre du fait des délais dans la propagation des chocs.
    Keywords: Price Puzzle,Production Network,Money,Monetary Non-Neutrality,Out-Of-Equilibrium dynamics,Réseaux de production,dynamique hors-équilibre
    Date: 2019–10
  12. By: Roy Cerqueti; Luca De Benedictis; Valerio Leone Sciabolazza
    Abstract: This paper generalizes the original Schelling (1969, 1971a,b, 2006) model of racial and residential segregation to a context of variable externalities due to social linkages. In a setting in which individuals' utility function is a convex combination of a heuristic function a la Schelling, of the distance to friends, and of the cost of moving, the prediction of the original model gets attenuated: the segregation equilibria are not the unique solutions. While the cost of distance has a monotonic pro-status-quo effect, equivalent to that of models of migration and gravity models, if friends and neighbours are formed following independent processes the location of friends in space generates an externality that reinforces the initial configuration if the distance to friends is minimal, and if the degree of each agent is high. The effect on segregation equilibria crucially depends on the role played by network externalities.
    Date: 2020–01
  13. By: Michel Grabisch (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Fen Li (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We provide a detailed study of the threshold model, where both conformist and anti-conformist agents coexist. Our study bears essentially on the convergence of the opinion dynamics in the society of agents, i.e., finding absorbing classes, cycles, etc. Also, we are interested in the existence of cascade effects, as this may constitute a undesirable phenomenon in collective behavior. We divide our study into two parts. In the first one, we basically study the threshold model supposing a fixed complete network, where every one is connected to every one, like in the seminal work of Granovetter. We study the case of a uniform distribution of the threshold, of a Gaussian distribution, and finally give a result for arbitrary distributions, supposing there is one type of anti-conformist. In a second-part, the graph is no more complete and we suppose that the neighborhood of an agent is random, drawn at each time step from a distribution. We distinguish the case where the degree (number of links) of an agent is fixed, and where there is an arbitrary degree distribution. We show the existence of cascades and that for most societies, the opinion converges to a chaotic situation.
    Abstract: Nous effectuons une étude détaillée du modèle à seuil, où des agents conformistes et anti-conformistes coexistent. Notre étude porte essentiellement sur la convergence de la dynamique d'opinion dans la société des agents, i.e., sur les classes absorbantes, cycles, etc. Nous sommes également intéressés par l'existence d'effets de cascade, phénomènes indésirables dans le comportement collectif. Nous divisons notre étude en deux parties. Dans la première, nous étudions le modèle à seuil en supposant un réseau complet fixé, comme dans les travaux de Granovetter. Nous étudions le cas de la distribution uniforme, de la distribution gaussienne, et nous donnons enfin un résultat pour le cas général avec un type d'anti-conformiste. Dans la deuxième partie, le graph n'est plus complet et nous supposons que le voisinage d'un agent est aléatoire, tiré à chaque étape d'une distribution. Nous distinguons le cas où le degré (le nombre de liens) d'un agent est fixé et où il y a une distribution quelconque pour le degré. Nous montrons l'existence de cascades et le fait que pour la plupart des sociétés, l'opinion converge vers une situation chaotique.
    Keywords: threshold model,anti-conformism,absorbing class,opinion dynamics,modèle à seuil,anti-conformisme,classe absorbante,dynamique d'opinion
    Date: 2019–10
  14. By: Alberto Tejero; Victor Rodriguez-Doncel; Ivan Pau
    Abstract: Innovation ecosystems can be naturally described as a collection of networked entities, such as experts, institutions, projects, technologies and products. Representing in a machine-readable form these entities and their relations is not entirely attainable, due to the existence of abstract concepts such as knowledge and due to the confidential, non-public nature of this information, but even its partial depiction is of strong interest. The representation of innovation ecosystems incarnated as knowledge graphs would enable the generation of reports with new insights, the execution of advanced data analysis tasks. An ontology to capture the essential entities and relations is presented, as well as the description of data sources, which can be used to populate innovation knowledge graphs. Finally, the application case of the Universidad Politecnica de Madrid is presented, as well as an insight of future applications.
    Date: 2020–01

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