nep-net New Economics Papers
on Network Economics
Issue of 2020‒01‒13
twenty-two papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Equilibria and Systemic Risk in Saturated Networks By Leonardo Massai; Giacomo Como; Fabio Fagnani
  2. Divergence Network: Graphical calculation method of divergence functions By Nishiyama, Tomohiro
  3. Emergent hypercongestion in Vickrey bottleneck networks By Dario Frascaria; Neil Olver; Erik T. Verhoef
  4. Systemic liquidity contagion in the European interbank market By V. Macchiati; G. Brandi; G. Cimini; G. Caldarelli; D. Paolotti; T. Di Matteo
  5. Disentangling shock diffusion on complex networks: Identification through graph planarity By Sudarshan Kumar; Tiziana Di Matteo; Anindya S. Chakrabarti
  6. Horizontal mergers on platform markets: cost savings v. cross-group network effects? By Baranes, Edmond; Cortade, Thomas; Cosnita-Langlais, Andreea
  7. A percolation model for the emergence of the Bitcoin Lightning Network By Silvia Bartolucci; Fabio Caccioli; Pierpaolo Vivo
  8. Network Data By Bryan S. Graham
  9. Efficient Algorithms for Constructing Multiplex Networks Embedding By Zolnikov, Pavel; Zubov, Maxim; Nikitinsky, Nikita; Makarov, Ilya
  10. Overfunding and Signaling Effects of Herding Behavior in Crowdfunding By Svatopluk Kapounek; Zuzana Kucerová
  11. Platform competition and incumbency advantage under heterogeneous switching cost — exploring the impact of data portability By Siciliani, Paolo; Giovannetti, Emanuele
  12. Logical Differencing in Dyadic Network Formation Models with Nontransferable Utilities By Wayne Yuan Gao; Ming Li; Sheng Xu
  13. Network Determinants of Cross-Border Merger and Acquisition Decisions By Tatiana Didier; Sebastian Herrador; Magali Pinat
  14. Long-Distance Relationships and Media Selection By Paola Soto Herrera; Rudy Pugliese
  15. Gainers and Losers from Market Integration By Hans Gersbach; Hans Haller
  16. Nonlinear factor models for network and panel data By Mingli Chen; Ivan Fernandez-Val; Martin Weidner
  17. Partisan Selective Engagement: Evidence from Facebook By Marcel Garz; Jil Sörensen; Daniel F. Stone
  18. Interdependencies in the euro area derivatives clearing network: a multi-layer network approach By Rosati, Simonetta; Vacirca, Francesco
  19. Trade, migration, and the dynamics of spatial interaction By Gauthier, Nicolas
  20. Global networks, local specialisation and regional patterns of innovation By Andrea Ascani; Luca Bettarelli; Laura Resmini; Pierre-Alexandre Balland
  21. Kernel density estimation for undirected dyadic data By Bryan S. Graham; Fengshi Niu; James L. Powell
  22. Network Distance and Fatal Outcomes among Gunshot Wound Victims By Circo, Giovanni M; Wheeler, Andrew Palmer

  1. By: Leonardo Massai; Giacomo Como; Fabio Fagnani
    Abstract: We undertake a fundamental study of network equilibria modeled as solutions of fixed point of monotone linear functions with saturation nonlinearities. The considered model extends one originally proposed to study systemic risk in networks of financial institutions interconnected by mutual obligations and is one of the simplest continuous models accounting for shock propagation phenomena and cascading failure effects. We first derive explicit expressions for network equilibria and prove necessary and sufficient conditions for their uniqueness encompassing and generalizing several results in the literature. Then, we study jump discontinuities of the network equilibria when the exogenous flows cross a certain critical region consisting of the union of finitely many linear submanifolds of co-dimension 1. This is of particular interest in the financial systems context, as it shows that even small shocks affecting the values of the assets of few nodes, can trigger catastrophic aggregated loss to the system and cause the default of several agents.
    Date: 2019–12
  2. By: Nishiyama, Tomohiro
    Abstract: In this paper, we introduce directed networks called ``divergence network'' in order to perform graphical calculation of divergence functions. By using the divergence networks, we can easily understand the geometric meaning of calculation results and grasp relations among divergence functions intuitively.
    Date: 2018–10–26
  3. By: Dario Frascaria (VU Amsterdam); Neil Olver (London School of Economics and Political Science); Erik T. Verhoef (VU Amsterdam)
    Abstract: Hypercongestion - the phenomenon that higher traffic densities can reduce throughput - is well understood at the link level, but has also been observed in a macroscopic form at the level of traffic networks; for instance, in morning rush-hour traffic into a downtown core. In this paper, we show that macroscopic hypercongestion can occur as a purely emergent effect of dynamic equilibrium behaviour on a network, even if the underlying link dynamics (we consider Vickrey bottlenecks with spaceless vertical queues) do not exhibit hypercongestion.
    Keywords: Hypercongestion, Vickrey bottlenecks, Spaceless vertical queues, Arbitrary networks, Homogeneous users, Optimal (first-best) pricing
    JEL: D62 R41 R48
    Date: 2020–01–06
  4. By: V. Macchiati; G. Brandi; G. Cimini; G. Caldarelli; D. Paolotti; T. Di Matteo
    Abstract: Systemic liquidity risk, defined by the IMF as "the risk of simultaneous liquidity difficulties at multiple financial institutions", is a key topic in macroprudential policy and financial stress analysis. Specialized models to simulate funding liquidity risk and contagion are available but they require not only banks' bilateral exposures data but also balance sheet data with sufficient granularity, which are hardly available. Alternatively, risk analyses on interbank networks have been done via centrality measures of the underlying graph capturing the most interconnected and hence more prone to risk spreading banks. In this paper, we propose a model which relies on an epidemic model which simulate a contagion on the interbank market using the funding liquidity shortage mechanism as contagion process. The model is enriched with country and bank risk features which take into account the heterogeneity of the interbank market. The proposed model is particularly useful when full set of data necessary to run specialized models is not available. Since the interbank network is not fully available, an economic driven reconstruction method is also proposed to retrieve the interbank network by constraining the standard reconstruction methodology to real financial indicators. We show that the contagion model is able to reproduce systemic liquidity risk across different years and countries. This result suggests that the proposed model can be successfully used as a valid alternative to more complex ones.
    Date: 2019–12
  5. By: Sudarshan Kumar; Tiziana Di Matteo; Anindya S. Chakrabarti
    Abstract: Large scale networks delineating collective dynamics often exhibit cascading failures across nodes leading to a system-wide collapse. Prominent examples of such phenomena would include collapse on financial and economic networks. Intertwined nature of the dynamics of nodes in such network makes it difficult to disentangle the source and destination of a shock that percolates through the network, a property known as reflexivity. In this article, a novel methodology is proposed which combines vector autoregression model with an unique identification restrictions obtained from the topological structure of the network to uniquely characterize cascades. In particular, we show that planarity of the network allows us to statistically estimate a dynamical process consistent with the observed network and thereby uniquely identify a path for shock propagation from any chosen epicenter to all other nodes in the network. We analyze the distress propagation mechanism in closed loops giving rise to a detailed picture of the effect of feedback loops in transmitting shocks. We show usefulness and applications of the algorithm in two networks with dynamics at different time-scales: worldwide GDP growth network and stock network. In both cases, we observe that the model predicts the impact of the shocks emanating from the US would be concentrated within the cluster of developed countries and the developing countries show very muted response, which is consistent with empirical observations over the past decade.
    Date: 2020–01
  6. By: Baranes, Edmond; Cortade, Thomas; Cosnita-Langlais, Andreea
    Abstract: We study the impact of cost savings on the outcome of horizontal mergers between two-sided platforms. We consider four symmetrically differentiated platforms located equidistantly on the unit circle and competing in membership fees. Users on both sides single-home, and we allow for both positive and negative cross-group externalities. We find that the impact of merger cost savings on prices is generally not monotonic, and that synergies are necessary for horizontal platform mergers to be Pareto-improving. Furthermore, the merger may benefit users on one side while harming users on the opposite side, which raises some interesting questions for the enforcement of merger control on two-sided markets.
    Keywords: horizontal merger, two-sided markets, cost savings, indirect network effects, merger control
    JEL: D43 K21 L41
    Date: 2019–05
  7. By: Silvia Bartolucci; Fabio Caccioli; Pierpaolo Vivo
    Abstract: The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we explore how the distributional properties of the volume and size of transactions per user may impact its feasibility. The agents are all able to reciprocally transfer Bitcoins using the main blockchain and also - if economically convenient - to open a channel on the Lightning Network and transact "off chain". We base our approach on fitness-dependent network models: as in real life, a Lightning channel is opened with a probability that depends on the "fitness" of the concurring nodes, which in turn depends on wealth and volume of transactions. The emergence of a connected component is studied numerically and analytically as a function of the parameters, and the phase transition separating regions in the phase space where the Lightning Network is sustainable or not is elucidated. We characterize the phase diagram determining the minimal volume of transactions that would make the Lightning Network sustainable for a given level of fees or, alternatively, the maximal cost the Lightning ecosystem may impose for a given average volume of transactions. The model includes parameters that could be in principle estimated from publicly available data once the evolution of the Lighting Network will have reached a stationary operable state, and is fairly robust against different choices of the distributions of parameters and fitness kernels.
    Date: 2019–12
  8. By: Bryan S. Graham
    Abstract: Many economic activities are embedded in networks: sets of agents and the (often) rivalrous relationships connecting them to one another. Input sourcing by firms, interbank lending, scientific research, and job search are four examples, among many, of networked economic activities. Motivated by the premise that networks' structures are consequential, this chapter describes econometric methods for analyzing them. I emphasize (i) dyadic regression analysis incorporating unobserved agent-specific heterogeneity and supporting causal inference, (ii) techniques for estimating, and conducting inference on, summary network parameters (e.g., the degree distribution or transitivity index); and (iii) empirical models of strategic network formation admitting interdependencies in preferences. Current research challenges and open questions are also discussed.
    Date: 2019–12
  9. By: Zolnikov, Pavel; Zubov, Maxim; Nikitinsky, Nikita; Makarov, Ilya
    Abstract: Network embedding has become a very promising techniquein analysis of complex networks. It is a method to project nodes of anetwork into a low-dimensional vector space while retaining the structureof the network based on vector similarity. There are many methods ofnetwork embedding developed for traditional single layer networks. Onthe other hand, multilayer networks can provide more information aboutrelationships between nodes. In this paper, we present our random walkbased multilayer network embedding and compare it with single layerand multilayer network embeddings. For this purpose, we used severalclassic datasets usually used in network embedding experiments and alsocollected our own dataset of papers and authors indexed in Scopus.
    Keywords: Network embedding; Multi-layer network; Machine learning on graphs
    JEL: C45 I20
    Date: 2019–09–23
  10. By: Svatopluk Kapounek; Zuzana Kucerová
    Abstract: The paper employs a dynamic market-wide herding behavior measure of 117,166 lending-based campaigns in 119 online platforms in 37 countries that explores whether lenders follow each other in the whole crowdfunding market, within the groups of top platforms, within the specific category or platform, and within the specific category in the specific platform. We show that herding behavior plays an important signaling role in reducing opportunity costs if the auction does not receive enough monetary bids. Additionally, our threshold models identify significant herding behavior after funding goals are raised and highlight the controversial effects of signaling mechanisms on adverse selection in crowdfunding markets.
    Keywords: asymmetric information, crowdfunding, herding behavior, overfunding, peer-to-peer lending, signaling
    JEL: C55 G21
    Date: 2019
  11. By: Siciliani, Paolo (Bank of England and UCL Laws); Giovannetti, Emanuele (Anglia Ruskin University & Hughes Hall, University of Cambridge)
    Abstract: The paper develops a static model to explore how, under platform competition, heterogeneous levels of switching costs can give rise to an incumbency advantage. The key condition required for the coexistence of both platforms on the market, to have effective competition, relies on the relative strength of switching costs over the network effects. Only when switching costs are stronger than cross-group network benefits is market tipping avoided. The same condition also underpins the presence of a material incumbency advantage vis-à-vis the entrant platform. Therefore, regulatory intervention aimed at facilitating switching, for example by imposing data portability, might worsen entry condition as the incumbent platform is less accommodative. Besides the standard configuration with exogenous singlehoming, we also fully characterise the model with endogenous multihoming on both sides. Partial multihoming occurs only on one side, the one with comparatively lower switching costs. However, in contrast to the seminal ‘competition bottleneck’ model, on the opposite side, where singlehoming arises endogenously, agents face higher prices than under exogenous singlehoming. Therefore, the incumbent platform would normally opt for this regime, whereas we show that the entrant is basically indifferent between the two.
    Keywords: two-sided markets; platform competition; switching costs; multihoming
    JEL: L11 L13
    Date: 2019–12–20
  12. By: Wayne Yuan Gao; Ming Li; Sheng Xu
    Abstract: This paper considers a semiparametric model of dyadic network formation under nontransferable utilities (NTU). Such dyadic links arise frequently in real-world social interactions that require bilateral consent but by their nature induce additive non-separability. In our model we show how unobserved individual heterogeneity in the network formation model can be canceled out without requiring additive separability. The approach uses a new method we call logical differencing. The key idea is to construct an observable event involving the intersection of two mutually exclusive restrictions on the fixed effects, while these restrictions are as necessary conditions of weak multivariate monotonicity. Based on this identification strategy we provide consistent estimators of the network formation model under NTU. Finite-sample performance of our method is analyzed in a simulation study, and an empirical illustration using the risk-sharing network data from Nyakatoke demonstrates that our proposed method is able to obtain economically intuitive estimates.
    Date: 2020–01
  13. By: Tatiana Didier; Sebastian Herrador; Magali Pinat
    Abstract: This paper assesses whether cross-border M&A decisions exhibit network effects. We estimate exponential random graph models (ERGM) and temporal exponential random graph models (TERGM) to evaluate the determinants of cross-country M&A investments at the sectoral level. The results show that transitivity matters: a country is more likely to invest in a new destination if one of its existing partners has already made some investments there. In line with the literature on export platforms and informational barriers, we find a sizable impact of third country effects on the creation of new investments. This effect is sizable and larger than some of the more traditional M&A determinants, such as trade openness.
    Date: 2019–12–04
  14. By: Paola Soto Herrera (Rochester Institute of Technology); Rudy Pugliese (Rochester Institute of Technology)
    Abstract: The present study investigated long-distance relationships and media use. It surveyed individuals involved in long distance relationships to determine which media are most often used, whether they are more likely to use rich or lean media, and whether family, friends, and romantic partners differ in their selection of media. Instant Messaging, social media (Instagram, Facebook, Twitter, Snapchat), telephone (cellular, mobile, or landline), online video chat, online audio chat, SMS, and regular mail were the most popular media. Romantic partners were more likely than either family or friends to use Instant messaging, the telephone, audio chat, and video chat. Results provide support for Rich Media Theory within the context of long-distance relationships. Additional findings are presented.
    Keywords: media, long-distance relationships
    JEL: L82 D83 J24
    Date: 2019–10
  15. By: Hans Gersbach; Hans Haller
    Abstract: We compare integration of economic, matching and networking markets. There can be losers from integration in all three cases, but their relative numbers depend on the type of market. There can be many losers from integration of pure exchange economies. There are relatively few losers from integration of networking markets. In the matching case, the relative numbers tend to lie between those of the other two cases.
    Keywords: competitive exchange, matching theory, networks, market integration
    JEL: C78 D02 D85
    Date: 2019
  16. By: Mingli Chen (Institute for Fiscal Studies and Warwick); Ivan Fernandez-Val (Institute for Fiscal Studies and Boston University); Martin Weidner (Institute for Fiscal Studies and cemmap and UCL)
    Abstract: Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables, which include logit, probit, ordered probit and Poisson speci cations. We establish that fi xed effect estimators of model parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might suffer from incidental parameter bias. We show how models with factor structures can also be applied to capture important features of network data such as reciprocity, degree heterogeneity, homophily in latent variables and clustering. We illustrate this applicability with an empirical example to the estimation of a gravity equation of international trade between countries using a Poisson model with multiple factors.
    Keywords: Panel data, network data, interactive fixed effects, factor models, bias correction, incidental parameter problem, gravity equation
    Date: 2019–04–11
  17. By: Marcel Garz; Jil Sörensen; Daniel F. Stone
    Abstract: This study investigates the effects of variation in “congeniality” of news on Facebook user engagement (likes, shares, and comments). We compile an original data set of Facebook posts by 84 German news outlets on politicians that were investigated for criminal offenses from January 2012 to June 2017. We also construct an index of each outlet’s media slant by comparing the language of the outlet with that of the main political parties, which allows us to measure the congeniality of the posts. We find evidence that users engaged with congenial posts more than with uncongenial ones, especially in terms of likes. The within-outlet, within-topic design allows us to infer that the greater engagement with congenial news is likely driven by psychological and social factors, rather than a desire for accurate or otherwise instrumental information.
    Keywords: filter bubble, media bias, political immunity, social media, polarization
    JEL: D83 D91 L82
    Date: 2019
  18. By: Rosati, Simonetta; Vacirca, Francesco
    Abstract: The global nature of derivatives markets, and the presence of large key financial institutions trading in several markets across the globe, call for taking a “macro” view on the interconnections arising in the clearing network. Based on the analysis of derivatives transactions data reported under the EMIR Regulation we reconstruct the network of relationships in the centrally-cleared derivatives market and analyse its topology providing insight into its structural features. The centrally-cleared derivatives network is modelled in the form of a multiplex network where each layer is represented by a derivatives asset class market. In turn, each node represents a single counterparty in that market. On the basis of different centrality measures applied to the collapsed aggregate and to the multiplex network, the critical participants of the euro area centrally-cleared derivatives market are identified and their level of interconnectedness analysed. This paper provides insight on how the collected data pursuant to the EMIR regulation can be used to shed light on the complex network of interrelations underlying the financial markets. It provides indications on structural features of the euro area centrally-cleared derivatives market and discusses policy relevant implications and future applications. JEL Classification: G01, G15, G23
    Keywords: CCP, derivatives markets, EMIR data, interconnectedness, multiplex network
    Date: 2019–12
  19. By: Gauthier, Nicolas (University of Arizona)
    Abstract: Archaeological settlement patterns are the physical remains of complex webs of human decision-making and social interaction. Entropy-maximizing spatial interaction models are a means of building parsimonious models that average over much of this small-scale complexity, while maintaining key large-scale structural features. Dynamic social interaction models extend this approach by allowing archaeologists to explore the co-evolution of human settlement systems and the networks of interaction that drive them. Yet, such models are often imprecise, relying on generalized notions of settlement "influence" and "attractiveness" rather than concrete material flows of goods and people. Here, I present a dis-aggregated spatial interaction model that explicitly resolves trade and migration flows and their combined influence on settlement growth and decline. I explore how the balance of costs and benefits of each type of interaction influence long-term settlement patterns. I find trade flows are the strongest determinant of equilibrium settlement structure, and that migration flows play a more transient role in balancing site hierarchies. This model illustrates how the broad toolkit for spatial interaction modeling developed in geography and economics can increase the precision of quantitative theory building in archaeology, and provides a road-map for connecting mechanistic models to the empirical archaeological record.
    Date: 2019–09–26
  20. By: Andrea Ascani; Luca Bettarelli; Laura Resmini; Pierre-Alexandre Balland
    Abstract: A large academic consensus exists on the idea that successful innovative processes are geographically bounded within regions. Nevertheless, the ability of regions to capture and re-use external knowledge is also regarded as a fundamental element to sustain and refine the local profile of specialisation and competitiveness. The present article combines these views to investigate the sources of the regional innovation process, by analysing data on Italian regions over the period 2007-2012. We define regional external networks based on all the foreign subsidiaries of local multinational enterprises identifiable as global ultimate owners. Our main results suggest that both the internal specialisation and the outward networks can generate indigenous innovation, but the role of the networks varies substantially according to its density, its degree of complementarity with the specialisation profile, its geographical spread and the specific location of the foreign subsidiaries. Our results, then, support a view of the regional innovation as an interactive process whereby valuable knowledge resources are not only generated within the reach of the local economy, but they are also integrated with external inputs. This contrasts with recent anti-globalisation views according to which the increase in the foreign operations of national companies impoverishes the local economy.
    Keywords: outward foreign direct investment, innovation, specialisation, networks, relatedness
    JEL: O3 F23 R10 F60
    Date: 2020–01
  21. By: Bryan S. Graham (Institute for Fiscal Studies and University of California, Berkeley); Fengshi Niu (Institute for Fiscal Studies); James L. Powell (Institute for Fiscal Studies and University of California, Berkeley)
    Abstract: We study nonparametric estimation of density functions for undirected dyadic random variables (i.e., random variables de?ned for all unordered pairs of agents/nodes in a weighted network of order N). These random variables satisfy a local dependence property: any random variables in the network that share one or two indices may be dependent, while those sharing no indices in common are independent. In this setting, we show that density functions may be estimated by an application of the kernel estimation method of Rosenblatt (1956) and Parzen (1962). We suggest an estimate of their asymptotic variances inspired by a combination of (i) Newey’s (1994) method of variance estimation for kernel estimators in the “monadic” setting and (ii) a variance estimator for the (estimated) density of a simple network ?rst suggested by Holland & Leinhardt (1976). More unusual are the rates of convergence and asymptotic (normal) distributions of our dyadic density estimates. Speci?cally, we show that they converge at the same rate as the (unconditional) dyadic sample mean: the square root of the number, N, of nodes. This di?ers from the results for nonparametric estimation of densities and regres-sion functions for monadic data, which generally have a slower rate of convergence than their corresponding sample mean.
    Date: 2019–08–07
  22. By: Circo, Giovanni M (University of New Haven); Wheeler, Andrew Palmer (University of Texas at Dallas)
    Abstract: Despite nation-wide decreases in crime, urban gun violence remains a serious and pressing issue in many cities. Victim survival in these incidents is often contingent on the speed and quality of care provided. Increasingly, new research has identified the role that specialized trauma care plays in victim survival from firearm-related injuries. Using nearly four years of data on shooting victimizations in Philadelphia we test whether distance to the nearest level 1 trauma center is associated with victim survival. We employ different distance measures based on street network distances, drive-time estimates, and Euclidean distance - comparing the predictive accuracy of each. Our results find that victims who are shot farther from trauma centers have an increased likelihood of death, and drive time distances provide the most accurate predictions. We discuss the practical implications of this research as it applies to urban public health.
    Date: 2019–08–06

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