nep-net New Economics Papers
on Network Economics
Issue of 2020‒03‒02
ten papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. Social Groups and the Effectiveness of Protests By Marco Battaglini; Rebecca B. Morton; Eleonora Patacchini
  2. Stability in shortest path problems By Bahel, Eric; Gómez-Rúa, María; Vidal-Puga, Juan
  3. Corporate boards, interorganizational ties and profitability: The case of Japan By Raddant, Matthias; Takahashi, Hiroshi
  4. The network of firms implied by the news By Zheng, Hannan; Schwenkler, Gustavo
  5. Output Spillovers from U.S. Monetary Policy: The Role of International Trade and Financial Linkages By Falk Bräuning; Viacheslav Sheremirov
  6. A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series By Daniel Felix Ahelegbey; Luis Carvalho; Eric D. Kolaczyk
  7. Regulating financial networks under uncertainty By Ramírez, Carlos
  8. The interbank market puzzle By Allen, Franklin; Covi, Giovanni; Gu, Xian; Kowalewski, Oskar; Montagna, Mattia
  9. Using generative adversarial networks to synthesize artificial financial datasets By Dmitry Efimov; Di Xu; Luyang Kong; Alexey Nefedov; Archana Anandakrishnan
  10. Modeling Risk Contagion in the Italian Zonal Electricity Market By Daniel Felix Ahelegbey; Emmanuel Senyo Fianu; Luigi Grossi

  1. By: Marco Battaglini; Rebecca B. Morton; Eleonora Patacchini
    Abstract: We present an informational theory of public protests, according to which public protests allow citizens to aggregate privately dispersed information and signal it to the policy maker. The model predicts that information sharing of signals within social groups can facilitate information aggregation when the social groups are sufficiently large even when it is not predicted with individual signals. We use experiments in the laboratory and on Amazon Mechanical Turk to test these predictions. We find that information sharing in social groups significantly affects citizens' protest decisions and as a consequence mitigates the effects of high conflict, leading to greater efficiency in policy makers' choices. Our experiments highlight that social media can play an important role in protests beyond simply a way in which citizens can coordinate their actions; and indeed that the information aggregation and the coordination motives behind public protests are intimately connected and cannot be conceptually separated.
    JEL: D72 D78
    Date: 2020–02
  2. By: Bahel, Eric; Gómez-Rúa, María; Vidal-Puga, Juan
    Abstract: We study three remarkable cost sharing rules in the context of shortest path problems, where agents have demands that can only be supplied by a source in a network. The demander rule requires each demander to pay the cost of their cheapest connection to the source. The supplier rule charges to each demander the cost of the second-cheapest connection and splits the excess payment equally between her access suppliers. The alexia rule averages out the lexicographic allocations, each of which allows suppliers to extract rent in some pre-specified order. We show that all three rules are anonymous and demand-additive core selections. Moreover, with three or more agents, the demander rule is characterized by core selection and a specific version of cost additivity. Finally, convex combinations of the demander rule and the supplier rule are axiomatized using core selection, a second version of cost additivity and two additional axioms that ensure the fair compensation of intermediaries.
    Keywords: Shortest path, cost sharing, core selection, additivity.
    JEL: C71 D85
    Date: 2020–01
  3. By: Raddant, Matthias; Takahashi, Hiroshi
    Abstract: We analyze the ties between 4,000 Japanese corporations in the time period from 2004 until 2013. We combine data about the board composition with ownership relationships and indicators of corporate profitability. We find that both the network of corporate board interlocks as well as the ownership network show a high degree of persistence. The overlap between these two networks is surprisingly small. In the analysis of the board composition we find that the number of outside board members is low yet increasing. Firms with large foreign shareholdership are at the forefront of this development. Upon retirement board members in central positions are replaced with similarly central executives, maintaining the general structure of the network. Women in corporate boards remain scarce. The connectivity of firms in the ownership and board network can be related to firm profitability. Firms that are linked to peers with above average profitability are likely more profitable than firms in other relationships.
    Keywords: corporate board interlock,firm performance,firm networks
    Date: 2020
  4. By: Zheng, Hannan; Schwenkler, Gustavo
    Abstract: We show that the news is a rich source of data on distressed firm links that drive firm-level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields predictable returns and downgrades. Shocks to the degree of news-implied firm connectivity predict increases in aggregate volatilities, credit spreads, and default rates, and declines in output. To obtain our results, we propose a machine learning methodology that takes text data as input and outputs a data-implied firm network. JEL Classification: E32, E44, L11, G10, C82
    Keywords: contagion, machine learning, natural language processing, networks, predictability, risk measurement
    Date: 2020–02
  5. By: Falk Bräuning; Viacheslav Sheremirov
    Abstract: We estimate that U.S. monetary policy has sizable spillover effects on global economic activity. In response to a surprise increase in the federal funds rate of 25 basis points, real output in our sample of 44 countries declines on average by 0.9% after three years. We find that international trade is a more important factor than international finance in explaining these spillovers. In particular, countries with a high share of exports and imports in output have 79% larger responses than countries with a low share, whereas we do not find significant heterogeneity depending on a country’s financial openness. Bilateral trade linkages appear to be quantitatively important, as the network amplification effect accounts for 45% of the total spillover effect at the peak horizon. We conclude that trade networks could be an important ingredient of theoretical models focusing on the international effects of U.S. monetary policy shocks.
    Keywords: financial linkages; international spillovers; monetary shocks; trade networks
    JEL: E52 F42 F44 G15
    Date: 2019–10–01
  6. By: Daniel Felix Ahelegbey (Università di Pavia); Luis Carvalho (Boston University); Eric D. Kolaczyk (Boston University)
    Abstract: Current understanding holds that financial contagion is driven mainly by system-wide interconnectedness of institutions. A distinction has been made between systematic and idiosyncratic channels of contagion, with shocks transmitted through the latter expected to be substantially more likely to lead to a crisis than through the former. Idiosyncratic connectivity is thought to be driven not simply by obviously shared characteristics among institutions, but more by the latent strategic position of ?rms in ?nancial markets. We propose a Bayesian hierarchical model for multivariate ?nancial time series that characterizes the interdependence in the idiosyncratic factors of a VAR model via a covariance graphical model whose structure is modeled through a latent position model. We develop an efficient algorithm that samples the network of the idiosyncratic factors and the latent positions underlying the network. We examine the dynamic volatility network and latent positions among 150 publicly listed institutions across the United States and Europe and how they contribute to systemic vulnerabilities and risk transmission.
    Keywords: Bayesian inference, Covariance graph model, Idiosyncratic Contagion Channels, Latent Space Models, Systemic Risk, VAR
    JEL: C11 C15 C51 C55 G01
    Date: 2020–02
  7. By: Ramírez, Carlos
    Abstract: I study the problem of regulating a network of interdependent financial institutions that is prone to contagion when there is uncertainty regarding its precise structure. I show that such uncertainty reduces the scope for welfare-improving interventions. While improving network transparency potentially reduces this uncertainty, it does not always lead to welfare improvements. Under certain conditions, regulation that reduces the risk-taking incentives of a small set of institutions can improve welfare. The size and composition of such a set crucially depend on the interplay between (i) the (expected) susceptibility of the network to contagion, (ii) the cost of improving network transparency, (iii) the cost of regulating institutions, and (iv) investors’ preferences. JEL Classification: C6, E61, G01
    Keywords: contagion, financial networks, policy design under uncertainty
    Date: 2020–02
  8. By: Allen, Franklin; Covi, Giovanni; Gu, Xian; Kowalewski, Oskar; Montagna, Mattia
    Abstract: This study documents significant differences in the interbank market lending and borrowing levels across countries. We argue that the existing differences in interbank market usage can be explained by the trust of the market participants in the stability of the country’s banking sector and counterparties, proxied by the history of banking crises and failures. Specifically, banks originating from a country that has lower level of trust tend to have lower interbank borrowing. Using a proprietary dataset on bilateral exposures, we investigate the Euro Area interbank network and find the effect of trust relies on the network structure of interbank markets. Core banks acting as interbank intermediaries in the network are more significantly influenced by trust in obtaining interbank funding, while being more exposed in a community can mitigate the negative effect of low trust. Country-level institutional factors might partially substitute for the limited trust and enhance interbank activity. JEL Classification: G01, G21, G28, D85
    Keywords: centrality, community detection, interbank market, networks, trust
    Date: 2020–02
  9. By: Dmitry Efimov; Di Xu; Luyang Kong; Alexey Nefedov; Archana Anandakrishnan
    Abstract: Generative Adversarial Networks (GANs) became very popular for generation of realistically looking images. In this paper, we propose to use GANs to synthesize artificial financial data for research and benchmarking purposes. We test this approach on three American Express datasets, and show that properly trained GANs can replicate these datasets with high fidelity. For our experiments, we define a novel type of GAN, and suggest methods for data preprocessing that allow good training and testing performance of GANs. We also discuss methods for evaluating the quality of generated data, and their comparison with the original real data.
    Date: 2020–02
  10. By: Daniel Felix Ahelegbey (Università di Pavia); Emmanuel Senyo Fianu (University Lüneburg); Luigi Grossi (Università di Verona)
    Abstract: Ensuring the security of stable, e?cient, and reliable energy supplies has intensi?ed the interconnections among energy markets. Imbalances between supply and demand due to operational failures, congestions and other sources of risk faced by these connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper lies in the adoption of recently proposed network models in an innovative way, which enhances the proper analysis of these market connections. The case of the Italian energy market is studied because it is a clear example of a zonal market where risk can spread across connected zones. We estimate within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, forecast demand and wind generation over the period 2010 – 2016 and evaluate the dynamics and persistence of zonal market connections examining the central market and the spread of risk in the zones of the Italian electricity market. Our ?ndings show that models based purely on prices give a better and more accurate explanation of risk contagion than models with exogenous regressors, revealing that the Central North and Central South zones are the most in?uential in terms of hub centrality for intraday and inter-day risk transmission, respectively, in the Italian energy market.
    Keywords: Bayesian inference, complex networks, energy prices, market e?ciency, systemic risk, volatility, zonal power market
    JEL: C11 C15 C32 C52 G01 Q41
    Date: 2020–02

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