nep-net New Economics Papers
on Network Economics
Issue of 2022‒05‒09
eight papers chosen by
Alfonso Rosa García
Universidad de Murcia

  1. An evolution of global and regional banking networks: A focus on Japanese banks’ international expansion By Harrison, Michael; Nakajima, Jouchi; Shabani, Mimoza
  2. Network Structure and Fragmentation of the Argentinean Interbank Markets By Pedro Elosegui; Federico Forte; Gabriel Montes-Rojas
  3. Stability of heteroclinic cycles: a new approach By Telmo Peixe; Alexandre A. Rodrigues
  4. Distress and default contagion in financial networks By Veraart, Luitgard A. M.
  5. The Social Integration of International Migrants: Evidence from the Networks of Syrians in Germany By Michael Bailey; Drew Johnston; Martin Koenen; Theresa Kuchler; Dominic Russel; Johannes Stroebel
  6. Stable and metastable contract networks By Vladimir I. Danilov; Alexander V. Karzanov
  7. Reinforcement Learning Policy Recommendation for Interbank Network Stability By Alessio Brini; Gabriele Tedeschi; Daniele Tantari
  8. Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network By Xinyu Wang; Liang Zhao; Ning Zhang; Liu Feng; Haibo Lin

  1. By: Harrison, Michael; Nakajima, Jouchi; Shabani, Mimoza
    Abstract: This paper examines the possible spillover effects of the global and regional crossborder claims of Japanese banks on domestic financial stability. We contribute to the existing literature by constructing a global banking network and applying the Spinglass methodology to detect communities formed within the network. Furthermore, we employ a novel spatial econometric approach, namely, a timevarying spatial autoregressive (SAR) model that captures the evolution of spillover effects over time. Our empirical results point to the dominant role of Japanese banks in the global banking network and the evolution of the East Asian regional banking network. Furthermore, our findings show considerable variation in the degree of influence of both the global and regional banking networks over time.
    Keywords: banking networks, spillover effect, spatial autoregression
    JEL: C23 G21 F34 R11
    Date: 2022–04
  2. By: Pedro Elosegui (Banco Central de la República Argentina); Federico Forte (BBVA); Gabriel Montes-Rojas (UBA/CONICET)
    Abstract: This paper studies the network structure and fragmentation of the Argentine interbank market. Both the unsecured (CALL) and the secured (REPO) markets are examined. The aim of this study is to understand their actual fragmentation, as well as its potential implications for monetary policy and financial stability. Applying network analysis, different underlying segments within the market are identified. We approximate the theoretical distribution that better fits the empirical degree distribution of the interbank loan networks. Based on standard topological metrics, it is found that, although the secured market has less participants, its nodes are more densely connected than in the unsecured market. In addition, the interrelationships in the unsecured market are less stable, as it was witnessed during the 2018 currency crisis, making its structure more volatile and vulnerable to negative shocks. The analysis identifies two “hidden” underlying sub-networks within the REPO market: one based on the transactions collateralized by Treasury bonds (REPO-T) and other based on the operations collateralized by Central Bank (CB) securities (REPO-CB). The connectivity indicators were significantly more stable in the REPO-T market than in the REPO-CB segment. The changes in monetary policy stance and monetary conditions seem to have a substantially smaller impact in former than in the latter “sub-market”. Hence, the connectivity levels within the REPO-T market remain relatively unaffected by the (in some period pronounced) swings in the other segment of the market. These results have implications in terms of the interpretation of the interest rates that arise from these markets.
    Date: 2022–03
  3. By: Telmo Peixe; Alexandre A. Rodrigues
    Abstract: This paper analyses the stability of cycles within a heteroclinic network lying in a three-dimensional manifold formed by six cycles, for a one-parameter model developed in the context of game theory. We show the asymptotic stability of the network for a range of parameter values compatible with the existence of an interior equilibrium and we describe an asymptotic technique to decide which cycle (within the network) is visible in numerics. The technique consists of reducing the relevant dynamics to a suitable one-dimensional map, the so called \emph{projective map}. Stability of the fixed points of the projective map determines the stability of the associated cycles. The description of this new asymptotic approach is applicable to more general types of networks and is potentially useful in computational dynamics.
    Date: 2022–04
  4. By: Veraart, Luitgard A. M.
    Abstract: We develop a new model for solvency contagion that can be used to quantify systemic risk in stress tests of financial networks. In contrast to many existing models it allows for the spread of contagion already before the point of default and hence can account for contagion due to distress and mark-to-market losses. We derive general ordering results for outcome measures of stress tests that enable us to compare different contagion mechanisms. We use these results to study the sensitivity of the new contagion mechanism with respect to its model parameters and to compare it to existing models in the literature. When applying the new model to data from the European Banking Authority we find that the risk from distress contagion is strongly dependent on the anticipated recovery rate. For low recovery rates the high additional losses caused by bankruptcy dominate the overall stress test results. For high recovery rates, however, we observe a strong sensitivity of the stress test outcomes with respect to the model parameters determining the magnitude of distress contagion.
    Keywords: systemic risk; contagion; financial networks; stress testing; mark-to-market losses; George Fellowship
    JEL: C62 D85 G21 G28 G33
    Date: 2020–07–01
  5. By: Michael Bailey; Drew Johnston; Martin Koenen; Theresa Kuchler; Dominic Russel; Johannes Stroebel
    Abstract: We use de-identified data from Facebook to study the social integration of Syrian migrants in Germany, a country that received a large influx of refugees during the Syrian Civil War. We construct measures of migrants’ social integration based on Syrians’ friendship links to Germans, their use of the German language, and their participation in local social groups. We find large variation in Syrians’ social integration across German counties, and use a movers’ research design to document that these differences are largely due to causal effects of place. Regional differences in the social integration of Syrians are shaped both by the rate at which German natives befriend other locals in general (general friendliness) and the relative rate at which they befriend local Syrian migrants versus German natives (relative friending). We follow the friending behavior of Germans that move across locations to show that both general friendliness and relative friending are more strongly affected by place-based effects such as local institutions than by persistent individual characteristics of natives (e.g., attitudes to-ward neighbors or migrants). Relative friending is higher in areas with lower unemployment and more completed government-sponsored integration courses. Using variation in teacher availability as an instrument, we find that integration courses had a substantial causal effect on the social integration of Syrian migrants. We also use fluctuations in the presence of Syrian migrants across high school cohorts to show that natives with quasi-random expo-sure to Syrians in school are more likely to befriend other Syrian migrants in other settings, suggesting that contact between groups can shape subsequent attitudes towards migrants.
    Keywords: integration, immigration, social networks, place effects
    JEL: F22 J15 K37 D85
    Date: 2022
  6. By: Vladimir I. Danilov; Alexander V. Karzanov
    Abstract: We consider a hypergraph (I,C), with possible multiple (hyper)edges and loops, in which the vertices $i\in I$ are interpreted as agents, and the edges $c\in C$ as contracts that can be concluded between agents. The preferences of each agent i concerning the contracts where i takes part are given by use of a choice function $f_i$ possessing the so-called path independent property. In this general setup we introduce the notion of stable network of contracts. The paper contains two main results. The first one is that a general problem on stable systems of contracts for (I,C,f) is reduced to a set of special ones in which preferences of agents are described by use of so-called weak orders, or utility functions. However, for a special case of this sort, the stability may not exist. Trying to overcome this trouble when dealing with such special cases, we introduce a weaker notion of metastability for systems of contracts. Our second result is that a metastable system always exists.
    Date: 2022–02
  7. By: Alessio Brini; Gabriele Tedeschi; Daniele Tantari
    Abstract: In this paper we analyze the effect of a policy recommendation on the performances of an artificial interbank market. Financial institutions stipulate lending agreements following a public recommendation and their individual information. The former, modeled by a reinforcement learning optimal policy trying to maximize the long term fitness of the system, gathers information on the economic environment and directs economic actors to create credit relationships based on the optimal choice between a low interest rate or high liquidity supply. The latter, based on the agents' balance sheet, allows to determine the liquidity supply and interest rate that the banks optimally offer on the market. Based on the combination between the public and the private signal, financial institutions create or cut their credit connections over time via a preferential attachment evolving procedure able to generate a dynamic network. Our results show that the emergence of a core-periphery interbank network, combined with a certain level of homogeneity on the size of lenders and borrowers, are essential features to ensure the resilience of the system. Moreover, the reinforcement learning optimal policy recommendation plays a crucial role in mitigating systemic risk with respect to alternative policy instruments.
    Date: 2022–04
  8. By: Xinyu Wang; Liang Zhao; Ning Zhang; Liu Feng; Haibo Lin
    Abstract: The systemic stability of a stock market is one of the core issues in the financial field. The market can be regarded as a complex network whose nodes are stocks connected by edges that signify their correlation strength. Since the market is a strongly nonlinear system, it is difficult to measure the macroscopic stability and depict market fluctuations in time. In this paper, we use a geometric measure derived from discrete Ricci curvature to capture the higher-order nonlinear architecture of financial networks. In order to confirm the effectiveness of our method, we use it to analyze the CSI 300 constituents of China's stock market from 2005--2020 and the systemic stability of the market is quantified through the network's Ricci type curvatures. Furthermore, we use a hybrid model to analyze the curvature time series and predict the future trends of the market accurately. As far as we know, this is the first paper to apply Ricci curvature to forecast the systemic stability of domestic stock market, and our results show that Ricci curvature has good explanatory power for the market stability and can be a good indicator to judge the future risk and volatility of the domestic market.
    Date: 2022–04

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