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The recent global financial crisis has revealed that borrowing and lending among banks and other financial intermediaries makes it possible for a shock to a single bank to spread through the entire system. One of the main sources of this chain-reaction is that financial intermediaries have come to indirectly hold many types of assets. Against this background, to provide a stylized representation of the interbank lending market, the present paper constructs a model in which banks' liabilities form a core–periphery network. The model is then employed to simulate contagion in the network in the wake of the hypothesized insolvency of one of the banks. The main contributions of the analysis are as follows. First, the simulation shows that when asset prices declines as contagion spreads, the degree of contagion in response to an insolvency is significantly greater than when prices are assumed to be exogenous. Second, the core–periphery network analysis shows that insolvency increases non-monotonically in the strength of the links between core banks. [ABSTRACT FROM AUTHOR]

This paper proposes a model of the dynamics of credit contagion through non-performing loans on financial networks. Credit risk contagion is modeled in the context of the classical SIS (Susceptibles-Infected-Susceptibles) epidemic processes on networks but with a fundamental novelty. In fact, we assume the presence of two different classes of infected agents, and then we differentiate the dynamics of assets subject to idiosyncratic risk from those affected by systemic risk by adopting a SIIS (Susceptible-Infected1-Infected2-Susceptible) model. In the recent literature in this field, the effect of systemic credit risk on the performance of the financial network is a hot topic. We perform numerical simulations intended to explore the roles played by two different network structures on the long-term behavior of assets affected by systemic risk in order to analyze the effect of the topology of the underlying network structure on the spreading of systemic risk on the structure. Random graphs, i.e., the Erdös−Rényi model, are considered “benchmark” network structures while core-periphery structures are often indicated in the literature as idealized structures, although they are able to capture interesting, specific features of real-world financial networks. Moreover, as a matter of comparison, we also perform numerical experiments on small-world networks.

Inspired by social networks and complex systems, we propose a core–periphery network architecture that supports fast computation for many distributed algorithms, is robust and uses a linear number of links. Rather than providing a concrete network model, we take an axiom-based design approach. We provide three intuitive and independent algorithmic axioms and prove that any network that satisfies all axioms enjoys an efficient algorithm for a range of tasks (such as MST, sparse matrix multiplication, and more). We also show the necessity of our axiom set: for networks that satisfy any subset of the axioms, the same efficiency cannot be guaranteed for any deterministic algorithm. [ABSTRACT FROM AUTHOR]

This paper aims to analyze patterns of participation of higher education institutions (HEIs) to European Framework Programs (EU-FP) and their association with HEI characteristics, country and geographical effects. We have analyzed a sample of 2235 HEIs in 30 countries in Europe, derived from the European Tertiary Education Register (ETER), which has been matched with data on participations in EU-FPs in 2011 using the EUPRO database. Our findings identified (1) a high concentration of EU-FP participation in a small group of HEIs with high reputation; (2) the participation of non-doctorate awarding HEIs in EU-FPs is very limited despite the fact that they account for a significant share of tertiary student enrolments; (3) the number of participations tends to increase proportionally to organizational size, and is strongly influenced by international reputation; (5) there is limited evidence of significant country effects in EU-FP participations, as well as of the impact of distance from Brussels. We interpret these results as an outcome of the close association between HEI reputation and the network structure of EU-FP participants. [ABSTRACT FROM AUTHOR]

This paper proposes a model of the dynamics of credit contagion through non-performing loans on financial networks. Credit risk contagion is modeled in the context of the classical SIS (Susceptibles-Infected-Susceptibles) epidemic processes on networks but with a fundamental novelty. In fact, we assume the presence of two different classes of infected agents, and then we differentiate the dynamics of assets subject to idiosyncratic risk from those affected by systemic risk by adopting a SIIS (Susceptible-Infected1-Infected2-Susceptible) model. In the recent literature in this field, the effect of systemic credit risk on the performance of the financial network is a hot topic. We perform numerical simulations intended to explore the roles played by two different network structures on the long-term behavior of assets affected by systemic risk in order to analyze the effect of the topology of the underlying network structure on the spreading of systemic risk on the structure. Random graphs, i.e., the Erdös–Rényi model, are considered "benchmark" network structures while core-periphery structures are often indicated in the literature as idealized structures, although they are able to capture interesting, specific features of real-world financial networks. Moreover, as a matter of comparison, we also perform numerical experiments on small-world networks. [ABSTRACT FROM AUTHOR]