nep-net New Economics Papers
on Network Economics
Issue of 2013‒01‒19
seven papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Mutual Insurance Networks in Communities By Pascal Billand; Christophe Bravard; Marie Sudipta Sarangi
  2. Contagious Bank Runs: Experimental Evidence By Martin Brown; Stefan Trautmann; Razvan Vlahu
  3. Journal Impact Factor, Eigenfactor, Journal Influence and Article Influence By Chia-Lin Chang; Michael McAleer; Les Oxley
  4. The Community Structure of the Global Corporate Network By Stefania Vitali; Stefano Battiston
  5. Coupling between time series: a network view By Saeed Mehraban; Amirhossein Shirazi; Maryam Zamani; Gholamreza Jafari
  6. Eficiência e/ou coesão territorial: de que modo uma rede de Instituições de Ensino Superior pode contribuir para estes objectivos? By Rego, Conceição; Caleiro, António; Vieira, Carlos; Vieira, Isabel; Baltazar, Maria da Saudade
  7. Using Supervised Environmental Composites in Production and Efficiency Analyses: An Application to Norwegian Electricity Networks By Orea, Luis; Growitsch, Christian; Jamasb, Tooraj

  1. By: Pascal Billand (Université de Lyon, Lyon, F-69007, France ; CNRS, GATE Lyon St Etienne,F-69130 Ecully, France ; Université Jean Monnet, Saint-Etienne, F-42000, France.); Christophe Bravard (Université Grenoble 2 ; UMR 1215 GAEL, F-38000 Grenoble, France ; CNRS, GATE Lyon St Etienne, Saint-Etienne, F-42000, France); Marie Sudipta Sarangi (DIW Berlin and Louisiana State University)
    Abstract: We study the formation of mutual insurance networks in a model where every agent who obtains more resources gives a fixed amount of resources to all agents who have obtained less resources. The low resource agent must be directly linked to the high resource agent to receive this transfer. We identify the pairwise stable networks and efficient networks. Then, we extend our model to situations where agents differ in their generosity with regard to the transfer scheme. We show that there exist conditions under which in a pairwise stable network agents who provide the same level of transfers are linked together, while there are no links between agents who provide high transfers and agents who provide low transfers.
    Keywords: Mutual insurance networks, Pairwise stable networks, Efficient networks
    JEL: C72 D81 D8
    Date: 2012
  2. By: Martin Brown; Stefan Trautmann; Razvan Vlahu
    Abstract: We conduct a laboratory experiment to examine under which circumstances a depositor-run at one bank may lead to a depositor-run at another bank. We implement two-person coordination games which capture the essence of the Diamond-Dybvig (1983) bank-run model. Subjects in the roles of followers observe the deposit withdrawal decisions of leaders before they make their own deposit withdrawal decisions. In one treatment followers know that there are no economic linkages between the leaders’ and the followers’ banks. In a second treatment followers know that there are economic linkages between the leaders’ and the followers’ banks. Our results suggest that deposit withdrawals are strongly contagious across banks only when depositors know that there are economic linkages between banks. The contagion of withdrawals is by a change in beliefs about bank asset quality and in beliefs about the behavior of other depositors, with the latter channel being more pronounced. Our results reconcile panic-based and information-based explanations of bank runs.
    Keywords: Contagion; Bank runs; Systemic risk
    JEL: D81 G21 G28
    Date: 2012–12
  3. By: Chia-Lin Chang (National Chung Hsing University); Michael McAleer (Erasmus University Rotterdam, Complutense University of Madrid, and Kyoto University); Les Oxley (University of Waikato)
    Abstract: This paper examines the practical usefulness of two new journal performance metrics, namely the Eigenfactor score, which may be interpreted as measuring “Journal Influence”, and the Article Influence score, using the Thomson Reuters ISI Web of Science (hereafter ISI) data for 2009 for the 200 most highly cited journals in each of the Sciences and Social Sciences, and compares them with two existing ISI metrics, namely Total Citations and the 5-year Impact Factor (5YIF) of a journal (including journal self citations). It is shown that the Sciences and Social Sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar. Moreover, the journal influence and article influence journal performance metrics are shown to be closely related empirically to the two existing ISI metrics, and hence add little in practical usefulness to what is already known. These empirical results are compared with existing results in the literature.
    Keywords: Journal performance metrics; Research assessment measures; Total citations; 5-year impact factor (5YIF); Eigenfactor; Journal and Article influence
    JEL: A12
    Date: 2013–01–04
  4. By: Stefania Vitali; Stefano Battiston
    Abstract: We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide the first quantitative assessment of the financial sector role in connecting the global economy.
    Date: 2013–01
  5. By: Saeed Mehraban; Amirhossein Shirazi; Maryam Zamani; Gholamreza Jafari
    Abstract: Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mapped to a network, "the cross-visibility graph", to demonstrate the correlation between them. We applied the algorithm to several correlated and uncorrelated time series, generated by the linear stationary ARFIMA process. The results demonstrate that the cross-visibility graph associated with correlated time series with power-law auto-correlation is scale-free. If the time series are uncorrelated, the degree distribution of their cross-visibility network deviates from power-law. For more clarifying the process, we applied the algorithm to real-world data from the financial trades of two companies, and observed significant small-scale coupling in their dynamics.
    Date: 2013–01
  6. By: Rego, Conceição; Caleiro, António; Vieira, Carlos; Vieira, Isabel; Baltazar, Maria da Saudade
    Abstract: The existence of higher education institutions (HEIs), dispersed in different locations throughout the country, is probably one of the most striking features associated with the expansion of this level of education in Portugal in the last 40 years. This phenomenon is particularly relevant since the level of qualification of the Portuguese active population remains small. The presence of HEIs causes very diverse effects of economic and social nature, which should be addressed as a whole (over the whole period of their occurrence). In confronting objectives of economic rationality and improvement of the qualification of Portuguese population, particularly of young people, it is important to discuss the possibility of a network of HEIs, at the same time, efficient and promoting territorial cohesion. In 2006, the OECD has pointed to the decline in demand associated with, among other factors, a sharp demographic contraction, in conjunction with the existence of an excess in installed supply, particularly in certain areas, in this level of education. In this scenario, it is now added a context of strong public budget constraints. A discussion of the characteristics of a network of HEIs, in terms of their efficiency and / or their contribution to territorial cohesion must take into account the supply available from the network, as well as the locations of the network. It is clear that the design of a network of HEIs is always political. Nevertheless, this decision making should be based on assumptions of a technical nature. A discussion of these assumptions is the goal we want to achieve with this paper.
    Keywords: Territorial Cohesion; Efficiency; Higher Education Policy; Network of Higher Education Institutions
    JEL: I23 R12 H52
    Date: 2013–01
  7. By: Orea, Luis (Energiewirtschaftliches Institut an der Universitaet zu Koeln); Growitsch, Christian (Energiewirtschaftliches Institut an der Universitaet zu Koeln); Jamasb, Tooraj (Energiewirtschaftliches Institut an der Universitaet zu Koeln)
    Abstract: Supervised dimension reduction methods have been extensively applied in different scientific fields like biology and medicine in recent years. However, they have hardly ever been used in micro economics, and in particular cost function modeling. Nonetheless, these methods can also be useful in regulation of natural monopolies such as gas, water, and electricity networks, where firms’ cost and performance can be affected by a large number of environmental factors. In order to deal with this ‘dimensionality’ problem we propose using a supervised dimension reduction approach that aims to reduce the dimension of data without loss of information. Economic theory suggests that in the presence of other relevant production (cost) drivers, the traditional all-inclusive assumption is not satisfied and, hence, production or cost predictions (and efficiency estimates) might be biased. This paper shows that purging the data using a partial regression approach allows us to address this issue when analyzing the effect of weather and geography on cost efficiency in the context of the Norwegian electricity distribution networks.
    Keywords: supervised composites; environmental conditions; electricity networks
    JEL: L15 L51 L94
    Date: 2012–12–02

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