nep-net New Economics Papers
on Network Economics
Issue of 2017‒04‒02
four papers chosen by
Pedro CL Souza
Pontifícia Universidade Católica do Rio de Janeiro

  1. Evidence That Calls-Based and Mobility Networks Are Isomorphic By Michele Coscia; Ricardo Hausmann
  2. The Impact of Initial Seeds in Connecting Two Separated Networks on Resulting Social Capital By Hamid Zargariasl; Hamed Jahangiri
  3. Price and Network Dynamics in the European Carbon Market By Andreas Karpf; Antoine Mandel; Stefano Battiston
  4. Identifying Productivity Spillovers Using the Structure of Production Networks By Bazzi, Samuel; Chari, Amalavoyal V.; Nataraj, Shanthi; Rothenberg, Alexander D.

  1. By: Michele Coscia (Center for International Development at Harvard University); Ricardo Hausmann (Center for International Development at Harvard University)
    Abstract: Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable.
    Date: 2015–12
    URL: http://d.repec.org/n?u=RePEc:cid:wpfacu:309&r=net
  2. By: Hamid Zargariasl; Hamed Jahangiri
    Abstract: Aggregating different networks is an important fact in socio-economical collaboration between different separated organizations. The first challenge is the quality of connecting nodes between two networks that some results have been reported in the recent years. The second obstacle is selecting the initial group of nodes for connecting to the other network in quantitative context. The latter, implies to the optimization the method so that a minimum effective group may yield higher outputs that a big randomly selected groups. Here, we do not intend to discuss about selecting method of nodes, oppositely the number of nodes (seed) will be addressed. The existence of sorted high priority nodes is the premises of this study and we aim to find the best number ( minimum number of nodes) that reduces the costs (connections) of aggregating procedure. Here, we study the diffusion of the information in the final network as one of the important parameters in the social capital of networks. The number of initially informed nodes for spreading the information in a given network is called seed and studies such as [5] address either the algorithms for selecting nodes or the percentage of nodes compared to all nodes of network in the first stage of information diffusion. This approach aims to use the previous studies to find initial seed number, not for spreading the information, but for selecting the number of initial group of nodes in both given networks for maximizing the flow of the information in the aggregated network. The main assumption is that the list of high priority nodes for connection is available. The mentioned list may be indicated with different algorithms like centrality in the network. Answering the following question is the main question of this study: What percentage of initial high priority nodes in initial networks must be selected to making bridges between them? Two different networks about co-presence and mobile phone connection of students are considered. All nodes are ranked in their network according to their priorities for connecting two networks. Different groups of nodes beginning from the node with highest priority are used for bridging two networks. In any arrangement, the performance of resulting network in flow of information is measured. For evaluating the performance of any topology, a group of usual parameters and also some new metric that have been recently introduced are used. A software module is used for calculating the parameters for examining the Cascade model of the information diffusion in final networks. Finally, the effect of resulting seeds on the performance of any network are studied.
    Keywords: Italy, Iran, Growth, Optimization models
    Date: 2015–07–01
    URL: http://d.repec.org/n?u=RePEc:ekd:008007:8301&r=net
  3. By: Andreas Karpf (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Antoine Mandel (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Stefano Battiston (Department of Banking and Finance - UZH - University of Zürich [Zürich])
    Abstract: This paper presents an analysis of the European Emission Trading System as a transaction network. It is shown that, given the lack of a centralized market place, industrial actors had to resort to local connections and financial intermediaries to participate in the market. This gave rise to a hierarchical structure in the transaction network. To empirically relate networks statistics to market outcomes a PLS-PM modeling technique is introduced. It is shown that the asymmetries in the network induced market inefficiencies (e.g. increased bid-ask spread). Albeit the efficiency of the market has improved from the beginning of Phase II, the asymmetry persists, imposing unnecessary additional costs on agents and reducing the effectiveness of the market as a mitigation instrument.
    Abstract: Cet article présente une analyse du système européen de négociation d'émissions comme un réseau de transactions. Il est démontré que, compte tenu de l'absence d'un marché centralisé, les acteurs industriels ont dû recourir à des structures locales des intermédiaires financiers pour participer au marché. Cela a donné lieu à une structure hiérarchique dans le réseau de transactions. Pour relier de manière empirique les statistiques de réseaux aux résultats du marché, une technique de modélisation PLS-PM est introduite. Il est démontré que les asymétries du réseau induisent des inefficiences du marché (bid-ask spread). Bien que l'efficacité du marché se soit améliorée depuis le début de la Phase II, l'asymétrie persiste, imposant des coûts supplémentaires inutiles aux agents et réduisant l'efficacité du marché en tant qu'instrument d'atténuation.
    Keywords: Carbon market,network,climate economics,réseaux,Marché du carbone,économie du climat
    Date: 2017–02
    URL: http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-01484117&r=net
  4. By: Bazzi, Samuel; Chari, Amalavoyal V.; Nataraj, Shanthi; Rothenberg, Alexander D.
    Abstract: Despite the importance of agglomeration externalities in theoretical work, evidence for their nature, scale, and scope remains elusive, particularly in developing countries. Identification of productivity spillovers between firms is a challenging task, and estimation typically requires, at a minimum, panel data, which are often not available in developing country contexts. In this paper, we develop a novel identification strategy that uses information on the network structure of producer relationships to provide estimates of the size of productivity spillovers. Our strategy builds on that proposed by Bramoulle et al. (2009) for estimating peer effects, and is one of the first applications of this idea to the estimation of productivity spillovers. We improve upon the network structure identification strategy by using panel data and validate it with exchange-rate induced trade shocks that provide additional identifying variation. We apply this strategy to a long panel dataset of manufacturers in Indonesia to provide new estimates of the scale and size of productivity spillovers. Our results suggest positive productivity spillovers between manufacturers in Indonesia, but estimates of TFP spillovers are considerably smaller than similar estimates based on firm-level data from the U.S. and Europe, and they are only observed in a few industries.
    Date: 2017–02
    URL: http://d.repec.org/n?u=RePEc:ran:wpaper:1182&r=net

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