nep-net New Economics Papers
on Network Economics
Issue of 2011‒04‒23
four papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Spatial network configurations of cargo airlines By Scholz, Aaron B.
  2. The network structure of mutual support links: Evidence from rural Tanzania By Margherita Comola
  3. Explaining the structure of inter-organizational networks using exponential random graph models: does proximity matter? By Tom Broekel; Matte Hartog
  4. Learning in networks: An experimental study using stationary concepts By Berninghaus, Siegfried K.; Neumann, Thomas; Vogt, Bodo

  1. By: Scholz, Aaron B.
    Abstract: The paper evaluates the spatial dimension of air cargo networks by means of concentration and centrality measures. Three groups of carriers are analyzed, namely combined carriers, their pure freighter operations and pure cargo airlines. Differences in their spatial network configuration are observed between the three groups. Combined carriers operate very centralized networks with high concentrations at a small number of airports. Hub-and-spoke schemes are their predominant network configuration. The freighter fleets of combined carriers have lower centrality and concentration scores but hub-and-spoke schemes are still the predominant network configuration. Pure cargo airlines operate the least concentrated and centralized networks. Round-trip configurations are wide spread among pure cargo airlines to cope with imbalances of demand. --
    Keywords: air cargo transport,network configuration,centrality,spatial network configuration
    Date: 2011
    URL: http://d.repec.org/n?u=RePEc:zbw:kitwps:20&r=net
  2. By: Margherita Comola (EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris, PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - Ecole des Hautes Etudes en Sciences Sociales (EHESS) - Ecole des Ponts ParisTech - Ecole Normale Supérieure de Paris - ENS Paris)
    Abstract: This paper takes a network perspective t oinvestigate how rural households in developing countries form the links through which they provide and get economic support. I test the hypothesis that indirect contacts (e.g. friends of friends) matter for link formation. An estimation procedure of a network formation model à la Jackson and Wolinsky (1996) is proposed and applied to data on a single village in Tanzania. Results show that when agents evaluate the net advantage of forming a link they also consider the wealth and the position of indirect contacts. The network externalities from indirect contacts are negative, which suggests a mechanism of competition over scarce resources. This paper proposes the first structural estimation of an endogenous network formation model, and also contributes to the development literature by overcoming the dyadic regression approach and providing evidence that village-level network structure has an explanatory value disregarded by all previous studies.
    Keywords: mutual support ; network formation ; structural estimation ; indirect contacts
    Date: 2010–06
    URL: http://d.repec.org/n?u=RePEc:hal:psewpa:halshs-00585968&r=net
  3. By: Tom Broekel; Matte Hartog
    Abstract: A key question raised in recent years is which factors determine the structure of inter-organizational networks. While the focus has primarily been on different forms of proximity between organizations, which are determinants at the dyad level, recently determinants at the node and structural level have been highlighted as well. To identify the relative importance of determinants at these three different levels for the structure of networks that are observable at only one point in time, we propose the use of exponential random graph models. Their usefulness is exemplified by an analysis of the structure of the knowledge network in the Dutch aviation industry in 2008 for which we find determinants at all different levels to matter. Out of different forms of proximity, we find that once we control for determinants at the node and structural network level, only social proximity remains significant.
    Keywords: exponential random graph models, inter-organizational network structure, network analysis, proximity, aviation industry, economic geography
    JEL: R11 D85 L14 L62
    Date: 2011–04
    URL: http://d.repec.org/n?u=RePEc:egu:wpaper:1107&r=net
  4. By: Berninghaus, Siegfried K.; Neumann, Thomas; Vogt, Bodo
    Abstract: Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008) and in the comment by Brunner, Camerer and Goeree (2009). Every participant played against four neighbors and could choose a different strategy against each of them. The games were played in two network structures: a lattice and a circle. We compare our results with the predictions of different theories (Nash equilibrium, quantal response equilibrium, action-sampling equilibrium, payoff-sampling equilibrium, and impulse balance equilibrium) and the experimental results of Selten and Chmura (2008). One result is that the majority of players choose the same strategy against each neighbor. As another result we observe an order of predictive success for the stationary concepts that is different from the order shown by Selten and Chmura. This result supports our view that learning in networks is different from learning in random matching. --
    Keywords: experimental economics,networks,learning
    JEL: C70 C73 C91 D83 D85
    Date: 2011
    URL: http://d.repec.org/n?u=RePEc:zbw:kitwps:15&r=net

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