nep-net New Economics Papers
on Network Economics
Issue of 2014‒08‒28
five papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. Supply function equilibria in transportation networks By Pär Holmberg; Andy Philpott
  2. Location and logistics By Alumura, Sibel A.; Karab, Bahar Y.; Melo, M. Teresa
  3. Competition in the Cryptocurrency Market By Neil Gandal; Hanna Halaburda
  4. Issues and Options in the Economic Regulation of European Network Security By Tooraj Jamasb; Rabindra Nepal
  5. Granger Causality Stock Market Networks: Temporal Proximity and Preferential Attachment By Tom\'a\v{s} V\'yrost; \v{S}tefan Ly\'ocsa; Eduard Baum\"ohl

  1. By: Pär Holmberg; Andy Philpott
    Abstract: Transport constraints limit competition and arbitrageurs' possibilities of exploiting price differences between commodities in neighbouring markets. We analyze a transportation network where oligopoly producers compete with supply functions under uncertain demand, as in wholesale electricity markets. For symmetric networks with a radial structure, we show that existence of symmetric supply function equilibria (SFE) is ensured if demand shocks are sufficiently evenly distributed. We can explicitly solve for them for uniform multi-dimensional nodal demand shocks.
    Keywords: Spatial competition, Multi-unit auction, Supply Function Equilibrium, Trading network, Transmission network, Wholesale electricity markets
    JEL: D43 D44 C72 L91
    Date: 2014–08–04
    URL: http://d.repec.org/n?u=RePEc:cam:camdae:1421&r=net
  2. By: Alumura, Sibel A.; Karab, Bahar Y.; Melo, M. Teresa
    Abstract: Facility location decisions play a critical role in designing logistics networks. This article provides some guidelines on how location decisions and logistics functions can be integrated into a single mathematical model to optimize the configuration of a logistics network. This will be illustrated by two generic models, one supporting the design of a forward logistics network and the other addressing the specific requirements of a reverse logistics network. Several special cases and extensions of the two models are discussed and their relation with the scientific literature is described. In addition, some interesting applications are outlined that demonstrate the interaction of location and logistics decisions. Finally, new research directions and emerging trends in logistics network design are provided. --
    Keywords: forward logistics network design,reverse logistics network design,models,applications
    Date: 2013
    URL: http://d.repec.org/n?u=RePEc:zbw:htwlog:5&r=net
  3. By: Neil Gandal; Hanna Halaburda
    Abstract: We analyze how network effects affect competition in the nascent cryptocurrency market. We do so by examining the changes over time in exchange rate data among cryptocurrencies. Specifically, we look at two aspects: (1) competition among different currencies, and (2) competition among exchanges where those currencies are traded. Our data suggest that the winner-take-all effect is dominant early in the market. During this period, when Bitcoin becomes more valuable against the U.S. dollar, it also becomes more valuable against other cryptocurrencies. This trend is reversed in the later period. The data in the later period are consistent with the use of cryptocurrencies as financial assets (popularized by Bitcoin), and not consistent with “winner-take-all” dynamics. For exchanges, we find little if any evidence of arbitrage opportunities. With no arbitrage opportunities, it is possible for multiple exchanges to coexist in equilibrium despite two-sided network effects.
    Keywords: E-Money
    JEL: L1
    Date: 2014
    URL: http://d.repec.org/n?u=RePEc:bca:bocawp:14-33&r=net
  4. By: Tooraj Jamasb; Rabindra Nepal
    Abstract: Incentive regulation needs to adapt to the emerging changes in the operating environment of the electricity networks and take into account the security of these. This paper assesses the current issues and options in economic regulation of network security across the European electricity systems. An output oriented incentive regulatory approach combines the efficiency promoting mechanisms in a revenue cap framework with output based incentives such as better provision of network security. Thus, incentive regulation is destined to move from pursuing the optimal to being more practical. The RIIO regulatory framework in the UK and the service quality regulation in Italy provide good examples of application of output-based regulation. We also propose an output-based approach for regulation of network security, which accounts for the risks from natural, accidental and malicious threats. We conclude that regulation for network security may also involve looking beyond economic network regulation and focus on the wider security policy and regulation interface considering the risks facing the electricity networks.
    Keywords: network security, exceptional events, incentive regulation, output-based
    JEL: L51 L94 L98
    Date: 2014–08–04
    URL: http://d.repec.org/n?u=RePEc:cam:camdae:1425&r=net
  5. By: Tom\'a\v{s} V\'yrost; \v{S}tefan Ly\'ocsa; Eduard Baum\"ohl
    Abstract: The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temporal proximity between market closing times for return spillovers, i.e. the time distance between national stock markets matters. Third, preferential attachment between stock markets exists, i.e. spillover from market j to market i is more likely if A) market j influences other markets other than i, or when B) market i is influenced by other markets other than j.
    Date: 2014–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1408.2985&r=net

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