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Decentralized Defence of a (Directed) Network Structure

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  • Marco Pelliccia

Abstract

We model the decentralized defence choice of agents connected in a directed graph and exposed to an external threat. The network allows players to receive goods from one or more producers through directed paths. Each agent is endowed with a finite and divisible defence resource that can be allocated to their own security or to that of their peers. The external threat is represented by either a random attack on one of the nodes or by an intelligent attacker who aims to maximize the flow-disruption by seeking to destroy one node. We show that under certain conditions a decentralized defence allocation is efficient when we assume the attacker to be strategic: a centralized allocation of defence resources which minimizes the flow-disruption coincides with a decentralized equilibrium allocation. On the other hand, when we assume a random attack, the decentralized allocation is likely to diverge from the central planner’s allocation.

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  • Marco Pelliccia, 2020. "Decentralized Defence of a (Directed) Network Structure," Defence and Peace Economics, Taylor & Francis Journals, vol. 31(6), pages 659-676, August.
    • Handle: RePEc:taf:defpea:v:31:y:2020:i:6:p:659-676
    DOI: 10.1080/10242694.2019.1587679
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    References listed on IDEAS

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    Cited by:

    1. Sonja Brangewitz & Behnud Mir Djawadi & Angelika Endres & Britta Hoyer, 2017. "Network Formation and Disruption - An Experiment. Are efficient networks too complex?," Working Papers CIE 101, Paderborn University, CIE Center for International Economics.
    2. Sonja Brangewitz & Behnud Mir Djawadi & Angelika Endres & Britta Hoyer, 2017. "Network Formation and Disruption - An Experiment - Are Efficient Networks too Complex?," Working Papers 2017.30, Fondazione Eni Enrico Mattei.
    3. Djawadi, Behnud Mir & Endres, Angelika & Hoyer, Britta & Recker, Sonja, 2019. "Network formation and disruption - An experiment are equilibrium networks too complex?," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 708-734.

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    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other

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