SPIROS BOUGHEAS spiros.bougheas@nottingham.ac.uk
Professor of Economics
Contagion in networks: Stability and efficiency
Bougheas, Spiros
Authors
Abstract
We study the formation of networks in environments where agents derive benefits from their neighbours (immediate links) but suffer losses through contagion when any agent on a path that connects them is hit by a shock. We first consider networks with undirected links (e.g. epidemics, underground resistance organizations, trade networks). We find that the only networks that satisfy strong notions of stability are comprised of disjoint subgraphs that are complete. Then, we consider networks with directed links and we find that stable networks can be asymmetric, connected but not completely connected, thus capturing the main features of production and financial networks. We also identify a trade-off between efficiency and stability.
Citation
Bougheas, S. (2022). Contagion in networks: Stability and efficiency. Mathematical Social Sciences, 115, 64-77. https://doi.org/10.1016/j.mathsocsci.2021.10.006
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 24, 2021 |
Online Publication Date | Nov 3, 2021 |
Publication Date | Jan 1, 2022 |
Deposit Date | Oct 25, 2021 |
Publicly Available Date | May 4, 2023 |
Journal | Mathematical Social Sciences |
Print ISSN | 0165-4896 |
Electronic ISSN | 1879-3118 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 115 |
Pages | 64-77 |
DOI | https://doi.org/10.1016/j.mathsocsci.2021.10.006 |
Keywords | Statistics, Probability and Uncertainty; General Psychology; General Social Sciences; Sociology and Political Science |
Public URL | https://nottingham-repository.worktribe.com/output/6536540 |
Publisher URL | https://www.sciencedirect.com/science/article/abs/pii/S0165489621001086?via%3Dihub |
Additional Information | This article is maintained by: Elsevier; Article Title: Contagion in networks: Stability and efficiency; Journal Title: Mathematical Social Sciences; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.mathsocsci.2021.10.006 |
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