One of the more interesting networks models is Duncan Watts model of cascading network failure. Simply, each node in the network has a specific tolerance to failure determined by the number of adjoining nodes that have failed. For example a node could have a tolerance of 0.5, so if more that half of its neighbours have failed, it will also fail, leading to a cascade of failures of its other neighbours.
This simple model, or more so a framework for analysis, is versatile. It can reveal how and why fashion fads arise, why investors tend to go with the herd, and why some industries produce superstars even though no one can objectively tell the difference in the quality of their skills.
The methodological individualism so fondly embraced by the economics crowd has at its core the concept of utility, but stops short of answering the far more important question – where does our utility function come from if not our environment and our interactions with others? A model of networks can help explain the source of utility, and begin to give picture of how unique cultures and customs arise.
In any case, I have generated an interactive version of the model that simulates over a random network, with 5 random nodes ‘shocked’ to initiate the model. The histogram shows how many of the 20 different shocks have led to cascades of failure of a particular number of nodes.
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