In ‘A simple model of crime waves, riots, and revolutions’, Alexander Tabarrok puts forward a model of crime waves that applies not only to crime but also to phenomena like riots, strikes, and revolutions.
- In each of these cases, the probability of being punished is a decreasing function of the total amount of the activity.
- The probability that a rioter is apprehended falls the more rioters there are.
- The probability that a striker or a revolutionary is punished is less the greater the number of strikers and revolutionaries. This is true even if the revolution or strike fails.
The standard model of crime analyses a criminal’s decisions as if they were unrelated to the decisions of other criminals.

The game-theoretic approach examines the entire system of criminal decisions exploring the implications of interdependence.

As crime increases, police resources become strained at the margin and the probability of punishment falls, causing other criminals to increase their criminal activities.
As others turn to crime, the probability of punishment falls even further, giving each individual an additional reason to increase his criminal activities.
Joining into a revolution or a riot has the same calculus of independence. You are less likely to be caught and punished if you will face in the crowd.
This interdependence in the probability of detection, arrest and punishment lowers the cost of participation. Not surprisingly, judges of been aware of this for some time and have hand out severe punishments such as after the 2011 London riots. These riots fell away sharply once these penalties were handed out and more police were on the streets to catch rioters.


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