Nonlinear Dynamics of Crime and Violence in Urban Settings
AbstractWe perform analysis of data on crime and violence for 5,660 U.S. cities over the period of 2005-2009 and uncover the following trends: 1) The proportion of law enforcement officers required to maintain a steady low level of criminal activity increases with the size of the population of the city; 2) The number of criminal/violent events per 1,000 inhabitants of a city shows non-monotonic behavior with size of the population. We construct a dynamical model allowing for system-level, mechanistic understanding of these trends. In our model the level of rational behavior of individuals in the population is encoded into each citizen's perceived risk function. We find strong dependence on size of the population, which leads to partially irrational behavior on the part of citizens. The nature of violence changes from global outbursts of criminal/violent activity in small cities to spatio-temporally distributed, decentralized outbursts of activity in large cities, indicating that in order to maintain peace, bigger cities need larger ratio of law enforcement officers than smaller cities. We also observe existence of tipping points for communities of all sizes in the model: reducing the number of law enforcement officers below a critical level can rapidly increase the incidence of criminal/violent activity. Though surprising, these trends are in agreement with the data.
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Bibliographic InfoArticle provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.
Volume (Year): 15 (2012)
Issue (Month): 1 ()
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Agent-Based Modeling; Crime; Violence; Anthropology; Socio-Cultural Model; Police;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Heiko Rauhut & Marcel Junker, 2009. "Punishment Deters Crime Because Humans Are Bounded in Their Strategic Decision-Making," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1.
- Michael D. Makowsky, 2005.
"An Agent-Based Model of Mortality Shocks, Intergenerational Effects, and Urban Crime,"
Computing in Economics and Finance 2005
91, Society for Computational Economics.
- Michael Makowsky, 2006. "An Agent-Based Model of Mortality Shocks, Intergenerational Effects, and Urban Crime," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(2), pages 7.
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