Some Reasons for Using Zipf's Law in the Analysis of Urban Crime: The Case of Mexico

The high concentration of crime in a handful of cities is clear. What is not clear, however, is why crime levels are high in particular places. Using crime victimization data from thirty-two Mexican cities, I test one proposition and develop another. First, I show that Zipf's law fits to a certain degree the distribution of crime victimization and fear of crime. Second, I argue that these patterns are due to opportunities to commit crimes that are created not only by the spatial-temporal convergence of potential victims and offenders, but to the principle of least effort, which helps explain urban development processes. In this regard, more and better conditions of production in a city mean not only more jobs and wealth, but also more crime victims. This suggests that urban crime is not only predictable, to some degree, but also a problem associated with the forces of urbanization.