Police crackdowns in Mexico City

Abstract

Purpose The purpose of this paper is to analyze the design and implementation of the police crackdown strategy employed in Mexico City and to discuss its limitations toward a medium-to-long-term reduction of crime rates for six types of robberies. Design/methodology/approach The present work employs generalized autoregressive conditional heteroscedasticity (GARCH) models to estimate the effect of police operations on the volatility of the rates of six types of robberies in Mexico City, as well as their persistence over time. Findings Results suggest that the concentration of policing in certain high-criminality spaces reduces crime rates in the immediate term; however, its permanence is contingent on policing design and behavioral characteristics of the targeted crime. Specifically, the Mexico City police crackdown strategy seems to be better suited for combating crimes of a “non-static” nature than those of a “static” nature. Research limitations/implications Due to the nature of the data used for this research, the performed analysis does not enable a precise determination of whether the crime rates respond to temporal or spatial displacement. Practical implications Considering the obtained results, a re-design of Mexico City’s police crackdown strategy is suggested for the sustained reduction of the number of reported cases of robberies of a static nature. Originality/value Despite their importance, few studies have measured the impact of police crackdowns on city-level crime rates and whether their effect is temporary or permanent. The present study proposes the use of GARCH models in order to integrate the study of this phenomenon into criminal time series models.