Generative Explanations of Crime: Using Simulation to Test Criminological Theory

Abstract

This study demonstrates that computational modeling and, in particular, agent-based modeling (ABM) offers a viable compatriot to traditional experimental methodologies for criminology scholars. ABM can be used as a means to operationalize and test hypothetical mechanisms that offer a potential explanation for commonly observed criminological phenomena. This study tests whether the hypothesized mechanisms of environmental criminology are sufficient to produce several commonly observed characteristics of crime. We present an ABM of residential burglary, simulating a world inhabited by potential targets and offenders who behave according to the theoretical propositions of environmental criminology. A series of simulated experiments examining the impact of these mechanisms on patterns of offending are performed. The outputs of these simulations then are compared with several well-established findings derived from empirical studies of residential burglary, including the spatial concentration of crime, repeat victimization, and the journey to crime curve. The results from this research demonstrate that the propositions of the routine activity approach, rational choice perspective, and crime pattern theory provide a viable generative explanation for several independent characteristics of crime.