Simulating spatial crime patterns: What do we learn in standard ecological studies of crime?

Objectives: Given the spatial nature of offender and target behavior, what do standard ecological studies of crime aggregating measures to different geographic units actually tell us? Methods: This study used a simple stylized simulation model of crime patterns based on offenders, an exponential distance decay function based on Euclidean distance to capture their typical mobility patterns when committing offenses, and immobile targets. Results: There were four key results. First, although a measure of targets can explain much of the variance in micro-level models, knowing where offenders live, and their typical distances traveled to offending, greatly improved the model performance. Second, accounting for the typical spatial movement of offenders before aggregating to larger units produces better results based on explanatory power. Third, the explanatory power of targets alone was much weaker when aggregating to larger units despite the fact that the simulated model of crime events was entirely based on micro processes, highlighting that variance explained is distinct from causal processes. Fourth, knowing how offenders behave in target-rich versus target-poor environment impacts the results considerably. Conclusions: The findings demonstrated the consequences of a spatially explicit model of offender and target behavior for ecological studies of crime that aggregate measures to geographic units that are either at the micro-, meso-, or macro-level