Population-Level Analysis of Residential Burglaries

In this chapter, we replicate previous research aimed at identifying those factors associated with solved residential burglaries, but in a large England and Wales context. A large number of factors were correlated with solved cases, but just 12 are effective solvability factors. This study confirms the findings of previous studies in identifying the following variables as effective solvability factors, a) fingerprints recovered; b) offender seen; c) witness recorded; d) offender’s vehicle sighted; e) offender disturbed; f) description of the suspect is recorded. However, this study advances the list of known solvability factors further by identifying six new variables that were traditionally overlooked and some of which result from advances in science, these are a) footwear marks; b) DNA; c) citizens’ reports on the burglary being in progress, d) the stolen property is recovered; e) articles left the scene by the offender and f) whether a vehicle was stolen in the crime. The magnitude of these effects, measured with standardised mean differences, suggest that the presence of these factors is strongly associated with solvability, some with very large effect sizes often exceeding Cohen’s d = 1.0. The analyses suggest that over 50% of all burglaries had one or more solvability factors present, and having one or more of these solvability factors was associated with over 60% accuracy in detection. If used as a screening tool, this solvability analysis approach Thames Valley Police would be required to investigate just over 40% of cases for investigation, as all other cases are unlikely to be solved. The policy implications of using solvability factors analysis is clear; implementing this approach as a screening tool enables police leaders to choose a suitable cut-off point that will allow an optimal balance between resource usage and detection levels.