Abstract
If and how policing affects crime has long been studied. On the relationship between police force size and crime, different authors come to different conclusions. This study examines the relationship between police resourcing, including workforce size, structure and stability over time using data for 42 police forces in the UK over a 13-year period.We construct two novel panel datasets. The first comprises measures of police workforce Size, Structure and Stability. The second provides measures of both crime frequency and crime severity. Issues of endogeneity make the modelling of the police-crime association complicated. Consequently, we analyse the data using a panel vector autoregression (PVAR) model which is capable of forecasting a temporal sequence of the interdependencies between police-crime relationships.Changes in total police personnel play an important role in reducing both crime frequency and severity, but the findings are more nuanced than this. Results highlight that the structure and stability of police organisations are important although these impacts are not always the same for crime volume and crime severity. We find that increases in frontline (non-sworn) support staff are associated with reductions in crime, while turnover rates of police staff are associated with increases in crime. In contrast, changes to the number of sworn police officers do not appear to be a good predictor of crime volume.The findings suggest that investment in frontline support staff and the development of strategies to retain skills and knowledge by reducing staff turnover may be efficient approaches for Police Forces to maximise the impact on crime of their workforce in resource-pressed policing settings. While previous research has found that police force size has a limited effect on crime, our findings indicate that more nuanced measurements of police resourcing are necessary to understand how police impact upon crime risk. The idea of police forces using basic officer-to-population ratios to make staffing decisions appears outdated and over-simplistic.
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