I was fortunate enough to be awarded a one-year ESRC Postdoctoral Fellowship with the ‘industrial strategy steer’ award at the London School of Economics for my project titled ‘Using advanced data analytics to assess the spatial causal effects of policing policies and practices’ (I will start in this position on the 1st of October). My principal aim with this fellowship is to test and advance theoretical understanding of some core causal claims of the policing literature. Specifically, I will scrutinise neighbourhood-level and location-based police effects.
There is a substantial heterogeneity in the citizens’ experiences and views regarding police officers but it is yet unclear to what extent this can be attributed to varying policing strategies in different neighbourhoods. By using geo-coded administrative police data, and merging it with public attitudes surveys, my research can identify policing practices that work best in particular neighbourhoods, to provide tailored recommendations to police forces. To identify causal effects, I will use state-of-the-art causal inference techniques, staggered difference-in-differences, multilevel matching, and location-based regression discontinuity designs. In a nutshell, I plan to address one crucial aspect of modern policing: how the causal effects of policing initiatives vary across neighbourhoods with different characteristics?
I will be working on three complementary research projects. The first project will scrutinise the rollout of body-worn video cameras (BWC) by the Metropolitan Police, using the staggered difference-in-differences method. This technique makes several causal effects estimable to test alternative hypotheses, including whether the length of exposure to BWC changes the effect of the policy (i.e., dynamic treatment effect), whether the early adopters of BWC benefited more than others (i.e., selective treatment timing), and whether the period when BWC was introduced (e.g., winter vs spring) had any impact (i.e., calendar time effect).
My second project will analyse the effects of disparities in police stop-and-searches in London, using multilevel matching. This method allows to compare people who differ in police activity in their area, but otherwise live in by and large identical neighbourhoods and possess approximately the same personal characteristics. The emerging results will inform the police about the effects of under- or over-policing certain areas on public confidence in the police.
Finally, my third project will make use of the MOPAC Youth Survey and examine the borough-level police effects on gang-related activities. The special design of the survey permits the study of (1) spill-over effects, which can determine to what extent policing behaviour and/or neighbourhood-level influences of one’s school/home have an impact on gang-related activities and (2) discontinuous treatment-assignments, namely, at the borders of London boroughs where different Command Units operate on each side which can show how the policing strategies used by the various police forces result in being involved in or being exposed to gang-related behaviours.
Stay tuned for updates regarding these projects!