Three waves from Understanding Society (2012, 2015 and 2018)

– necessary to observe changes in neighbourhoods across time

– remove those who moved to a different address

– lots of attrition (about 60% missing in 2015 and 90% in 2018)

– adjusted using multiple imputation

Subjective measures of motor traffic and perceptions of crime

– derived from the interviewer and the interviewee

– which eliminates methods effects

We model the within-person change across time

– control for average change in perceptions of crime across time

We focus on the total effect of traffic on crime

– and indirect effects through social capital and disorder

Total effects

– when a neighbourhood goes from “non-heavy traffic” to “heavy traffic”…

– we estimate an 8.6%, 6.4% and 6.9% increase in perceptions of vandalism, theft, and violence

Mediating effects

– traffic leads to perceptions of disorder (graffity, litter, and boarded houses)

– and undermines social capital (whether neighbours are perceived to help each other)

– these in turn increase perceptions of crime

A “small” confounder could render our findings non-significant

– our robustness values range from 2.8% to 4%

We cannot anticipate an obvious time-changing confounder

– we cannot rule it out either

Interviewee’s records of ‘heavy traffic’ are noisy

– can see this as classical measurement error

– leads to attenuation bias (roughly) proportional to the errors

– e.g. a reliability of 0.8, attenuates our estimates by 1.2

Motor traffic appears to have a causal effect on street crime

– to some extent mediated through disorder and social capital

LTN initiatives are likely more beneficial than we thought

Crime prevention policy needs to recognise the criminogenic effect of motor traffic

– Secured by Design HOMES should be reconsidered

– e.g. culs-de-sac might be less affected burglaries but they likely force higher crime elsewhere by encouraging driving