Quantifying the causal effects of 20 mph zones on road casualties in London via doubly robust estimation

• A panel data set of 234 20 mph zones in London is constructed.
• Results from four causal methods including the doubly robust are compared.
• The treatment assignment is related to deprivation, population and land use.
• A reduction of 24% in KSI is found in 20 mph zones.
• The treatment is more effective for pedestrian than cyclists.

This paper estimates the causal effect of 20 mph zones on road casualties in London. Potential confounders in the key relationship of interest are included within outcome regression and propensity score models, and the models are then combined to form a doubly robust estimator. A total of 234 treated zones and 2844 potential control zones are included in the data sample. The propensity score model is used to select a viable control group which has common support in the covariate distributions. We compare the doubly robust estimates with those obtained using three other methods: inverse probability weighting, regression adjustment, and propensity score matching. The results indicate that 20 mph zones have had a significant causal impact on road casualty reduction in both absolute and proportional terms.