Replication Data for: Slow Streets and Dockless Travel: Using a Natural Experiment for Insight into the Role of Supportive Infrastructure on Non- Motorized Travel

In the early stages of the COVID-19 pandemic, cities across the globe converted street space to non-automobile uses. We study four of these slow street programs in the U.S., in Los Angeles, Portland, Oakland, and San Francisco. In each city, we use the slow streets (implemented in late spring to early fall 2020) as a treatment, and compare those slow streets to non-implemented control groups. Our dependent variable is counts of dockless scooter trips passing a mid-block screenline for time periods both before and after slow street implementation. We obtained those dockless scooter counts from historical data provided by Lime, a dockless scooter provider in each of our study cities. We use two methodological approaches: differences-in-differences (DID) and panel regression analysis with block fixed effects. For the DID analysis, we use networks of candidate slow streets that were not implemented as the control group. Such control networks were available in Los Angeles, Oakland, and San Francisco. For the panel analysis, we use slow street segments implemented later in our study period as control segments for earlier implemented slow street segments, including fixed effects for blocks and for time periods in the panel regressions. We find statistically significant associations between increased dockless scooter trips and slow street implementation in each study city, using both DID and panel analyses. The associations are robust to different specifications. We calculate the magnitude of the slow street treatment effect by dividing the estimated treatment effect by a 2019 baseline of dockless trip counts. In the DID analysis, we find that slow street implementation increased dockless scooter trip counts by from 54.78% to 74.5% relative to a 2019 (before slow streets) baseline. In the panel analysis, the increase in dockless trip counts on slow streets ranged from 10.77% to 16.75% relative to a 2019 baseline.