# **1 Introduction**

Historically, curfews have been used to manage social unrest and control crime, looting and violence. Often, they have been used to contain specific populations, especially young people. Their effectiveness in achieving public safety goals remains ambiguous, with some research finding decreases in crime, while others find curfews lead to increases in gun violence (Carr & Doleac, 2018; Kline, 2012). Curfews can have significant direct costs on freedom of movement, assembly and expression, especially when enforcement resorts to violence (Ravindran & Shah, 2023; Katana et al., 2021). Their indirect costs are even less well understood. The use of curfews must thus be carefully scrutinized and their effects, especially unintended ones, must be rigorously measured.

During COVID, more than 100 countries resorted to lockdowns and curfews to manage the spread of the virus. However, their justification did not have an empirical or theoretical underpinning. First, was the use of curfews during the onset of the pandemic justified? Did curfews reduce assembly or simply displace and concentrate assembly from night to daytime, potentially increasing transmission? Curfews appear to have had little impact on slowing the pandemic (de Haas et al., 2022; Huber & Langen, 2020) and may have even increased the spread of disease as individuals shifted activities to pre-curfew hours, increasing contact-density during these times (Sprengholz et al., 2021). Second, what were the effects of curfews on mobility and what was the effect of that change on other economic outcomes? For instance, did curfews reduce the volume of cars and road crashes, or did they lead to an increase in speeds and car crashes? Providing evidence on these questions is important for preventing the use of policy instruments in future pandemics and crises that are inherently costly as well as ineffective.

In this study, we shed some light on the question of whether curfews affect road safety. This is important because the cost of road safety is measured in people’s lives just as is done in pandemics. The context we use is Nairobi, a capital in a low- and middle-income (LMIC) country with high rates of car crashes, and where we have made a multiyear investment in data infrastructure for urban management that turned a data-poor into a relatively data-rich environment.

A small pre-COVID literature looks at curfews used in various contexts to curb night driving by inexperienced drivers. This is effective in reducing crashes (Williams & Preusser, 1997). Even when inexperienced drivers fully substitute night with day driving, crashes are reduced (Bolduc et al., 2013). Here we investigate what happens when these restrictions are extended to all drivers. The question we ask is whether the reduction of cars on the road mechanically decreases the number of car crashes, or whether the curfew displaces driving, increases speeds and has a rebound effect on car crashes.

In our context, the dusk-to-dawn curfew was implemented in March 2020 purportedly to prevent the spread of COVID-19. We use a double-difference strategy, harnessing detailed high-frequency data on road traffic crashes, to look at crashes before and after the curfew implementation and relative to the same period a year earlier. In so doing, 2