Third, we demonstrate this using a matched difference-in-difference method introduced by Mueller and Rauh (2023) but at the local cell level. This method matches treated cells with other untreated cells on the predicted conflict risk before treatment. Treated and untreated units are then analyzed together using a new two-way fixed effects method introduced by Callaway and Sant’Anna (2021). If road completion is selected for de-escalating conflict dynamics, then this would be detected by the local conflict forecast and lead to significantly lower treatment effects. By contrast, and in line with the declared international stabilization strategy for DR Congo of the 2010s (see DFID 2011), we find that controlling for conflict risk during the construction period, if anything, increases the estimated treatment effect of road project completion.

To answer our second question, we use novel techniques to extract information on changes in road quality based on satellite images. This allows us to observe how long road rehabilitation has had effects on road quality, and whether decreasing road quality correlates with an uptake of violence. Our findings can be summarized as follows. First, we see a statistically significant reduction in the incidence of violence after road rehabilitation projects are completed. Depending on the estimation method, we find that the completion of a project reduces violence by around 5-10 percentage points. The association between roads and reduction in violence tends to be the strongest for violence against civilians. Within our sample, the improved quality of transport infrastructure thus has a beneficial effect on conflict dynamics and stabilization (a ’peace dividend’). Second, we observe statistically that the effect of road rehabilitation on the number of violent incidents diminishes significantly after some time. The dynamic treatment effects we estimate around the completion date show that violence is first reduced directly after completion of a road project, but rebounds to pre-rehabilitation levels within three years. These findings are consistent with the suggestion that rehabilitated roads deteriorate again after projects are completed. To further substantiate this, we combine machine learning with thousands of remote sensing data observations to estimate overall road degradation patterns. Doing so, we arrive at a road discount factor of 0.735 per year, meaning that within three years, the road quality of rehabilitated roads on average decreases by 60 percent.<sup>1</sup> Our findings speak back to the literature on the links between transport infrastructure and conflict. Theories on these links vary wildly. On the one hand, road density is often used as a proxy for government control and associated with peace. Bad geography, from this perspective, is seen as an opportunity for rebels and an impediment to international peacekeepers and government security forces (Ruggeri et al. 2016; M ̈uller-Crepon et al. 2021). Faulty transport networks also dampen economic activity that may constitute stumbling blocks to peace and prosperity. On the other hand, transport infrastructure and the ease of access it entails may also increase violence by facilitating the logistics of armed actors, whether rebels or military, and roads may act as magnets for violence (Zhukov 2012; Getmanski et al. 2019; Moreno et al. 2019; Rogall 2021; Voigtl ̈ander and Voth 2022; Gonz ́alez et al. 2023; Raleigh and Hegre 2009). If there are strong hypotheses for both a negative

> 1See section 3.3 for details on the calculation.

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