{"__content__"=>"\n Objective\n \n \n Methods\n \n \n Results\n \n \n Conclusion\n \n ", "p"=>[{"__content__"=>"This study evaluates the impact of acoustic gunshot detection technology (ShotSpotter) on crime rates, emergency call volume, police response times, and case clearance rates in Detroit, Michigan."}, {"__content__"=>"We employ a difference-in-differences design leveraging the staggered rollout of ShotSpotter across Detroit neighborhoods. The treatment group consists of several areas receiving coverage in March 2021, while the control group is comprised of areas covered by ShotSpotter starting in October 2022. Using Detroit Police Department data from January 2017 to October 2022, we estimate Poisson regression models for crime and call volume outcomes and log-linear regression models for police travel times. All models include area and time fixed effects, with robust standard errors."}, {"__content__"=>"ShotSpotter installation is associated with a 6.5% reduction in violent crime (<0.10) but a 8.5% increase in nonviolent crime (<0.1). The technology produces a 322% increase in gunshot-related calls for service and a 10.4% decrease in total non-gunshot Priority 1 calls. There was no significant different in police travel time. We find no significant change in case clearance rates for any crime category.", "i"=>[{"__content__"=>"p"}, {"__content__"=>"p"}]}, {"__content__"=>"While gunshot detection technology reduces violent crime in Detroit, it imposes substantial operational costs through increased call volume and slower response to technology-generated alerts. Municipalities must weigh public safety benefits against resource constraints when considering adoption. The heterogeneous effects across crime types and policing outcomes highlight the need for context-specific cost-benefit analysis."}]}