This paper offers novel experimental evidence that violent crimes can be successfully reduced by changing the situational environment that potential victims and offenders face. We focus on a ubiquitous but understudied feature of the urban landscape—street lighting—and report the first experimental evidence on the effect of street lighting on crime.
Through a unique public partnership in New York City, temporary street lights were randomly allocated to 40 of the city’s public housing developments.
We find evidence that communities that were assigned more lighting experienced sizable reductions in nighttime outdoor index crimes. We also observe a large decline in arrests indicating that deterrence is the most likely mechanism through which the intervention reduced crime.
Results suggests that street lighting, when deployed tactically, may be a means through which policymakers can control crime without widening the net of the criminal justice system.
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Oil lamps were used to improve nighttime public safety in the Greco-Roman world at least as far back as 500 B.C. and accordingly, it is probably reasonable to conclude that street lighting is an idea that is nearly as old as civilization itself (Ellis 2007).
For important reviews of the limitations of experimental research especially with respect to external validity, see: Deaton (2010), Deaton and Cartwright (2018), Heckman and Smith (1995) and Sampson (2010) for an excellent review that is specific to the study of crime. Also see Nagin and Sampson (2019) for a wonderfully nuanced and equally important discussion of the inherent challenges in identifying a policy-relevant counterfactual in an experimental design.
One potential exception is quasi-experimental research by Arvate et al. (2018) who study a rural electrification program in Brazil and find that electrification which includes improvements to street lighting, led to a reduction in violent crimes in affected communities. However, electrification in a developing country might affect crime through a number of different mechanisms in addition to street lighting.
This research has recently been replicated in Chile and extended by Domınguez and Asahi (2017).
One notable aspect of this field experiment perhaps worth mentioning here was the level of interaction between the City and NYCHA residents during the planning of this project. In early 2016, MOCJ and the research team coordinated a series of meetings with NYCHA residents from treatment developments in order to begin planning the study implementation process. The major goal of these meetings was to receive resident input on where they thought additional lighting would be most beneficial within their development. During these meetings, residents found out how many lights towers would be allocated to their development and were asked to hold a vote at their next tenant’s association meeting on light tower placements for their development. Using resident voting data, the research team produced a “heat map” of residents’ lighting preferences for each development. These maps were presented to NYPD during subsequent meetings to help inform their decision-making about lighting placement. NYCHA residents and NYPD officers also provided constant feedback about the lighting conditions (e.g., excessive or insufficient lighting in specific locations) within the developments, resulting in frequent movement of light towers throughout the study period.
With respect to the implications that the latter feature of the intervention has for external validity, we note that demonstration effects are a common feature of place-based crime reduction strategies. For instance, consider a hot spots policing intervention which is designed to maximize the deterrence value of available police officers by making their presence as visible as possible. Such an intervention might impact crime by changing the probability that an offender is apprehended but it might also signal that an area is a priority for city planners or that it is cared for. Naturally, a hot spots policing intervention which places less priority on the visibility of police patrols might have different effects. Given that the intervention described in this research operates by increasing the amount of ambient lighting and potentially also via a demonstration effect, the results are most readily applicable to a tactical lighting intervention rather than a permanent change to urban infrastructure.
We show, in Online Appendix Figure 1, that these 80 developments tend to be drawn from the top of the distribution of developments, ranked by outdoor nighttime crimes.
In practice, one development (East River) was randomized into the control group but subsequently received a randomized dosage of lights because of operational considerations. Additionally, one control development (Smith) received some lights post-dosage randomization. We report intention-to-treat results throughout the paper.
In order to determine whether a complaint occurred during daytime or nighttime hours, we use daily data on civil twilight hours—those hours in which natural sunlight is present. Civil twilight generally begins approximately half an hour after the official sunset and ends approximately half an hour before the sunrise.
As is noted by Casella et al. (2013), there is a bias-variance trade-off associated with the choice of k in k-fold cross-validation. Setting k = 5 has been shown empirically to yield test error rate estimates that suffer neither from excessively high bias nor from very high variance.
A challenge in applying LASSO to our data is that the sample size is relatively small and the outcome is fairly noisy. As a result, the variables selected by the LASSO can be sensitive to how the data are randomly partitioned into the five folds. To ensure the stability and robustness of the estimates, we re-run the LASSO 500 times, each time retaining the subset of selected variables. This is done to ensure that a single iteration of the LASSO does not lead to an unusual partitioning of the data and, therefore, a misleading estimate of the treatment effect.
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We are grateful to the New York City Police Department for making available the data upon we used. The data were provided by and belong to the NYPD. Any further use of these data must be approved by the NYPD. We are also grateful to the New York City Mayor’s Office of Criminal Justice for coordinating this study and to the New York City Housing Authority for coordinating logistics,providing invaluable data and facilitating communication with residents. We are also grateful to the Laura and John Arnold Foundation for its generous support of the University of Chicago Crime Lab and for this project. We would like to thank Valentine Gilbert, Melissa McNeill and Anna Solow-Collins for exceptional research assistance. We also thank Roseanna Ander, Robert Apel, Monica Bhatt, Charles Branas, Stuart Buck, Monica Deza, Jennifer Doleac, Katy Falco, Justin Gallagher, David Hafetz, Zubin Jelveh, Jacob Kaplan, Max Kapustin, Mike LaForest, Jens Ludwig, John MacDonald, Vikram Maheshri, Aurelie Ouss, Greg Ridgeway, Nick Sanders and Sarah Tahamont for providing helpful comments on earlier versions of the manuscript. Points of view and opinions contained within this document are those of the authors. They do not necessarily represent those of the Laura and John Arnold Foundation, nor do they necessarily represent the official position or policies of the New York City Police Department.
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Chalfin, A., Hansen, B., Lerner, J. et al. Reducing Crime Through Environmental Design: Evidence from a Randomized Experiment of Street Lighting in New York City. J Quant Criminol (2021). https://doi.org/10.1007/s10940-020-09490-6
- Street lights
- Randomized control trial