A group at the University of Pennsylvania looked for statistical evidence that “eyes on the street” are a deterrent to crime. The results are a bit puzzling, as real world data often can be.
Statistical analyses of urban environments have been recently improved through publicly available high resolution data and mapping technologies that have adopted across industries. These technologies allow us to create metrics to empirically investigate urban design principles of the past half-century. Philadelphia is an interesting case study for this work, with its rapid urban development and population increase in the last decade. We focus on features of what urban planners call vibrancy: measures of positive, healthy activity or energy in an area. Historically, vibrancy has been very challenging to measure empirically. We explore the association between safety (violent and non-violent crime) and features of local neighborhood vibrancy such as population, economic measures and land use zoning. Despite rhetoric about the negative effects of population density in the 1960s and 70s, we find very little association between crime and population density. Measures based on land use zoning are not an adequate description of local vibrancy and so we construct a database and set of measures of business activity in each neighborhood. We employ several matching analyses within census block groups to explore the relationship between neighborhood vibrancy and safety at a higher resolution. We find that neighborhoods with more vacancy have higher crime but within neighborhoods, crimes tend not to be located near vacant properties. We also find that more crimes occur near business locations but businesses that are active (open) for longer periods are associated with fewer crimes.
This is particularly fascinating to me because I live my life in the middle of this particular data set and am part of it. So it is very interesting to compare what the data seem to be saying with my own experiences and impressions.
The lack of correlation between population density and crime is not surprising. Two neighborhoods with identical density can be drastically different. The correlation between poverty and crime is not surprising – people who are not succeeding in the formal economy and who are not mobile turn to the informal economy, in other words drug dealing, loan sharking and other illegal ways of trying to earn an income. If they are successful at earning an income, they tend to have a lot of cash around, and other people who know about the cash will take advantage of them, knowing they will not go to the police. Other than going to the police, the remaining options are to be taken advantage of repeatedly, or to retaliate. This is how violence escalates, I believe, and it goes hand in hand with development of a culture that tolerates and even celebrates violence, in a never-ending feedback loop.
The puzzling part comes when they try to drill down and look at explanatory factors at a very fine spatial scale. They found a correlation between crime and mixed use zoning, which appears to contradict the idea that eyes on the street around the clock will help to deter crime. And they found more crime around businesses like cafes, restaurants, bars and retail shops. They found that longer open hours seemed to have some deterrent effect on crime relative to shorter open hours.
I think they have made an excellent effort to do this, and I am not sure it can be done a lot better, but I will point out one idea I have. They talk about some limitations and nuances of their data, but one they do not mention is the idea that they are looking at reported crimes, most likely police reports or 911 calls. It could be that business owners, staff and patrons are much more likely to call 911 and report a crime than are residential neighbors. The business staff and patrons may see this as being in the economic interest, increasing the safety of their families, and the (alleged) criminals they are reporting are generally strangers. In quieter all-residential neighborhoods, people may not observe as many of the crimes that do occur (fewer “eyes on the street”), they may prefer not to report crimes either through a sense of loyalty to one’s neighbors, minding one’s own business, quid pro quo, or in some cases a fear of retaliation. There is also the factor of some demographic groups trusting the police more than others, although the authors’ statistical attempts to control for demographics may tend to factor this out.