Could Innovations in Policing have Contributed to the New York City Crime Drop even in a Period of Declining Police Strength?: The Case of Stop, Question and Frisk as a Hot Spots Policing Strategy

Abstract

Available data make it impossible to reach strong conclusions about the role of policing in the New York crime decline. Instead, we examine whether innovations implemented in New York fit with what is known about effective policing strategies. Our main analysis focuses on how the New York City Police Department (NYPD) could have continued to contribute to the crime drop over the last decade when the number of police declined significantly. We examine geographic data on crime and stop, question and frisks (SQFs) to show that SQFs are concentrated at crime hot spots. We also show that the NYPD increased these specific hot spots policing strategies despite declining numbers. In our discussion, we speculate on whether this “doing more with less” could be an explanation for the continued crime drop in New York, noting the limitations of drawing conclusions from existing data. We also raise concerns about possible backfire effects of SQF hot spots approaches.

Keywords:

• crime decline
• stop, question and frisk
• police innovation
• hot spots policing
• New York City

Notes

An earlier version of this paper was prepared for the “Understanding the Crime Decline in NYC” conference funded by the Open Society Institute. The authors thank Assistant Commissioner Philip McGuire of the New York City Police Department for his help in gaining and interpreting crime incident data at the address level. We also thank the anonymous reviewers for their helpful comments and suggestions.

1. UCR data were gathered from the annual Crime in the United States report and from the FBI’s UCR website at http://www.fbi.gov/about-us/cjis/ucr/ucr

2. The decline is even greater, just over 40%, when comparing 2001-2009. Violent crime increased slightly in New York City in 2010, but declined again in 2011.

3. See a description of these changes in NYPD management at http://council.nyc.gov/html/budget/PDFs/2012/police.pdf and http://www.factcheck.org/cop-counting_cop-out.html.

4. Beginning in 1996, some of this increase resulted from funding from the Office of Community Oriented Policing Services (COPS).

5. See the overviews by White (2012) and Chauhan (2011) for more on the contribution of the police to the crime decline and the strategies of the NYPD. See Telep and Weisburd (2012) for a more detailed description of effective strategies for policing.

6. See http://www.campbellcollaboration.org/reviews_crime_justice/index.php

7. See http://home2.nyc.gov/html/unccp/gprb/downloads/pdf/NYC_Safety%20and%20Security_OperationImpact.pdf.

8. For examples of how SQFs are an important tactic in Operation Impact, see Ridgeway’s (2007: 3) discussion of whether or not Operation Impact officers understand how to properly fill out SQF paperwork and Smith and Purtell’s (2008) analysis of the impact of police stops as part of Operation Impact on precinct-level crime rates.

9. Identifying a map of all intersections across the five boroughs raised some challenges. Efforts were made to be sure that we were able to identify a population of the intersections, as well as be sure that they were in fact “true intersections,” or intersections that indicated the conjunction of two or more streets. In order to do this, the New York City Department of City Planning (DCP) LION shapefile was used to create a map of all intersections of street segments in the city. Then, creating a buffer around each of these points, it was determined whether the surrounding streets composed only a single street (i.e. a sharp turn, or extended road), or were in fact composed of multiple streets, indicating the conjunction of multiple streets coming together. There were an estimated 53,857 true intersections in the five borough area. Street segments were defined as both sides of the street between two intersections. The initial GIS shapefile used was the DCP LION file. However, the structure of the file was modified due to the inflated number of records in the database. This was the result of multiple records being used to characterize a single street segment. In order to alleviate this concern, streets were first merged by both their name and proximity and then secondly split by true intersections that indicated the conjunction of two or more streets. This resulted in an estimate of 109,468 valid street segments, excluding alleys, paths, and private streets, as well as highways and interstates.

10. While it is possible to randomly assign the events at intersections to the street segments involved for the purposes of statistical analysis, this strategy has its drawbacks. For example, it could artificially inflate the crime rate (or SQF rate) for low crime street segments attached to a high crime intersection, especially in a situation where the crime is “flowing” from other participating segments to the intersection but is mostly unrelated to the low crime segment.

11. It is tempting to try to assess whether the correlations between crime and SQFs change over time as an indicator of the crime prevention effectiveness of such strategies. As we noted earlier in the paper, we think that an assessment of the role of the police in the crime decline is strongly hindered by the lack of adequate data on possible confounding causes. However, one could, for example, examine a time series to see whether crime declines as a result of increases in SQFs. Such an analysis would have to pay particular attention to multiple possible time spans used for analysis, and the possible displacement and diffusion of benefit effects associated with SQFs in nearby spatial units. This exercise is beyond the scope of the present paper. Nonetheless, we have requested from the NYPD crime data for a longer time series that would allow exploration of these approaches.

12. We bounded these estimates at 0 crime incidents.

13. Assistant Commissioner Phil McGuire suggested that subtracting such incidents may also create bias, as SQFs may result from an emergency call to the police identifying problematic behavior.

14. The skew of SQFs to intersections may just reflect the ease of identification for officers. In turn, the SQF reporting form provides the intersection as a clear option for recording SQFs, making it easy for officers to choose this outcome.

15. Because the large number of zeros may inflate the significance statistics, we also estimated significance using a negative binomial distribution. The results are still highly significant.

16. It is interesting to note that in personal correspondence with the authors, Assistant Commissioner Philip McGuire has argued that the NYPD was interested in police analysis of data but researchers did not seem interested: “After the first year of Compstat the originators (Bratton, Maple, etc.) were initially surprised at the magnitude of the drop in crime. At that time we looked at a lot of potential changes in the city’s characteristics and environment and none had changed in anything like the magnitude of the crime drop. Some had even gone in a direction that might suggest an increase in crime. That data was tabulated and provided to the National Institute of Justice (NIJ) and the attendees of a workshop held by NIJ at which Commissioner Bratton presented. It is interesting that after that presentation (Fall 1995 I think) a far as I know there was no interest from researchers or NIJ in working with the NYPD to investigate the reductions.”

Additional information

Notes on contributors

David Weisburd

David Weisburd is the Walter E. Meyer professor of Law and Criminal Justice at the Hebrew University Law School in Jerusalem, and a distinguished professor of Criminology, Law and Society at George Mason University and director of its Center for Evidence-Based Crime Policy. He has had a career interest in police effectiveness. He is the recipient of the 2010 Stockholm Prize in Criminology and the 2011 Klachky Family Award for the Advancement of the Frontiers of Science.

Cody W. Telep

Cody W. Telep is a doctoral student in the Department of Criminology, Law and Society at George Mason University and a research assistant in the Center for Evidence-Based Crime Policy. He received an MA from the Department of Criminology and Criminal Justice at the University of Maryland in 2008.  His research interests include innovations in policing, police education, and evidence-based policy. His publications have appeared in Justice Quarterly, Journal of Criminal Justice Education, Journal of Experimental Criminology, Police Quarterly, and Criminology and Public Policy.

Brian A. Lawton

Brian A. Lawton is an assistant professor in the Department of Criminology, Law and Society at George Mason University and is co-director of the Research Program on Crime and Place at the Center for Evidence-Based Crime Policy. He received his B.A. from Rhode Island College and his M.A. and Ph.D. from Temple University. His research interests include crime and place as well as police discretion and accountability. His publications have appeared in Justice Quarterly, Journal of Research in Crime and Delinquency, Journal of Quantitative Criminology, Crime & Delinquency, and Journal of Criminal Justice.