Frisky business: race, gender and police activity during traffic stops

Abstract

Since the United States Supreme Court laid the foundation for “stop-and-frisk” activity by police departments, a substantial amount of research has explored the behavior of police departments, particularly with respect to race. But previous work rarely focuses on the individual’s probability of receiving a frisk. By exploiting a traffic stop-level dataset from the Pittsburgh Police Department, the marginal effects of assorted driver characteristics are estimated. While the broad characterization of African-American drivers being more likely to receive a frisk remains accurate, several related factors are identified that create a more nuanced picture of a driver’s probability of being frisked. The interaction of the gender of the driver, the time of day of the traffic stop, and the existence of passengers in the stopped vehicle with the race of the driver all impact the probability of receiving a frisk.

This is a preview of subscription content, access via your institution.

Notes

  1. 1.

    For a related discussion in this analysis pertaining to successful versus unsuccessful frisks, please see Sect. 4.3.

  2. 2.

    Note that the rate at which white drivers are frisked is mildly higher even though fewer white drivers were pulled over; see subsequent paragraph for additional race-specific discussion.

  3. 3.

    Indeed, there exists no racial subset of males in any year that receives a lower rate of frisking during a traffic stop than any racial subset of females in any year.

  4. 4.

    Models run solely on 2012 and 2013 data utilizing five race variables produce equivalent results.

  5. 5.

    The author thanks an anonymous referee for this useful suggestion.

  6. 6.

    Note that “Controlled conditions” in Tables 5 and 6 do not constitute the total number of additional variables added to the model but the number of conditions considered—i.e., year fixed effects over three years are three conditions.

  7. 7.

    Another possibility for a greater rate of unsuccessful frisks among African-American drivers is a rational response by African-American drivers to carry fewer items of interest knowing that they have a higher probability of receiving a frisk.

References

  1. Alexander, M. (2012). The new Jim Crow: Mass incarceration in the age of colorblindness. New York: The New Press.

    Google Scholar 

  2. Antonovics, K., & Knight, B. (2009). A new look at racial profiling: Evidence from the Boston police department. Review of Economics and Statistics, 91(1), 163–177.

    Article  Google Scholar 

  3. Berjarano, D. (2001). Vehicle stop study year end report: 2000. San Diego: San Diego Police Department.

    Google Scholar 

  4. Brown, R., & Frank, J. (2006). Race and officer decision making: Examining differences in arrest outcomes between Black and White officers. Justice Quarterly, 23(1), 96–126.

    Article  Google Scholar 

  5. Durlauf, S. (2005). Racial profiling as a public policy question: Efficiency, equity and ambiguity. American Economic Review, 95(2), 132–136.

    Article  Google Scholar 

  6. Engel, R., & Calnon, J. (2004). Examining the influence of drivers’ characteristics during traffic stops with police: Results from a national survey. Justice Quarterly, 21(1), 49–90.

    Article  Google Scholar 

  7. Farrell, A. (2011). Explaining leniency: Organizational predictors of the differential treatment of men and women in traffic stops. Crime and Delinquency (forthcoming).

  8. Ferrandino, J. (2012). The efficiency of frisks in the NYPD, 2004–2010. Criminal Justice Review, 38(2), 149–168.

    Article  Google Scholar 

  9. Geller, A., & Fagan, J. (2010). Pot as pretext: Marijuana, race, and the new disorder in New York City street policing. Journal of Empirical Legal Studies, 7(4), 591–633.

    Article  Google Scholar 

  10. Gelman, A., Fagan, J., & Kiss, A. (2007). An analysis of the New York City police department’s “stop-and-frisk” policy in the context of claims of racial bias. Journal of the American Statistical Association, 102(479), 813–823.

    Article  Google Scholar 

  11. Gilliard-Matthews, S., Kowalski, B., & Lundman, R. (2008). Officer race and citizen-reported traffic ticket decisions by police in 1999 and 2002. Police Quarterly, 11(2), 202–219.

    Article  Google Scholar 

  12. Grogger, J., & Ridgeway, G. (2006). Testing for racial profiling in traffic stops from behind the veil of darkness. Journal of the American Statistical Association, 101(475), 878–887.

    Article  Google Scholar 

  13. Huggins, C. (2011). Traffic stop encounters: Officer and citizen race and perceptions of police propriety. American Journal of Criminal Justice, 37(1), 92–100.

    Article  Google Scholar 

  14. Knowles, J., Persico, N., & Todd, P. (2001). Racial bias in motor vehicle searches: Theory and evidence. Journal of Political Economy, 109(1), 203–229.

    Article  Google Scholar 

  15. Lamberth, J. (1996). In the courts. Washington, DC: American Civil Liberties Union.

    Google Scholar 

  16. Lundman, R., & Kaufman, R. (2003). Driving while black: Effects of race, ethnicity, and gender on citizen self-reports of traffic stops and police actions. Criminology, 41(1), 195–220.

    Article  Google Scholar 

  17. MacDonald, J., Stokes, R., Ridgeway, G., & Riley, K. (2007). Race, neighborhood context and perceptions of injustice by the police in Cincinnati. Urban Studies, 44(13), 2567–2585.

    Article  Google Scholar 

  18. Makowsky, M., & Stratmann, T. (2009). Political economy at any speed: What determines traffic citations? American Economic Review, 99(1), 509–527.

    Article  Google Scholar 

  19. Mauer, M. (2006). Race to incarcerate. New York: The New Press.

    Google Scholar 

  20. Mechan, A., & Ponder, M. (2001). Race and place: The ecology of racial profiling African-American motorists. Paper presented at the annual meetings of the American Sociological Association.

  21. Minnesota v. Dickerson, 508 U.S. 366, 113 S. Ct. 2130, 124 L. Ed. 2d 334 (1993).

  22. Persico, N., & Todd, P. (2006). Generalising the hit rates test for racial bias in law enforcement, with an application to vehicle searches in Wichita. Economic Journal, 116(515), F351–F367.

    Article  Google Scholar 

  23. Ridgeway, G. (2007). Analysis of racial disparities in the New York Police Department’s stop, question and frisk practices. Santa Monica: RAND Corporation.

    Google Scholar 

  24. Ritter, J. 2013. Racial bias in traffic stops: Tests of a unified model of stops and searches. No. 152496, University of Minnesota, Department of Applied Economics.

  25. Rosenfeld, R., Rojek, J., & Decker, S. (2012). Age matters: Race differences in police searches of young and older male drivers. Journal of Research in Crime and Delinquency, 49(1), 31–55.

    Article  Google Scholar 

  26. Ryan, M. (2014). A ticket to ride? Passengers as a determinant of traffic citations. Pittsburgh, PA: Mimeo.

    Google Scholar 

  27. Sklansky, D. (2006). Not your father’s police department: Making sense of the new demographics of law enforcement. Journal of Criminal Law and Criminology, 96(3), 1209–1243.

    Google Scholar 

  28. Skogan, W., & Frydl, K. (2004). Fairness and effectiveness in policing: the evidence. Washington, DC: National Academies Press.

    Google Scholar 

  29. Terry v. Ohio, 392 U.S. 1, 88 S. Ct. 1868, 20 L. Ed. 2d 889 (1968).

  30. Verniero, P., & Zoubeck, P. (1999). Interim report of the state police review team regarding allegations of racial profiling. Trenton, NJ: Attorney General’s Office.

    Google Scholar 

  31. Walker, S. (2000). Searching for the denominator: Problems with police traffic stop data and an early warning system solution. Washington, DC: National Institute of Justice.

    Google Scholar 

  32. Warren, P., Tomaskovic-Devey, D., Smith, W., Zingraff, M., & Mason, M. (2006). Driving while black: Bias processes in racial disparity in police stops. Criminology, 44(3), 709–737.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Matt E. Ryan.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ryan, M.E. Frisky business: race, gender and police activity during traffic stops. Eur J Law Econ 41, 65–83 (2016). https://doi.org/10.1007/s10657-015-9493-0

Download citation

Keywords

  • Frisking
  • Race
  • Traffic stops
  • Gender

JEL Classification

  • K00
  • K42