Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Officer bias, over-patrolling and ethnic disparities in stop and search


Black and Asian people in the United Kingdom are more likely to be stopped and searched by police than White people. Following a panel of 36,000 searches by 1,100 police officers at a major English police force, we provide officer-specific measures of over-searching relative to two baselines: the ethnic composition of crime suspects officers interact with and the ethnic composition of the areas they patrol. We show that the vast majority of officers over-search ethnic minorities against both baselines. But we also find that the over-searching by individual officers cannot account for all of the over-representation of ethnic minorities in stop and search: over-patrolling of minority areas is also a key factor. Decomposing the overall search bias, we find that the over-representation of Asian people in stop and search is primarily accounted for by over-patrolling, while the over-representation of Black people is a combination of officer and patrol effects, with the larger contribution coming from biases of officers.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Posterior densities of search shares.
Fig. 2: Posterior densities of the coefficients used to infer search shares p.
Fig. 3: Posterior densities of \({D}_{ite}^{\mathrm{S}}\) and \({D}_{ite}^{\mathrm{P}}\) aggregated over all officers and time periods.
Fig. 4: Histograms of the posterior probabilities of officer over-searching relative to suspects and patrol.
Fig. 5: Decomposition of over-searching into officer over-searching, over-patrolling and aggregation discrepancy.

Data availability

This research is based on data resources provided by West Midlands Police. Data were originally collected as part of routine police record-keeping. The data are not publicly available and were provided to the authors under an Information Sharing Agreement with West Midlands Police. Under the terms of this agreement, the authors are not at liberty to share the data. Other researchers can contact West Midlands Police to obtain a data-sharing agreement.

Code availability

All the code used to produce the results is available online on Github at Since the original data from West Midlands Police may not be publicly shared, we generated synthetic data to demonstrate our code. The repository includes a folder, “/data”, that contains the synthetic data as well as the file “code/generate_synthetic_data.R” used to generate the data. The distributions of the variables in the synthetic data match the distributions in our data.


  1. 1.

    Home Office. Police Powers and Procedures England and Wales Year Ending 31 March 2018 (Home Office Statistical Bulletin, 2018).

  2. 2.

    Quinton, P. The formation of suspicions: police stop and search practices in England and Wales. Polic. Soc. 21, 357–368 (2011).

    Article  Google Scholar 

  3. 3.

    Brayne, S. Big data surveillance: the case of policing. Am. Sociol. Rev. 82, 977–1008 (2017).

    Article  Google Scholar 

  4. 4.

    May, T, Gyateng, T. & Hough, M. Differential Treatment in the Youth Justice System (Equality and Human Rights Commission, 2010).

  5. 5.

    Kohler-Hausmann, I. Misdemeanor justice: control without conviction. Am. J. Sociol. 119, 351–393 (2013).

    Article  Google Scholar 

  6. 6.

    Sharp, D. & Atherton, S. To serve and protect? The experiences of policing in the community of young people from black and other ethnic minority groups. Br. J. Criminol. 47, 746–763 (2007).

    Article  Google Scholar 

  7. 7.

    Lerman, A. E. & Weaver, V. Staying out of sight? Concentrated policing and local political action. Ann. Am. Acad. Pol. Soc. Sci. 651, 202–219 (2014).

    Article  Google Scholar 

  8. 8.

    Tyler, T. R., Fagan, J. & Geller, A. Street stops and police legitimacy: teachable moments in young urban men’s legal socialization. J. Empir. Leg. Stud. 11, 751–785 (2014).

    Article  Google Scholar 

  9. 9.

    Bradford, B. in Stop and Search: The Anatomy of a Police Power (eds Delsol, R. & Shiner, M.) 102–122 (Palgrave Macmillan, 2015).

  10. 10.

    Bradford, B. Stop and Search and Police Legitimacy (Routledge, 2017).

  11. 11.

    Laniyonu, A. Police, politics and participation: the effect of police exposure on political participation in the United Kingdom. Br. J. Criminol. 58, 1232–1253 (2018).

    Article  Google Scholar 

  12. 12.

    Skogan, W. G. Asymmetry in the impact of encounters with police. Polic. Soc. 16, 99–126 (2006).

    Article  Google Scholar 

  13. 13.

    Geller, A., Fagan, J., Tyler, T. & Link, B. G. Aggressive policing and the mental health of young urban men. Am. J. Public Health 104, 2321–2327 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Delsol, R. in Stop and Search: The Anatomy of a Police Power (eds Delsol, R. & Shiner, M) 79–101 (Palgrave Macmillan, 2015).

  15. 15.

    Sampson, R. J. & Lauritsen, J. L. Racial and ethnic disparities in crime and criminal justice in the United States. Crime Justice 21, 311–374 (1997).

    Article  Google Scholar 

  16. 16.

    Shiner, M., Carre, Z., Delsol, R. & Eastwood, N. The Colour of Injustice: ‘Race’, Drugs and Law Enforcement in England and Wales (StopWatch & Release, 2018).

  17. 17.

    Shiner, M. Post-Lawrence policing in England and Wales: guilt, innocence and the defence of organizational ego. Br. J. Criminol. 50, 935–953 (2010).

    Article  Google Scholar 

  18. 18.

    Stop and Think Again, Towards Equality in Police PACE Stop and Search (Equality and Human Rights Commission, 2013).

  19. 19.

    It Can be Stopped: A Proven Blueprint to Stop Violence and Tackle Gang and Related Offending in London and Beyond (The Centre for Social Justice, 2018).

  20. 20.

    Scarman, L. G. The Brixton Disorders, 10–12th April 1981 (Her Majesty’s Stationary Office, 1981).

  21. 21.

    Macpherson, W. The Stephen Lawrence Inquiry (Home Office, 1999).

  22. 22.

    Delsol, R. & Shiner, M. Regulating stop and search: a challenge for police and community relations in England and Wales. Crit. Criminol. 14, 241–263 (2006).

    Article  Google Scholar 

  23. 23.

    Bowling, B. & Phillips, C. Disproportionate and discriminatory: reviewing the evidence on police stop and search. Mod. Law Rev. 70, 936–961 (2007).

    Article  Google Scholar 

  24. 24.

    Ward, L., Nicholas, S. & Willoughby, M. An Assessment of the Tackling Knives and Serious Youth Violence Action Programme (TKAP)—Phase II. Tech. Rep. 53 (Home Office, 2011).

  25. 25.

    McCandless, R., Feist, A., Allan, J. & Morgan, N. Do Initiatives Involving Substantial Increases in Stop and Search Reduce Crime? Assessing the Impact of Operation BLUNT 2 (Home Office, 2016).

  26. 26.

    Weisburd, D., Wooditch, A., Weisburd, S. & Yang, S.-M. Do stop, question, and frisk practices deter crime? Evidence at microunits of space and time. Criminol. Public Policy 15, 31–56 (2016).

    Article  Google Scholar 

  27. 27.

    MacDonald, J., Fagan, J. & Geller, A. The effects of local police surges on crime and arrests in New York City. PLoS ONE 11, e0157223 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  28. 28.

    Tiratelli, M., Quinton, P. & Bradford, B. Does stop and search deter crime? Evidence from ten years of London-wide data. Br. J. Criminol. 58, 1212–1231 (2018).

    Article  Google Scholar 

  29. 29.

    Quinton, P., Bland, N. & Miller, J. Police Stops, Decision-Making and Practice (Home Office, 2000).

  30. 30.

    Rudovsky, D. Law enforcement by stereotypes and serendipity: racial profiling and stops and searches without cause. Univ. Pa J. Const. Law 3, 296–366 (2001).

    Google Scholar 

  31. 31.

    Stop and Search Powers: Are the Police Using Them Effectively and Fairly? (Her Majesty’s Inspectorate of Constabulary, 2013).

  32. 32.

    Phillips, C. & Bowling, B. in Oxford Handbook of Criminology 4th edn (eds Maguire, M. et al.) 579–619 (Oxford Univ. Press, 2007).

  33. 33.

    Smith, S. J. Crime, Space and Society (Cambridge Univ. Press, 1986).

  34. 34.

    Elliott, D. S. Lies, Damn Lies, and Arrest Statistics (Institute of Behavioral Science, Regents of the University of Colorado, 1995).

  35. 35.

    Fagan, J. & Davies, G. Street stops and broken windows: Terry, race, and disorder in New York City. Fordham Urb. Law J. 28, 457–504 (2000).

    Google Scholar 

  36. 36.

    Kane, R. J. Social control in the metropolis: a community-level examination of the minority group-threat hypothesis. Justice Q. 20, 265–295 (2003).

    Article  Google Scholar 

  37. 37.

    Lammy, D. The Lammy Review: An independent review into the treatment of, and outcomes for, Black, Asian and Minority Ethnic individuals in the Criminal Justice System (Ministry of Justice, 2017).

  38. 38.

    Gounev, P. & Bezlov, T. The Roma in Bulgaria’s criminal justice system: from ethnic profiling to imprisonment. Crit. Criminol. 14, 313–338 (2006).

    Article  Google Scholar 

  39. 39.

    Richardson, R., Schultz, J. & Crawford, K. Dirty data, bad predictions: how civil rights violations impact police data, predictive policing systems, and justice. NYU Law Rev. Online 94, 15–55 (2019).

    Google Scholar 

  40. 40.

    Mawby, R. C. & Wright, A. in Handbook of Policing 2nd edn (ed. Newburn, T.) 224–228 (Taylor & Francis, 2008).

  41. 41.

    Oberfield, Z. W. Socialization and self-selection: how police officers develop their views about using force. Adm. Soc. 44, 702–730 (2012).

    Article  Google Scholar 

  42. 42.

    Smith, D. J. & Gray, J. Police and People in London: The PSI Report (Gower Publishing, 1985).

  43. 43.

    Waddington, P. A. Police (canteen) sub-culture. An appreciation. Br. J. Criminol. 39, 287–309 (1999).

    Article  Google Scholar 

  44. 44.

    Eberhardt, J. L., Goff, P. A., Purdie, V. J. & Davies, P. G. Seeing Black: race, crime, and visual processing. J. Pers. Soc. Psychol. 87, 876–893 (2004).

    PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Alpert, G. P., MacDonald, J. M. & Dunham, R. G. Police suspicion and discretionary decision making during citizen stops. Criminology 43, 407–434 (2005).

    Article  Google Scholar 

  46. 46.

    Warren, P., Tomaskovic-Devey, D., Smith, W., Zingraff, M. & Mason, M. Driving while Black: bias processes and racial disparity in police stops. Criminology 44, 709–738 (2006).

    Article  Google Scholar 

  47. 47.

    Correll, J. et al. Across the thin blue line: police officers and racial bias in the decision to shoot. J. Pers. Soc. Psychol. 92, 1006–1023 (2007).

    PubMed  Article  PubMed Central  Google Scholar 

  48. 48.

    Morris, W., Burden, A. & Weekes, A. The Report of the Morris Inquiry—The Case for Change: People in the Metropolitan Police Service (Metropolitan Police Authority, 2004).

  49. 49.

    American Civil Liberties Union (ACLU). The Persistence of Racial and Ethnic Profiling in the United States (Rights Working Group, 2009).

  50. 50.

    Adebowale, V. Independent Commission on Mental Health and Policing Report (Independent Commission on Mental Health and Policing, 2013).

  51. 51.

    Quinton, P. in Stop and Search: The Anatomy of a Police Power (eds Delsol, R. & Shiner, M.) 57–78 (Palgrave Macmillan, 2015).

  52. 52.

    Lea, J. The Macpherson report and the question of institutional racism. Howard J. Crim. Justice 39, 219–233 (2000).

    Article  Google Scholar 

  53. 53.

    Reiner, R. The Politics of the Police (Oxford Univ. Press, 2010).

  54. 54.

    Shiner, M. in Stop and Search: The Anatomy of a Police Power (eds Delsol, R. & Shiner, M.) 146–169 (Palgrave Macmillan, 2015).

  55. 55.

    Shiner, M. & Thornbury, P. Regulating Police Stop and Search: An Evaluation of the Northamptonshire Police Reasonable Grounds Panel (Open Society Justice Initiative, 2019).

  56. 56.

    Sekhon, N. Dangerous warrants. Washington Law Rev. 93, 967–1017 (2018).

    Google Scholar 

  57. 57.

    Ross, C. T. A multi-level Bayesian analysis of racial bias in police shootings at the county-level in the United States, 2011–2014. PLoS ONE 10, e0141854 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  58. 58.

    Edwards, F., Esposito, M. H. & Lee, H. Risk of police-involved death by race/ethnicity and place, United States, 2012–2018. Am. J. Public Health 108, 1241–1248 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Cesario, J., Johnson, D. J. & Terrill, W. Is there evidence of racial disparity in police use of deadly force? Analyses of officer-involved fatal shootings in 2015–2016. Soc. Psychol. Personal. Sci. 10, 586–595 (2019).

    Article  Google Scholar 

  60. 60.

    Johnson, D. J., Tress, T., Burkel, N., Taylor, C. & Cesario, J. Officer characteristics and racial disparities in fatal officer-involved shootings. Proc. Natl Acad. Sci. USA 116, 15877–15882 (2019).

    CAS  PubMed  Article  Google Scholar 

  61. 61.

    Fryer Jr, R. G. An Empirical Analysis of Racial Differences in Police Use of Force. Tech. Rep. 22399 (National Bureau of Economic Research, 2016).

  62. 62.

    Ross, C. T., Winterhalder, B. & McElreath, R. Resolution of apparent paradoxes in the race-specific frequency of use-of-force by police. Palgrave Commun. 4, 61 (2018).

    Article  Google Scholar 

  63. 63.

    Simpson, E. H. The interpretation of interaction in contingency tables. J. R. Stat. Soc. Series B Methodol. 13, 238–241 (1951).

    Google Scholar 

  64. 64.

    Neil, R. & Winship, C. Methodological challenges and opportunities in testing for racial discrimination in policing. Annu. Rev. Criminol. 2, 73–98 (2018).

    Article  Google Scholar 

  65. 65.

    Gelman, A., Fagan, J. & Kiss, A. An analysis of the New York City Police department’s ‘stop-and-frisk’ policy in the context of claims of racial bias. J. Am. Stat. Assoc. 102, 813–823 (2007).

    CAS  Article  Google Scholar 

  66. 66.

    Ridgeway, G. Analysis of Racial Disparities in the New York Police Department’s Stop, Question, and Frisk Practices (Technical Report) (Rand Corporation, 2007).

  67. 67.

    Pierson, E. et al. A large-scale analysis of racial disparities in police stops across the united states. Nat. Human Behav. 4, 736–745 (2020).

    Article  Google Scholar 

  68. 68.

    Alpert, G. P., Smith, M. R. & Dunham, R. G. Toward a better benchmark: assessing the utility of not-at-fault traffic crash data in racial profiling research. Justice Res. Policy 6, 43–69 (2004).

    Article  Google Scholar 

  69. 69.

    Lamberth, J. Revised Statistical Analysis of the Incidence of Police Stops and Arrests of Black Drivers/Travelers on the New Jersey Turnpike Between Exits or Interchanges 1 and 3 from the Years 1988 through 1991 (Lamberth Consulting, 1994).

  70. 70.

    Lamberth, J. C. Racial Profiling Data Analysis Study: Final report for the San Antonio Police Department (Lamberth Consulting, 2005).

  71. 71.

    Rojek, J., Rosenfeld, R. & Decker, S. Policing race: the racial stratification of searches in police traffic stops. Criminology 50, 993–1024 (2012).

    Article  Google Scholar 

  72. 72.

    Withrow, B. L. & Williams, H. Proposing a benchmark based on vehicle collision data in racial profiling research. Criminal Justice Rev. 40, 449–469 (2015).

    Article  Google Scholar 

  73. 73.

    Ridgeway, G. & MacDonald, J. M. Doubly robust internal benchmarking and false discovery rates for detecting racial bias in police stops. J. Am. Stat. Assoc. 104, 661–668 (2009).

    CAS  Article  Google Scholar 

  74. 74.

    Home Office. CODE A—Revised Code of Practice for the Exercise by: Police Officers of Statutory Powers of Stop and Search (Her Majesty’s Stationary Office, 2014).

  75. 75.

    Office for National Statistics. Census Geography—An Overview of the Various Geographies used in the Production of Statistics Collected via the UK Census. Office for National Statistics (2016).

  76. 76.

    Simoiu, C., Corbett-Davies, S. & Goel, S. The problem of infra-marginality in outcome tests for discrimination. Ann. Appl. Stat. 11, 1193–1216 (2017).

    Article  Google Scholar 

  77. 77.

    Knox, D., Lowe, W. & Mummolo, J. Administrative records mask racially biased policing. Am. Political Sci. Rev. 114, 619–637 (2020).

    Article  Google Scholar 

  78. 78.

    Kruschke, J. K. & Liddell, T. M. The Bayesian new statistics: hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon. Bull. Rev. 25, 178–206 (2018).

    PubMed  Article  Google Scholar 

  79. 79.

    Mastrofski, S. D., Parks, R. B. & Worden, R. E. Community Policing in Action: Lessons from an Observational Study (US Department of Justice, 1998).

  80. 80.

    Engel, R. S., Sobol, J. J. & Worden, R. E. Further exploration of the demeanor hypothesis: the interaction effects of suspects’ characteristics and demeanor on police behavior. Justice Q. 17, 235–258 (2000).

    Article  Google Scholar 

  81. 81.

    Terrill, W. Police Coercion: Application of the Force Continuum (LFB Scholarly Publishing, 2001).

  82. 82.

    Antonovics, K. & Knight, B. G. A new look at racial profiling: evidence from the Boston Police Department. Rev. Econ. Stat. 91, 163–177 (2009).

    Article  Google Scholar 

  83. 83.

    McCrary, J. The effect of court-ordered hiring quotas on the composition and quality of police. Am. Econ. Rev. 97, 318–353 (2007).

    Article  Google Scholar 

  84. 84.

    Legewie, J. & Fagan, J. Group Threat, Police Officer Diversity and the Deadly use of Police Force. Columbia Public Law Research Paper No. 14-512 (Columbia Law School, 2016).

  85. 85.

    Goff, P. A., Steele, C. M. & Davies, P. G. The space between us: stereotype threat and distance in interracial contexts. J. Pers. Soc. Psychol. 94, 91–107 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  86. 86.

    Malleson, N. & Andresen, M. A. The impact of using social media data in crime rate calculations: shifting hot spots and changing spatial patterns. Cartogr. Geogr. Inf. Sci. 42, 112–121 (2015).

    Article  Google Scholar 

  87. 87.

    Miller, J., Le Masurier, P. & Wicks, J. Profiling Populations Available for Stops and Searches (Home Office, Policing and Reducing Crime Unit, 2000).

  88. 88.

    Waddington, P. A., Stenson, K. & Don, D. In proportion: race, and police stop and search. Br. J. Criminol. 44, 889–914 (2004).

    Article  Google Scholar 

  89. 89.

    Stop and Think: A Critical Review of the Use of Stop and Search Powers in England and Wales (Equality and Human Rights Commission, 2010).

  90. 90.

    Shiner, M. & Delsol, R. in Stop and Search: The Anatomy of a Police Power (eds Delsol, R. & Shiner, M.) 31–56 (Palgrave Macmillan, 2015).

  91. 91.

    Whitfield, J. Unhappy Dialogue. The Metropolitan Police and Black Londoners in Postwar Britain (Willan Publishing, 2004).

  92. 92.

    Haining, R. & Law, J. Combining police perceptions with police records of serious crime areas: a modelling approach. J. R. Stat. Soc. Series A Stat. in Soc. 170, 1019–1034 (2007).

    Article  Google Scholar 

  93. 93.

    Williams, P. Being Matrixed: The (Over)policing of Gang Suspects in London (StopWatch, 2018).

  94. 94.

    Otoyo, E. Policing of Ethnic Minorities in Britain. PhD thesis, London Metropolitan Univ. (2018).

  95. 95.

    Fatsis, L. Policing the beats: the criminalisation of UK drill and grime music by the London Metropolitan Police. Sociol. Rev. 67, 1300–1316 (2019).

    Article  Google Scholar 

  96. 96.

    Home Office. Arrest Statistics Data Tables: Police Powers and Procedures Year ending 31 March 2016. Table A_01c: Number of Persons Arrested by Ethnic Group. GOV.UK (2016).

  97. 97.

    Office for National Statistics. KS201EW: 2011 Census: ethnic group, local authorities in England and Wales. Office for National Statistics (2011).

  98. 98.

    Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Soft. 76, 1–32 (2017).

    Article  Google Scholar 

  99. 99.

    Stan Development Team. RStan: the R interface to Stan. R package version 2.19.3 (2020).

Download references


Support for this research was provided by a grant from the Leverhulme Trust (to L.V.), and the West Midlands Police and Crime Commissioner and Economic and Social Research Council grants ES/P008976/1, ES/V004867/1 and ES/N018192/1 (to N.S.). West Midlands Police provided access to the data. Members of West Midlands Police and the West Midlands Police and Crime Commissioner provided comments on the manuscript, but had no role in study design and analysis, decision to publish or preparation of the manuscript. The other funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Special thanks goes to J. Knoblauch for invaluable discussions. We also thank P. Newall, J. Richards, J. Trueblood, G. Wall, D. Whordley and the West Midlands Police Stop and Search Commission for comments.

Author information




L.V. analysed data, designed and executed the research. L.V. and N.S. wrote the paper.

Corresponding author

Correspondence to Lara Vomfell.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature Human Behaviour thanks Michael Shiner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Aisha Bradshaw.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Densities of posterior distributions of search shares over all officers for each 6-month time period based on 10,103 observations of officer search counts.

The black dot represents the median of the distributions aggregated over officers and the black lines show 50% and 90% uncertainty intervals.

Extended Data Fig. 2 Posterior densities of DS and DP by time period based on 10,103 observations of officer search counts.

For visual clarity, we only show values between [0.3, 10.0]. Note that the y-axis is on the log scale. The black dots represent the medians; the black lines represent 50% and 90% uncertainty intervals.

Extended Data Fig. 3 Comparison of observed search counts to predicted search counts based on inferred search shares p.

Each grey dot is the observed search count by an officer in time period t and ethnic group e against the prediction error (observed - predicted). The black dots show the observed data against the error from the median prediction for that observation. The plot shows that key features of the data are captured in the model. The figure is based on 10,103 observations of officer search counts.

Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Results and Supplementary Tables 1 and 2.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Vomfell, L., Stewart, N. Officer bias, over-patrolling and ethnic disparities in stop and search. Nat Hum Behav (2021).

Download citation


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing