IDEAS home Printed from https://ideas.repec.org/a/nat/nathum/v4y2020i7d10.1038_s41562-020-0858-1.html
   My bibliography  Save this article

A large-scale analysis of racial disparities in police stops across the United States

Author

Listed:
  • Emma Pierson

    (Stanford University)

  • Camelia Simoiu

    (Management Science & Engineering, Stanford University)

  • Jan Overgoor

    (Management Science & Engineering, Stanford University)

  • Sam Corbett-Davies

    (Stanford University)

  • Daniel Jenson

    (Management Science & Engineering, Stanford University)

  • Amy Shoemaker

    (Management Science & Engineering, Stanford University)

  • Vignesh Ramachandran

    (Management Science & Engineering, Stanford University)

  • Phoebe Barghouty

    (Management Science & Engineering, Stanford University)

  • Cheryl Phillips

    (Communication, Stanford University)

  • Ravi Shroff

    (Applied Statistics, Social Science, and Humanities, New York University)

  • Sharad Goel

    (Management Science & Engineering, Stanford University)

Abstract

We assessed racial disparities in policing in the United States by compiling and analysing a dataset detailing nearly 100 million traffic stops conducted across the country. We found that black drivers were less likely to be stopped after sunset, when a ‘veil of darkness’ masks one’s race, suggesting bias in stop decisions. Furthermore, by examining the rate at which stopped drivers were searched and the likelihood that searches turned up contraband, we found evidence that the bar for searching black and Hispanic drivers was lower than that for searching white drivers. Finally, we found that legalization of recreational marijuana reduced the number of searches of white, black and Hispanic drivers—but the bar for searching black and Hispanic drivers was still lower than that for white drivers post-legalization. Our results indicate that police stops and search decisions suffer from persistent racial bias and point to the value of policy interventions to mitigate these disparities.

Suggested Citation

  • Emma Pierson & Camelia Simoiu & Jan Overgoor & Sam Corbett-Davies & Daniel Jenson & Amy Shoemaker & Vignesh Ramachandran & Phoebe Barghouty & Cheryl Phillips & Ravi Shroff & Sharad Goel, 2020. "A large-scale analysis of racial disparities in police stops across the United States," Nature Human Behaviour, Nature, vol. 4(7), pages 736-745, July.
    • Handle: RePEc:nat:nathum:v:4:y:2020:i:7:d:10.1038_s41562-020-0858-1
    DOI: 10.1038/s41562-020-0858-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41562-020-0858-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41562-020-0858-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kate Antonovics & Brian G. Knight, 2009. "A New Look at Racial Profiling: Evidence from the Boston Police Department," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 163-177, February.
    2. Shamena Anwar & Hanming Fang, 2006. "An Alternative Test of Racial Prejudice in Motor Vehicle Searches: Theory and Evidence," American Economic Review, American Economic Association, vol. 96(1), pages 127-151, March.
    3. John Knowles & Nicola Persico & Petra Todd, 2001. "Racial Bias in Motor Vehicle Searches: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 203-232, February.
    4. Becker, Gary S, 1993. "Nobel Lecture: The Economic Way of Looking at Behavior," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 385-409, June.
    5. Ridgeway, Greg & MacDonald, John M., 2009. "Doubly Robust Internal Benchmarking and False Discovery Rates for Detecting Racial Bias in Police Stops," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 661-668.
    6. Grogger, Jeffrey & Ridgeway, Greg, 2006. "Testing for Racial Profiling in Traffic Stops From Behind a Veil of Darkness," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 878-887, September.
    7. Matt Ryan, 2016. "Frisky business: race, gender and police activity during traffic stops," European Journal of Law and Economics, Springer, vol. 41(1), pages 65-83, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:grz:wpsses:2022-01 is not listed on IDEAS
    2. Wright, Nicholas A. & Dorilas, Ernest, 2022. "Do Cellphone Bans Save Lives? Evidence From Handheld Laws on Traffic Fatalities," Journal of Health Economics, Elsevier, vol. 85(C).
    3. Celislami, Elda & Kastoryano, Stephen & Mastrobuoni, Giovanni, 2023. "Strategic Bureaucratic Opacity: Evidence from Death Investigation Laws and Police Killings," IZA Discussion Papers 16609, Institute of Labor Economics (IZA).
    4. Mayer, Duncan J., 2024. "Lead and delinquency rates; A spatio-temporal perspective," Social Science & Medicine, Elsevier, vol. 341(C).
    5. Mitchell, Jeffrey & Chihaya, Guilherme Kenji, 2022. "Tract level associations between historical residential redlining and contemporary fatal encounters with police," Social Science & Medicine, Elsevier, vol. 302(C).
    6. Gian Maria Campedelli, 2022. "Explainable Machine Learning for Predicting Homicide Clearance in the United States," Papers 2203.04768, arXiv.org.
    7. Campedelli, Gian Maria, 2022. "Explainable machine learning for predicting homicide clearance in the United States," Journal of Criminal Justice, Elsevier, vol. 79(C).
    8. Dasom Lee & David J. Hess, 2022. "Public concerns and connected and automated vehicles: safety, privacy, and data security," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    9. Short, Martin B. & Mohler, George O., 2023. "A fully Bayesian tracking algorithm for mitigating disparate prediction misclassification," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1238-1252.
    10. Miner, Patrick & Smith, Barbara M. & Jani, Anant & McNeill, Geraldine & Gathorne-Hardy, Alfred, 2024. "Car harm: A global review of automobility's harm to people and the environment," Journal of Transport Geography, Elsevier, vol. 115(C).
    11. Tim Goddard, 2021. "The Trouble with Using Risk Assessment Instruments to Quantify the Chance of Future Offending," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    12. Förster, Manuel & Karos, Dominik, 2021. "From prejudice to racial profiling and back. A naἴve intuitive statistician's curse," Center for Mathematical Economics Working Papers 644, Center for Mathematical Economics, Bielefeld University.
    13. Saltiel, Fernando & Tuttle, Cody, 2022. "Business Cycles and Police Hires," IZA Discussion Papers 15665, Institute of Labor Economics (IZA).
    14. Holt, Stephen B & Vinopal, Katie M., 2021. "It's About Time: Examining Inequality in the Time Cost of Waiting," SocArXiv jbk3x, Center for Open Science.
    15. Chen, Ted Hsuan Yun & McLachlan, Paul & Fariss, Christopher J, 2021. "Exposure to Discretionary Arrests Increases Support for Anti-Police Protests," SocArXiv r78ys, Center for Open Science.
    16. Riser, Quentin H. & Rouse, Heather L. & Dorius, Cassandra J., 2023. "Association between early income variation around poverty thresholds, income trajectories, and birth, child, and family characteristics," Children and Youth Services Review, Elsevier, vol. 145(C).
    17. David Crockett, 2022. "Racial Oppression and Racial Projects in Consumer Markets: A Racial Formation Theory Approach [The Ghetto Marketing Life Cycle: A Case of Underachievement]," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(1), pages 1-24.
    18. Barajas, Jesus, 2021. "Biking Where Black: Connecting Transportation Planning and Infrastructure to Disproportionate Policing," SocArXiv wszgv, Center for Open Science.
    19. Xinming Du, 2023. "Symptom or Culprit? Social Media, Air Pollution, and Violence," CESifo Working Paper Series 10296, CESifo.
    20. Federico Masera, 2022. "The economics of policing and crimeThe economics of policing and crime," Chapters, in: Paolo Buonanno & Paolo Vanin & Juan Vargas (ed.), A Modern Guide to the Economics of Crime, chapter 2, pages 12-29, Edward Elgar Publishing.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Felipe Goncalves & Steven Mello, 2021. "A Few Bad Apples? Racial Bias in Policing," American Economic Review, American Economic Association, vol. 111(5), pages 1406-1441, May.
    2. Kevin Lang & Ariella Kahn-Lang Spitzer, 2020. "Race Discrimination: An Economic Perspective," Journal of Economic Perspectives, American Economic Association, vol. 34(2), pages 68-89, Spring.
    3. Ingrid Gould Ellen & Stephen L. Ross, 2018. "Race and the City," Working Papers 2018-022, Human Capital and Economic Opportunity Working Group.
    4. Makofske, Matthew, 2020. "Pretextual Traffic Stops and Racial Disparities in their Use," MPRA Paper 100792, University Library of Munich, Germany.
    5. Anwar Shamena & Fang Hanming, 2012. "Testing for the Role of Prejudice in Emergency Departments Using Bounceback Rates," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 13(3), pages 1-49, December.
    6. Nicolás Grau & Damián Vergara, "undated". "A Simple Test for Prejudice in Decision Processes: The Prediction-Based Outcome Test," Working Papers wp493, University of Chile, Department of Economics.
    7. Lieberman, Carl, 2024. "Variation in racial disparities in police use of force," Journal of Urban Economics, Elsevier, vol. 141(C).
    8. Shi, Ying & Zhu, Maria, 2022. "Equal time for equal crime? Racial bias in school discipline," Economics of Education Review, Elsevier, vol. 88(C).
    9. Brady P. Horn & Jill J. Mccluskey & Ron C. Mittelhammer, 2014. "Quantifying Bias In Driving-Under-The-Influence Enforcement," Economic Inquiry, Western Economic Association International, vol. 52(1), pages 269-284, January.
    10. Bhattacharya, Debopam, 2013. "Evaluating treatment protocols using data combination," Journal of Econometrics, Elsevier, vol. 173(2), pages 160-174.
    11. Abrahams, Scott, 2020. "Officer differences in traffic stops of minority drivers," Labour Economics, Elsevier, vol. 67(C).
    12. Mark Hoekstra & CarlyWill Sloan, 2022. "Does Race Matter for Police Use of Force? Evidence from 911 Calls," American Economic Review, American Economic Association, vol. 112(3), pages 827-860, March.
    13. Ritter, Joseph A., 2017. "How do police use race in traffic stops and searches? Tests based on observability of race," Miscellaneous Publications 253354, University of Minnesota, Department of Applied Economics.
    14. Brock, William A. & Cooley, Jane & Durlauf, Steven N. & Navarro, Salvador, 2012. "On the observational implications of taste-based discrimination in racial profiling," Journal of Econometrics, Elsevier, vol. 166(1), pages 66-78.
    15. Bjerk, David J. & Helland, Eric, 2018. "What Can DNA Exonerations Tell Us about Racial Differences in Wrongful Conviction Rates?," IZA Discussion Papers 11837, Institute of Labor Economics (IZA).
    16. Ritter, Joseph A., 2017. "How do police use race in traffic stops and searches? Tests based on observability of race," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 82-98.
    17. Anbarci, Nejat & Lee, Jungmin, 2014. "Detecting racial bias in speed discounting: Evidence from speeding tickets in Boston," International Review of Law and Economics, Elsevier, vol. 38(C), pages 11-24.
    18. Dragan Ilić, 2013. "Marginally discriminated: the role of outcome tests in European jurisdiction," European Journal of Law and Economics, Springer, vol. 36(2), pages 271-294, October.
    19. Stroube, Bryan K., 2021. "Using allegations to understand selection bias in organizations: Misconduct in the Chicago Police Department," Organizational Behavior and Human Decision Processes, Elsevier, vol. 166(C), pages 149-165.
    20. Ritter, Joseph A., 2013. "Racial Bias in Traffic Stops: Tests of a Unified Model of Stops and Searches," Miscellaneous Publications 152496, University of Minnesota, Department of Applied Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nathum:v:4:y:2020:i:7:d:10.1038_s41562-020-0858-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.