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Predicting Police Misconduct

Author

Listed:
  • Greg Stoddard
  • Dylan J. Fitzpatrick
  • Jens Ludwig

Abstract

Whether police misconduct can be prevented depends partly on whether it can be predicted. We show police misconduct is partially predictable and that estimated misconduct risk is not simply an artifact of measurement error or a proxy for officer activity. We also show many officers at risk of on-duty misconduct have elevated off-duty risk too, suggesting a potential link between accountability and officer wellness. We show that targeting preventive interventions even with a simple prediction model – number of past complaints, which is not as predictive as machine learning but lower-cost to deploy – has marginal value of public funds of infinity.

Suggested Citation

  • Greg Stoddard & Dylan J. Fitzpatrick & Jens Ludwig, 2024. "Predicting Police Misconduct," NBER Working Papers 32432, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:32432
    Note: LE LS PE
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    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • K0 - Law and Economics - - General

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