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A Discussion of Current Crime Forecasting Indices and an Improvement to the Prediction Efficiency Index for Applications

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  • White, Veronica
  • Hunt, Joel
  • Green, Brannon

Abstract

Hot-spot maps regularly aid many policing resource allocation decisions in today’s data-driven age. However, it is unclear what forecasting algorithm(s) should be used to create these maps. To address this gap, we must be able to assess how “good” a generated hot-spot map is. Currently, four main metrics are used for evaluation: the prediction accuracy index (PAI), the recapture rate index (RRI), the prediction efficiency index (PEI), and the prediction efficiency index* (PEI*). This article discusses PAI, RRI, and PEI’s strengths and weaknesses, articulates and justifies PEI*, and demonstrates the differences in calculations and interpretations of each metric. We argue that PEI* measures the efficiency of a crime forecasting algorithm while being operationally realistic and should be used in conjunction with other appropriate measures.

Suggested Citation

  • White, Veronica & Hunt, Joel & Green, Brannon, 2022. "A Discussion of Current Crime Forecasting Indices and an Improvement to the Prediction Efficiency Index for Applications," SocArXiv pf8hy_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:pf8hy_v1
    DOI: 10.31219/osf.io/pf8hy_v1
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    1. Drawve, Grant & Wooditch, Alese, 2019. "A research note on the methodological and theoretical considerations for assessing crime forecasting accuracy with the predictive accuracy index," Journal of Criminal Justice, Elsevier, vol. 64(C), pages 1-1.
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