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

Veronica White, Joel Hunt and Brannon Green

No pf8hy_v1, SocArXiv from Center for Open Science

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.

Date: 2022-04-23
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:pf8hy_v1

DOI: 10.31219/osf.io/pf8hy_v1

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