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

NCJ Number
306617
Journal
Security Journal Dated: 2023
Author(s)
Veronica M. White; Joel Hunt; Brannon Green
Date Published
March 2023
Annotation

This article presents the strengths and weaknesses of various crime forecasting algorithms and argues that, to be efficient and realistic, models should be used in conjunction with other measures.

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. The authors 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. (Published Abstract Provided)