Campus Units

Statistics

Document Type

Article

Publication Version

Published Version

Publication Date

7-3-2019

Journal or Book Title

PloS ONE

Volume

14

Issue

7

First Page

e0218375

DOI

10.1371/journal.pone.0218375

Abstract

Interest in modeling contemporary crime trends, a task that has historically been considered valuable to the public, researchers, and policymakers, is resurging. Advancements in criminology have made it clear that understanding crime trends necessarily involves understanding trends in how likely individuals are to report crimes to the police, as well as how likely the police are to accurately record those crimes. In this paper, we use dynamic linear models to simultaneously model the time series for several crime types in order to gain insight into trends in crime and crime reporting. We analyze crime data from Chicago spanning 2007 through 2016 and show how correlations in the way crime trends evolve may contain information about drivers of crime and crime reporting. We provide evidence of substantial differences in the relationships between the trends of crimes of different types depending on whether crimes are violent or nonviolent and whether or not crimes are tracked in the FBI’s Uniform Crime Report.

Comments

This article is published as Garton N, Niemi J (2019) Multivariate temporal modeling of crime with dynamic linear models. PLoS ONE 14(7): e0218375. doi: 10.1371/journal.pone.0218375.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

Garton, Niemi

Language

en

File Format

application/pdf

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