Popli, G.K. (2015) Examining the Link between Crime and Unemployment: A Time Series Analysis for Canada. Applied Economics. ISSN 1466-4283
Abstract
We use national and regional Canadian data to analyse the relationship between economic activity (as reflected by the unemployment rate) and crime rates. Given potential aggregation bias, we disaggregate the crime data and look at the relationship between six different types of crimes rates and unemployment rate; we also disaggregate the data by region. We employ an error correction model in our analysis to test for short-run and long-run dynamics. We find no evidence of long-run relationship between crime and unemployment, when we look at both disaggregation by type of crime and disaggregation by region. Lack of evidence of a long-run relationship indicates we have no evidence of the motivation hypothesis. For selected types of property crimes, we find some evidence of a significant negative short-run relationship between crime and unemployment, lending support to the opportunity hypothesis. Inclusion of control variables in the panel analysis does not alter the findings, qualitatively or quantitatively.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 Taylor & Francis. This is an author-produced version of a paper accepted for publication in Applied Economics. Uploaded in accordance with the publisher's self-archiving policy |
Keywords: | crime rates in Canada; time-series analysis; unemployment; C22; K1 |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 18 Mar 2015 15:27 |
Last Modified: | 02 Nov 2016 12:24 |
Published Version: | http://dx.doi.org/10.1080/00036846.2015.1023942 |
Status: | Published |
Publisher: | Taylor & Francis (Routledge) |
Refereed: | Yes |
Identification Number: | 10.1080/00036846.2015.1023942 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84077 |