Testing Theory and the Analysis of Time Series Data
Although the relationship between unemployment and crime has been a longstanding interest in criminology, there is little agreement about appropriate models for analyzing this relationship. David Greenberg's (this issue) discussion highlights two issues that raise questions about recent researc...
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Format: | Electronic Article |
Language: | English |
Published: |
2001
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In: |
Journal of quantitative criminology
Year: 2001, Volume: 17, Issue: 4, Pages: 343-357 |
Online Access: |
Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
Journals Online & Print: | |
Check availability: | HBZ Gateway |
Keywords: |
Summary: | Although the relationship between unemployment and crime has been a longstanding interest in criminology, there is little agreement about appropriate models for analyzing this relationship. David Greenberg's (this issue) discussion highlights two issues that raise questions about recent research on the unemployment–crime relationship. First, he extends the work of Hale and Sabbagh (1991) and argues that cointegration methods should be used instead of first-differenced regression models to analyze unemployment and crime time series data. Second, he argues that previous attempts to test his strain theory linking unemployment to the age distribution of crime rely on flawed hypotheses, inappropriate data, and faulty measurement. In this paper, I address both of Greenberg's claims. I begin with a discussion of the relative utility of cointegration analysis and of first-differenced regression models for the analysis of the unemployment–crime relationship, focusing on the link between theory and statistical model. I then discuss the possibility of ever testing and falsifying Greenberg's strain theory. |
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ISSN: | 1573-7799 |
DOI: | 10.1023/A:1012537720478 |