The decomposition and graphical analysis of crime and sanctions data: A cross-national application
This article attempts to illustrate the utility of isoquant map analysis from the field of production theory in microeconomics for the analysis of criminal justice data. Cross-national comparisons of aggregate crime and justice data are used to demonstrate the ability of this technique to reveal imp...
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| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
1997
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| In: |
Journal of quantitative criminology
Jahr: 1997, Band: 13, Heft: 2, Seiten: 97-119 |
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Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
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| 520 | |a This article attempts to illustrate the utility of isoquant map analysis from the field of production theory in microeconomics for the analysis of criminal justice data. Cross-national comparisons of aggregate crime and justice data are used to demonstrate the ability of this technique to reveal important patterns that are often obscured by simple rate comparisons and multivariate treatments such as pooled time-series analysis. For each jurisdiction, aggregate trends in criminal justice processing rates are systematically analyzed as a sequence of two-input production processes: gross imprisonment rates (prison population divided by resident population) can be partitioned in terms of the crime rate and punitiveness (prison population divided by the number of offenses); punitiveness can, in turn, be partitioned in terms of severity and certainty of punishment; certainty of punishment can then be partitioned, seriatim, in terms of the incarceration rate, the conviction rate, and the arrest or clearance rate and the rate at which citizens report crimes. Cross-national data collected by Farrington, Langan, and Wikström are used to illustrate the utility of the method for displaying comparisons of the decomposition of aggregate criminal justice data for the United States, England, and Sweden. | ||
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| 650 | 4 | |a cross-national comparisons | |
| 650 | 4 | |a graphical presentation of data | |
| 650 | 4 | |a production function | |
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