Measurement Error in County-Level UCR Data
Maltz and Targonski (2002) have provided an important service by disaggregating the county level data to help researchers examine measurement errors in the county level data, but their conclusion that county-level crime data, as they are currently constituted, should not be used, especially in polic...
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2003
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| In: |
Journal of quantitative criminology
Year: 2003, Volume: 19, Issue: 2, Pages: 185-198 |
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Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
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| 520 | |a Maltz and Targonski (2002) have provided an important service by disaggregating the county level data to help researchers examine measurement errors in the county level data, but their conclusion that county-level crime data, as they are currently constituted, should not be used, especially in policy studies is not justified. All data has measurement error, presumably even their measures of this error. Unfortunately, however, Maltz and Targonski provide no systematic test for how bad the data are. Their graphs obscure both the small number of counties affected, that these are rural counties, and that just because some of the population in a county is not represented in calculating the crime rate, that is not the same thing as showing that the reported number is in error. Nor do they provide evidence for the more important issue of whether there is a systematic bias in the data. The evidence provided here indicates right-to-carry laws continue to produce substantial reductions in violent crime rates when states with the greatest measurement error are excluded. In fact, restricting the sample results in somewhat larger reductions in murders and robberies, but smaller reductions in aggravated assaults. | ||
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