Reassessing the Cross-National Relationship Between Income Inequality and Homicide Rates: Implications of Data Quality Control in the Measurement of Income Distribution
A significant positive relationship between income inequality and homicide rates has been found in a large number of cross-sectional studies and a few longitudinal analyses; a theoretically interesting interaction effect between income inequality and social welfare has also been found. For the most...
| Authors: | ; ; |
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2002
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| In: |
Journal of quantitative criminology
Year: 2002, Volume: 18, Issue: 4, Pages: 377-395 |
| Online Access: |
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| Summary: | A significant positive relationship between income inequality and homicide rates has been found in a large number of cross-sectional studies and a few longitudinal analyses; a theoretically interesting interaction effect between income inequality and social welfare has also been found. For the most part researchers have been willing to use generous quality criteria in collecting income-distribution data, to maximize sample size and thereby enhance statistical power and representativeness. In the present paper we use a recently developed data set with explicit quality ratings for the income-distribution data, which permits systematic assessment of the consequences of relying on income-distribution measures of varying quality in examining the inequality-homicide relationship. Our analyses reveal that the income inequality-homicide relationship is remarkably robust in cross-sectional analyses. Regardless of the quality of income-distribution data, we observe significant positive effects of the Gini coefficient on homicide rates in cross-sectional multivariate models. Consistent results are also observed when an interaction term for income inequality and decommodification is examined. The results of longitudinal analyses differ; we observe a significant positive effect of changes in inequality on changes in homicide rates only when income-distribution measures of low quality are used. |
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| ISSN: | 1573-7799 |
| DOI: | 10.1023/A:1021169610837 |