Recidivism and social interactions

被引:21
作者
Sirakaya, Sibel [1 ]
机构
[1] Univ Washington, Dept Econ & Stat, Seattle, WA 98195 USA
[2] Univ Washington, Ctr Stat & Social Sci, Seattle, WA 98195 USA
关键词
Bayesian model averaging; model uncertainty; recidivism; social interactions;
D O I
10.1198/016214506000000177
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Using a national sample, this article identifies the risk factors for recidivism among female, male, black, white, and Hispanic felony probationers. The individual hazard function is assumed to depend on individual and neighborhood characteristics, as well as on social interactions among probationers. In selecting the covariates from a set of potential candidates, Bayesian model averaging is used to account for both model uncertainty and the subsequent inference. The results point to social interactions as one of the most significant factors affecting recidivism among all gender, ethnicity, and race groups. When a frailty parameter is added to account for the possibility of unobserved risk factors shared by probationers within neighborhoods, the empirical results remain robust indicating negligible unobserved neighborhood-level heterogeneity.
引用
收藏
页码:863 / 877
页数:15
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