The nonparametric identification of treatment effects in duration models

被引:245
作者
Abbring, JH [1 ]
Van den Berg, GJ [1 ]
机构
[1] Vrije Univ Amsterdam, Dept Econ, NL-1081 HV Amsterdam, Netherlands
关键词
program evaluation; bivariate duration analysis; selectivity bias; hazard rate; partial likelihood; unobserved heterogeneity; anticipation;
D O I
10.1111/1468-0262.00456
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper analyzes the specification and identification of causal multivariate duration models. We focus on the case in which one duration concerns the point in time a treatment is initiated and we are interested in the effect of this treatment on some outcome duration. We define "no anticipation of treatment" and relate it to a common assumption in biostatistics. We show that (i) no anticipation and (ii) randomized treatment assignment can be imposed without restricting the observational data. We impose (i) but not (ii) and prove identification of models that impose some structure. We allow for dependent unobserved heterogeneity and we do not exploit exclusion restrictions on covariates. We provide results for both single-spell and multiple-spell data. The timing of events conveys useful information on the treatment effect.
引用
收藏
页码:1491 / 1517
页数:27
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