Department of Sociology, Minnesota Population Center, 909 Social Sciences, 267 19th Avenue S, Minneapolis, MN, 55455, USA,
Demography. 2013 Dec;50(6):1945-67. doi: 10.1007/s13524-013-0243-z.
In many different fields, social scientists desire to understand temporal variation associated with age, time period, and cohort membership. Among methods proposed to address the identification problem in age-period-cohort analysis, the intrinsic estimator (IE) is reputed to impose few assumptions and to yield good estimates of the independent effects of age, period, and cohort groups. This article assesses the validity and application scope of IE theoretically and illustrates its properties with simulations. It shows that IE implicitly assumes a constraint on the linear age, period, and cohort effects. This constraint not only depends on the number of age, period, and cohort categories but also has nontrivial implications for estimation. Because this assumption is extremely difficult, if not impossible, to verify in empirical research, IE cannot and should not be used to estimate age, period, and cohort effects.
在许多不同的领域,社会科学家都希望了解与年龄、时间段和队列成员相关的时间变化。在解决年龄-时期-队列分析中的识别问题的方法中,内建估计量(IE)被认为假设条件较少,并且能够很好地估计年龄、时期和队列组的独立影响。本文从理论上评估了 IE 的有效性和适用范围,并通过模拟说明了其性质。结果表明,IE 隐含地假设了线性年龄、时期和队列效应的约束。这种约束不仅取决于年龄、时期和队列类别的数量,而且对估计有重要的影响。由于在实证研究中很难(如果不是不可能的话)验证这一假设,因此 IE 不能也不应该用于估计年龄、时期和队列效应。