Moffitt Robert
Department of Economics, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA.
Demography. 2005 Feb;42(1):91-108. doi: 10.1353/dem.2005.0006.
The problem of determining cause and effect is one of the oldest in the social sciences, where laboratory experimentation is generally not possible. This article provides a perspective on the analysis of causal relationships in population research that draws upon recent discussions of this issue in the field of economics. Within economics, thinking about causal estimation has shifted dramatically in the past decade toward a more pessimistic reading of what is possible and a retreat in the ambitiousness of claims of causal determination. In this article, the framework that underlies this conclusion is presented, the central identification problem is discussed in detail, and examples from the field of population research are given. Some of the more important aspects of this framework are related to the problem of the variability of causal effects for different individuals; the relationships among structural forms, reduced forms, and knowledge of mechanisms; the problem of internal versus external validity and the related issue of extrapolation; and the importance of theory and outside evidence.
确定因果关系的问题是社会科学中最古老的问题之一,在社会科学中通常无法进行实验室实验。本文从经济学领域最近对这一问题的讨论中汲取观点,对人口研究中的因果关系分析提供了一个视角。在经济学领域,过去十年里,关于因果估计的思考发生了巨大转变,朝着对可能性的更悲观解读以及因果确定性主张的雄心壮志的退缩方向发展。本文介绍了这一结论背后的框架,详细讨论了核心识别问题,并给出了人口研究领域的例子。该框架一些更重要的方面与不同个体因果效应的变异性问题、结构形式、简化形式和机制知识之间的关系、内部有效性与外部有效性问题以及相关的外推问题,以及理论和外部证据的重要性有关。