Issues in estimation of dynamic panel data and duration models

该项目为经济学家和其他对研究个人行为和结果感兴趣的社会科学家开发了新的统计工具。这项研究主要集中在两种情况下。第一个场景涉及研究人员对某些事件的持续时间感兴趣的情况。在这部分项目中开发的工具将在经济学的许多领域有用：在劳动经济学中，研究失业的持续时间；在公共经济学中，研究福利计划的参与；在市场营销中，研究广告的长期效果；在卫生经济学中，研究健康状况的演变。这些方法的创新之处在于，它们将明确地纳入一个人的行为对其他人的行为产生重要影响的可能性。例如，一个青少年开始吸烟的决定可能受到她朋友吸烟行为的影响，反之亦然，或者一个家庭成员决定工作多少可能受到其他家庭成员决定的影响。这种相互作用意味着，改变一个人的行为的政策的效果将被这个人的行为影响到其他人这一事实所扩大。因此，重要的是要有工具来衡量这些相互作用的重要性。本研究中提到的另一种一般情况涉及两种结果随着时间的推移相互作用的情况。例如，众所周知，健康和社会经济地位是相关的。在解释这种相关性时，重要的是要确定相关性是否存在，因为两者中一个的变化会导致另一个在未来发生变化（如果是，哪个导致哪个），还是因为它们都是由同一因素决定的。该项目开发了可用于回答这些问题的一般方法，并使用它们来调查美国以及一些欧洲国家的健康与社会经济地位之间的关系。更广泛的影响：最直接的更广泛的影响来自新统计工具的软件将在网上提供这一事实，以及对参与该项目的学生的培训。该项目还将改进经济学家和其他社会科学家思考其实证发现的方式。

This project develops new statistical tools for economists and other social scientists interested in studying individual behavior and outcomes over time. The research is centered on two general scenarios. The first scenario involves situations in which a researcher is interested in the duration of some event. The tools developed in this part of the project will be useful in many areas of economics: in labor economics, to study the duration of unemployment; in public economics, to study participation in welfare programs; in marketing, to study the long-run effects of advertising; and in health economics, to study the evolution in health status. The innovation in these methods is that they will explicitly incorporate the possibility that one person's actions have an important impact upon the actions of others. For example, a teenager's decision to start smoking may be influenced by the smoking behavior of her friends and vice versa, or one family member's decision about how much to work may be effected by the decisions of the other family members. Such interactions imply that the effect of a policy that changes one person's behavior will be enlarged by the fact that that person's behavior will influence others. It is therefore important to have tools for measuring the importance of these interactions. The other general scenario addressed in this research involves situations in which two outcomes interact with each other over time. For example, it is well-established that health and socioeconomic status are related. In interpreting such correlations, it is important to determine whether the correlation exists because a change in one of the two causes the other to change in the future (and, if so, which causes which), or because they are both determined by the same factor. The project develops general methods that can be used to answer such questions, and uses them to investigate the relationship between health and socioeconomic status in the US, as well as in a number of European countries. Broader impacts: The most direct broader impact comes from the fact that software for the new statistical tools will be made available online, and from the training of the students involved in the project. The project will also improve the way economists and other social scientists think about their empirical findings.