Issues in estimation of dynamic panel data and duration models

动态面板数据和持续时间模型的估计问题

• 批准号: 0718063
• 负责人: Bo Honore
• 金额: $ 22.81万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0718063&HistoricalAwards=false
• 关键词: Issues; estimation; dynamic; panel; data

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.

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新的统计工具。研究集中在两个一般场景。第一个场景涉及研究人员对某个事件的持续时间感兴趣的情况。在这一部分的项目中开发的工具将在经济学的许多领域是有用的：在劳动经济学中，研究失业的持续时间;在公共经济学中，研究参与福利计划;在市场营销中，研究广告的长期影响;在健康经济学中，研究健康状况的演变。这些方法的创新之处在于，它们将明确纳入一个人的行动对其他人的行动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会受到她朋友吸烟行为的影响，反之亦然，或者一个家庭成员关于工作多少的决定可能会受到其他家庭成员决定的影响。这种相互作用意味着，改变一个人行为的政策的效果将被这个人的行为影响其他人的事实所放大。因此，重要的是要有衡量这些相互作用的重要性的工具。本研究中涉及的另一个一般场景涉及两种结果随着时间的推移相互作用的情况。例如，健康和社会经济地位是相互关联的，这一点已得到公认。在解释这种相关性时，重要的是要确定这种相关性是否存在，因为两者之一的变化会导致另一个在未来发生变化（如果是这样，则是哪个导致哪个），或者因为它们都是由同一个因素决定的。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：最直接的广泛影响来自于新的统计工具软件将在网上提供，以及对参与该项目的学生进行培训。该项目还将改善经济学家和其他社会科学家思考其实证研究结果的方式。