Theoretical and practical issues in estimation of nonlinear panel data models
非线性面板数据模型估计的理论与实践问题
基本信息
- 批准号:0111342
- 负责人:
- 金额:$ 19.48万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2001
- 资助国家:美国
- 起止时间:2001-07-15 至 2005-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Panel data sets play an important role in empirical work in almost all areas of economics. Formally, panel data sets are data sets where there is more than one observation for each unit of observation. Typically, this is because the data set consists of observations for the same individual over a period of time, but the methods for dealing with panel data are equally applicable to situations where the unit of observation is firms, municipalities, etc. This project develops new econometric methods for dealing with nonlinear panel data models, including duration models. The project also develops software to implement these methods. The advantage of panel data is that by following an individual over time, it is possible to investigate an individual's dynamic behavior while controlling for that individual's characteristics. It is easiest to illustrate the importance of this by considering the following simple example. Suppose, as is often the case, that one observed that individuals, who use a certain social program in one period, are also more likely to use it the next period. This ``persistence'' could be observed because some characteristic of the individual makes him or her more likely to use the program. If that characteristic does not change much over time, then the same people will tend to use the program in different time periods. On the other hand, the persistence is also consistent with a situation in which using the program causes the individual to be more likely to use the program in the future (for example, because the individual learns about the program by using it). Being able to distinguish between these explanations of the persistence is important because under the second explanation, a policy that changes the availability of the program in a single period will also have an indirect effect on participation in the program in future periods. This project develops econometric tools for dealing with panel data in situations like this one, although the tools are more generic and hence applicable in many other empirical situations as well.
面板数据集在几乎所有经济学领域的实证工作中发挥着重要作用。形式上,面板数据集是每个观测单位有多个观测的数据集。通常情况下,这是因为数据集由同一个人在一段时间内的观察结果组成,但面板数据的处理方法同样适用于观察单位为企业,市政当局等的情况。本项目开发了新的计量经济学方法,用于处理非线性面板数据模型,包括持续时间模型。该项目还开发了软件来实现这些方法。 面板数据的优点是,通过随时间推移跟踪个体,可以在控制个体特征的同时调查个体的动态行为。通过考虑以下简单的例子,最容易说明这一点的重要性。假设人们观察到,在一个时期使用某种社会计划的个体,在下一个时期也更有可能使用它。这种“持久性”可以被观察到,因为个人的某些特征使他或她更有可能使用该程序。如果这个特征不会随着时间的推移而改变,那么同一个人将倾向于在不同的时间段使用该程序。另一方面,持久性也与使用程序导致个体在未来更有可能使用程序的情况一致(例如,因为个体通过使用它来了解程序)。能够区分这些持续性的解释是很重要的,因为在第二种解释下,在一个时期内改变计划可用性的政策也会对未来时期的计划参与产生间接影响。这个项目开发了计量经济学工具,用于处理类似这种情况下的面板数据,尽管这些工具更通用,因此也适用于许多其他经验情况。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Bo Honore其他文献
Bo Honore的其他文献
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{{ truncateString('Bo Honore', 18)}}的其他基金
Research towards a better understanding of logit type models with fixed effects
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2116630 - 财政年份:2021
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$ 19.48万 - 项目类别:
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Standard Grant
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0718063 - 财政年份:2007
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$ 19.48万 - 项目类别:
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$ 19.48万 - 项目类别:
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