Issues in Identification and Estimation of Discrete Choice Panel Data Models and Discrete Time Duration Models

离散选择面板数据模型和离散持续时间模型的识别和估计问题

• 批准号: 0417859
• 负责人: Bo Honore
• 金额: $ 16.78万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-07-15 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0417859&HistoricalAwards=false
• 关键词: Issues; Identification; Estimation; Discrete; Choice

There are cases in econometrics when the parameters of a model may not be easily identified making estimation and inference very difficult. This research will study and develop techniques for a number of related statistical and economic models that can be used to empirically investigate how economic agents (such as individual or firms) behave over time. These models have been used in many areas of economics: in labor economics to study the duration of employment or 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 differences in health status across demographic groups. These are all important questions, and to answer them it is important to have appropriate techniques. The main contribution of this project will be to investigate exactly what features of these models can be estimated, and how to estimate them. Even though it is often not possible to exactly estimate the parameters of interest, even if one had an infinite number of observations, it is in practice often possible to precisely find bounds for the parameters of such models. This research will provide techniques to provide such bounds of the parameters of interest. By providing methods to develop the bounds of parameters, the PI provides a way to estimate models that hitherto had been inestimable in a wide range of fields in economics.Although the main contributions of the research will be methodological, the project will also include applications of the methods that are developed. This research will be joint with more applied economists who are interested in the dynamics of unemployment and in health economics and thus provide ready applications of the theory developed in this research.

在计量经济学中，有时模型的参数可能不容易确定，这使得估计和推断非常困难。本研究将研究和开发一些相关的统计和经济模型，可用于实证调查经济主体（如个人或公司）如何随着时间的推移而表现的技术。这些模型已被用于经济学的许多领域：在劳动经济学中，研究就业或失业的持续时间;在公共经济学中，研究福利计划的参与;在营销中，研究广告的长期影响;在健康经济学中，研究不同人口群体的健康状况差异。这些都是重要的问题，要回答这些问题，重要的是要有适当的技术。 该项目的主要贡献将是研究这些模型的哪些特征可以被估计，以及如何估计它们。尽管通常不可能精确地估计感兴趣的参数，即使有无限数量的观测，但在实践中通常可以精确地找到这些模型的参数的界限。这项研究将提供技术，以提供这样的边界的参数的利益。 通过提供方法来开发参数的界限，PI提供了一种方法来估计模型，迄今为止，在经济学的广泛领域是不可估量的。虽然研究的主要贡献将是方法，该项目也将包括开发的方法的应用。这项研究将与更多的应用经济学家谁感兴趣的失业和健康经济学的动态，从而提供现成的应用在这项研究中开发的理论。