Estimation of Cross-sectional and Panel Data Duration Models with General Forms of Censoring (Revised)

使用一般审查形式估计横截面和面板数据持续时间模型（修订版）

• 批准号: 0452364
• 负责人: Shakeeb Khan
• 金额: $ 4.47万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2006-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0452364&HistoricalAwards=false
• 关键词: Estimation; Cross; sectional; Panel; Data

ABSTRACTProp ID: SES-0452364P I: Khan, Shakeeb Organization: University of Rochester Title: Estimation of Cross-sectional and Panel Data Duration Models with General Forms of Censoring The primary intellectual merit of the proposed activities is the development of new econometric and statistical methods for conducting estimation and inference in duration models. The statistical models considered in this proposal are motivated by particular features of duration data, which often arise in empirical settings. For example, censoring often arises in time-to event data, for a variety of reasons that are usually a consequence of the empirical researcher's observation or data collection plan. Unemployment spell-length may be censored because the agent is lost from the sample, or to control data collection costs, unemployed agents are only followed for short period of time. If they are still unemployed at the end of this period, their spell length is censored. The estimators introduced in this proposal will permit a general form of censoring, in the sense that they permit the censoring variable to depend in an arbitrary way on the observed variables that explain the duration length. This is motivated by, (but not restricted to) a specific empirical setting. With certain welfare programs, such as those in TANF (Temporary Assistance to Needy Families), entitlement depends on individual labor market histories. In this case, duration until one finds employment would be censored at the period when entitlement expires. In addition to general forms of censoring, the proposal includes new estimation procedures for models encountering other features of duration data encountered in practice. One such class of duration models is those for panel data, where the researcher observes multiple times-to-event, either for the same individual, or for different individuals within the same group, i.e. either family members, or firms within the same industry. Generally speaking, panel data allows researchers to control for unobserved factors that cannot be controlled for in a cross-sectional data set. In the context of durations models, this proposal suggests a new estimator for a panel data model which allows for a very general form (in this case spell specific) censoring. The other components of this proposal develop estimators for duration models which exhibit the following features: doubly censored data, duration models with time varying covariates, and stock sampled duration data, all of which have been encountered in practice.Broader Impacts: The project provides applied economists with new tools to conduct inference in duration analysis. Duration models are widely applied in practice in a variety of fields in applied economics, since they are used to address important policy issues, such as the effect of welfare reform, tax incentive effects on retirement, and the incentive effects of unemployment insurance. Duration models are also used in labor, development, public finance and finance. The new methods introduced here, and the software code will be made available on the investigator's website.

摘要Prop ID： SES-0452364P I： Khan，Shakeeb组织： 罗切斯特大学 一般截尾形式下横截面和面板数据持续时间模型的估计拟议活动的主要智力价值是开发新的计量经济学和统计方法，用于持续时间模型的估计和推断。在这个建议中考虑的统计模型的动机是持续时间数据的特定功能，这往往出现在经验设置。例如，审查经常出现在时间到事件的数据，出于各种原因，通常是实证研究者的观察或数据收集计划的结果。失业的拼写长度可能会被删失，因为代理人从样本中丢失，或者为了控制数据收集成本，失业的代理人只被跟踪很短的一段时间。如果他们在这段时间结束时仍然失业，他们的法术长度将被审查。在这个建议中引入的估计量将允许一般形式的删失，在这个意义上，他们允许删失变量以任意的方式依赖于解释持续时间长度的观测变量。这是由（但不限于）特定的经验背景所激发的。对于某些福利计划，如TANF（贫困家庭临时援助），权利取决于个人劳动力市场的历史。在这种情况下，直到一个人找到工作的时间将在权利到期时被审查。 除了一般形式的删失，该提案还包括新的估计程序，用于在实践中遇到持续时间数据的其他特征的模型。一类这样的持续时间模型是面板数据，研究人员观察多个时间到事件，无论是同一个人，或同一组中的不同个人，即家庭成员，或同一行业内的公司。一般来说，面板数据允许研究人员控制无法在横截面数据集中控制的未观察到的因素。在持续时间模型的背景下，该建议提出了一个新的估计面板数据模型，允许一个非常一般的形式（在这种情况下拼写特定）审查。这个建议的其他组成部分开发估计的持续时间模型，表现出以下特点：双删失数据，持续时间模型随时间变化的协变量，和股票抽样持续时间数据，所有这些都遇到了在practice.Broader影响：该项目提供了新的工具，应用经济学家进行推理持续时间分析。持续期模型被广泛应用于应用经济学的各个领域，因为它被用来解决重要的政策问题，如福利改革的效果，退休的税收激励效果，以及失业保险的激励效果。持续时间模型也用于劳动力、发展、公共财政和金融。 这里介绍的新方法和软件代码将在研究者的网站上提供。