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

[摘要]I: Khan， Shakeeb组织：罗切斯特大学标题：具有一般审查形式的横断面和面板数据持续时间模型的估计提出的活动的主要智力价值是开发了新的计量经济学和统计方法，用于在持续时间模型中进行估计和推断。本建议中考虑的统计模型是由持续时间数据的特定特征所驱动的，这些特征通常出现在经验设置中。例如，由于各种原因，审查经常出现在时间到事件的数据中，这些原因通常是经验研究者的观察或数据收集计划的结果。失业时间长度可能会被删减，因为失业代理人从样本中消失了，或者为了控制数据收集成本，失业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后仍然失业，他们的法术长度将被审查。本建议中引入的估计器将允许一种一般形式的审查，因为它们允许审查变量以任意方式依赖于解释持续时间长度的观察变量。这是由（但不限于）特定的经验背景所驱动的。对于某些福利项目，如TANF（贫困家庭临时援助），福利取决于个人的劳动力市场历史。在这种情况下，直到一个人找到工作的持续时间将在权利到期时进行审查。除了一般形式的审查外，该建议还包括针对在实践中遇到的持续时间数据的其他特征的模型的新的估计程序。其中一类持续时间模型是针对面板数据的模型，在这种模型中，研究人员对事件进行多次观察，要么是针对同一个人，要么是针对同一群体中的不同个人，即家庭成员或同一行业中的公司。一般来说，面板数据允许研究人员控制在横断面数据集中无法控制的未观察到的因素。在持续时间模型的上下文中，该建议建议为面板数据模型提供一个新的估计器，该模型允许非常通用的形式（在本例中是特定于拼写的）审查。本提案的其他组成部分开发了持续时间模型的估计器，该模型具有以下特征：双重审查数据，具有时变协变量的持续时间模型和库存采样持续时间数据，所有这些都在实践中遇到过。更广泛的影响：该项目为应用经济学家提供了在持续时间分析中进行推理的新工具。持续时间模型在实践中被广泛应用于应用经济学的各个领域，因为它们被用来解决重要的政策问题，如福利改革的影响、税收对退休的激励作用、失业保险的激励作用等。持续时间模型也用于劳动、发展、公共财政和金融领域。这里介绍的新方法和软件代码将在研究者的网站上提供。

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.