ESTIMATING PANEL DATA DURATION MODELS WITH CENSORED DATA
提出一种估计面板数据持续时间模型的方法，该模型允许未知变换的持续时间变量与解释变量和未观测异质性线性相关，估计量在右删失下具有一致性和渐近正态性，并通过蒙特卡洛模拟验证有限样本表现。
This paper presents a method for estimating a class of panel data duration models, under which an unknown transformation of the duration variable is linearly related to the observed explanatory variables and the unobserved heterogeneity (or frailty) with completely known error distributions. This class of duration models includes a panel data proportional hazards model with fixed effects. The proposed estimator is shown to be n 1/2 -consistent and asymptotically normal with dependent right censoring. The paper provides some discussions on extending the estimator to the cases of longer panels and multiple states. Some Monte Carlo studies are carried out to illustrate the finite-sample performance of the new estimator.