Abstract

In this article we study the semiparametric estimation of the Tobit model simultaneously jointed with an endogenous regressor. The model usually is estimated by maximum likelihood method and two-stage estimation under the normality assumption of the error terms. The possible misspecification motivates our semiparametric study. We first construct a semiparametric estimator for the parameters in the reduced form equations and prove its consistency and asymptotical normality. Then the parameters in the structural models are recovered by system minimum distance estimator. The simulation shows that our estimator performs well in different designs in finite samples. Finally, an empirical application is given to show the usefulness of the estimator.

摘要

在本文中，我们研究了与内生回归器同时结合的 Tobit 模型的半参数估计。该模型通常在误差项的正态性假设下采用最大似然法和两阶段估计进行估计。可能的错误指定激发了我们的半参数研究。我们首先为简化形式方程中的参数构造一个半参数估计器，并证明其一致性和渐近正态性。然后通过系统最小距离估计器恢复结构模型中的参数。模拟表明我们的估计器在有限样本的不同设计中表现良好。最后，给出了一个实证应用来展示估计器的实用性。