Semiparametic Nonlinear Least-Squares Estimation of Truncated Regression Models
提出一种半参数方法估计截断回归模型，利用截断前扰动项与回归元独立的性质，证明估计量的一致性和渐近正态性，并通过蒙特卡洛实验考察有限样本性质。
This article provides a semiparametric method for the estimation of truncated regression models where the disturbances are independent of the regressors before truncation. This independence property provides useful information on model identification and estimation. Our estimate is shown to be -consistent and asymptotically normal. A consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.