SEMIPARAMETRIC ESTIMATION OF MULTIPLE EQUATION MODELS
提出一种针对多方程多指标模型的半参数估计量，该估计量最小化因变量无条件均值与条件均值间的平均距离，具有√N一致性和渐近正态性，并通过蒙特卡洛实验评估有限样本表现。
This paper proposes a semiparametric estimator for multiple equations multiple index (MEMI) models. Examples of MEMI models include several sample selection models and the multinomial choice model. The proposed estimator minimizes the average distance between the dependent variable unconditional and conditional on an index. The estimator is √N-consistent and asymptotically normally distributed. The paper also provides a Monte Carlo experiment to evaluate the finite-sample performance of the estimator.