非线性计量经济模型的非参数估计方法研究

本文提出使用核估计的方法构造平滑转移模型(STR)的非参数模拟最大似然估计(NPSML),给出了NPSML估计量的构造方法、渐近性质以及相应的核函数和窗宽的选择准则,并利用滑动窗宽算法对估计量的构造过程进行了改进。通过Monte Carlo实验证明,该方法是可靠的,并且当误差项存在序列相关时,此种估计量是稳健的。

Study on Nonparametric Estimation of Nonlinear Econometric Model

This paper proposes nonparametric simulated maximum likelihood(NPSML) estimation for smooth transition model by kernel method.We provide a unified framework for constructing NPSML estimator and give rules for the choice of kernel function and bandwidth,and then use a slide variable bandwidth algorithm to improve its accuracy and reliability.Monte Carlo simulation study shows NPSML estimator is consistent and asymptotically efficient and robust when the error terms represent serial correlation.