报告题目：Estimation and model selection in general spatial dynamic panel data models
报告时间：5月15日下午4:30-5:30
报告地点：博远楼309教室
摘要：Common methods for estimating parameters of spatial dynamic panel data models include two-stage least squares, quasi-maximum likelihood, and generalized moments. In this talk, we present a method that uses the eigenvalues and eigenvectors of a spatial weight matrix to directly construct consistent least squares estimators of parameters of general spatial dynamic panel data models for both undirected and directed networks. Our method is conceptually simple and effective,and easy to implement. Results show that our parameter estimators are consistent and asymptotically normally distributed under mild conditions. We demonstrate the superior performance of our method through extensive simulation studies. We also provide two real data examples.
报告人简介：吴月华，加拿大约克大学数学与统计系教授。1989年获得美国匹兹堡大学统计学博士学位，师从世界著名统计学家C. R. Rao。研究领域广泛，包括空间统计、M-估计、模型选择、变点检测、非参数统计、金融统计等，以及在环境科学、信息科学、计量经济学、生物医学等领域中的应用，目前是国际统计学会的当选会员。在Proceedings of the National Academy Science USA，（美国国家科永利皇宫 院刊），Computational Statistics & Data Analysis，Statistica Sinica，Journal of Multivariate Analysis，Biometrika等期刊发表学术论文140多篇。承担加拿大国家自然科学基金、加拿大环境署等多项科研项目。
邀请人：徐礼柏