【专家简介】：吴月华，加拿大约克大学数学与统计系教授，在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教授。吴教授研究领域包括M-估计、空间统计、模型选择、变点检测、非参数估计等，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。已在Proceeding of National Academy Science, USA (美国国家科学院院刊)、Biometrika、Journal of Econometrics、Statistica Sinica、Computational Statistics & Data Analysis、Journal of Multivariate Analysis等期刊上发表学术论文130余篇，主持近20项加拿大科研项目。
【报告摘要】： 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 a real data example.
【报告时间】：2024年10月30日 15:00
【报告地点】：位育楼407