主题｜Topic：A weighted sieve estimator for nonparametric time series models with nonstationary variables
时间｜Time：11月22号（周五）｜Nov. 22th (Friday), 2:00-5:15PM
地点｜Venue：文澴楼709会议室｜Meeting Room 709, WENHUAN
主讲｜Speaker
董朝华老师现为bv伟德源自英国始于1946统计与数学学院教授，博士生导师。他于澳大利亚阿德莱德大学 (The University of Adelaide) 获得经济学博士学位，曾任澳大利亚莫纳什大学 (Monash University) 博士后研究员。已在统计学和计量经济学的国际顶尖期刊 Annals of Statistics, Statistica Sinica, Journal of Econometrics, Econometric Theory, Econometric Reviews 等发表多篇学术论文，同时也是 Annals of Statistics, Journal of time series analysis, Journal of econometrics, Journal of nonparametric statistics, Journal of testing and evaluation 等国际期刊的匿名审稿人。
研究领域｜Research Interests
时间序列模型、面板数据模型、微观计量和金融计量、非参数和半参数方法
摘要｜Abstract
We study a class of nonparametric regression models that includes deterministic time trends and both stationary and nonstationary stochastic processes (whose shocks are allowed to be mutually correlated). We propose a unified approach to estimation based on the weighted sieve method to tackle the issue of unbounded support of the covariates. This approach improves on the existing technology in terms of some key regularity conditions such as moment conditions and the alpha-mixing coefficients for the stationary process. We establish self-normalized central limit theorems for the sieve estimator and other related quantities. Monte Carlo simulation confirms the theoretical results. We use our methodology to study the effect of CO2 and solar irradiance on global sea level rise.
