讲座主题：Additive nonparametric models with time variable and both stationary and nonstationary regressors

主讲人：董朝华教授

时间：2018年6月25日（周一）13：40-15：40

地点：经济学院（6号楼）210

主办单位：浙江省一流学科“应用经济学”数量经济学方向、经济学院

主讲人简介：

董朝华，西南财经大学教授，博士生导师，澳大利亚阿德莱德大学(the University of Adelaide)经济学博士，澳大利亚莫纳什大学(Monash University)博士后研究员。研究领域涉及时间序列模型，面板数据模型，微观计量和金融计量，非参数和半参数方法。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等上发表多篇学术论文，并且是国际期刊Annals of Statistics, Journal of time series analysis，Journal of econometrics, Journal of nonparametric statistics, Journal of testing and evaluation等期刊的匿名审稿人。

内容摘要：

This paper considers nonparametric additive models that have a deterministic time trend and both stationary and integrated variables as components. The diverse nature of the regressors caters for applications in a variety of settings. In addition, we extend the analysis to allow the stationary regressor to be instead locally stationary, and we allow the models to include a linear form of the integrated variable. Heteroscedasticity is allowed for in all models. We propose an estimation strategy based on orthogonal series expansion that takes account of the different type of stationarity/nonstationarity possessed by each covariate. We establish pointwise asymptotic distribution theory jointly for all estimators of unknown functions and also show the conventional optimal convergence rates jointly in the L2 sense. In spite of the entanglement of different kinds of regressors, we can separate out the distribution theory for each estimator. We provide Monte Carlo simulations that establish the favourable properties of our procedures in moderate sized samples. Finally, we apply our techniques to the study of a pairs trading strategy.