Kernel-Based Inference in Time-Varying Coefficient Cointegrating Models

报告题目： Kernel-Based Inference in Time-Varying Coefficient Cointegrating Models

报告人： Professor Degui Li

Department of Mathematics, University of York, UK

时间地点：2019年4月4日(星期四)上午9:50-

浙江大学玉泉校区工商管理楼二楼200-9报告厅

摘要： In this talk, we consider nonlinear cointegrating models with time-varying coefficients and multiple non-stationary regressors using classic kernel smoothing methods to estimate the coefficient functions. Extending earlier work on nonstationary kernel regression to take account of practical features of the data, we allow the regressors to be cointegrated and to embody a mixture of stochastic and deterministic trends, complications which result in asymptotic degeneracy of the kernel-weighted signal matrix. To address these complications new local and global rotation techniques are introduced to transform the covariate space to accommodate multiple scenarios of induced degeneracy. Under regularity conditions we derive asymptotic results that differ substantially from existing kernel regression asymptotics, leading to new limit theory under multiple convergence rates. In addition, we also discuss the generalized Wald test statistic in model specification test and derive the relevant theory. This talk is based on some joint research works with P.C.B. Phillips and J. Gao.

欢迎参加！

联系人: 张立新教授 stazlx@zju.edu.cn

浙江大学数据科学研究中心、浙江大学数学科学学院统计学研究所

李德柜教授简介： 李德柜，现为英国约克大学数学系统计学正教授，2003年获浙江大学统计学学士学位，2008年获浙江大学理学博士学位，曾在澳大利亚阿德莱德大学经济系和莫纳什大学商学院从事博士后研究。主要的研究领域包括非参数统计学，（非平稳）时间序列分析，面板数据建模，稳健统计量，高维统计学和计量经济学，并有数十篇论文发表于国际知名统计学和计量经济学刊物如Annals of Statistics，Journal of the American Statistical Association，Journal of Econometrics等。2011年获澳大利亚科研委员会DECRA奖。