报告题目： Nonparametric Homogeneity Pursuit in Functional-Coefficient Models

主 讲 人： 李德柜，约克大学

报告时间：2021年7月 6 日（周二） 17:00-18:00

报告地点：腾讯会议 ID：333 387 849

点击链接入会：https://meeting.tencent.com/s/sdBHgfeRHWa1

报告摘要：

This paper explores the homogeneity of coefficient functions in nonlinear models with functional coefficients and identifies the underlying semiparametric modelling structure. With initial kernel estimates of coefficient functions, we combine the classic hierarchical clustering method with a generalised version of the information criterion to estimate the number of clusters, each of which has a common functional coefficient, and determine the membership of each cluster. To identify a possible semi-varying coefficient modelling framework, we further introduce a penalised local least squares method to determine zero coefficients, non-zero constant coefficients and functional coefficients which vary with an index variable. Through the nonparametric kernel-based cluster analysis and the penalised approach, we can substantially reduce the number of unknown parametric and nonparametric components in the models, thereby achieving the aim of dimension reduction. Under some regularity conditions, we establish the asymptotic properties for the proposed methods including the consistency of the homogeneity pursuit. Numerical studies, including Monte-Carlo experiments and an empirical application, are given to demonstrate the finite-sample performance of our methods.

主讲人简介：

李德柜, 现为英国约克大学数学系统计学正教授, 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AoS, JASA, JoE, JBES, ET 等。2011 年获澳大利亚科研委员会 DECRA 奖,现担任Econometric Theory, Journal of Time Series Analysis 以及 Econometrics & Statistics 等学术刊物的编委。

主办单位：山东大学金融研究院，山东大学数学学院

邀请人：王汉超