GMM estimation for high-dimensional semiparametric panel data models
Holder： Chaohua Dong（Zhongnan University of Economics and Law）
Time：2024-11-07 15:10-17:00
Location：Room 217, Guanghua Building 2
Abstract:
In this talk, we show a class of high dimensional moment restriction panel data models with interactive effects, where the factors are unobserved and these factor loadings are nonparametrically unknown smooth functions of individual characteristic variables. We allow the dimension of the parameter vector and the number of moment conditions to diverge with the sample size. This is a very general framework and is closely related to many existing linear and nonlinear panel data models. In order to estimate the unknown parameters, factors and factor loadings, we propose a sieve-based generalized method of moments estimation method and we show that under a set of simple identification conditions, all those unknown quantities can be consistently estimated. Further we establish asymptotic distributions of the proposed estimators. In addition, we propose tests for over-identification, specification of factor loading functions, and establish their large sample properties. Moreover, a number of simulation studies are conducted to examine the performance of the proposed estimators and test statistics in finite samples. An empirical example on stock return prediction is studied to demonstrate both the empirical relevance and the applicability of the proposed framework and corresponding estimation and testing methods.
About the Speaker:
董朝华系中南财经政法大学统计与数学学院教授，博士生导师，“文澜学者”特聘教授；董朝华教授2012年于澳大利亚阿德莱德大学获得经济学博士学位，2012-2015年在澳大利亚莫纳什大学做博士后研究。董朝华教授的学术兴趣聚焦于非平稳时间序列和面板数据建模，非参数和半参数方法，微观计量应用和金融计量经济学。
董朝华教授迄今为止在计量经济学和统计学顶级期刊发表了一系列论文，将非参数筛分法应用于非平稳、非参数和半参数时间序列和面板数据模型，获得国内外相关领域专家好评。他的研究成果获得了第九届全国高等学校科学研究优秀成果奖三等奖，第十二届湖北省社会科学优秀成果奖二等奖。董朝华教授主持了国家自然科学基金面上项目三项，其中已结项的项目（项目号71671143）在国家自然科学基金委员会管理科学部绩效评估中被评为“特优”。
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