An Integrated GMM Shrinkage Approach with Consistent Moment Selection from Multiple External Data Sources
Holder： Fang Fang（East China Normal University）
Time：2024-06-06 10:00-11:30
Location：Room 217, Guanghua Building 2
Abstract:
Interest has grown in analyzing primary internal data by utilizing some independent external aggregated statistics for efficiency gain. However, when population heterogeneity exists, inappropriate incorporation may lead to a biased estimator. With multiple external sources under generalized estimation equations and possibly heterogeneous populations, we propose an integrated generalized moment method that can perform a data-driven selection of valid moment equations from external sources and make efficient parameter estimation simultaneously. Moment equation selection consistency and asymptotic normality are established for the proposed estimator. Further, when the sample sizes of all external sources are large compared to the internal sample size, asymptotically the proposed estimator is more efficient than the estimator based on the internal data only and is oracle-efficient in the sense that it is as efficient as the oracle estimator based on all valid moment equations. Simulation studies confirm the theoretical results and the efficiency of proposed method empirically. An example is also included for illustration.
About the Speaker:
方方，华东师范大学统计学院教授，博士生导师。入选上海市东方英才计划拔尖项目。曾任统计与数据科学前沿理论及应用教育部重点实验室副主任。本科和博士先后毕业于北京大学数学系和美国威斯康星大学统计系。在2013年加入华东师范大学之前，曾在通用电气金融集团和上海浦东发展银行任职多年。主要研究方向为缺失数据、模型平均、碎片化数据分析、KS学习。在包括 AOS/JOE/Biometrika/JBES 在内的国际一流统计学和计量经济学期刊上发表论文30余篇。先后主持和参与国家和省部级项目13项。目前主持国家自然科学基金重点项目“大数据背景下不完全数据的统计分析方法、理论和应用”。授权专利6项。曾获上海市自然科学二等奖。全国工业统计学教学研究会常务理事、数字经济与区块链技术分会副理事长，IMS China委员会委员，SCI期刊 Journal of Nonparametric Statistics 副主编。在应用领域长期关注信用评分和民航QAR大数据分析。出版统计科普小说《统计王国奇遇记》和专著《多源数据的统计分析与建模》。
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