报告形式👩🏻‍🎤：腾讯会议

报告主题：Imputation for Spatial Dynamic Panel Data with Dependent Variable Missing at Random

Missing data is a common problem that researchers face in practice. In this article, we focus on the missing response problem for a spatial dynamic panel data (SDPD) model, which allows for both spatial and temporal dependencies. A logistic regression with a set of pre-specified covariates is used to model the missingness mechanism, which is assumed to be missing at random (MAR). A weighted maximum likelihood estimator (WMLE) is proposed for parameter estimation in the presence of incomplete data. The associated asymptotic properties are investigated. Thereafter, we develop a novel imputation method, which makes use of the information from spatial dependence, temporal dependence, and exogenous regression covariates. Lastly, the performance of WMLE and the proposed imputation method are demonstrated by both simulation studies and a real data example.

报告人简介🚴🏼‍♀️：

甄峰🧑🏻‍🌾，经济学博士🏥，北京AG尊龙凯时平台娱乐登录官方网站统计学院副教授，经济与社会统计系主任，国际统计学会当选会员🧊。主要研究方向是经济统计、政府统计👨‍🦼，关注经济社会发展的统计分析与应用研究。