报告题目：Estimation and Inference in Heterogeneous Spatial Panels with a Multifactor Error Structure
报 告 人：陈佳 教授
报告地点：腾讯会议 会议 ID：655 870 423
We develop a unifying econometric framework for the analysis of heterogeneous panel data models that can account for both spatial dependence and common factors. To tackle the challenging issue of endogeneity due to the spatial lagged term and the correlation between the regressors and factors, we propose an estimation procedure that approximates factors by cross-section averages of regressors only and deals with the spatial endogeneity via internal instrumental variables. We develop the individual estimator as well as the Mean Group and the Pooled estimators, and establish their consistency and asymptotic normality. Monte Carlo simulations confirm that the finite sample performance of the proposed estimators is quite satisfactory. We demonstrate the usefulness of our approach with an application to a gravity model of bilateral trade flows for 14 EU countries, finding that the trade flows between UK and EU members would fall significantly following a hard Brexit.
陈佳，英国约克大学经济系教授，2008年在浙江大学数学系取得理学博士学位。 主要从事计量经济学和时间序列的研究，在国际学术刊物上发表论文二十余篇，其中多篇发表在AOS，JASA，JOE，JBES等国际统计学与计量经济学顶级期刊上，现为Journal of Nonparametric Statistics 的Associate Editor。