文章基本信息

标题：Estimation and Inference in Heterogeneous Spatial Panel Data Models with a Multifactor Error Structure
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作者：Jia Chen ; Yongcheol Shin ; Chaowen Zheng 等
期刊名称：Discussion Papers in Economics / Department of Economics, University of York
出版年度：2020
卷号：20
语种：English
出版社：University of York
摘要：In this paper, we develop a unifying econometric framework for the analysis of heterogeneous panel data models that can account for both spatial dependence and unobserved common factors. To tackle the challenging issues of endogeneity caused by both the spatial lagged term and the correlation between regressors and factors, we propose to approximate common factors by cross-section averages of independent variables only, and deal with the spatial endogeneity via the instrumental variables. We develop the individual estimators 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 our proposed estimators are quite satisfactory. We demonstrate the usefulness of our approach with an application to a gravity model of bilateral trade flows for 91 pairs of 14 European Union (EU) countries, and find that the trade flows between the UK and EU members would fall substantially following a hard Brexit.