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Spatial panel data models with structural change


主 题:Spatial panel data models with structural change



时 间:2022年9月29日(星期四) 14:30

地 点:腾讯会议(会议号:229-615-721)


李鲲鹏,博士、教授、国家杰出青年和优秀青年科学基金获得者,兼任Journal of Business & Economic Statistics期刊编委、中国数量经济学学会常务理事等。主要研究领域为理论计量经济学,研究方向包括高维因子模型、面板数据模型、交互效应模型、空间计量模型等。在国内外高水平期刊上发表论文20余篇,包括Annals of Statistics、Review of Economics and Statistics、Journal of Econometrics、Journal of Business and Economic Statistics、Economics Letters、Econometric Reviews等。

摘 要:Spatial panel data models are widely used in social science, especially in the economics discipline. The existing studies on spatial models usually assume parameters stabilities. Such an assumption may be restrictive given that the presenceof structural changes in the relationship of economic variables has been well documented in the literature. This paper proposes and studies spatial panel data models with structural change. Our benchmark model is a static spatial autoregressive panel data one, and we consider using the quasi maximum likelihood (QML) method to estimate it. The asymptotic theory of the QML estimators including consistency, convergence rate and limiting distribution, is established under large-N and large-T setup. We next extend our theory in two directions: dynamic model and large-N and fixed-T setup. We also study the hypothesis testing for the presence of structural change. The three super-type statistics are proposed. We run simulations to investigate the performance of the QML estimators and find that the QML estimators behave well in our simulations.