【主题】Applications of Functional Dependence to Spatial Econometrics
【摘要】In this paper, we generalize the concept of functional dependence from time series (Wu, 2005) and stationary random fields (El Machkouri, Volný and Wu, 2013) to nonstationary spatial processes. Within conventional settings in spatial econometrics, we define the concept of spatial functional dependence measure and establish a moment inequality, an exponential inequality, a Nagaev-type inequality, a law of large numbers, and a central limit theorem. We show that the dependent variables generated by some common spatial econometric models, including spatial autoregressive models, threshold spatial autoregressive models and spatial panel data models, are functionally dependent under regular conditions. Furthermore, we investigate the properties of functional dependence measures under various transformations, which are useful in applications. Moreover, we compare spatial functional dependence with the spatial mixing and spatial near-epoch dependence proposed in Jenish and Prucha (2009, 2012), and we illustrate its advantages.
【报告人简介】许杏柏，厦门大学王亚南经济研究院和经济学院常任副教授，博士生导师。2016年从俄亥俄州立大学获得经济学博士学位。现在主持国家自然科学基金面上项目一项。主要研究领域为空间计量经济学和网络计量经济学。多份研究成果发表在Journal of Econometrics, Econometric Theory, Regional Science and Urban Economics等学术期刊上。