Time:2023/04/28 (Fri.), 13:30 -15:00 (Beijing Time)

Title:   Application of Functional Dependence to Spatial Econometrics

Venue:  Zhonghui Building 106

About the speaker:

Xingbai Xu is a Tenured Associate Professor at Wang Yanan Institute for Studies in Economics and the School of Economics, Xiamen University. He obtained his Ph.D. in Economics from the Ohio State University. His areas of specialization include spatial econometrics, network econometrics, econometric theory and applied econometrics. He has published in Journal of Econometrics, Econometric Theory.

Abstract:

This paper generalizes the concept of functional dependence from time series (Wu, 2005) and stationary random fields (El Machkouri, Volný and Wu, 2013) to non-stationary 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 law of large numbers, and a central limit theorem under it. We show that the dependent variables generated by some common spatial econometric models, including 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 is 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 illustrate its advantages.