Seminar Vol. 187

Title: Large Sample Properties of Bayesian Estimation of Spatial Econometric Models

Speaker: Xingbai Xu, Xiamen University

Time: October 18th, 2019    13:30-15:00

Venue: Conference Room 106B, IESR, Zhonghui Building (College of Economics)

About the speaker:

Xingbai Xu received his Ph.D. in Economics from the Ohio State University in 2016. He is currently an Associate Pofessor at Xiamen University. His research focuses on Spatial Econometrics, Econometric Theory, Social Network, Applied Econometrics. Xingbai Xu has published some papers in the Journal of Econometrics, Regional Science and Urban Economics.

Abstract:

This paper studies asymptotic properties in the classical statistical framework of a posterior probability density and Bayesian estimators of spatial econometric models. We focus on the high order spatial autoregressive model with spatial autoregressive disturbance terms, due to a computational advantage of the Bayesian estimation. We also study the asymptotic properties of the Bayesian estimation of the spatial autoregressive Tobit model, as an example of nonlinear spatial models. Simulation studies show that even when the sample size is small or moderate, the posterior distribution of parameters is well approximated by a normal distribution, and Bayesian estimators have satisfactory performance, as the classical large sample theory has predicted.