The Estimation and Testing of a Linear Regression with Near Unit Root in the Spatial Autoregressive Error Term

This paper considers the estimation of a linear regression involving the spatial autoregressive (SAR) error term, which is nearly nonstationary. The asymptotics properties of the ordinary least squares (OLS), true generalized least squares (GLS) and feasible generalized least squares (FGLS) estimators as well as the corresponding Wald test statistics are derived. Monte Carlo results are conducted to study the sampling behavior of the proposed estimators and test statistics. Key Words: Spatial Autocorrelation; Ordinary Least Squares; Generalized Least Squares; Two-stage Least Squares; Maximum Likelihood Estimation JEL No. C23, C33