Quasi-generalized least squares regression estimation with spatial data

We use a particular quasi-generalized least squares (QGLS) approach to study a linear regression model with spatially correlated error terms. The QGLS estimator is consistent, asymptotically normal, computationally easier than GLS, and it appears to not lose much efficiency. A variance–covariance estimator for QGLS, which is robust to heteroskedasticity, spatial correlation and general variance–covariance misspecification is provided.