We investigate the finite-sample bias of the quasi-maximum likelihood estimator (QMLE) in spatial autoregressive models with possible exogenous regressors. We derive the approximate bias result of the QMLE in terms of model parameters and also the moments (up to order 4) of the error distribution, and thus a feasible bias-correction procedure is directly applicable. In some special cases, the analytical bias result can be significantly simplified. Our Monte Carlo results demonstrate that the feasible bias-correction procedure works remarkably well.
Address correspondence to Yong Bao, Department of Economics, Krannert School of Management, Purdue University, 403 W. State St., West Lafayette, IN 47907, USA; e-mail: firstname.lastname@example.org.
The author is grateful to Peter Phillips and four anonymous referees for their constructive and detailed feedback that greatly improved the paper. The author benefited from discussions with Robert de Jong and Lung-Fei Lee. The author also thanks conference participants at the IVth World Conference of the Spatial Econometrics Association (Chicago) and seminar participants at the Ohio State University for helpful comments. The author is solely responsible for any remaining errors.