GMM estimation of spatial autoregressive models in a system of simultaneous equations with heteroskedasticity |
| |
Authors: | Xiaodong Liu Paulo Saraiva |
| |
Affiliation: | Department of Economics, University of Colorado Boulder, Boulder, Colorado, USA |
| |
Abstract: | This paper proposes a GMM estimation framework for the SAR model in a system of simultaneous equations with heteroskedastic disturbances. Besides linear moment conditions, the proposed GMM estimator also utilizes quadratic moment conditions based on the covariance structure of model disturbances within and across equations. Compared with the QML approach, the GMM estimator is easier to implement and robust under heteroskedasticity of unknown form. We derive the heteroskedasticity-robust standard error for the GMM estimator. Monte Carlo experiments show that the proposed GMM estimator performs well in finite samples. |
| |
Keywords: | Simultaneous equations spatial autoregressive models quadratic moment conditions unknown heteroskedasticity |
|