Abstract
Due to different types of weights matrix, estimation and test, many kind of spatial econometric models are deduced especially depend on space effects and spatial correlation. The general formulation of several important spatial regression models for cross-sectional or panel data are analyzed based on adequate consideration of spatial effects and the formal expression of spatial autocorrelation. For spatial econometric model estimation, there are mainly three methods (maximum likelihood estimation, GMM estimation, and Bayesian estimation). Spatial model specification tests (such as Moran's I test, KR test, GMM-based test, LM/RS test, Wald test and likelihood ratio test) are used for several reasons based on the estimated regression and spatial weights matrix. So, the empirical study based on spatial econometrics should consider the different types of model specification and tests, especially the objectives for your research and application.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
