Abstract
Some robust approaches are outlined that form a basis for a more realistic statistical inference in spatial econometric models. Three specific issues are addressed: significance tests on coefficients in the spatial expansion method that are robust to the presence of heteroskedasticity of unknown form; heteroskedasticity-robust specification tests for spatial dependence; and boot-strap estimation in spatial autoregressive models. The techniques are presented in formal terms and their application to spatial analysis is illustrated in a number of simple empirical examples.
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.
