|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CVER | CEP | SERC | STICERD||Cookies?|
Paper No' EM 596: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: Efficient test; adaptive estimation; spatial models
JEL Classification: C12; C13; C14; C21
Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: Econometrics
Share this page: Google Bookmarks | Facebook | Twitter
Abstract:We consider adaptive tests and estimates which are asymptotically efficient in the presence of unknown, nonparametric, distributional form in pure spatial models. A novel adaptive Lagrange Multiplier testing procedure for lack of spatial dependence is proposed and extended to linear regression with spatially correlated errors. Feasibility of adaptive estimation is verified and its efficiency improvement over Gaussian pseudo maximum likelihood is shown to be either less than, or more than, for models with explanatory variables. The paper covers a general class of semiparametric spatial models allowing nonlinearity in the parameters and/or the weight matrix, in addition to unknown distribution.
Copyright © RLAB & LSE 2003 - 2018 | LSE, Houghton Street, London WC2A 2AE | Contact: RLAB | Site updated 15 August 2018