|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CVER | CEP | SERC | STICERD||Cookies?|
Paper No' SERCDP0061: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: statistical methods; spatial, modeling
JEL Classification: C1; C12; C21; R000; R15
Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: SERC Discussion Papers
Share this page: Google Bookmarks | Facebook | Twitter
Abstract:We argue that identification problems bedevil most applied spatial research. Spatial econometrics solves these problems by deriving estimators assuming that functional forms are known and by using model comparison techniques to let the data choose between competing specifications. We argue that in most situations of interest this, at best, achieves only very weak identification. Worse, in most cases, such an approach will simply be uninformative about the economic processes at work rendering much applied spatial econometric research ‘pointless’, unless the main aim is simply description of the data. We advocate an alternative approach based on the ‘experimental paradigm’ which puts issues of identification and causality at centre stage.
Copyright © RLAB & LSE 2003 - 2016 | LSE, Houghton Street, London WC2A 2AE | Contact: RLAB | Site updated 26 September 2016