EconPapers    
Economics at your fingertips  
 

Improved Lagrange multiplier tests in spatial autoregressions

Peter M. Robinson and Francesca Rossi ()

Econometrics Journal, 2014, vol. 17, issue 1, 139-164

Abstract: For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (χ-super-2) first‐order asymptotic approximation to critical values can be poor in small samples. We develop refined tests for lack of spatial error correlation in regressions, based on Edgeworth expansion. In Monte Carlo simulations, these tests, and bootstrap tests, generally significantly outperform χ-super-2‐based tests.

Date: 2014
References: Add references at CitEc
Citations View citations in EconPapers (7) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1111/ectj.12025

Related works:
Working Paper: Improved Lagrange multiplier tests in spatial autoregressions (2014) Downloads
Working Paper: Improved Lagrange Multiplier Tests in Spatial Autoregressions (2013) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:emjrnl:v:17:y:2014:i:1:p:139-164

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1368-423X

Access Statistics for this article

Econometrics Journal is currently edited by Jaap Abbring, Victor Chernozhukov, Michael Jansson and Dennis Kristensen

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2018-08-15
Handle: RePEc:wly:emjrnl:v:17:y:2014:i:1:p:139-164