Improved Lagrange multiplier tests in spatial autoregressions

Peter M. Robinson and Francesca Rossi ()

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (χ2) 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 χ2-based tests.

Keywords: bootstrap; Edgeworth expansion; finite-sample corrections; Lagrange multiplier test; spatial autocorrelation (search for similar items in EconPapers)
JEL-codes: C0 (search for similar items in EconPapers)
Date: 2014-02
New Economics Papers: this item is included in nep-geo, nep-ore and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Published in Econometrics Journal, February, 2014, 17(1), pp. 139-164. ISSN: 1368-4221

Downloads: (external link)
http://eprints.lse.ac.uk/56049/ Open access version. (application/pdf)

Related works:
Journal Article: Improved Lagrange multiplier tests in spatial autoregressions (2014)
Working Paper: Improved Lagrange Multiplier Tests in Spatial Autoregressions (2013)
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:ehl:lserod:56049

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().