Improved Lagrange Multiplier Tests in Spatial Autoregressions

Peter M Robinson and Francesca Rossi ()

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (x squared) 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 ones, generally significantly outperform x squared-based tests.

Keywords: Spatial autocorrelation; Lagrange multiplier test; Edgeworth expansion; bootstrap; finite-sample corrections. (search for similar items in EconPapers)
JEL-codes: C29 (search for similar items in EconPapers)
Date: 2013-10
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://sticerd.lse.ac.uk/dps/em/em566.pdf (application/pdf)

Related works:
Journal Article: Improved Lagrange multiplier tests in spatial autoregressions (2014)
Working Paper: Improved Lagrange multiplier tests in spatial autoregressions (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:566

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