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
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Citations: View citations in EconPapers (17)

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http://hdl.handle.net/10.1111/ectj.12025

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