Improved Lagrange multiplier tests in spatial autoregressions

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.

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Year of publication:	2014-02
Authors:	Robinson, Peter M. ; Rossi, Francesca
Institutions:	London School of Economics (LSE)
Subject:	bootstrap \| Edgeworth expansion \| finite-sample corrections \| Lagrange multiplier test \| spatial autocorrelation

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Extent:	application/pdf
Series:	LSE Research Online Documents on Economics.
Type of publication:	Book / Working Paper
Notes:	Published in The Econometrics Journal, February, 2014, 17(1), pp. 139-164. ISSN: 1368-4221
Classification:	C0 - Mathematical and Quantitative Methods. General
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011125890