Improved Lagrange multiplier tests for spatial autoregressions
For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (X2) 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 X2 based tests.
Year of publication: |
2013-10-07
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Authors: | Rossi, Francesca ; Robinson, Peter |
Institutions: | Economics Division, University of Southampton |
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