Testing for spatial autocorrelation: the regressors that make the power disappear

Federico Martellosio ()

MPRA Paper from University Library of Munich, Germany

Abstract: We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cliff-Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that define the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided.

Keywords: Cliff-Ord test; point optimal tests; power; spatial error model; spatial lag model; spatial unit root (search for similar items in EconPapers)
JEL-codes: C12 C21 (search for similar items in EconPapers)
Date: 2008-09
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-ore and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:10542

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