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Nontestability Of Equal Weights Spatial Dependence

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  • Martellosio, Federico

Abstract

We show that any invariant test for spatial autocorrelation in a spatial error or spatial lag model with equal weights matrix has power equal to size. This result holds under the assumption of an elliptical distribution. Under Gaussianity, we also show that any test whose power is larger than its size for at least one point in the parameter space must be biased.

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  • Martellosio, Federico, 2011. "Nontestability Of Equal Weights Spatial Dependence," Econometric Theory, Cambridge University Press, vol. 27(06), pages 1369-1375, December.
  • Handle: RePEc:cup:etheor:v:27:y:2011:i:06:p:1369-1375_00
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    Cited by:

    1. Preinerstorfer, David & Pötscher, Benedikt M., 2017. "On The Power Of Invariant Tests For Hypotheses On A Covariance Matrix," Econometric Theory, Cambridge University Press, vol. 33(01), pages 1-68, February.
    2. Tony Smith & Ka Lee, 2012. "The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach," Journal of Geographical Systems, Springer, vol. 14(1), pages 91-124, January.

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