Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-24T19:36:56.955Z Has data issue: false hasContentIssue false
  • English
  • Français

NONTESTABILITY OF EQUAL WEIGHTS SPATIAL DEPENDENCE

Published online by Cambridge University Press:  31 May 2011

Federico Martellosio
Federico Martellosio*
Affiliation:
University of Reading
*
*Address correspondence to Federico Martellosio, School of Economics, University of Reading, Whiteknights, Reading RG6 6AW, UK; e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

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.

Type
NOTES AND PROBLEMS
Information
Econometric Theory , Volume 27 , Issue 6 , December 2011 , pp. 1369 - 1375
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Arnold, S.F. (1979) Linear models with exchangeably distributed errors. Journal of the American Statistical Association 74, 194–199.CrossRefGoogle Scholar
Baltagi, B.H. (2006) Random effects and spatial autocorrelation with equal weights. Econometric Theory 22, 973–984.CrossRefGoogle Scholar
Baltagi, B.H. & Liu, L. (2009) Spatial lag test with equal weights. Economics Letters 104, 81–82.CrossRefGoogle Scholar
Baltagi, B.H. & Liu, L. (2010) Spurious spatial regression with equal weights. Statistics and Probability Letters 80, 1640–1642.CrossRefGoogle Scholar
Gross, L. & Yellen, J., eds. (2004) Handbook of Graph Theory. CRC Press.Google Scholar
Kariya, T. (1980a) Locally robust tests for serial correlation in least squares regression. Annals of Statistics 8, 1065–1070.CrossRefGoogle Scholar
Kariya, T. (1980b). Note on a condition for equality of sample variances in a linear model. Journal of the American Statistical Association 75, 701–703.CrossRefGoogle Scholar
Kelejian, H.H. & Prucha, I.R. (2002) 2SLS and OLS in a spatial autoregressive model with equal spatial weights. Regional Science and Urban Economics 32, 691–707.CrossRefGoogle Scholar
Kelejian, H.H., Prucha, I.R., & Yuzefovich, Y. (2006) Estimation problems in models with spatial weighting matrices which have blocks of equal elements. Journal of Regional Science 46, 507–515.CrossRefGoogle Scholar
Lehmann, E.L. & Romano, J. (2005) Testing Statistical Hypotheses. Springer.Google Scholar
Marsh, P. (2007) The available information for invariant tests of a unit root. Econometric Theory 23, 686–710.CrossRefGoogle Scholar
Martellosio, F. (2010). Power properties of invariant tests for spatial autocorrelation in linear regression. Econometric Theory 26, 152–186.CrossRefGoogle Scholar
Smith, T.E. (2009) Estimation bias in spatial models with strongly connected weight matrices. Geographical Analysis 41, 307–332.CrossRefGoogle Scholar