Skip to main content
    • Aa
    • Aa


  • David Preinerstorfer (a1) and Benedikt M. Pötscher (a1)

The behavior of the power function of autocorrelation tests such as the Durbin–Watson test in time series regressions or the Cliff-Ord test in spatial regression models has been intensively studied in the literature. When the correlation becomes strong, Krämer (1985, Journal of Econometrics 28, 363–370.) (for the Durbin–Watson test) and Krämer (2005, Journal of Statistical Planning and Inference, 128, 489–496) (for the Cliff-Ord test) have shown that power can be very low, in fact can converge to zero, under certain circumstances. Motivated by these results, Martellosio (2010, Econometric Theory, 26, 152–186) set out to build a general theory that would explain these findings. Unfortunately, Martellosio (2010) does not achieve this goal, as a substantial portion of his results and proofs suffer from nontrivial flaws. The present paper now builds a theory as envisioned in Martellosio (2010) in an even more general framework, covering general invariant tests of a hypothesis on the disturbance covariance matrix in a linear regression model. The general results are then specialized to testing for spatial correlation and to autocorrelation testing in time series regression models. We also characterize the situation where the null and the alternative hypothesis are indistinguishable by invariant tests.

Corresponding author
*Address correspondence to David Preinerstorfer, Department of Statistics, University of Vienna, Oskar-Morgenstern-Platz 1, A-1090 Vienna, Austria. e-mail:
Hide All
R.A. Horn & C.R. Johnson (1985) Matrix analysis. Cambridge University Press.

T Kariya . (1980) Note on a condition for equality of sample variances in a linear model. Journal of the American Statistical Association, 75, 701703.

W. Krämer & H. Zeisel (1990) Finite sample power of linear regression autocorrelation tests. Journal of Econometrics, 43, 363372.

K Mynbaev . (2012) Distributions escaping to infinity and the limiting power of the Cliff-Ord test for autocorrelation. ISRN Probability and Statistics.

J Tillman . (1975) The power of the Durbin-Watson test. Econometrica, 43, 959974.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Econometric Theory
  • ISSN: 0266-4666
  • EISSN: 1469-4360
  • URL: /core/journals/econometric-theory
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
Type Description Title
Supplementary Materials

Preinerstorfer supplementary material
Preinerstorfer supplementary material 1

 PDF (145 KB)
145 KB


Full text views

Total number of HTML views: 2
Total number of PDF views: 151 *
Loading metrics...

Abstract views

Total abstract views: 590 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 18th October 2017. This data will be updated every 24 hours.