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Biometrika 1971 58(1):53-60; doi:10.1093/biomet/58.1.53
© 1971 by Biometrika Trust
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On a new test for autocorrelation in least squares regression

A. P. J. ABRAHAMSE and A. S. LOUTER

Netherlands School of Economics, Econometric Institute

The Durbin-Watson test on autocorrelation is based on the least squares residual vector. It is well known that the distribution of this vector depends upon the regression matrix which implies that tabulation of the test statistic's significance points is senseless. The best linear unbiased scalar test circumvents this difficulty and gives a test statistic whose distribution does not depend upon the regression matrix; it is an exact test. However, some objections can be made against this test. In this paper, a new exact procedure which meets these objections is presented. A method to compute the test statistic is outlined. Powers of the new procedure for some examples are computed and compared with the corresponding powers of the Durbin-Watson test and the best linear unbiased scalar test.

Key Words: Least squares regression in time series • Serial correlation tests • Disturbance estimation in the linear model • Best linear unbiased scalar residuals


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