On the Impact of the Tests for Serial Correlation Upon the Test of Significance for the Regression Coefficient
Journal of Econometrics, Vol. 7, 1978
Posted: 28 May 2013 Last revised: 30 May 2013
Date Written: June 29, 1977
Monte Carlo methods are used to investigate the relationship between the power of different pretests for autocorrelation, and the Type I error and power of the significance test for a resulting two-stage estimate of the slope parameter in a simple regression. Our results suggest it may be preferable to always transform without pretesting. Moreover we find little room for improvement in the Type I errors and power of two-stage estimators using existing pretests for autocorrelation, compared with the results obtained given perfect knowledge about when to transform (i.e., given a perfect pretest). Rather, researchers should seek better estimators of the transformation parameter itself.
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