A nonparametric adjustment for tests of changing mean

Ted Juhl ()
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Ted Juhl: University of Kansas

Economics Bulletin, 2004, vol. 3, issue 34, 1-11

Abstract: When testing for a change in mean of a time series, the null hypothesis is no change in mean. However, a change in mean causes a bias in the estimation of serial correlation parameters. This bias can cause nonmonotonic power to the point that if the change is big enough, power can go to zero. In this paper, we show that a nonparametric correction can restore power. The procedure is illustrated with a small Monte Carlo experiment.

JEL-codes: C2 (search for similar items in EconPapers)
Date: 2004-09-22
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