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FINITE-SAMPLE MOMENTS OF THE COEFFICIENT OF VARIATION

We study the finite-sample bias and mean squared error, when properly defined, of the sample coefficient of variation under a general distribution. We employ a Nagar-type expansion and use moments of quadratic forms to derive the results. We find that the approximate bias depends on not only the skewness but also the kurtosis of the distribution, whereas the approximate mean squared error depends on the cumulants up to order 6.
Year of publication:
2009
Authors: Bao, Yong
Published in:
Econometric Theory. - Cambridge University Press. - Vol. 25.2009, 01, p. 291-297
Publisher: Cambridge University Press
Description of contents: Abstract [journals.cambridge.org]
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005411806
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