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Finite-Sample Moments Of The Coefficient Of Variation

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  • Bao, Yong

Abstract

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.

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  • Bao, Yong, 2009. "Finite-Sample Moments Of The Coefficient Of Variation," Econometric Theory, Cambridge University Press, vol. 25(1), pages 291-297, February.
    • Handle: RePEc:cup:etheor:v:25:y:2009:i:01:p:291-297_09
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    Cited by:

    1. Dennis D. Boos & Jason A. Osborne, 2015. "Assessing Variability of Complex Descriptive Statistics in Monte Carlo Studies Using Resampling Methods," International Statistical Review, International Statistical Institute, vol. 83(2), pages 228-238, August.

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