We investigate the effects of asymmetry on estimates of variance of robust estimates in location and regression problems, thus showing that heavy skewness of errors can bias seriously the common variance estimates for location and intercept. This is a problem that can be corrected by jackknifing for location, but is more intractable for the intercept in regression. The slope parameters in linear regression seem not to be so seriously subject to this bias if the sample size is large compared with the number of parameters.
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Raymond J. Carroll (1979) studied this question.
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