Errors in variables regression techniques are used when one or more of the independent variables in an econometric model are subject to sampling or measurement error. These techniques require one to estimate the variances and covariances of the errors prior to running the regression. When the errors are due to sampling variation, this is done by estimating the variance of the mean (or proportion, or whatever is appropriate) of a random sample of size N. This paper deals with the case where the data in a time series are not obtained from a succession of independent samples but rather from a continuing panel, only some of whose members are replaced each period. Correction factors for sampling variances and covariances are developed and numerical results presented. These factors depend upon the structure of the panel, its rate of turnover, and the length of the data period. The results show that it is very dangerous to ignore panel turnover when estimating error variances and covariances for use in errors in variables regression.