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We estimate an AR(1) for the time series associated with each cell kt. For each cell, the error Δr = r − r^* is computed, where r and r^* are the first-order serial correlation coefficient computing using confidential data and protected data, respectively. Table 2.1 shows the distribution of the errors Δr across SIC-division × county cells, for accessions A, beginning-of-quarter employment B, full-quarter employment F, net job flows JF, and separations S (for additional tables, see Abowd et al. 2012). Table 2.1 shows that the time series properties of the QWI remain largely unaffected by the distortion. The central tendency of the bias (as measured by the median of the Δr distribution) is never greater than 0.001, and the error distribution is tight: the semi-interquartile range of the distortion for B in Table 2.1 is 0.022, which is less than the precision with which estimated serial correlation coefficients are normally displayed.¹⁰ The overall spread of the distribution is slightly higher when considering two-digit SIC × county and three-digit SIC × county cells (not reported here), due to the greater sparsity. The time series properties of the QWI data are unbiased. The small amount additional noise in the time series statistics is, in general, economically meaningless.