Other things equal, the higher the match rate, the lower will be the DSE population estimate and the estimated net undercount in the census. Conversely, the more nonmatches, the higher will be the DSE population estimate and the estimated net undercount. In contrast, the higher the correct enumeration rate, the higher will be the DSE population estimate and the estimated net undercount. Conversely, the more erroneous enumerations, the lower will be the DSE population estimate and the estimated net undercount (for how this result obtains, refer to Equation 5.1 in Section 5-A).
The A.C.E. and PES design and estimation focused on estimating the net undercount and not on estimating the numbers or types of gross errors of erroneous enumerations (overcounts) or of gross omissions. There are not widely accepted definitions of components of gross error, even though such errors are critically important to analyze in order to identify ways to improve census operations. Some types of gross errors depend on the level of geographic aggregation. For example, assigning a census household to the wrong small geographic area (geocoding error) is an erroneous enumeration for that area (and an omission for the correct area), but it is not an erroneous enumeration (or an omission) for larger areas. Also, the original A.C.E. design, similar to the PES, did not permit identifying duplicate census enumerations as such outside a ring or two of blocks surrounding a sampled block cluster. On balance, about one-half of duplicate enumerations involving different geographic areas should be classified as an “other residence” type of erroneous enumeration at one of the two addresses because the person should have been counted only once, but this balancing may not be achieved in practice.
Several aspects of the original A.C.E. design were modified from the PES design in order to improve the timeliness and reduce the variance and bias of the results (see Section 5-D.1). Some of these changes were clearly improvements. In particular, the larger sample size (300,000 households in the A.C.E. compared with 165,000 households in the PES) and the reduction in variation of sampling rates considerably reduced the variance of the original A.C.E. estimates compared with the PES estimates (see Starsinic et al., 2001). The coefficient of variation for the originally estimated coverage correction factor of 1.012 for the total population in 2000 was 0.14 percent, a reduction of 30 percent from the comparable coefficient of variation