ABSEst: New Estimation Facilities for ABS Surveys
The introduction of a New Tax System in Australia in July 2000 has enabled the ABS to access Business Activity Statement (BAS) data for most Australian businesses. This data can be used as auxiliary information to reduce cost, provider load and/or sampling errors for many ABS business surveys. A new estimation facility, ABSEst, has been developed to enable maximum use of the auxiliary data through alternative estimation methodologies.
ABSEst is a collection of linked software components. The most important is a generalized regression estimation (GREG) component. This component applies the GREG methodology, which enables the flexible use of auxiliary information using general linear models. If the auxiliary information is correlated with survey variables, then the GREG methodology will improve the accuracy of the estimates for the current sample sizes or reduce the current sample sizes with no reduction in the accuracy of the estimates.
Other software components include: automated outlier detection and treatment using winsorization; and variance estimation using a half-sample bootstrap method.
A number of methodological innovations were made as part of the ABSEst development. The existing winsorization techniques needed to be extended to deal with linear models, using outlier-robust model fitting. A "zeroes-adjusted" GREG estimator was developed to provide more accurate estimates for surveys with many zero values due to defunct and out of scope businesses.
The ABSEst components will be introduced to the Monthly Retail Trade Survey in the March quarter 2004. The introduction of the GREG methodology, as well as redesigning the sample, is expected to result in a 16% reduction in sample size while also slightly improving the precision of the estimates.
ABSEst is expected to be applied to other ABS business surveys over the next few years, as well as be an alternative to GREGWT currently used for household surveys.
If you have any queries on the ABSEst development, please contact: John Preston on (02) 6252 6970.