Implementation of Generalised Regression (GREG) Estimation for the Retail Business Survey Analysis
In recent years, the ABS has put a major focus on reducing respondent burden. As part of this a conscious effort to better utilise external or administrative data sources has been sought. One of the best forms of administrative data that the ABS can access for business surveys is tax data especially Business Activity Statement (BAS) data. BAS data has been incorporated to reduce respondent burden in the Retail Business Survey through improvement of sample designs via stratification and estimation.
Prior to June 2004 the Retail Business Survey used Ratio Estimation, which utilises one auxiliary variable, Derived Size Benchmark (DSB), to improve the level and accuracy of estimates. DSB is a tax derived item which models the old ABS employment which forms a part of stratification for all ABS business surveys. The retail survey was last redesigned in 1994 on the basis of state, industry and number of employed persons.
Preliminary investigations indicated that gains could be achieved for the retail survey through the use of tax data and Generalised Regression Estimation, but these would be maximised through redesigning the survey at the same time, incorporating the tax data into stratification. MD developed a strategy to coincidentally implement both a change to stratification and estimation.
One problem evident through initial testing of the BAS data was a large number of units with a zero retail sales value but a non-zero benchmark. A large number of these were legitimate due to recent deaths and out of scope units. This problem was limiting the potential gains that could be achieved from the BAS data. A solution to this was to post-stratify in generalised regression estimation by zero and non-zero units to essentially fit separate regression lines to the two types of units. This addition resulted in gains that aligned more with expectation.
A significant reduction in both sampling error and sample size was achieved. This was primarily due to the much better correlation of the BAS data with the variable of interest, retail sales, than the previous benchmark variable. While the improved method of estimation has been significant, the majority of the gains were realised when complementing this with the new stratification.
For more information, please contact, Glenys Bishop (02) 6252 5140
Email: glenys.bishop@abs.gov.au
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