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TECHNICAL NOTE 1 METHODOLOGY
8 The balance of units on the ABSBR classified to these industries were ABN units, from the ATO maintained population.
9 In order to decrease the statistical reporting load placed on providers while maintaining the range and quality of information available to users of statistical data, the strategy for this survey was to adopt the use of directly collected data from a smaller sample of businesses, in combination with information sourced from the ATO. The frame (from which the direct collect sample was selected) was stratified using information held on the ABS Business Register. Businesses eligible for selection in the direct collect sample were then selected from the frame using stratified random sampling techniques.
10 Businesses were selected to participate in the survey (the direct collect sample) only if they met two criteria: their turnover exceeded a threshold level and the business was identified as having been an employing business (based on ATO information) during the reference period. Turnover thresholds were set for each ANZSIC class so that the contribution of surveyed businesses accounted for 97.5% of total industry class turnover as determined by ATO Business Activity Statement data.
11 Businesses which met neither of these criteria are referred to as 'micro non-employing businesses'. These businesses were not eligible for selection in the sample. For these units, BAS data were obtained and annualised, then added to the directly collected estimates to produce the statistics in this publication. The total estimated value of annual turnover of micro non-employing businesses during the 2006-07 reference year, as determined by ATO Business Activity Statement data, was $223m.
12 Estimates from previous iterations of this survey were produced using number raised estimation methodology. The 2006-07 survey used generalised regression estimation. This estimation method enables maximum use of observed linear relationships between data directly collected from businesses in the survey and auxiliary information. When the auxiliary information is strongly correlated with data items collected in a survey, the generalised regression estimation methodology will improve the accuracy of the estimates. The auxiliary variables used in this survey were turnover and wages sourced from ATO Business Activity Statement data.
13 The following diagram illustrates the ways in which Australian businesses contribute to the estimates in this publication.
14 For the purpose of compiling the estimates in this publication, data for businesses as recorded on the ABSBR contribute via one of three categories (or 'streams') in accordance with significance and collection-related characteristics.
Completely Enumerated (CE) Stream:
15 The CE stream consists of directly collected survey data for those units recorded on the ABSBR as having employment greater than 300, plus additional 'significant' units in the ABS maintained population.
Generalised regression (GREG) estimation Stream:
16 The GREG stream comprises directly collected data for those sampled units which are not in the CE stream and have turnover, in aggregate, above the bottom 2.5 percentile of BAS sales for that industry. The accuracy of the estimates produced from this data is then improved by using wages and turnover data sourced from businesses' BAS data.
Business Activity Statement (BAS) Stream:
17 The BAS stream comprises data for those businesses in the ATO maintained population whose turnover, in aggregate, is below the bottom 2.5 percentile of BAS sales for that industry.
PRODUCING INDUSTRY ESTIMATES
18 Estimates for each of the selected industries were produced by aggregating the contributing data streams.
19 An indication of the importance of these populations to the data can be gained from their contribution to the national estimate of sales and service income. The following table shows their proportional contributions to this estimate for each of these industries.
20 One implication of the use of BAS data in these statistics is that no direct measure of employment is available for those units which contribute to the estimates solely through the BAS source. This is because the ATO does not collect information about employment numbers. Unlike financial variables, which have a direct relationship to the data available from the BAS files, employment data are not amenable to being modelled using the same techniques. Hence a different methodology is used in order to estimate employment for those units whose data are sourced solely from the BAS files. For each such business, the number of employees is assumed to be zero. For each unincorporated business, an estimate of its number of working proprietors or partners is used as the estimate of its total employment. These estimates are then aggregated to the directly collected data to produce the estimates in this publication.
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