TECHNICAL NOTE 1 METHODOLOGY


INTRODUCTION

1 The estimates in this publication are produced using a combination of ABS directly collected data and Business Activity Statement (BAS) data sourced from the Australian Taxation Office (ATO).

2 The directly collected data have been reported by a sample of businesses, as recorded on the ABS Business Register (ABSBR). The ABS uses an economic statistics units model on the ABSBR to describe the characteristics of businesses, and the structural relationships between related businesses. Within large and diverse business groups, the units model is also used to define reporting units that can provide data to the ABS at suitable levels of detail.


STATISTICAL UNITS DEFINED ON THE ABS BUSINESS REGISTER

3 The current economic statistics units model was introduced in mid 2002, to better use the information available as a result of The New Tax System (TNTS). This units model allocates businesses to one of two sub-populations. The vast majority of businesses are in what is called the ATO maintained population, while the remaining businesses are in the ABS maintained population. Together, these two sub-populations make up the ABSBR population.


ATO MAINTAINED POPULATION

4 Most businesses and organisations in Australia need to obtain an Australian Business Number (ABN). They are then included on the whole-of-government register of businesses, the Australian Business Register (ABR), which is maintained by the ATO. Most of these businesses have simple structures; therefore, the unit registered for an ABN will satisfy ABS statistical requirements. For these businesses, the ABS has aligned its statistical units structure with the ABN unit. The businesses with simple structures constitute the ATO maintained population (ATOMP), and the ABN unit is used as the statistical unit for all ABS economic collections.


ABS MAINTAINED POPULATION

5 For the population of businesses where the ABN unit is not suitable for ABS statistical requirements, the ABS maintains its own units structure through direct contact with the business. These businesses constitute the ABS maintained population (ABSMP). This population consists typically of large, complex and diverse businesses. The statistical units model described below caters for such businesses.

• Enterprise group: This is a unit covering all the operations in Australia of one or more legal entities under common ownership and/or control. It covers all the operations in Australia of legal entities which are related in terms of the current Corporations Law (as amended by the Corporations Legislation Amendment Act 1991), including legal entities such as companies, trusts and partnerships. Majority ownership is not required for control to be exercised.
• Enterprise: An institutional unit comprising:
  • a single legal entity or business entity, or
  • more than one legal entity or business entity within the same enterprise group and in the same institutional sub-sector (i.e. they are all classified to a single Standard Institutional Sector Classification of Australia (SISCA) sub-sector).
• Type of activity unit (TAU): The TAU comprises one or more business entities, sub-entities or branches of a business entity within an enterprise group that can report production and employment data for similar economic activities. When a minimum set of data items are available, a TAU is created which covers all the operations within an industry subdivision (and the TAU is classified to the relevant subdivision of the ANZSIC). Where a business cannot supply adequate data for each industry, a TAU is formed which contains activity in more than one industry subdivision.

CONTRIBUTION OF THE STATISTICAL UNITS TO THE ESTIMATES

6 The following paragraphs outline the way in which categories of statistical units contribute to the estimates of financial and economic variables presented in this publication.


TAUs

7 All units in the ABS maintained population (i.e. TAUs) were eligible to be selected for direct collection. Direct collection of data from these units is necessary because:

• many large and complex employing businesses have more than one legal entity, making it difficult to identify all legal entities for that business in the BAS data
• BAS data do not include all of the detailed information that the ABS requires from large and complex businesses.

ABN units

8 The balance of units on the ABSBR were ABN units, from the ATO maintained population.

9 An indication of the importance of these populations can be gained from their contribution to the national estimate of sales and service income for Total selected industries. The following table shows their proportional contributions to sales and service income.

Contribution to sales and service income
	TAU	ABN unit	Total
	%	%	%
Agriculture, forestry and fishing	16	84	100
Mining	89	12	100
Manufacturing	69	31	100
Electricity, gas, water and waste services	90	10	100
Construction	27	73	100
Wholesale trade	50	50	100
Retail trade	49	51	100
Accommodation and food services	21	79	100
Transport, postal and warehousing	52	48	100
Information media and telecommunications	82	18	100
Rental, hiring and real estate services	14	87	100
Professional, scientific and technical services	28	72	100
Administrative and support services	33	68	100
Education and training (private)	20	80	100
Health care and social assistance (private)	31	69	100
Arts and recreation services	55	45	100
Other services	20	80	100
Total selected industries	49	51	100

COLLECTION DESIGN

10 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.

11 Businesses were selected to participate in the survey (the direct collect sample) only if their turnover exceeded a threshold level or 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.

12 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 $41.1b.


ESTIMATION METHODOLOGY

13 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.


PRODUCING ESTIMATES

14 The following diagram illustrates the ways in which Australian businesses contribute to the estimates in this publication.

DATA STREAMING

15 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:

16 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 and units significant to small state estimates..


Generalised regresssion (GREG) estimation stream:

17 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:

18 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.

19 Estimates for each of the selected industries were produced by aggregating the contributing data streams.


STATE AND TERRITORY ESTIMATES

20 A small component of the sample survey was not specifically designed to produce state estimates. For these units state data was apportioned utilising BAS data obtained from the ATO. For the remainder of sampled units, direct collected data was used. For the remainder of sampled units, a question on the survey form requesting state break ups of wages and salaries and sales and service income was used. This is the first time this has been done in the EAS collection. Previous issues of this publication used factors to model that range of state data and published the results as 'experimental estimates'. The state data produced in 2006-07 is considered to be of a higher quality and not deemed experimental.


BUSINESS SIZE ESTIMATES

21 For consistency, business size estimates have been presented using the same size categories as in previous issues, except for non-employing businesses which have been classified as small businesses. As a result of methodological changes introduced in 2006-07, stratification boundaries no longer align as closely with these size ranges. As a consequence the relative standard errors (RSE) for business size may be higher than in previous industries.


HISTORICAL ESTIMATES

22 Data collected for 2004-05 and 2005-06 (under ANZSIC93) have been updated to take account of any revisions to the data since they were published in the previous issue of this publication. The data so revised have then been mapped to ANZSIC06, and further adjusted to incorporate the scope changes outlined in Explanatory Notes paragraph 9 and the methodological changes discussed in this chapter. This process is known as 'bridging' and was used to create the key data items presented in table 1.1.