Content
The largest enterprise groups are determined using the variable "Sales of Goods and Services". It is possible to use other variables, such as Employment or Industry Value Added to determine and rank the largest enterprise groups. This data is available upon request and is a charged service.
Each group consists of four large businesses. The exception is where groups have either been combined or suppressed following standard ABS confidentiality rules. However, their data does appear in the 'total' figures. Where groups have been combined, this is indicated in the category title.
Reference period
The statistical results presented in these tables are based on details of profit and loss statements and balance sheets collected from selected businesses, mainly by mail out questionnaires. For 1998–99, businesses were asked to provide data in respect of the financial year ending June 1999. In a minority of cases, where businesses did not account on a June-year basis, details were reported in respect of the accounting year which ended between October 1998 and September 1999.
Scope and coverage
The estimates relate to businesses in the public trading and private employing sectors of the economy only. The population frame for the EAS statistics consisted of all business units in the Australian economy except for:
(a) Agricultural businesses with an estimated value of agricultural operations less than $22,500;
(b) non-employing businesses in all other industries i.e. businesses which have not registered as group employers with the ATO; and
(c) businesses classified to the General Government sector (note: government-owned Public Trading Enterprises were included).
Statistical unit
The enterprise group 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). These may be legal entities such as trusts and partnerships as well as companies. Majority ownership is not required for control to be exercised.
The business unit about which information is collected and published for the Economic Activity Survey is termed the management unit. This is the highest level unit within a business, for which a set of management accounts are maintained. In most cases it coincides with the legal entity owning the business (i.e. company, partnership, trust, sole operator, etc.). However, in the case of large diversified businesses there are often a number of management units, each coinciding with a 'division' or 'line of business'. A division or line of business is recognised where separate and comprehensive accounts are compiled for it.
The ABS Business Register provided the population frame from which management units were selected for inclusion in the EAS.
Approximately 19,000 management units were selected for the EAS-based collection using stratified random sampling techniques. All management units with employment of 200 or more persons were automatically selected in the sample.
Data in these tables have been adjusted to allow for lags in processing new businesses to the ABS business register, and the omission of some businesses from the register.
Classification by industry
This publication presents statistics classified according to the Australian and New Zealand Standard Industrial Classification, 1993 (Cat. no. 1292.0). Each business unit is classified to a single industry. The industry allocated is based on an estimate of the primary activity of the management unit irrespective of whether a range of activities or a single activity is undertaken by the unit. For example, a management unit which derives most of its income from construction activities would have all operations included in the aggregates and ratios for the Construction industry division, even if significant secondary activities (e.g. quarrying) were undertaken. This is different from the approach that might be taken to the collection of statistics on an activity basis.
A non-standard industry label, Private Community Services has been adopted for ANZSIC divisions N and O to emphasise the fact that general government units are excluded.
Employment
Includes working proprietors, working partners, permanent, part-time, temporary and casual employees, and managerial and executive employees working for a business during the last pay period in June each year. Employees absent on paid or prepaid leave are included.
Industry Value Added (IVA)
Represents the value added by an industry to the intermediate inputs used by that industry. From 1997–98, IVA has replaced IGP as the official measure of the contribution by industries to GDP. While IVA and IGP both represent gross output less intermediate inputs (or alternatively, the value added to intermediate inputs), introduction of new international standards for measuring economic variables has meant changes to the way in which gross output and intermediate inputs are defined, as follows.
Trading profit
plus Operational funding from Government
plus Own account capital work
equals Capitalised wages and salaries
plus Capitalised purchases
less Capitalised purchases
equals IGP
plus Computer software (non capitalised) expense
plus Indirect taxes (fringe benefits tax, payroll tax, land rates and taxes)
plus Exploration expenditure written off
less Intellectual property royalty expense
equals IVA
Sales of Goods and Services
Includes sales of goods whether or not manufactured by the business and sales or transfers to related businesses, plus all rent, leasing and hiring income. Also included is repair, maintenance and service income and fees, income from work done or sales made on a commission basis, delivery or installation charges which are invoiced separately to customers, advertising income and management fees/charges from related or unrelated businesses. As a result of revised international standards, income from royalties from intellectual property are also a component of estimates of income from services commencing with estimates for 1997-98. (Excluded are rent. leasing and hiring income, government bounties and subsidies, income from natural resource royalties, interest income and dividends).
Related publications
Some of the industry-specific collections used to compile the statistics in this publication can provide fine level breakdowns of the data (e.g. by State). For more information on these surveys refer to the following ABS publications.
(i) Agriculture, Australia, 1998-99 (Cat. no. 7113.0)
(ii) Electricity, Gas, Water and Sewerage Industries, Australia, 1997-98 (Cat. no. 8208.0)
(iii) Manufacturing Industry, Australia, 1998-99 (Cat. no. 8221.0)
(iv) Mining Operations, Australia, 1997-98 (Cat. no. 8415.0)
Unpublished statistics
A considerable amount of data from the EAS collection exists in unpublished form. In general, unpublished data consists of finer industry dissections and can be presented by size classifications tailored to a client's specific need. For example, size classifications based on specified ranges in the value of sales, profits or assets can be generated. Additionally, many other performance measures or ratios apart from those included in the publication can be generated. Some examples are liquidity, debt coverage, stocks turnover and assets turnover ratios. A charge is made for providing unpublished information.
Further information
For more information about these statistics, including a full glossary of terms, refer to the publication Business Operations and Industry Performance, Australia, 1998–99 (Cat. no. 8140.0).
RELIABILITY AND LIMITATIONS
Relative standard error
Since the estimates in this publication are based on information obtained from a sample drawn from units in the surveyed population, the estimates are subject to sampling variability. That is, they may differ from the figures that would have been produced if all units had been included in the survey.
One measure of the likely difference is given by the standard error (SE), which indicates the extent to which an estimate might have varied by chance because only a sample of units was included. The relative standard error (RSE) provides an immediate indication of the percentage errors likely to have occurred due to sampling, and thus avoids the need to refer to the size of the estimate. The relative standard errors table on page 32, provides RSEs for a selection of estimates presented in this publication. It should be noted that estimates for large businesses are generally not subject to sampling error as every effort is made to completely enumerate these businesses.
There are about 2 chances in 3 that the difference between the estimate shown and the true value will be within one SE, and about 19 chances in 20 that the difference will be within two SEs. Thus, for example, if the estimated value of a variable is $12,000 million and its RSE is 5%, its reliability in terms of sampling error can be interpreted as follows. There are about 2 chances in 3 that the true value of the variable lies within the range $11,400 million to $12,600 million, and 19 chances in 20 that it lies within the range $10,800 million and $13,200 million.
The imprecision due to sampling variability, which is measured by the SE, is not to be confused with inaccuracies that may occur because of inadequacies in available sources from which the population frame was compiled, imperfections in reporting by providers, errors made in collection such as in recording and coding data, and errors made in processing data. Inaccuracies of this kind are collectively referred to as non-sampling error and they may occur in any enumeration, whether it be a full count or a sample.
While it is not possible to quantify non-sampling error, every effort is made to reduce it to a minimum. Collection forms are designed to be easy to complete and assist businesses to report accurately. Efficient and effective operating procedures and systems are used to compile the statistics.
Limitations of financial data analysis
This product presents a wide range of data that can be used to analyse business and industry performance. It is important that any analysis be based upon a range of data presented rather than focusing on one variable.
Differences in accounting policy and practices across businesses and industries also lead to some inconsistencies in the data input to the statistics. While much of the accounting process is subject to standards, there is still a great deal of flexibility left to managers and accountants in the accounting policy and practices they adopt. For example, acceptable methods of asset valuation include historical cost, replacement cost and current market value. The timing of asset revaluations also varies considerably across businesses. The way profit is measured is affected by management policy on such things as depreciation rates, bad debt provisions and write off and goodwill write off.
The above limitations are not meant to imply that analysis based on this data should be avoided, only that they should be borne in mind when interpreting the data presented in this product.
The counts of operating businesses included in this publication should be used with some caution. Over and above the sampling error associated with these estimates, they are more affected than are other estimates presented by such things as internal restructuring of businesses (e.g. changes in divisional structure), mergers, takeovers and changes in the quality of the ABS Business Register. These management unit counts exclude management units which were part year operators i.e. operating at the beginning of the reference period but not at the end.
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