1 The statistical results presented in this publication have been derived from the annual Economic Activity Survey (EAS) for the financial year ending June 2001.
2 The EAS results are from details of statements of financial performance (profit and loss statements) and statement of financial position (balance sheets) collected from selected businesses, mainly by mail-out questionnaires. For 2000-01, businesses were asked to provide data in respect of the financial year ending June 2001. 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 2000 and September 2001.
3 The estimates relate to businesses in the public trading and private employing sectors of the economy only.
SCOPE AND COVERAGE
4 The diagram below illustrates the dissection of business in the Australian economy.
5 The population for the 2001 EAS statistics consisted of all business units in the Australian economy except for:
§ all businesses classified to the Agricultural, forestry and fishing industry.
§ non-employing businesses in all other industries i.e. businesses which have not registered as group employers with the ATO
§ businesses classified to the General Government sector (note: government-owned Public Trading Enterprises were included).
6 The business unit about which information is collected and published for the EAS 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.
7 The ABS Business Register provided the population frame from which management units were selected for inclusion in the EAS.
8 Approximately 20,000 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.
9 Data in this publication 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.
10 Since the beginning of the survey, 'surprise outliering' has been used as the methodology to identify and reduce the impact on the estimates of businesses whose response to the survey was significantly different to those of its peers. Where the extreme values have been confirmed as correct, the sample weight that had originally been applied to the business is reduced to 1. That is, the business represents itself and not others. In the vast majority of cases surprise outliering has the effect of reducing the estimates by more than they should. To compensate for this, the methodology has been changed since the 1999–2000 reference period by the introduction of 'winsorised outliering'. The introduction of winsorisation was not industry wide, with the Mining, and Electricity, gas and water supply industries expected to convert at a later date.
11 Winsorising reduces the harsh impact of surprise outliering by moderating the impact of businesses who perform differently to their peers. The improved methodology, which does not rely on a subjective judgement, will provide for more stable time series estimates.
12 An analysis of the 1998–99 estimate was undertaken to identify the impact on the estimates of the change in methodology. At the All industries level the impact of the change is minimal. However for some data items in some industries there is an impact on the estimates. The industries most affected by the implementation of winsorising were Retail trade and Personal and other services with balance sheet data items demonstrating the greatest impact. A detailed table showing the impact of the changed methodology is available by contacting the inquiries officer listed on the front page of this publication.
CLASSIFICATION BY SIZE
13 This publication presents statistics broken into two categories, defined as follows:
§ large businesses include all management units which employ 200 or more persons or have assets worth more than $200m
§ other businesses are those management units which employ less than 200 persons and do not have assets worth more than $200m.
14 Other size dissections can be made available on request, subject to the data passing confidentiality tests.
CLASSIFICATION BY INDUSTRY
15 This publication presents statistics classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 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.
16 Where figures have been rounded, a discrepancy may occur between the sum of the component items and the total. Published percentages are calculated prior to rounding of figures and therefore a discrepancy may occur between the published percentages and percentages which could be calculated from the published estimates.
17 Care should be exercised when comparing results from different ABS surveys due to likely differences in scope, methodology, data item definition and reference period.
18 Significant units came into scope of the estimates of the Property and Business Services industry during the 2000-01 reference period. Due to the introduction of these units, care should be taken when comparing the series overtime.
19 Although data providers were requested to report all income and expense items exclusive of Goods and Services Tax (GST), there is some evidence that in a minority of cases data has been provided inclusive of GST. The impact of this misreporting is estimated to be minimal.
LIMITATIONS OF FINANCIAL DATA ANALYSIS
20 This publication 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.
21 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 varying degree to which businesses consolidate their accounts may also affect the ratios calculated.
22 Those ratios compiled from a combination of flow and level items need to be treated with additional caution. The information contained in balance sheets indicates the level of assets and liabilities at a point in time. Information contained in profit and loss statements summarise the flows (or transactions) which have taken place during the past financial year. Ratios which include both level and flow items in their derivation may be volatile due to the timing differences involved.
23 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 publication.
24 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. Because of these influences, estimates of the number of businesses have been smoothed, using a three-year moving average. This technique reduces the effect the above influences have on movements in the number of operating businesses across the years. Having applied this technique, the estimates are then considered suitable for use in analysing changes in the relative composition of industries and the generation of business averages (NB a two-year average is applied to the most recent year's estimate, incorporating the current year's estimate with that of the previous year). 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.
25 It is important to note that if an industry is dominated by a number of large businesses, it is possible for one or more of the significant businesses to affect the aggregates, business averages and industry ratios without having a similar effect on the business comparisons and business profitability measures. It is also possible for a business to rank highly in the business comparisons, while having little effect on the industry ratios and aggregates. For example, if a unit reported an operating profit of $50,000 and total assets of $10,000 it would have a return on assets of 500% and rank well above the 75th percentile for return on assets, while its contribution to the aggregates and industry ratios would be minimal.
26 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
27 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.
§ Agriculture, Australia, 1999–2000 (cat.no.7113.0)
§ Electricity, Gas, Water and Sewerage Industries, Australia, 1999–2000 (cat.no.8208.0)
§ Manufacturing Industry, Australia, 1999–2000 (cat.no.8221.0)
§ Mining Operations, Australia, 2000–01 (cat.no.8415.0).
STATISTICS AVAILABLE ON REQUEST
28 Finer industry dissections than those presented in this publication can be found in the ABS product Summary of Industry Performance (cat.no.8140.0.55.002). This product provides a one page summary of each industry's structure, income statement, balance sheet, economic values, business averages and performance ratios to the ANZSIC subdivision (two digit) level. For most ANZSIC subdivisions, separate Summaries of Industry Performance are available for small and medium (combined) and for large sizes of businesses.
29 Another source of more detailed data is the ABS product Industry Concentration Statistics (cat.no.8140.0.55.001). This product shows the proportions of sales, persons employed and industry value added (IVA) that are concentrated among the 20 largest enterprise groups operating in each industry. The 'largest 20' are further subdivided by groups of four, viz. first four groups, second four groups, and so on.
30 Both the Summaries of Industry Performance and Industry Concentration Statistics can either be purchased separately as a product, or accessed through the ABS web based information service, AusStats. AusStats is a subscription service, providing access to a comprehensive range of ABS material. It is available on-line, via the World Wide Web, and is a part of the ABS web site where both free and charged data are integrated.
31 Additionally, a considerable amount of data from the EAS collection is available on request. In general, data requests entail a finer industry dissection 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 non standard data requests and information is only made available if it passes confidentiality testing.