|Page tools: Print Page Print All|
10 The business unit about which information is collected and published for the EAS collection is termed the management unit. This is the highest level unit within a business for which a set of management accounts is 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.
11 For the ATO, business income tax returns are submitted for legal entities. Management units are generally made up of one or more legal entities, but it is possible for legal entities to be made up of one or more management units.
12 The ABS Business Register provided the population frame from which management units were selected for inclusion in the EAS. It also provided a multi-State indicator which was used as a starting point in the methodology to derive State level estimates from the EAS/Tax data.
13 For non-employing businesses, which are not included on the ABS Business Register, ATO business income tax records were used as the population frame. All non-employing businesses were assumed to operate in a single State.
14 Since the estimates in this publication are the result of combining ABS directly collected data with ATO data, the statistical unit has been referred to as a 'business entity'. As explained in paragraphs 10 and 11 above, the ABS unit and the ATO unit are not always comparable. Therefore, providing a count of the number of business entities is not simply a matter of summing the legal entities in the ABS data and the ATO data. Any legal or other business entities that are not included in ABS or ATO data files (e.g. shelf companies) are not included in the estimates shown in this publication.
15 The 2,097,000 business entities referred to in the diagram on page 4 consists of 1,410,000 non-employing business entities sourced directly from the ATO and 687,000 employing business entities sourced from a combination of ABS and ATO data.
16 Estimates in this publication from the directly collected businesses have been adjusted to allow for lags in the processing of new businesses to the ABS Business Register, and the omission of some businesses from the register.
17 A sample of approximately 20,000 management units was selected for the directly collected part of the EAS/Tax collection. Stratified random sampling techniques were used. All management units with employment of 200 or more persons were automatically selected in the sample. A further sample of approximately 82,400 employing businesses was selected from the business income tax file to supplement the estimates from the 20,000 directly collected businesses.
18 The EAS/Tax sample was not selected on the basis of State for single State businesses. As a result, an increase in sampling error in some States may have occurred. To some extent, any increase in sampling error will have been offset by the expanded use of business income tax data, which provides an increase in sample size across each State. The sampling error may become more significant at the ANZSIC division and subdivision levels, depending on the number of businesses that each business in the sample represents in that particular State. Refer to Technical Note 2: Limitations of Financial Data Analysis on page 36 and the relative standard error tables 9, 10 and 11 on pages 20 - 22 for further details.
CLASSIFICATION BY INDUSTRY
19 This publication presents industry estimates classified according to the Australian and New Zealand Standard Industrial Classification, 1993, (Cat.no.1292.0), commonly known as ANZSIC. Each business unit is classified to a single industry class, even where it operates across more than one State. The industry allocated is based on an estimate of the primary activity of the management unit, irrespective of whether the management unit undertakes a single activity or a range of activities. For example, a management unit which derives most of its income from construction activities would have all of its operations included in estimates for the Construction division, even if significant secondary activities (e.g. quarrying) were undertaken by the management unit. This differs from the approach that might be taken to the collection of statistics on an activity basis.
20 Refer to Technical Note 1: Methodology for details on the process used to derive State proportions from EAS/Tax data. Outlined below are some of the assumptions users should be aware of when using the State level estimates presented in this publication.
21 Differences in scope, coverage and business classifications exist between the ABS collections used to obtain State dissection information for businesses. In some instances, State dissections have been based on quarterly rather than annual data due to the unavailability of annual State estimates.
22 Sales-based proportions obtained for each multi-State business have been used to apportion EAS/Tax estimates of Total income, Total expenses and Operating profit before tax (OPBT) data across the States for that business. Similarly, Wages-based proportions have been used to apportion Labour costs across States.
23 ABS collections used to obtain State proportions for multi-State businesses are not always consistent in the wording of the State-based questions. For example, the Wholesale Industry Survey collects estimates of income from the sales of goods and services on the basis of the State or Territory from which the goods were despatched, while the Retail Industry Survey collects estimates of income from the sales of goods and services on the basis of where the final purchase occurred. These different treatments are necessary depending on the industries in scope of each collection. Wherever possible, the State dissections for a particular industry have used the data source best suited to that industry. In some cases employment has been used as a proxy for obtaining State proportions.
24 Due to the nature of their activity, some businesses find it difficult to respond to State-based questions. Examples include businesses in the Communication Services industry, and to a lesser extent the Transport and Storage industry, where the activity of the business is not necessarily confined by State boundaries. Additional effort has been put into assisting businesses in these industries report State dissections and as a result revisions have been made to the 1998-99 estimates.
25 For some businesses, income-based State proportions sourced from one ABS direct collection have been used in conjunction with wages-based State proportions sourced from another direct collection.
26 Significant contributors to each industry were reviewed to check the consistency and reliability in relation to State proportions. The accuracy of State proportions reported by many of these businesses appeared reasonable. In some instances proportions were amended where better information was available.
27 As much State information as possible was collected for each selected business, however, it is recognised that some identified single State businesses may actually operate across more than one State. In most cases, the effect on the estimates due to this factor is minimal - refer to the diagram on page 33 in Technical Note 1: Methodology.
28 The movements between 1998-99 and 1999-2000 were analysed and compared with other data sources. While most unusual discrepancies could be explained as being within the bounds of sampling error, the estimates of proportions of the Australian total between 1998-99 and 1999-2000 for the Health division (ANZSIC division O) showed substantial change. In particular, New South Wales was showing a nine percent increase in its contribution to the Australian total for Health and Queensland showed an eight percent decrease in its contribution to the Australian total. Further analysis of the components to movements indicated that a recent change to the sample design and high rotation contributed to this unusual level of movement. Therefore, in this publication an adjustment has been made which removed these two effects to produce a better estimate of movement which has then been used to recalculate the State contributions to the Australian totals for 1999-2000. The assumption used by this technique is that the 1998-99 estimates are without sampling error. While this is not true the adjustment outcome provides a more coherent State distribution.
29 Limited editing has been undertaken on estimates for the Agriculture industry data due to the lack of available sources with which to confront the estimates. As a result, the published estimates should be used with extreme caution.
30 Where figures have been rounded, discrepancies may occur between the sums of the component items and totals. Published percentages are calculated prior to the rounding of figures and therefore some discrepancy may occur between those percentages and those that could be calculated from rounded figures.
31 There are small changes in totals from those in Australian Industry, (Cat.no.8155.0), published in March 2001 due to revisions in estimates. The 1998-99 estimates have also been revised due to improved editing practices and additional information from providers.
32 Users may wish to refer to the following ABS publications and data products:
33 A range of individual service industry publications are also produced by the ABS. In general, these publications contain considerable detail about the employing sector of each industry.
APPENDIX; COMPARISON WITH OTHER ABS ESTIMATES
A BRIEF HISTORY
The experimental EAS/Tax State estimates presented in this publication are produced by apportioning the results from the national EAS/Tax estimates across States using proportions obtained from a range of ABS statistical collections.
Australian level EAS/Tax estimates have been compiled using a combination of data from the annual Economic Activity Survey (EAS), conducted by the ABS, and business income tax data provided by the ATO. For details on this methodology please refer to the Technical Note 1: Methodology, on page 31.
A range of ABS collections produce estimates at the State level. However, most ABS collections providing a State dissection cover only part of the economy at a given point in time, e.g. the manufacturing industry. By contrast, the State estimates presented in this publication aim to provide a comprehensive view across a number of industries at the same time, rather than for any one specific industry. To achieve this aim, new approaches (including greater use of business income tax data and utilising data already collected by the ABS) are being used. Given the difference in approach, these methods will result in differences with other State estimates presented by the ABS. To help users understand these differences, this appendix outlines some of the investigations performed in comparing EAS/Tax State estimates with data from other ABS sources and presents likely explanations for the differences.
COMPARISON WITH THE ANNUAL MANUFACTURING SURVEY
Each year the ABS conducts a detailed survey in relation to the Manufacturing industry. Data from this survey for the 1999-2000 reference period was compared to the State EAS/Tax estimates for the Manufacturing industry. The most recent results from the survey are presented in Manufacturing Industry, Australia, 1999-2000 (Cat.no.8221.0).
For the 1999-2000 reference period, the Manufacturing survey approached a sample of approximately 17,000 manufacturing establishments, which were asked to provide data on a number of items, such as turnover and wages and salaries.
An establishment is the smallest accounting unit of a business, within a State or Territory, controlling its productive activities and maintaining a specified range of detailed accounting data. Generally, an establishment covers all operations of a business at a physical location, but it may consist of groups of locations provided they are within the same State or Territory. Most establishments operate at one location only.
While the Manufacturing survey collects data at the establishment level, data from the EAS/Tax collection is primarily collected at the management unit level. The management unit is a higher level unit than the establishment, i.e. a management unit may consist of one or more establishments. Each establishment in the Manufacturing survey is allocated to a specific ANZSIC class, as is each management unit in the EAS/Tax collection. A management unit consisting of one establishment will be allocated to the same ANZSIC class as the establishment. However, a management unit consisting of more than one establishment will be allocated to one ANZSIC class only, that being the class of its predominant activity.
To illustrate this distinction and how it can effect estimates, consider a hypothetical business, comprising one management unit with three establishments; one in ANZSIC class 2811 (Motor vehicle manufacturing), one in class 2812 (Motor vehicle body manufacturing) and one in class 4621 (Car wholesaling).
The management unit derives 60% of its income from motor vehicle manufacturing, 30% from car wholesaling and 10% from the manufacture of vehicle bodies, so motor vehicle manufacturing is regarded as the predominant activity of the management unit. In the EAS/Tax collection, all of the activity of the business would therefore be regarded as being in ANZSIC class 2811, so the business would be considered to be primarily involved in motor vehicle manufacturing and all of its activity would be included in estimates for the Manufacturing industry. However, in the Manufacturing survey, only the activity of the establishments in ANZSIC classes 2811 and 2812 would contribute to estimates for the Manufacturing industry.
This example illustrates how differences in the type of business units surveyed can lead to differences in the resulting estimates. Estimates compiled from management unit level data for businesses that consist of a number of different establishments, each with different predominant activities, will most likely differ from the equivalent estimates compiled from establishment level data.
The difference in estimates can become more noticeable at finer industry levels, e.g. if the third establishment in the above example was in ANZSIC class 2764 (Metal coating and finishing), all three establishments would be in classes within the Manufacturing division. Estimates from EAS/Tax and the Manufacturing survey for the business would therefore be similar at the ANZSIC division level. However, the estimates would differ at the ANZSIC subdivision level due to the management unit being wholly in subdivision 28, while the establishments would be in subdivisions 27 and 28.
The above examples go some way towards explaining the results of comparisons between State EAS/Tax estimates and the equivalent estimates from the Manufacturing survey. Investigations undertaken for 1999-2000 estimates showed that estimates from the two sources were broadly comparable at the ANZSIC division level and that differences between the two sets of estimates became more noticeable at the subdivision level.
COMPARISON WITH THE QUARTERLY ECONOMIC ACTIVITY SURVEY
Since the March quarter 2001 reference period, the ABS has conducted the Quarterly Economic Activity Survey (QEAS). This comparatively new survey replaces a number of previous similar quarterly business surveys in the ABS' statistical program, most notably the Survey of Inventories, Sales and Services and the Survey of Company Profits. The most recent results from the survey are contained in Business Indicators, Australia, December quarter 2001 (Cat.no.5676.0).
The QEAS collection is conceptually similar to the annual Economic Activity Survey (EAS), in that it collects economic data from businesses across most industries in the Australian economy. Both surveys also collect data at the management unit level. However, there are a number of differences between the two surveys, most notably in timing, scope and sampling methodology.
The most obvious difference between the EAS and QEAS collections is that the former is conducted annually and the latter conducted quarterly. The quarterly nature of QEAS means that for some industries, data for individual quarters is likely to be influenced by seasonal factors. The method used to derive State estimates for EAS/Tax used QEAS proportions from one quarter as one source of State proportions, but any seasonal factors were not taken into account when applying the State proportions from QEAS to the annual EAS/Tax data.
The other major difference between the two collections is related to scope, i.e. the types of businesses that make up the population frame for each collection. The QEAS frame excludes all public sector businesses, i.e. all departments, authorities and other organisations controlled by Commonwealth, State or Local Government. The EAS frame excludes all public sector businesses in the General Government sector, but it includes Public Trading Enterprises (PTEs). PTEs are likely to be significant contributors to EAS/Tax estimates for some industries, particularly Electricity, Gas and Water Supply, Transport and Storage and Communication Services, so estimates for these industries from the two collections are not conceptually consistent.
The survey samples for the two collections are also designed very differently. The State in which each business operates forms part of the sample design for QEAS, but not for EAS. Also, while the QEAS sample consists of approximately 16,000 management units and the EAS sample consists of approximately 20,000 management units, the number of businesses common to the two survey samples is kept to a minimum in order to spread the provider load associated with completing the forms for the two surveys. Some medium-sized and large businesses may have been selected in the samples for both collections, but there should be very few small businesses common to both samples.
When EAS/Tax State level estimates were compared with those from QEAS, it was apparent that the most significant differences were due to scope differences between the two collections, particularly for those industries most likely to include significant PTEs.
COMPARISONS WITH OTHER ABS DATA SOURCES
As well as the comparisons mentioned in this appendix, EAS/Tax State estimates for 1999-2000 were compared with data from the following ABS sources:
In general, it was found that differences between the EAS/Tax State estimates and those from the other ABS data sources listed above most commonly resulted from differences in one of more of the following: scope, coverage, classifications or reference periods.
TECHNICAL NOTE 1: METHODOLOGY
PRODUCING EAS/TAX ESTIMATES
1 The methodology used to produce the estimates contained in this publication is outlined in the ABS Information Paper: Experimental Estimates: Australian Industry, a State Perspective, 1998-99 (Cat No. 8156.0). The information contained here is a summarised account of the methodology, aimed at providing users with a broad overview of the techniques used. For additional details, readers should refer to the information paper mentioned above. For details on caveats and cautions that should be considered when using this data, readers should refer to the Explanatory Notes on pages 23 - 27.
2 The estimates in this publication are the result of combining ABS directly collected data with business income tax data sourced from the ATO. The diagram below is a summary of the different data sources used for businesses in producing these estimates.
3 Information for large employing businesses was sourced from the EAS collection. The two main reasons for this approach were:
COMPLEX SMALL AND MEDIUM EMPLOYING BUSINESSES
4 Information for complex small and medium employing businesses was also sourced from the EAS collection. There are two main types of businesses that are collectively termed 'complex small and medium employing businesses', and there are difficulties in sourcing business financial data from the business income tax files for these businesses. These businesses are:
SIMPLE SMALL AND MEDIUM EMPLOYING BUSINESSES
5 Small and medium employing businesses that have simple structures (i.e.management units with one legal entity) had their data sourced from the business income tax files.
6 There were 493,622 simple small and medium employing businesses on the ABS Business Register as at June 30, 2000. Of these, a sample of 65,140 businesses was selected to have their data sourced from the business income tax files.
MATCHING THE ATO BUSINESS INCOME TAX FILES TO ABS SOURCES FOR 'SIMPLE SMALL AND MEDIUM EMPLOYING' BUSINESSES
7 Business entities must be matched to the business income tax files to obtain their business financial data. Given the complex nature of reconciling businesses on the business income tax files with the ABS Business Register, a complete match for all businesses is not possible. However, it is expected that for future years the number of records matched will increase as a result of the introduction of the Australian Business Number (ABN) and its inclusion on both the business income tax files and the ABS Business Register.
8 The ABS was able to identify 69% of selected businesses on the business income tax files. There are several reasons why there is not a 100% match rate:
9 The sampling and estimation methods used by the ABS take into account selected businesses that are not able to be identified on the business income tax files.
10 For 'matched businesses', the information is extracted from the business income tax files.
11 Data for non-employing businesses was sourced from the business income tax files. The ABS Business Register excludes non-employing businesses, but the business income tax files provides a rich source of data for businesses in the non-employing sector.
12 For non-employing businesses, the ABS used a definition based on reported values for wages and salaries, employee superannuation expenses and size of reported income and expenses. In this process some businesses may be included in both the population of employing businesses and the population of non-employing businesses, while other businesses may be excluded from both populations. Any overlaps or gaps between the two populations are not statistically significant.
13 Estimates for the non-employing sector of the selected industries were produced by aggregating unit record data obtained using the above methodology.
14 Estimates for the whole of the selected industries were produced by adding together the components for each of the business types, i.e. Large businesses, Complex small and medium employing businesses, Simple small and medium employing businesses and Non-employing businesses.
15 The methodology for producing State estimates was implemented following the finalisation of EAS/Tax estimates at the Australia level.
16 The methodology separated business entities into two groups;
17 For all employing businesses, a single State/multi-State indicator was obtained from the ABS Business Register. If up-to-date information regarding the State activities of a business was obtained from an ABS direct collection, the indicator information from the ABS Business Register was not used.
18 It was assumed that all non-employing businesses operated in a single State only.
19 The following diagram provides information on the number of businesses and percent of contribution of all single State and multi-State businesses as identified on the ABS Business Register, and after allocation based on information from ABS direct collections.
SINGLE STATE BUSINESSES
20 Non-employing businesses (Q4.2) were allocated to a single State using the mailing address postcode obtained from the business income tax files. A small number of non-employing businesses had illegal or missing postcodes . These businesses were allocated across the States on a proportional basis.
21 Employing businesses identified as operating in only one State on the ABS Business Register and where no match was found to an ABS direct collection were divided into two groups (Q4.1 & Q4.2). Those businesses with income of less than $100m (Q4.2) were allocated to a State using their mailing address postcode on the ABS Business Register and those businesses with income of $100m or more (Q4.1) were investigated to determine the State/s of operation and to obtain proportions across States. This methodology of contacting large Single State businesses was not employed in the 1998-99 estimates, however, where the same unit existed in 1999-2000 the proportions obtained for the business were applied back to the 1998-99 file.
22 One of the most difficult aspects of the production of State level estimates was the correct treatment of businesses that received income or paid wages in more than one State. In 1999-2000, of the 67,346 employing businesses, 2,716 businesses (Q1, Q2.1 and Q2.2) were identified as multi-State businesses from the ABS Business Register. These businesses contributed 36.5% of the Total operating income estimate at the Australian level.
23 ABS economic collections with similar concepts to the EAS collection ask businesses a variety of State-based questions. In order of relevance, the ABS collections used to obtain State proportions for Sales and Wages for employing businesses were:
MATCHING MULTI-STATE BUSINESSES TO ABS DIRECT COLLECTIONS
24 From the EAS/Tax collection, 67,346 employing businesses were matched to the ABS direct collections listed above. If a business matched to more than one direct collection, the source with the highest relevance was used.
25 Of the 2,716 multi-State businesses identified from the ABS Business Register, State dissections for 1,994 businesses (73.0%) were obtained from ABS direct collections. Of these businesses, 1,454 (73.0%) were matched to the QEAS collection, 127 businesses (6.4%) matched to the WIS collection, 112 businesses (5.6%) were matched to the RIS collection and 144 businesses (7.2%) were matched to the EAS collections. The remaining units matched across the other listed collections.
26 Some bias may be present in relation to obtaining State dissections from various ABS collections with different reporting periods, definitions and scope. Please refer to the Explanatory Notes for further information.
27 Of the large multi-State businesses, 90.4% of these units were matched. Those businesses identified as multi-State and single State businesses which did not match to an ABS direct collection were investigated (sometimes involving contact with the business) if the Total operating income of the business was $100m or more (Q2.1 & Q4.1). Approximately 200 such businesses were contacted, all of which were able to provide a useable State breakdown of their business activity.
28 Multi-State and single State employing businesses, for which no match was found, with Total income less than $100m were allocated to the State of their postcode on the ABS Business Register (Q2.2 & Q4.2). There were 64,134 such businesses in this category, contributing 51.4% to the Total operating income estimate for Australia.
29 Sales proportions obtained for each business were used to apportion EAS/Tax Total operating income, Total operating expenses and OPBT data across the States for that business. Similarly, wages proportions were used to apportion Labour costs across the States.
30 Editing of the significant contributing businesses for Total operating income, Total operating expenses, OPBT and Labour costs was carried out at the State and Industry levels to ensure that data had been apportioned or allocated correctly. In some instances, the State of allocation was changed for single State businesses, or proportions for multi-State businesses were reallocated due to additional information being provided.
TECHNICAL NOTE 2: LIMITATIONS OF DATA ANALYSIS
RELATIVE STANDARD ERROR
1 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 estimates that would have been produced if all units had been included in the survey.
2 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. Tables 9, 10 and 11, on pages 20 - 22, provide RSEs for a selection of estimates presented in this publication.
3 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 $12,000m and its RSE is 5%, its quality 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 $11,400m to $12,600m, and about 19 chances in 20 that it lies within the range $10,800m and $13,200m.
4 The size of the RSE may be a misleading indicator of the quality of some of the estimates for Operating profit before tax (OPBT). This situation may occur where an estimate may legitimately include positive and negative values reflecting the financial positions of different business entities. In these cases the aggregate estimate can be small relative to the contribution of individual business entities, resulting in a SE which is large relative to the estimate.
5 The EAS/Tax sample is not selected on the basis of State and this could have an impact on the size of the sampling error at the State level. To some extent this is offset by the use of business income tax data which increases the sample size, resulting in a broader coverage of units for each State.
6 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.
7 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.
8 There are also non-sampling errors associated with the ATO business income tax file. For example, the ATO accounts for non-response in the business income tax file by either bringing forward the previous year's data for a non-responding business, or leaving the data as zero if the business does not have an ATO response history.
9 Differences in accounting policy and practices across businesses and industries can also lead to some inconsistencies in the data used to compile the estimates. While much of the accounting process is subject to standards, there remains a great deal of flexibility available to businesses in the accounting policies and practices they adopt.
10 Users should be aware that because direct collection has not been used to apportion EAS/Tax estimates to States, some non-sampling error will result from the techniques used. For full details of the methodology used to allocate estimates to States please refer to the Technical Note 1: Methodology, on page 31.
11 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.
12 This publication presents a wide range of data that can be used to analyse business and industry performance.
13 It is important that any analysis undertaken be based upon a range of data presented rather than focusing on one variable.
The Australian and New Zealand Standard Industrial Classification (Cat.no.1292.0).
A term used to describe the combination of business units from the Economic Activity Survey and the business units provided by the ATO.
A list of businesses maintained by the ABS and used for creating survey frames for ABS business surveys.
ECONOMIC ACTIVITY SURVEY (EAS)
An annual business survey conducted by the ABS which is one of the sources of the estimates presented in this publication.
Estimates derived by combining (a) data directly collected via the ABS Economic Activity Survey in respect of selected industries with (b) business income tax data provided by the ATO.
Wages and salaries plus employer contributions to superannuation funds plus workers' compensation costs.
The largest type of unit within an enterprise group which controls its productive activities and for which separate accounts are kept.
Those businesses with operations in more than one State or Territory.
OPERATING PROFIT BEFORE TAX (OPBT)
A measure of profit before extraordinary items are brought into account and prior to the deduction of income tax and appropriations to owners (e.g. dividends paid). OPBT is broadly defined as follows. Total operating income less Total operating expenses less Opening stocks plus Closing stocks equals OPBT
The percentage of operating income available as operating profit, i.e.
Comprises the following industries: Services to Agriculture; Hunting and Trapping; Forestry and Logging; Commercial Fishing; Mining; Manufacturing; Electricity, Gas and Water Supply; Construction; Wholesale Trade; Retail Trade; Accommodation, Cafes and Restaurants; Transport and Storage; Communication Services; Property and Business Services; Cultural and Recreational Services and selected ANZSIC classes in the Health and Personal Services industries.
SELECTED GOODS PRODUCING INDUSTRIES
Comprises the following industries: Services to Agriculture; Hunting and Trapping; Forestry and Logging; Commercial Fishing; Mining; Manufacturing; Electricity, Gas and Water Supply.
SELECTED SERVICE INDUSTRIES
Comprises the following industries: Construction; Wholesale Trade; Retail Trade; Accommodation, Cafes and Restaurants; Transport and Storage; Communication Services; Property and Business Services; Cultural and Recreational Services and selected ANZSIC classes in the Health and Personal Services industries.
SINGLE STATE BUSINESSES
Those businesses with operations in one State or Territory only.
TOTAL OPERATING EXPENSES
The total expenses of a business, excluding extraordinary items.
TOTAL OPERATING INCOME
The total income of a business, excluding extraordinary items.
These documents will be presented in a new window.