Business Indicators, Australia methodology

This publication contains estimates of sales of goods and services, wages and salaries (from the December quarter 2001 issue), company profits, and the book value of inventories for selected industries in Australia. The series have been compiled from data collected by the Australian Bureau of Statistics (ABS) in its Quarterly Business Indicators Survey. The survey, which was fully implemented in the March quarter 2001, collects data from private sector businesses.

The Quarterly Business Indicators Survey, like most ABS economic collections, takes its frame from Employing and Non-Employing Units on the ABS Business Register which is primarily based on ABN registrations to the Australian Business Register, which is managed by the Australian Taxation Office (ATO). The frame is updated quarterly to take account of new businesses and changes in the characteristics of businesses, such as industry and size.

Businesses are removed from the frame when their ABN has been cancelled by the ATO. This may occur when the business requests for its ABN to be cancelled or otherwise has not remitted either Income Tax Withholding, or Goods and Services Tax, for the previous five quarters.

The statistics in this publication exclude micro non-employing businesses. Though there are a substantial number of these businesses, it is expected that they would not contribute significantly to the estimates, although the impact would vary from industry to industry.

Inventories data are not collected from businesses with fewer than 20 employees, as smaller businesses generally have difficulty in providing accurate quarterly information on the level of their inventories. Estimates for these businesses are derived by applying sales information to an estimated inventories to sales ratio.

Profits data are not collected from employing businesses with fewer than 20 employees. Estimates for these businesses are derived by applying sales information to an estimated profits to sales ratio.

The industries included in this publication are classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006. The data items collected vary from industry to industry and are displayed in the following table:

In the Quarterly Business Indicators Survey the statistical unit used to represent businesses, and for which statistics are reported, is the Australian Business Number (ABN) unit in most cases. The ABN unit is the business unit which has registered for an ABN, and thus appears on the ATO administered Australian Business Register. This unit is suitable for ABS statistical needs when the business is simple in structure.

For more significant and diverse businesses where the ABN unit is not suitable for ABS statistical needs, the statistical unit used is the Type of Activity Unit (TAU). A TAU is comprised of 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 is 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 Australian and New Zealand Standard Industrial Classification (ANZSIC)). Where a business cannot supply adequate data for each industry, a TAU is formed which contains activity in more than one industry subdivision and the TAU is classified to the predominant ANZSIC subdivision. The businesses that contribute to the statistics in this publication are classified:

• by institutional sector, in accordance with the Standard Institutional Sector Classification of Australia (SISCA), which is detailed in Standard Economic Sector Classifications of Australia (SESCA).
• by industry, in accordance with the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006.

The Australian and New Zealand Standard Industrial Classification has been developed for use in both countries for the production and analysis of industry statistics. For more information, users are referred to Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006.

In order to classify data by industry, each statistical unit (as defined above) is classified to the Australian and New Zealand Standard Industrial Classification industry in which it mainly operates.

The survey is conducted by web form on a quarterly basis. It is based on a random sample of units which is stratified by industry, state/territory and number of employees. The sample size was reduced from around 16,200 businesses to around 12,750 businesses in the March quarter 2024.

Respondents are asked to provide data on the same basis as their own management accounts. Where a selected unit does not respond in a given survey period, a value is estimated. If data are subsequently provided, the estimated value is replaced with the reported data. Data are edited at both individual unit level and aggregate level. In general, aggregates are calculated using the ‘composite regression estimation' (CRE) method, which is further explained in Methodological News, March Quarter 2024. The ‘general regression estimation’ method was used in place of the CRE method for the March quarter 2024 only, as this is a more appropriate method when the sample composition changes significantly. The CRE method will be used from June quarter 2024 onwards. 

Surveys are conducted with respect to each quarter of the financial year. Returns are completed during the eight or nine week period after the end of the quarter to which survey data relate e.g. December quarter survey returns are completed during January and February.

The survey frames and samples are revised each quarter to ensure that they remain representative of the survey population. The timing for creating each quarter’s survey frame is consistent with that of other ABS business surveys. This provides for greater consistency when comparing data across surveys.

Additionally, with these revisions to the sample, some of the units from the sampled sector are rotated out of the survey and are replaced by others, to spread the reporting workload equitably.

The quarterly original estimates in this publication are affected in varying degrees by seasonal influences. The seasonal adjustment process estimates and removes the effects of normal seasonal variations from the original estimates so that the effects of other influences can be more clearly recognised.

In the seasonal adjustment process, account has been taken of normal seasonal factors (e.g. increase in retail sales due to the Christmas period) to produce the seasonally adjusted estimates. Particular care should be taken in interpreting quarterly movements in the seasonally adjusted estimates because seasonal adjustment does not remove the effect of irregular or non-seasonal influences (e.g. change in interest rates) and reflects the sampling and other errors to which the original estimates are subject.

In this publication, estimates that are seasonally adjusted are produced by the concurrent seasonal adjustment method which takes account of the latest available original estimates. This method improves the estimation of seasonal factors, and therefore, the seasonally adjusted and trend estimates for the current and previous quarters. As a result of this method, revisions to the seasonally adjusted and trend estimates will be observed for recent periods. In general, a detailed seasonal review is conducted annually; however, an Extraordinary Annual Seasonal Review (EASR) was completed prior to the March quarter 2024 release. The EASR individually assessed each series still on forward factors to determine how each observation from the previous year should be treated for estimation of the seasonal factors at the current end of the series. This process ensured that disruption to series caused by COVID-19 does not unduly affect estimates of the seasonal factors.

For series previously on forward factors and then changed back to the concurrent method, revisions to the seasonally adjusted series were larger than the revisions historically observed each quarter when concurrent adjustment was used. Series previously on forward factors used static seasonal factor estimates for the previous year prior to March quarter 2024, and the review updated these seasonal factor estimates by incorporating relevant information from the previous year's observations. When concurrent adjustment is used, revisions to the seasonally adjusted estimates will typically be smaller because seasonal factor estimates are updated quarterly on the basis of the addition of one extra data point. During the EASR, a decision was made about the future use of forward factors/concurrent adjustment. The forward factors method will not be continued from this quarter onwards unless required; in that case, new forward factors would need to be calculated.

The revision properties of the seasonally adjusted and trend estimates can be improved by using Auto Regressive Integrated Moving Average (ARIMA) modelling. ARIMA modelling relies on the characteristics of the series being analysed to project future period data. The projected values are temporary, intermediate values, that are only used internally to improve the estimation of the seasonal factors. The projected data do not affect the original estimates and are discarded at the end of the seasonal adjustment process. The Quarterly Business Indicators Survey uses ARIMA modelling where appropriate for individual time series. The ARIMA model is assessed as part of the annual reanalysis and following the 2024 Extraordinary Annual Seasonal Review, the majority of the Quarterly Business Indicators Survey eligible series use an ARIMA model.

The trend series attempts to measure underlying behaviour in business activity. In the short term, this measurement will be significantly affected by changes to regular patterns in spending that will occur during coronavirus (COVID-19), as certain businesses are restricted from trading for example. If the trend estimates in this publication were to be calculated without fully accounting for this irregular event, they would likely provide a misleading view of underlying business activity. It may be some time before the underlying trend in business activity can be accurately estimated. The Business Indicators trend series have therefore been suspended and will be reinstated when more certainty emerges in the underlying trend in business activity.

The trend estimates are derived by applying a 7-term Henderson moving average to the seasonally adjusted estimates. The 7-term Henderson moving average is symmetric, but as the end of a time series is approached, asymmetric forms of the moving average are applied. The asymmetric moving average has been tailored to suit the particular characteristics of individual series and enable trend estimates for recent quarters to be produced. Estimates of the trend will be improved at the current end of the time series as additional observations become available. This improvement is due to the combined effect of the concurrent seasonal adjustment methodology and the application of different asymmetric moving averages for the most recent three quarters. As a result of the improvement, revisions to the trend estimates will generally be observed for the most recent three quarters. ABS research shows that about 75% of the total revision to the trend estimate at the current end is due to the use of different asymmetric moving averages when the original estimate is available for the next quarter. There may also be revisions because of changes in the original estimates. As a result of these revisions, the seasonally adjusted and trend estimates will also be revised. For further information, see Information Paper: A Guide to Interpreting Time Series - Monitoring Trends.

The chain volume measures appearing in this publication are annually reweighted chain Laspeyres indexes referenced to current price values in the chosen reference year (currently 2021-22). The current price values may be thought of as being the product of a price and quantity. The value in chain volume terms can be derived by linking together movements in volumes, calculated using the average prices of the previous financial year and applying compound movements to the current price estimates of the reference year. Each year’s quarter-to-quarter growth rates in the chain volume series are based on the prices of the previous financial year, except for those quarters of the latest incomplete year which are based upon the second most recent financial year. Quarterly chain volume estimates are benchmarked to annual chain volume estimates, so that the quarterly estimates for a financial year sum to the corresponding annual estimate.

With each release of the September quarter issue of this publication, a new base year is introduced, and the reference year is advanced one year to coincide with it. This means that with the release of the September quarter 2023 issue of this publication, the chain volume measures for 2022-23 will have 2021-22 (the previous financial year) as their base year rather than 2020-21, and the reference year is 2021-22. A change in the reference year changes levels but not growth rates for all periods. A change in the base year can result in revisions, small in most cases, to growth rates for the last year.

Chain volume measures are not generally additive. In other words, component chain volume measures do not, in general, sum to a total in the way original current price components do. For inventories and sales data, this means that the chain volume estimates for industry groups will not add to the total for Australia. In order to minimise the impact of this, the ABS uses the latest base year as the reference year. By adopting this approach, additivity does exist for the quarters following the reference year and non-additivity is relatively small for the quarters in the reference year and those immediately preceding it. For further information on chain volume measures, refer to the Information Paper: Introduction of Chain Volume Measures in the Australian National Accounts.

The data collected in the Quarterly Business Indicators Survey are used in the compilation of the quarterly estimates of the Australian National Accounts. Inventories data are used to compile estimates of the increase in book value of non-farm inventories. Estimates of sales of goods and services are used to help derive quarterly chain volume measures of gross value added for selected industries. Company gross operating profits data are used to compile estimates of gross operating surplus of private non-financial corporations. From March quarter 2002, estimates of wages and salaries are being used to compile estimates for compensation of private sector employees. For further details see Australian System of National Accounts: Concepts, Sources and Methods.

However, the statistics in this publication will differ from corresponding statistics in the quarterly Australian National Accounts for the following reasons:

• The national accounts estimates are benchmarked to annual supply and use tables which are based on annual Economy Wide Survey and taxation data.
• The national accounts estimates include estimates for businesses classified to industries not in scope of the Quarterly Business Indicators Survey.
• The national accounts estimates for gross operating surplus of private non-financial corporations are after deduction of the inventory valuation adjustment which measures the portion of income attributable to holding gains or losses resulting from inventory valuation practices.
• In many cases, the processes used to seasonally adjust national accounts estimates are different to those used for the seasonally adjusted estimates in this publication.

The estimates for sales of goods and services by Retail trade in this publication will differ from turnover estimates included in Retail Trade, Australia. The latter publication presents monthly estimates of the value of turnover of retail businesses, and is sourced from the Retail Business Survey. Estimates for sales of goods and services in this publication exclude the Goods and Services Tax, while turnover collected in the Retail Business Survey includes the Goods and Services Tax. In addition, the Retail Business Survey includes some businesses classified to ANZSIC divisions other than the Retail trade division, and includes retail establishments associated with management units that are not classified to the Retail trade division. The use of different samples in the Retail Business Survey and Quarterly Business Indicators Survey will also contribute to differences. 

The estimates for sales of goods and services by industry in this publication will also differ from turnover estimates in the Monthly Business Turnover Indicator. The Monthly Business Turnover Indicator is derived from Australian Taxation Office (ATO) Business Activity Statements (BAS) turnover data from monthly BAS remitters and differs from Business Indicators, Australia in terms of scope and coverage. Monthly BAS reporting for the Monthly Business Turnover Indicator covers businesses with GST annual turnover of $20 million or more and a proportion of smaller businesses that report monthly on a voluntary basis. The estimates of Sales and Service Income in Business Indicators, Australia are compiled from the Quarterly Business Indicators Survey (QBIS) which is based on a random sample of approximately 12,750 businesses. For further information see Table 3: Summary of differences between Monthly Business Turnover Indicator and QBIS Sales in the Monthly Business Turnover Indicator methodology. 

The new Australian equivalents to International Financial Reporting Standards (AIFRS) began to be progressively implemented in Australia from 1 January 2005. As a result, a number of items in the financial accounts of Australian businesses have been affected by changed definitions which have in turn impacted upon both Income Statements and Balance Sheets. A range of ABS economic collections source data from financial accounts of businesses and use those data to derive economic statistics. There have been no changes in the associated economic definitions.

After monitoring data items since March quarter 2005 it has been concluded that most affected published data series have been impacted by data breaks, but that the magnitude of such breaks cannot be determined without imposing disproportionate load upon data providers to ABS surveys and other administratively collected data. ABS will continue to monitor developments and report any significant identified impacts or changes in methodology as a result of AIFRS.

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.

The results of these statistics are based, in part, on ABR data supplied by the Registrar to the ABS under A New Tax System (Australian Business Number) Act 1999 and tax data supplied by the ATO to the ABS under the Taxation Administration Act 1953. These require that such data is only used for the purpose of carrying out functions of the ABS. No individual information collected under the Census and Statistics Act 1905 is provided back to the Registrar or the ATO for administrative or regulatory purposes. Any discussion of data limitations or weaknesses is in the context of using the data for statistical purposes, and is not related to the ability of the data to support the ABR or ATO’s core operational requirements. Legislative requirements to ensure privacy and secrecy of this data have been followed. Only people authorised under the Australian Bureau of Statistics Act 1975 have been allowed to view data about any particular firm in conducting these analyses. In accordance with the Census and Statistics Act 1905, results have been confidentialised to ensure that they are not likely to enable identification of a particular person or organisation.

Users may also wish to refer to the following publications:

• Australian System of National Accounts: Concepts, Sources and Methods
• Australian National Accounts: National Income, Expenditure and Product
• Australian Industry
• Information Paper: Introduction of Chain Volume Measures in the Australian National Accounts
• Information Paper: Improvements to Australian Bureau of Statistics Quarterly Business Indicators
• Monthly Business Turnover Indicator
• Private New Capital Expenditure and Expected Expenditure, Australia
• Retail Trade, Australia

If the information you require is not available as a standard product or service, then ABS Consultancy Services can help you with customised services to suit your needs. For inquiries about these and related statistics, contact the Customer Assistance Service via the ABS website Contact Us page. The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.

Estimates provided in this publication are subject to non-sampling and sampling error. The most common way of quantifying sampling error is to calculate the standard error for the published estimate. This is discussed in the following three sections below.

Estimates that have an estimated relative standard error between 10% and 25% are annotated with the symbol '^'. These estimates should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% are annotated with the symbol '*', indicating that the estimate should be used with caution as it is subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with the symbol '**' indicating that the sampling variability causes the estimates to be considered too unreliable for general use. These annotations have only been applied to estimates from the March quarter 2009.

Non-sampling errors may arise as a result of errors in the reporting, recording or processing of the data and can occur even if there is a complete enumeration of the population. These errors can be introduced through inadequacies in the questionnaire, treatment of non-response, inaccurate reporting by respondents, errors in the application of survey procedures, incorrect recording of answers, and errors in data entry and processing. Inventories data for businesses with fewer than 20 employees are derived and could therefore be subject to error (although this error is estimated to be less than the sampling and non-sampling error resulting from directly collecting this data).

Estimates for the latest quarter presented in this publication are considered preliminary, and revised estimates may be released within the next issue. As discussed in the 'Seasonal adjustment' and 'Trend estimates' sections of the Explanatory Notes, seasonally adjusted and trend estimates are also subject to revision as additional data becomes available and is revised.

It is difficult to measure the size of non-sampling errors. However, every effort is made in the design of the survey and development of survey procedures to minimise their effects.

The estimates in this publication are based on a sample drawn from units in the surveyed population. Given that the entire population is not surveyed, the published estimates are subject to sampling error. In calculating the standard error for the statistics in this publication, the ABS prefers to produce a smoothed standard error for the major published aggregates. This approach accounts for the variability in standard error estimates for quarterly statistics. The estimated standard error is an indication of the sampling error for the current published series. Standard errors are based on the data in the currently published quarter.

To illustrate, let us say that the published level estimate for company profits before income tax is $8,900m and the calculated standard error in this case is $200m. The standard error is then used to interpret the level estimate of $8,900m. For instance, the standard error of $200m indicates that:

• There are approximately two chances in three that the real value falls within the range $8,700m to $9,100m ($8,900m ± $200m).
• There are approximately nineteen chances in twenty that the real value falls within the ranges $8,500m and $9,300m ($8,900m ± $400m).
• The true value in this case is the result we would obtain if we could enumerate the total population.

The following tables shows the standard errors for national and state quarterly level estimates based upon the data in the current quarter.

The following example illustrates how to use the standard error to interpret a movement estimate. Let us say that one quarter the published level estimate for inventories is $90,000m, and the next quarter the published level estimate is $92,000m. In this example the calculated standard error for the movement estimate is $850m. The standard error is then used to interpret the published movement estimate of +$2,000m. For instance, the standard error of $850m indicates that:

• There are approximately two chances in three that the real movement over the two quarter period falls within the range $1,150m to $2,850m ($2,000m ± $850m).
• There are approximately nineteen chances in twenty that the real movement falls within the range $300m to $3,700m ($2,000m ± $1,700m).

The following table shows the standard errors for national quarterly movement estimates based upon the data in the current quarter.

Adjustments are included in the estimates to allow for lags in processing new businesses to the Australian Business Register. The following table shows the adjustments made to the current quarter's original estimates in current price terms:

As previously discussed, the estimates presented in this publication are partial indicators used in the compilation of the quarterly national accounts. The movements in the Business Indicators estimates will not always be the same as the movements in the comparable national accounts series but they should be reasonably consistent after taking account of differences in concepts, scope and methodology described under the 'Comparability with national accounts and other ABS estimates' section of the Explanatory Notes. If after taking account of these differences, there are concerns about data quality and coherence, the national accounts area provides feedback to the survey area. This process may result in adjustments being applied to the Business Indicators estimates prior to release in this publication. The objective use of the national accounts framework to provide data coherence across all ABS economic statistics ensures that a common understanding of recent economic developments is presented.

This publication includes estimates of sales of goods and services, by industry, and by state/territory, but estimates of national total sales of goods and services are not published. Total sales of goods and services is not an adequate indicator of the performance of the Australian economy as it includes duplication; for example, goods sold by retailers may also be included in goods sold by wholesalers in the same period. However, this publication does include total sales of goods and services by state/territory, as it is considered that there may be interest in this item as a measure of relative activity. This data should be used with caution given the potential for the data to include duplication across industries.

Estimates of gross operating profits are compiled by deducting estimates of items that do not involve the production of goods and services from estimates of profits before income tax. These items include: depreciation, net interest paid, net foreign exchange gains/losses and unrealised gains/losses on the revaluation of assets. These items are considered out of scope of the national accounts item gross operating surplus.

As indicated in the 'Scope and coverage' section of the Explanatory Notes, income items (other than sales of goods and services), expense items (other than labour costs) and profits are only collected for businesses employing 20 or more persons in the Quarterly Business Indicators Survey (QBIS).

The introduction of the Quarterly Business Indicators Survey (QBIS) from March quarter 2001 included the collection of private sector wages and salaries by industry.

From September quarter 2020 onwards, direct collection of wages for a subset of units in ANZSIC Subdivision 62 (Finance) from the ABS Quarterly Business Indicators Survey (QBIS) ceased. Data is now being collected on behalf of the ABS by APRA as part of the Economic Financial Statistics (EFS) collection. This change has helped to reduce respondent burden for entities that are also required to report to APRA and has streamlined reporting for the Finance industry.

Three significant privatised marketing authorities came into scope of the estimates in this publication from the September quarter 1999. The introduction of these units resulted in a break in series for estimates for inventories and sales of goods and services between the June and September quarters 1999 and comparison of the series over time should be undertaken with care.

The methodology used by the ABS has ensured that the trend series has not been distorted by the introduction of these units, although there is a trend break evident between the June and September quarters 1999. For this reason, the trend estimates of movement have not been released for the Wholesale trade inventories, Total inventories and Wholesale trade sales series in respect of the September quarter 1999.

Telstra Corporation was effectively privatised on 20 November 2006. For the purposes of ABS statistics this change from public sector to private sector was effective from March quarter 2007. This has impacted on some data series presented in this publication, particularly the March quarter 2007 movements. The data items affected are sales of goods and services, wages and salaries, company gross operating profits and the related profits series in the Manufacturing and Information media and telecommunications industries. The introduction of Telstra has resulted in a break in series for some series in this publication between the December quarter 2006 and March quarter 2007. The movement trend estimates, in percentage terms, have therefore not been released for the March quarter 2007.

In the June quarter 2010 release, trend break corrections were applied to Mining and Total company gross operating profits, company profits before income tax, business gross operating profits and Mining sales. These corrections were necessary due to very large mining commodity contract price rises that occurred on 1st April 2010. Trend break corrections were also applied to Manufacturing and Western Australian Sales of goods and services due to the movement of a major manufacturing business from the private to public sector. When a trend break occurs in a time series it is important that the trend movement estimate be treated with caution, hence the suppression of the quarterly and annual movement estimates for June 2010.

In the December quarter 2017 release, trend break corrections were applied to the December quarter 2016 estimates for Mining and Total company gross operating profits, company profits before income tax and business gross operating profits. These corrections were due to a large increase in the price of mining commodities.

In the March quarter 2020, trend estimates were suspended due to the impacts of Coronavirus (COVID-19). The trend series attempts to measure underlying behaviour in business activity. In the short term, this measurement has been significantly affected by changes to regular patterns in business activity due to COVID-19. Therefore, the publication of trend estimates for this period may provide a misleading view of underlying business activity. 

The reintroduction of concurrent adjustment for all seasonally adjusted series following the Extraordinary Annual Seasonal Review (EASR) in the March quarter 2024 indicates greater certainty in the underlying business activity of the series. The ABS will continue to review the trend series with a view to reinstating trend data in the near future.