Introduction
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.
Scope and coverage
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:
Industries | Sales of goods and services | Wages and salaries | Profits | Inventories | |
---|---|---|---|---|---|
Mining (Division B) | Y | Y | Y | Y | |
Manufacturing (Division C) | Y | Y | Y | Y | |
Electricity, gas, water and waste services (Division D) | |||||
Electricity supply (26) | Y | Y | Y | Y | |
Gas supply (27) | Y | Y | Y | Y | |
Water supply, sewerage and drainage services (28) | Y | Y | Y | N | |
Waste collection, treatment and disposal services (29) | Y | Y | Y | N | |
Construction (Division E) | Y | Y | Y | N | |
Wholesale trade (Division F) | Y | Y | Y | Y | |
Retail trade (Division G) | Y | Y | Y | Y | |
Accommodation and foods services (Division H) | Y | Y | Y | Y | |
Transport, postal and warehousing (Division I) | Y | Y | Y | N | |
Information media and telecommunications (Division J) | Y | Y | Y | N | |
Finance and insurance services (Division K) | |||||
Depository financial intermediation (622) | N | Y | N | N | |
Non-depository financing (623) | N | Y | N | N | |
Financial asset investing (624) | N | Y | N | N | |
Health and general insurance (632) | N | Y | N | N | |
Auxiliary finance and insurance services (64) | Y | Y | Y | N | |
Rental, hiring and real estate services (Division L) | Y | Y | Y | N | |
Professional, scientific and technical services (Division M) | Y | Y | Y | N | |
Administrative and support services (Division N) | Y | Y | Y | N | |
Education and training (Division P) | N | Y | N | N | |
Health care and social assistance (Division Q) | N | Y | N | N | |
Arts and recreational services (Division R) | Y | Y | Y | N | |
Other services (Division S) | Y | Y | Y | N |
Statistical unit
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.
Classifications
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.
Survey methodology
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.
Timing of survey cycle
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.
Sample revision
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.
Seasonal adjustment
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, during the period of disruption caused by the COVID-19 pandemic, forward factor seasonal adjustment was used temporarily, and several series were still on forward factors for the December quarter 2023 release. An Extraordinary Annual Seasonal Review (EASR) was completed prior to the March quarter 2024 release to assess each series still on forward factors individually and 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 March quarter 2024 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 annual reanalysis, the majority of the Quarterly Business Indicators Survey eligible series use an ARIMA model.
Trend estimates
The trend estimates attempt to measure underlying behaviour in business activity. These measurements have been significantly affected by changes to regular patterns in business activity during the COVID-19 pandemic. Due to the degree of disruption caused by COVID-19, the ABS will not publish trend estimates for all series from March quarter 2020 to September quarter 2022 (inclusive), as estimates are likely to be misleading for users throughout the pandemic period. However, the underlying trend in business activity can be accurately measured from December quarter 2022 as the impact of COVID-19 is no longer considered significant.
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.
Chain volume measures
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.