Weekly Payroll Jobs and Wages in Australia methodology

The STP data are reported on a cash basis (the time when the payment was made) rather than an accrual basis (the time when the payment was earned). Production of real time estimates require the conversion of STP data from a cash basis to an accrual basis. This is done through a “calendarisation” method. This method breaks down all records to a common period (daily), which allows the data to be aggregated and analysed for any longer period (e.g. weekly).

The calendarisation method includes the following steps:

• calculation of the periodicity (payment frequency) using the start and end date of the payment period,
• calculation of a daily pay rate by dividing the total payments by the payment frequency (for example, weekly pay is divided by seven), and
• an adjustment to the periodicity for a job to exclude the days before commencement (or after termination), where the start or termination date for a job occurs within the payment period.

Towards the end of the financial year, unadjusted STP data includes higher than usual week-to-week changes in total wages paid. Some employers report lumped fringe benefits tax (FBT) payment amounts for eligible employees at the end of the financial year. This is most evident in the Health care and social assistance industry. To reduce the reporting variability introduced by these payments, the ABS has determined and applied an adjustment factor to accrue reported FBT amounts across the relevant financial year wages series. It is applied to all records which include reportable FBT amounts, not just those in the Health care and social assistance industry. It will be periodically revised to ensure it remains current. 

This treatment complements the existing calendarisation methodology and is consistent with the definition of wages and salaries used in the Australian System of National Accounts. More information about employer reporting of FBT is available from the ATO website.

This adjustment methodology is not applicable to other extraordinary payments (such as bonuses) where they are included with the wages data in the period they are paid. Unlike reportable FBT amounts, bonuses are not currently readily distinguishable from the wages component of the STP job level dataset and can be paid at any time. Further information on bonuses can be found in the Seasonality section of Data variability and revisions and in the Seasonality spotlight: 2021 year-end article.  

In addition to cash reporting, extracted STP payment data for a specific week cycle may be incomplete due to:

• different business reporting habits, 
• different pay frequencies, and
• the lag between the reference week and the release of estimates. 

To produce reliable weekly statistics, an imputation method is applied to account for incompleteness. Imputation includes the following considerations: 

• Imputation is not applied where no established pattern of payment exists to enable forward extrapolation. For example, a small proportion of employees paid on an ad hoc basis.
• If an employee has not yet had payment data reported and they have not been flagged for termination, it is assumed that their payment status is consistent with their previous reporting record. The previous calculated daily rate will be imputed for the current period.
• If an employee has no payment data for a second consecutive pay period, it is assumed that their employment has been terminated. No further forward imputation is applied. Imputed data remains in place until 16 weeks have elapsed, to account for any lags in business reporting.
• No imputation is applied for new employees without historical payment information, until a pattern can be determined. This means that there can be a lag before a new payroll job appears in the data (after their initial pay period). The lag is longer for new jobs with employers who have less frequent payment and reporting periods. No adjustment is applied to account for this new job lag.

STP reported data can take several months to be fully complete at a specific reference date, due to infrequent and quarterly STP reporters. From the 26 August 2021 release, the lag between the reference and release date extended to around 26 days. The additional week of lag allows for the receipt of more complete data (around 90%), resulting in an imputation rate of around 10% in the most recent week's data. 

From the 7 October 2021 release, the imputation retention threshold was updated from eight pay periods to 16 weeks for all jobs. As more complete data is received and historical imputation is removed, larger than usual revisions may occur in estimates around 16 weeks prior to the latest week. This is more evident during brief periods of labour market shock, which were likely to experience slight over-imputation. 

In each reference week, employer reported data is included for almost all weekly paid employees, most employees paid fortnightly and some employees paid monthly. For example, an employer with a fortnightly payroll will only report payments in alternate weeks in the STP dataset. As at the end of March 2021, the data indicated that 33% of employees are paid weekly; 52% are paid fortnightly; 12% are paid monthly; and 3% are paid quarterly or infrequently.

While a fortnightly pay frequency is the most common amongst all industries, the dominant pay frequency varies across industry (seen in the graph below), which can affect the level of imputation for each industry in any given week. 

Once STP data are converted via the calendarisation method and imputation is applied, the data are aggregated for each week (ending Saturday) to produce:

• total payroll jobs, which is the average of the seven days of payroll job counts, and
• total wages, which is the sum of all daily wages for the week, except for employees who cease a job during the week where only the wages for the days worked are included.

To protect the confidentiality of individuals, data are subject to suppression where a small number of individuals contribute to an individual estimate (such as sub-state indexes). A detailed index may be suppressed throughout the time series, if it is produced from consistently low numbers of individuals.

Estimates are supplied as indexes to provide an indication of movements rather than level estimates. In order to compare changes over time, the week in which Australia recorded its 100th confirmed coronavirus case (i.e. the week ending 14 March 2020) is used as the reference period for constructing the indexes and given an index value of 100.0. These indexes differ from the ABS' suite of price indexes (including the Wage Price Index) which measure changes in price over time unaffected by quality or quantity and should not be directly compared.

Indexes allow comparison of data between two points in time, the points in time can be adjacent (this week and the previous week) or many weeks apart. Movements in the index from one period to another can be expressed as either points or percentage change and these are rounded to one decimal place. The following example illustrates the method of calculating changes in index points and percentage changes between any two periods:

The following example illustrates the method of calculating a recovery percentage change between any two periods:

Individual STP transactions are not amended, however aggregate levels may be adjusted at a state/territory by industry level to remove the effect of: 

• reporting anomalies which are significant at the state/territory by industry level, and
• large organisation onboarding. 

Aggregate adjustments are applied to the applicable state/territory by industry levels. The adjustments in each release are:  

• calculated individually for each state/territory by industry level, and
• removed as the underlying data becomes more complete, or the adjustment is no longer required. 

Currently, it is not possible to calculate individual adjustments for all output groups, hence the adjustments applied at a state/territory by industry are also applied equally to all component indexes (such as state/industry by age group or sex or employment size). Aggregate level adjustments can also affect the relative proportion of characteristics. The effect is more pronounced around large organisation onboarding events (where they are dominant in their state and industry). 

Large organisation onboarding

The ABS has reviewed and updated the method used to account for large organisation onboarding, resulting in higher than usual revisions across the time series in this release. Where existing large employers commence reporting through STP for the first time, the ABS determines when the employer first appears in the dataset and adjusts underlying jobs and wages to the start of the time series. This ensures that weekly estimates best reflect change in the labour market over time through payment activities, rather than changes in the uptake of STP reporting. This approach can result in historical revisions across the time series and can impact component indexes differently.

The updated method implemented in this release reduces impacts on the underlying characteristics distributions, particularly after the onboarding event, and are a step toward the future release of levels. The ABS recommends that analyses of previously published estimates be refreshed with updated data from this release.  

Weekly payroll jobs and wages indexes are available for a combination of employer characteristics (industry, employment size and sector) and jobholder characteristics (state and region of residential address, age, and sex). These characteristics are populated from variables found in the snapshots of the ABS Business and ATO Client Registers. These Registers are described in more detail in the Glossary and How data are collected (Other data sources) sections of this release. 

The snapshot vintage, frequency of update and refresh timing can differ and are described further below. 

Employer variables

ABS Business Register snapshots

Up until the 6 July 2021 release, a March 2020 ABS Business Register (ABSBR) snapshot was used to determine the industry and employment size of a jobholder’s employer. In the 6 July 2021 release, the March 2021 ABSBR snapshot was used to update employer variables back to the week ending 29 August 2020 (also known as the transition point).

Some indexes of employer characteristics have a visible change in levels at the transition point. The ABS is working on a method to smooth this change, which will be applied in a future release. Consequently, users should exercise caution when comparing week-on-week change and index levels for industry and employment size across the transition point. More information on the changes around the transition point are documented in a historical Methods review section.

Once an employers’ payroll job is allocated to an employer characteristic it is held constant until the next snapshot, when missing values will be populated and existing values refreshed (if they have changed). Employers whose employer characteristics can't be linked or derived from the latest ABSBR snapshot are assigned an ‘unknown’ category for the relevant employer characteristic. As the March 2021 ABSBR snapshot ages, the proportion of records with unknown industry and employment size is expected to increase. The ABS anticipates that snapshots will be refreshed on at least an annual basis, to enable a regular update of employer characteristics and minimise the number of unknowns. 

Determining employer characteristics of newly reported payroll jobs

In the 9 December 2021 release, the method used to determine employer characteristics of payroll jobs as they are added to the series was also updated.

Newly reported payroll jobs are either part of two population groups (profiled and non-profiled), and the assignment of employer characteristics depends on which population group the employer falls within. For non-profiled businesses, employer characteristics match those of the business’ Australian Business Number (ABN). The remainder of payroll jobs are part of the profiled population. These payroll jobs are assigned to a Type of Activity Unit (TAU), and conceptual modelling is used to predict and assign suitable employer characteristics (industry, employment size and sector) to each payroll job.

The updated allocation method determining employer characteristics saw payroll jobs assigned to more representative industries, enhancing statistical quality. More information on the changes as a result of the updated process are documented in a historical Methods review section.

Sector

Employer characteristics have been expanded to include a public/private sector variable throughout the time series. The release of 7 October 2021 includes the first set of sector indexes, payroll jobs by selected private sector industries. Private sector indexes are included for industries where the payroll jobs in the private sector are more than 80% of all payroll jobs. Industries not included in the sector tables are Electricity, gas, water and waste services; Public administration and safety; Education and training; and Health care and social assistance.

It is intended that both private and public sector by industry indexes and private and public sector by state and territory indexes will be released in the future. The current method of applying adjustments, for anomalous reporting and commencement of employer reporting through STP, does not differentiate on sector. While there is a small impact in indexes where the private sector dominates, the adjustment method requires enhancement to allow for more granular application and more accurate representation of change for both private and public sector indexes (for all industries and at state and territory levels).

Jobholder characteristics

Determining jobholder characteristics  

Jobholder characteristics used in these estimates are sourced from both the ATO Client Register and STP data. A limited set of characteristics are drawn directly from the STP data, which are received weekly, whereas most characteristics are based on (or, in time, replaced by) information from annual snapshots of the ATO Client Register. These snapshots reflect a historical point-in-time.

To reduce the volatility in fluctuating characteristics, jobholder variables are held constant between snapshot updates. While the date of birth variable is held constant, the jobholder’s age (as derived from date of birth) continues to be updated at the start of a jobholder’s birth month each year.

STP records whose jobholder characteristics cannot be determined from STP or the Client Register snapshot are assigned an ‘unknown’ category for the relevant jobholder characteristic. As persons join the workforce or register with the ATO for the first time, the Client Register snapshot becomes outdated and the number of payroll jobs with an unknown characteristic can increase. Proportions of unknown age and residential geography (state or territory) remain small over time, as they can also be derived from STP data.

However, the proportion of unknown sex (which is only sourced from the Client Register), and sub-state geography is expected to increase over time as the snapshot ages.  The effect of the increasing number of unknowns, and level of revisions for various jobholder characteristics is explained in detail in a historical Methods Review.

ATO Client Register snapshots

Jobholder variables such as date of birth (from which age is derived), sex and residential geography (including sub-state region) are updated from the annual Client Register snapshot. Up until the 10 March 2022 release, a mid-2020 ATO Client Register snapshot was used to assign sex, age and residential geography characteristics. In the 10 March 2022 release, an updated mid-2021 snapshot of the ATO Client Register was used to refresh jobholder variables throughout the time series.

The transition point for these updates using the Client Register snapshots, is at the change in financial year as:

• the STP reporting is financial year based, ensuring jobholder characteristics are held constant across each STP reporting year, and
• the annual ATO Client Register snapshot is taken in July each year, aligning the update point to that of the snapshot.

Some jobholder characteristics indexes have a visible change in levels at the transition point between ATO Client Register snapshots. This is particularly visible for geography, where changes in residential addresses from across a year will currently all be reflected at a single point. The ABS is developing a smoothing method to remove the visible transition between snapshots, particularly to improve the longer time series comparability of geography indexes.

The ABS anticipates that snapshots will be refreshed on an annual basis, to enable regular update of jobholder characteristics and minimise the number of unknowns.

STP data is linked to other information held by the ABS to derive demographic and business characteristics such as age group, sex, geography and industry. If a specific characteristic cannot be linked or derived, and does not appear on the STP file, it is assigned an 'unknown' category (for that characteristic).

Records with 'unknown' characteristics are included in the calculation of index totals for that category. As 'total' and 'component' indexes are calculated independently, the inclusion of records with 'unknown' characteristics in a 'total' index can result in independent movement from 'component' indexes. For example, the ‘total’ index of Persons is calculated from the combined levels of Males, Females and 'unknown’ (persons for whom a Male/Female sex cannot be determined). As a result, the Persons index can move independently from Male and Female indexes, which do not include ‘unknown’ persons. While the proportion of unknown characteristics vary by characteristic, their impact will be compounded in components of finer indexes (such as in State and territory by sex by age group).

Proportion of unknown characteristics

Records with ‘unknown’ characteristics are excluded from the calculations of proportions included in the Distribution of characteristics section of the release.

The proportions of ‘unknown’ characteristics at mid-July 2022 are:

• almost no payroll jobs have an unknown state or territory,
• less than 0.3% of payroll jobs have an unknown age,
• less than 3.1% of payroll jobs have an unknown industry, and
• less than 2.9% of payroll jobs have unknown sex.

STP is a dynamic administrative data source, hence these estimates may be subject to the following sources of error:

• Conceptual misalignment - The Australian tax system is purpose-built and complex, and in some cases it is difficult to determine how a particular STP item should be used to describe impact on payroll jobs and wages. While all care is taken, some income items are subject to this type of validity error. Coherence with other sources indicates that this has a low impact on the aggregate series.
• Reporting error - This is likely to be present in both employee and employer information used. While only the most significant reporting errors are identified or adjusted, some reporting errors may remain. These errors are considered to have a low impact on the aggregate series given their coherence with other similar statistics.

There are differences between these estimates and similar statistics produced by the ABS. When compared to other ABS sources, the change in payroll jobs and wages paid in these estimates may differ due to differences in the concepts, scope and methodology used. For example, these estimates:

• contain a combination of administrative data collected for taxation purposes from employers, whereas other ABS data sources are compiled for the explicit purpose of producing statistics,
• exclude unreported cash in hand payments which may be included in household and business surveys,
• may include information relating to a reference week, rather than a particular point in time,
• are not yet adjusted with respect to seasonality, unlike other Labour Force releases, 
• provide a payroll jobs measure whereby those people who hold more than one job at a time (i.e. secondary jobs) are counted in each job, whereas each person is counted once in the employed persons measure in the Labour Force survey, and
• do not account for hours worked, hours paid for, job attachment where a payment has not been made, or jobholders temporarily stood down without pay, or employment status of employees (i.e. full time or part time), which are considerations in the Labour Force survey measures. For further information, see Differences to Labour Force employment statistics.

These estimates are presented as an ‘original’ data series, and do not include seasonally adjusted or trend data time series found in other labour statistics releases (e.g. Labour Force). 

STP is a relatively new program (and data source). Generally, three to five years of data are required before good seasonally adjusted data can be produced, hence it is not yet possible to produce a seasonally adjusted series (with seasonal elements removed) or trend series (with both the seasonal elements and irregular fluctuations removed). This means that variations in these estimates may reflect seasonal changes in the labour market in addition to COVID-19 related impacts in the economy.

Seasonal characteristics may be seen:

• around national public holidays, where increases in the total wages series are evident in industries where penalty rates are paid;
• ahead of the Christmas period, where considerable labour market activity in a range of industries increases payroll jobs and wages,
• across school holiday periods, where some industries experience lower business activity. This is particularly pronounced in the holiday period after Christmas, resulting in a decrease in the national payroll jobs and total wages series,
• in industries where periodic bonuses are paid. While bonuses may be paid at any time during the year, they often have an industry pattern. For example, the effect of bonus payments is seen in the total wages series in the Mining industry around February/March and August/September, and around March and September in the Financial and insurance services industry.

As seasonal characteristics are further identified in these data, this list will be expanded.

Agriculture, forestry and fishing industry

The Agriculture, forestry and fishing industry is subject to higher rates of week-on-week change in the payroll jobs and wages series than other industries. This is primarily due to greater peaks and troughs caused by seasonal factors that affect employment such as harvesting or shearing. Employers in this industry have also had STP reporting concessions which permit them to report on a less frequent basis than each pay event. These concessions ceased at the end of June 2021.

Wages estimates are subject to a higher degree of reporting seasonality (due to seasonal variation in payments, changes in working hours and overtime) and revisions than the payroll jobs estimates. While the ABS accounts for employees being paid with different frequencies (weekly, fortnightly etc.) there are periods where additional reporting activity is more common, which may flow through to published estimates. 

End of financial year

Payroll jobs and wages data during June and July see increased seasonality in employer reporting, due to:

• employers finalising their year to date employee earnings information,
• a reset of financial year in payroll systems, and
• end of financial year bonus and commission payments.

These factors can translate to a higher variation in estimates over this period, as well as revisions, particularly in wages estimates.

In addition, June 2021 saw the conclusion of many STP reporting concessions which have contributed additional index movement around the end of financial year (particularly for smaller employers). 

Re-submission of historical pay periods

The dynamic nature of STP data can result in revisions to payroll jobs and wages indexes, caused by the re-submission of payroll data for historical pay periods (including prior financial years) by STP-enabled employers. When re-submission results in an update to payroll jobs and wages levels at the index base reference period (of 14 March 2020), a revision across the index time series in component indexes may be observed.

The size of revisions and the period over which they apply can vary between indexes. Some component indexes are subject to higher than usual levels of revision, over a longer period. For example, the employment size indexes show both a higher incidence and duration of revision. This is most noticeable in the small employers group (those with under 20 employees). Characteristics which contribute to revisions in the estimates for this group are:

• higher levels of reporting seasonality; 
• a greater incidence of longer payment periods (such as quarterly); and 
• graduated STP onboarding (the effect of which was more prevalent up to July 2021). 

The ABS is currently investigating methods to reduce the future level of revisions in this series. In the interim, to provide more stability at the end point of all employment size indexes, a month lag in the reference week is in place. 

Week ending 12 February 2022

• Update of jobholder characteristics - revisions to all sex, age and geography indexes as noted in Methods review

Week ending 13 November 2021

• Update of employer characteristics - refinement of Job-TAU allocation process as noted in Methods review

Week ending 11 September 2021

• Update to imputation retention - the imputation retention threshold updated from 8 pay periods to 16 weeks

Week ending 31 July 2021

• Change in lag between reference week and release date - reducing imputation in the latest weeks of data, as noted in the Imputation section

Week ending 19 June 2021

• Update of employer characteristics - ABS Business Register snapshot update to industry and employment size variables

Week ending 10 April 2021

• Historical imputation - period over which historical imputation is removed for terminated employees changed from 3 to 8 pay periods

Week ending 27 March 2021

• Update of jobholder characteristics - Client Register snapshot update to sex, age and geography variables

Week ending 30 January 2021

• Imputation update - to deliver a reduced magnitude of future revisions, particularly in the most recent week's data

Week ending 16 January 2021

• Age derivation update - a person is aged at the start of their birthday month instead of redefining age each reference week

Week ending 2 January 2021

• Update of characteristics variables - Employers with unknown industry included in estimates, as noted in Data limitations and revisions

Week ending 14 November 2020

• Week on week revisions - persons aged under 15 years excluded from the under 20s age group

Recording wages when they are earned, accrued or incurred regardless of when payment is made or received.

A register of all Australian businesses and organisations maintained by the Australian Bureau of Statistics (ABS) for the purpose of producing statistical frames and business demography outputs. It contains identifying and classificatory data for each business and organisation.

Information to populate the ABS Business Register is largely sourced from the Australian Business Register.

The ABS Business Register consists of two subpopulations, the profiled population and the non-profiled population. The ABS Business Register uses an economic units model to describe the characteristics of businesses and the structural relationships between related businesses.

A unique identifier. To be entitled to an Australian Business Number (ABN), an organisation must be one or more of the following:

• a company registered under the Corporations Act 2001
• an entity carrying on an enterprise in Australia
• a government entity
• a non-profit sub-entity for Goods and Services Tax purposes
• a superannuation fund.
   

A non-resident entity may be entitled to an ABN if they are carrying on an enterprise in Australia and/or, in the course of carrying on an enterprise, the entity makes sales that are connected with Australia.

The data store containing details about businesses and organisations that have registered for an Australian Business Number. More information can be found on the ABR website.

A register of persons that have interacted with the Australian Tax Office (ATO) and have been issued with an Australian Tax File Number (TFN). The ATO person-level Client Register comprises demographic information such as sex, date of birth, and residential address.

Recording the wage payment in the pay period when the payment was received by the employee.

Commencement and termination dates associated with each job as reported through Single Touch Payroll.

Persons who work for a private or public sector employer, where the employee has received payment in the reference week through Single Touch Payroll (STP) enabled software and reported to the Australian Taxation Office (ATO).

An organisation with an Australian Business Number that provides employment income to one or more people, and reports through the ATO STP system.

An institutional unit covering all the operations within Australia's economic territory of legal entities under common control. Control is defined in Corporations legislation. Majority ownership is not required for control to be exercised. An enterprise group may have one or more TAUs.

Based on residential address as sourced from either the ATO Client Register or STP data. See also 'Greater Capital City Statistical Area' and 'Statistical area' entries. For more information, see the Australian Statistical Geography Standard (ASGS): Volume 1 – Main Structure and Greater Capital City Statistical Areas.

Geographical areas built from Statistical Areas Level 4 (SA4), designed to represent the functional extent of each of the eight State and Territory capital cities. Greater capital city statistical areas (GCCSA) are presented with the 'rest of state' region to cover the whole of Australia without gaps or overlaps. The GCCSA is named according to the city it represents, for example, Greater Sydney. The remainder of the state or territory is named rest of state/territory, for example, Rest of New South Wales (NSW).

A homogenous grouping of economic activities undertaken to produce goods and services. The Australian and New Zealand Standard Industrial Classification is used to classify an entity to an industry based on its dominant activity.

The broadest grouping of industries within the Australian and New Zealand Standard Industrial Classification. The main purpose of the industry division level is to provide a limited number of categories, which give a broad overall picture of the economy. There are 19 mutually exclusive divisions. For more information see the Australian and New Zealand Standard Industrial Classification.

The second broadest grouping of industries within the Australian and New Zealand Statistical Industrial Classification. Industry subdivisions are built up from the industry groups which, in turn, are built up from industry classes. For more information see the Australian and New Zealand Standard Industrial Classification.

See payroll job.

The vast majority of businesses included on the ABSBR are in the non-profiled population. Most of these businesses have simple structures that are suitable for ABS statistical purposes at the Australian Business Number (ABN) level. For the non-profiled population, one ABN equates to one business.

Statistic is not available. This can be to protect the confidentiality of data providers or to prevent misinterpretation of statistics due to poor quality.

A person who operates their own unincorporated enterprise, which does not possess a separate legal identity to that of its owner(s), or engages independently in a profession or trade.

OMUEs can also be referred to as self-employed. Owner managers of unincorporated enterprises are not included in these estimates as they are not in scope of STP-enabled software reporting to the ATO.

Unincorporated enterprises are further defined in the Type of Legal Organisation (TOLO) classification section of the Standard Economic Sector Classifications of Australia (SESCA) release.

A payroll job is a relationship between an employee and their employing enterprise, where the employee is paid in the reference week through STP-enabled payroll or accounting software and reported to the ATO. Where an employee is paid other than weekly, the established payment pattern is used to identify jobs in weeks outside the payment week.

For a small number of businesses, the ABN unit is not suitable for ABS economic statistics purposes and the ABS maintains its own economic units structure through direct contact with businesses. These businesses constitute the profiled population and are represented by Type of Activity Units (TAUs). This population consists of large, complex and diverse groups of businesses (known as enterprise groups).

The Public/Private classification divides the economy into two sectors: Public (government units and units controlled by government); and Private (all other units). For more information, see the Standard Economic Sector Classifications of Australia (SESCA) release.

The Single Touch Payroll (STP) system sends taxation and superannuation information from a business' STP-enabled payroll or accounting software to the ATO as a business runs its payroll.

Self reported sex (i.e. male/ female) of a person as reported through the ATO taxation system. Categories other than male or female are not published separately in this release but are included in published totals.

Statistical area level 3 (SA3) regions are designed to provide a regional breakdown of Australia. They generally have a population of between 30,000 and 130,000 people. In regional areas, SA3s represent the area serviced by regional cities that have a population over 20,000 people. In the major cities, SA3s represent the area serviced by a major transport and commercial hub. They often closely align to large urban Local Government Areas (e.g. Gladstone, Geelong). In outer regional and remote areas, SA3s represent areas which are widely recognised as having a distinct identity and similar social and economic characteristics.

Statistical area level 4 (SA4) regions are specifically designed to reflect labour markets within each state and territory within population limits. In regional areas, SA4s tend to have lower populations (100,000 to 300,000), while in metropolitan areas, SA4s tend to have larger populations (300,000 to 500,000).

A TAU consists of one or more business entities, sub entities or branches of a business that can be grouped according to production activity, and can report a minimum set of data items. TAUs are classified according to the industry of their main activity. The relationship between TAUs and their associated legal entities (ABNs) may be one-to-one, many-to-one, or one-to-many.

All legal entities on the ABS Business Register are classified according to their type of legal organisation, of which there are three types:

• incorporated private sector entities
• unincorporated private sector entities
• public sector entities.
   

The type of legal organisation indicates whether a business is part of the private or public sector and the type of ownership structure. For more information see the Standard Economic Sector Classifications of Australia (SESCA) release.

Wages include salary payments and allowances, labour hire payments and foreign income, as well as the value of payments in kind (where a fringe benefit amount is recorded). Bonuses are typically included where they are reported in the same field as normal payments. Wages are calculated as gross amounts, prior to taxation and deductions.

Wages exclude payments to employee's superannuation as well as severance and termination payments. Wages are only available for payroll jobs and do not include income from own businesses or other sources.