Earnings guide

Guide to labour statistics

Learn about our different earnings measures and how to use them

Released

7/11/2022

Overview

We produce a wide range of earnings statistics from a mix of data sources, for many different purposes. It can be challenging to choose the right earnings data to use. This guide will help you to understand the different features of our various earnings measures and sources and choose the correct measure to suit your needs.

Our definition of earnings

Earnings statistics generally refer to gross (pre-tax) cash wages and salaries paid to employees at regular intervals for work done as well as paid leave. They exclude irregular payments, employers' social contributions and severance and termination pay, as well as the value of 'non-cash' benefits provided to employees as part of a salary package.

Earnings statistics are one of four main areas of interest in measuring employee remuneration. The Earnings chapter of Labour Statistics: Concepts, Sources and Methods has more information on earnings and employee remuneration related concepts and how we produce the data.

Earnings measures and uses

Each measure is designed for different purposes and has its own strengths and weaknesses - they are not simply different ways of measuring the same thing.

Use the guides linked below to learn more about the ways we measure earnings and when to use each measure.

Measures available by data source

This table summarises the most relevant data sources for each earnings measure. We produce additional data sources which also include earnings statistics.

Measures available by data source (a)
	Earnings levels / average earnings	Wage growth / change	Weekly earnings	Hourly earnings	Aggregate earnings
Average Weekly Earnings	✔	◼	✔
Australian National Accounts					✔
Employee Earnings and Hours	✔		✔	✔
Employee earnings (b)	◼	◼	◼	◼
Employment and Earnings, Public Sector					◼
Jobs in Australia	◼				◼
Labour Account	◼	◼			✔
Personal Income in Australia	✔				◼
Wage Price Index		✔
Weekly Payroll Jobs and Wages		◼

✔ Recommended for this topic in relation to earnings data.
◼ Published for this topic in relation to earnings data however some limitations should be noted.

Ratings provide guidance on the relative quality of the different sources. Business sources generally provide more accurately reported earnings than household sources as data are obtained from employers' payrolls. Business sources are recommended for each topic where available. For more information, please see the Earnings chapter of Labour Statistics: Concepts, Sources and Methods.
Based on data from the annual Characteristics of Employment Labour Force supplementary survey.

I'm looking for earnings by...

Use this section to find earnings data you're interested in by topic. Clicking on the topic heading will provide more details.

Sex and gender pay gap

Earnings by sex

Average Weekly Earnings, Australia provides estimates of weekly earnings by sex for full-time adults and all employees every six months.

Weekly Payroll Jobs and Wages in Australia provides timely estimates of week-to-week change in total wages and salaries paid by sex. Estimates are published monthly and provide insight into short term changes in the labour market.

Detailed data

Employee earnings provides estimates of median weekly and hourly earnings, as well as distribution estimates by sex. Estimates are published annually and can be further broken down by education qualification and employment and working arrangements, including full-time and part-time status.

Employee Earnings and Hours, Australia includes the most detailed earnings data by sex and is available every two years. It provides weekly and hourly earnings estimates by sex, as well as distributional estimates and measures of hours paid for. Sex data can be broken down further by a broad range of employer and demographic characteristics, including age range, managerial and non-managerial status, method of setting pay and employer size.

Personal Income in Australia provides annual income estimates by sex for more than 2,200 geographic areas, including local government areas and SA2s (areas of approximately 10,000 people).

Gender pay gap

The gender pay gap is the difference between male and female wages, expressed as a proportion of male wages.

Many factors influence the gender pay gap, including labour force participation over time and experience, hours worked, industry of employment, occupation, and qualifications. While a measure from Average Weekly Earnings has traditionally been the most frequently cited, no single measure provides a complete view of the gender pay gap. Instead, a range of measures should be considered together to understand what influences the gender pay gap and what this means for comparative male and female earnings.

For more detailed information on the gender pay gap, see our Gender pay gap guide.

Advice for data users

Median estimates are the most representative measure of earnings of an "average" male or female, as median estimates provide the mid-point value in a distribution - with half of people above the value and half below it. Mean (average) estimates present an arithmetic average. Earnings data has a positively skewed distribution, due to the small number of people with very high earnings. A higher proportion of males have very high earnings than females.

Earnings estimates for longer time periods (such as weekly or annual) and broad groupings (for example, all employees) are also more likely to be affected by compositional factors influencing the gender pay gap. These measures provide insight into total earnings received by males and females.

Estimates of hourly earnings and for tightly defined groups of people (for example, full-time employees by occupation) provide a more common basis for comparison, reducing the impact of compositional factors, including differences in the amount of paid work. These measures allow for a purer assessment of the difference in male and female earnings. However, these comparisons do not account for a range of other factors contributing to pay differentials such as concentration in higher or lower paying industries or occupations or reflect the overall economic position of females compared to males.

Age

Employee Earnings and Hours, Australia includes both compositional and distributional estimates of weekly and hourly earnings by age range for several employer and employee characteristics. Finer level age groupings and additional breakdowns are available from Microdata and TableBuilder: Employee Earnings and Hours or through a customised data request.

Employee earnings includes weekly earnings estimates by age group by sex and full-time/part-time status. Finer level age groupings and additional breakdowns are available from Microdata and TableBuilder: Characteristics of Employment.

Personal Income in Australia includes earnings estimates for 10 year age groups by sex for small geographic areas. Single year age groupings are available from Microdata and TableBuilder: Jobs in Australia.

Weekly Payroll Jobs and Wages in Australia includes estimates of change in total wages and salaries paid by to each 10 year age group by industry, state and territory and sex. The estimates are published monthly however include weekly data, providing timely insights into short term changes in the labour market by age group.

Region and small geographic areas

Personal Income in Australia provides annual income estimates for more than 2,200 geographic areas, including local government areas and SA2s (areas of approximately 10,000 people).

Census of Population and Housing data includes a 5 yearly point in time snapshot of personal, family and household income for a range of different geographic areas, down to the SA1 level (areas of between 200 and 800 people).

Employee earnings includes earnings estimates for greater capital cities (for example, Greater Melbourne) and the rest of state. SA4 level estimates (usually areas of more than 100,000 people) are available from Microdata and TableBuilder: Characteristics of Employment.

The Australian Statistical Geography Standard (ASGS) is used to classify Australia into a hierarchy of statistical areas such as SA1s and Greater Capital City Statistical Areas.

Education

Employee earnings includes mean, median earnings and distribution estimates annually by educational qualification for a wide range of employer and demographic characteristics.

Employment arrangements and full-time / part-time status

Average Weekly Earnings, Australia includes average weekly earnings for full-time adults and all employees every six months.

Employee Earnings and Hours, Australia includes composition and distribution of weekly (and hourly) earnings and hours paid for estimates every two years by:

employment arrangement (permanent, fixed-term contract or casual)
full-time and part-time status
managerial and non-managerial status
method of setting pay (award, collective agreement, individual arrangement)
adult, junior, apprentice and disability rate of pay.

Employee earnings includes mean and median weekly (and hourly) earnings and distribution estimates annually by:

employment arrangement (for example, various measures of casual employment, and fixed-term contract)
full-time and part-time status
working arrangements (for example, job stability measures, shift work, work from home, flexible hours).

Occupation and skill level

Occupation

Employee Earnings and Hours, Australia provides earnings data for more than 350 occupations by sex and method of setting pay every two years. Distributional data and additional cross-classifications are available for broader occupational groupings. Detailed occupation data broken down further by employer and demographic characteristics are available from Microdata and TableBuilder: Employee Earnings and Hours or through a customised data request.

Employee earnings includes mean and median earnings for 8 occupation groupings annually by sex, industry, status in employment and education qualification. Distribution data is also available for the 8 occupation groupings. More detailed occupation data is available from Microdata and TableBuilder: Characteristics of Employment.

The Australian and New Zealand Standard Classification of Occupations (ANZSCO) is used to categorise occupations.

Skill level

Employee Earnings and Hours, Australia and Employee earnings both also provide data on skill level, as each occupation is assigned a skill level in ANZSCO.

Skill level data provides insight into the range and complexity of tasks performed in a particular occupation. The skill level is applied to the occupation (not individuals) and measures the level or amount of formal education and training, previous experience in a related occupation, and on-the-job training required to perform the tasks of a particular occupation.

For more information, please see How ANZSCO works.

Pay-setting method (award, collective agreement, individual arrangement)

Employee Earnings and Hours, Australia includes earnings data by method of setting pay, identifying how an employee’s pay is set. Methods are classified into four categories:

award only,
collective agreement,
individual arrangement,
owner manager of incorporated enterprise.

Method of setting pay data can be broken down further by employer and demographic characteristics.

Industry and other employer characteristics (including employer size, sector)

Average Weekly Earnings, Australia provides estimates of weekly earnings by industry and public/private sector every six months.

Employee Earnings and Hours, Australia includes compositional and distributional earnings data by industry, public/private sector, and employer size every two years. These employer characteristics can be broken down further by demographic characteristics including age, sex and state and territory.

Wage Price Index, Australia measures changes in the price of wages and salaries, and is available by industry and sector.

Industry only

Labour Account, Australia includes quarterly industry division and annual industry sub-division estimates of costs incurred by enterprises in employing labour, and the income received by people for working. The Labour Account is a recommended source for industry data as it brings together a range of labour market statistics into a single framework, providing a coherent and consistent dataset.

Weekly Payroll Jobs and Wages in Australia provides timely estimates of week-to-week change in total wages and salaries paid by industry. Estimates are published monthly and provide insight into short term changes in the labour market.

Sector by industry

Business Indicators, Australia provides quarterly estimates of employee wages and salaries for the private sector by industry.

Employment and Earnings, Public Sector, Australia includes annual estimates of cash wages and salaries for the public sector by industry and level of government.

Topics available by data source

This table summarises the most relevant earnings data sources by topic. Preferred sources change depending on who is providing the information - household sources are generally preferred for person characteristics with business sources preferred for job and employer characteristics. However, business sources also generally provide more accurately reported earnings as data are obtained from employers' payrolls. The quality of earnings data has been prioritised when assigning ratings in the table below. For more information on the strengths and limitations of different sources, please see the Earnings chapter of Labour Statistics: Concepts, Sources and Methods.

Some of these data sources have extra topics available through their TableBuilder or microdata products. We produce additional data sources which also include earnings statistics on these topics.

Topics available by data source (a)(b)
	AWE	Census	EE (c)	EEH	JIA	LA	PIA	SEE	WPI	WPJW
Person characteristics
Sex	✔	◼	◼	✔	✔		✔			◼
Age groups		◼	◼	✔	✔		✔			◼
State/territory	✔	◼	◼	✔	◻		✔	◼	✔	◼
Region		◼			✔		✔
Education		◼	✔
Job characteristics
Part-time and full-time	◼ (d)		✔	✔
Employment arrangement		◼	✔	◼	◼		◻
Occupation and skill level		◼	✔	✔	◻		◻
Pay setting method				✔
Employer characteristics
Industry	✔	◼	◼	✔	◼	✔	◻	◼	✔	◼
Sector	✔		◼	✔	◼	✔	◻	◼(e)	✔
Employer size				✔	◼		◻

✔ Recommended for this topic in relation to earnings data.
◼ Published for this topic in relation to earnings data however some limitations should be noted.
◻ Available for this topic upon request or via TableBuilder and microdata products.

Ratings provide guidance on the relative quality of the different sources. Business sources generally provide more accurately reported earnings than household sources as data are obtained from employers' payrolls. Business sources are recommended for each topic where available. For more information, please see the Earnings chapter of Labour Statistics: Concepts, Sources and Methods.
Acronyms: Average Weekly Earnings (AWE), Employee earnings (EE), Employee Earnings and Hours (EEH), Jobs in Australia (JIA), Labour Account (LA), Personal Income in Australia (PIA), Employment and Earnings, Public Sector (SEE), Wage Price Index (WPI) and Weekly Payroll Jobs and Wages in Australia (WPJW).
Based on data from the annual Characteristics of Employment Labour Force supplementary survey.
Full-time adults and all employees.
Public sector only.

Data and resources available

This section summarises the earnings data available according to their key features. It also lists other information which may help you to understand earnings data.

Earnings data sources

We produce many data sources measuring earnings and employee remuneration related concepts. The most relevant data sources are included below.

ABS earnings data sources
Release	Pillar	Frequency	Description
Average Weekly Earnings	Business survey	Six monthly	Headline estimates of weekly earnings. Used extensively in legislation.
Employee earnings	Household survey	Annual	Median weekly and hourly earnings as well as distribution estimates for detailed demographic and employment characteristics. More detailed data is available through Microdata and TableBuilder: Characteristics of Employment.
Employee Earnings and Hours	Business survey	Two-yearly	Compositional and distributional estimates of hourly and weekly earnings, hours paid for and methods used to set employees' pay for a range of demographic and employer characteristics. More detailed data is available through Microdata and TableBuilder: Employee Earnings and Hours or customised data request.
Employment and Earnings, Public Sector	Business survey	Annual	Public sector employment estimates by state/territory, and level of government.
Jobs in Australia	Admin data	Annual	Job level income estimates for more than 2,200 regions, as well as by industry and occupation detail sourced from personal income tax data in the Linked Employer Employee Dataset (LEED). More detailed data available through Microdata and TableBuilder: Jobs in Australia.
Labour Account	Accounts	Quarterly	Labour payments, labour income and compensation of employees by sector, industry division (quarterly) and sub-division (annually).
Labour Costs	Business survey	Irregular	Components of labour costs - earnings, superannuation, payroll tax, workers compensation, fringe benefits tax.
Personal Income in Australia	Admin data	Annual	Personal income estimates for more than 2,200 regions, as well as by industry and occupation detail sourced from personal income tax data in the Linked Employer Employee Dataset (LEED). More detailed data available through Microdata and TableBuilder: Jobs in Australia.
Wage Price Index	Business survey	Quarterly	Quarterly and annual wage indexes, unaffected by changes in compositional factors including employee characteristics and hours worked by industry, state/territory and sector.
Weekly Payroll Jobs and Wages in Australia	Admin data	Monthly	Weekly total wage indexes including percentage change movement, based on Single Touch Payroll data.

Other information

Earnings levels guide

Learn about our earnings levels measures and how to use them

Released

7/11/2022

Overview

Earnings level estimates measure the value of earnings in dollar terms. The Earnings guide includes information about other earnings measures.

Headline measure

Average Weekly Earnings, Australia (AWE) is our headline measure of average earnings.

We have produced average weekly earnings estimates since 1941. The current survey commenced in 1983 and data has been released every six months since 2012, and quarterly before that. You can learn more about AWE over time on the Average Weekly Earnings methodology page.

AWE provides estimates by sex, state/territory, and public/private sector for three earnings series:

Full-time adult ordinary time earnings
Full-time adult total earnings
Total earnings.

We also produce a cash earnings series, which is the most comprehensive measure of average earnings in Australia.

You can use AWE to analyse earnings levels over time.

Average weekly earnings (Original)
	Full-time adult ordinary time earnings ($)	Full-time adult total earnings ($)	Total earnings ($)	Full-time adult ordinary time cash earnings ($)	Full-time adult total cash earnings ($)	Total cash earnings ($)
Nov-94	630.10	672.60	542.40
Feb-95	640.10	681.10	549.20
May-95	648.20	688.80	548.90
Aug-95	653.20	692.70	548.90
Nov-95	661.20	704.40	555.40
Feb-96	667.00	708.50	563.80
May-96	673.80	716.50	565.50
Aug-96	677.20	717.80	567.40
Nov-96	686.10	730.90	570.60
Feb-97	694.20	733.20	582.20
May-97	696.30	736.70	578.10
Aug-97	706.30	746.00	582.40
Nov-97	710.60	752.70	592.60
Feb-98	721.40	761.50	597.70
May-98	725.70	766.90	596.00
Aug-98	734.70	774.90	602.70
Nov-98	739.50	783.50	603.40
Feb-99	742.90	782.10	607.90
May-99	748.50	788.60	610.40
Aug-99	749.50	787.50	604.80
Nov-99	760.80	802.90	613.00
Feb-00	772.10	808.60	625.00
May-00	779.10	818.40	633.80
Aug-00	794.10	833.20	645.40
Nov-00	798.10	834.70	643.10
Feb-01	805.90	840.10	658.40
May-01	818.80	856.10	660.30
Aug-01	833.00	867.60	670.20
Nov-01	842.60	879.60	673.60
Feb-02	853.90	891.40	684.60
May-02	860.10	899.50	683.80
Aug-02	872.40	911.60	694.10
Nov-02	882.10	924.70	699.40
Feb-03	892.50	933.10	713.90
May-03	912.80	954.30	721.40
Aug-03	920.50	964.70	728.80
Nov-03	929.10	979.20	740.30
Feb-04	937.90	985.00	749.80
May-04	939.00	984.00	741.40
Aug-04	952.00	999.80	754.80
Nov-04	965.00	1,017.20	761.70
Feb-05	980.60	1,034.40	783.20
May-05	993.80	1,047.10	784.20
Aug-05	1,009.20	1,056.70	799.50
Nov-05	1,011.80	1,066.00	800.60
Feb-06	1,023.30	1,072.10	816.50
May-06	1,025.80	1,073.60	819.70
Aug-06	1,037.10	1,084.30	830.20
Nov-06	1,044.10	1,093.80	837.40
Feb-07	1,058.50	1,105.10	857.10
May-07	1,076.80	1,124.10	858.50
Aug-07	1,093.10	1,141.80	871.10
Nov-07	1,098.60	1,151.00	873.20
Feb-08	1,113.10	1,164.90	886.60
May-08	1,119.60	1,171.50	885.00
Aug-08	1,144.50	1,195.20	901.80
Nov-08	1,158.00	1,210.80	909.50
Feb-09	1,175.60	1,222.70	921.10
May-09	1,187.80	1,234.90	918.60
Aug-09	1,204.20	1,250.30	940.00
Nov-09	1,226.80	1,276.70	955.00
Feb-10	1,243.90	1,290.70	973.80
May-10	1,250.10	1,300.30	977.10	1,301.40	1,351.50	1,016.00
Aug-10	1,258.80	1,309.70	978.40	1,310.60	1,361.50	1,017.50
Nov-10	1,275.20	1,328.50	996.10	1,327.80	1,381.00	1,035.50
Feb-11	1,291.30	1,343.70	1,011.80	1,344.20	1,396.60	1,051.90
May-11	1,304.70	1,357.90	1,015.20	1,357.40	1,410.60	1,055.10
Aug-11	1,324.90	1,376.20	1,024.20	1,377.70	1,429.00	1,063.60
Nov-11	1,330.10	1,390.50	1,033.70	1,381.40	1,441.80	1,072.30
Feb-12	1,348.10	1,406.80	1,056.20	1,400.70	1,459.40	1,096.90
May-12	1,349.20	1,413.10	1,053.20	1,401.50	1,465.40	1,093.60
Aug-12
Nov-12	1,396.00	1,458.00	1,081.30	1,441.00	1,503.10	1,116.40
Feb-13
May-13	1,420.90	1,482.50	1,105.00	1,464.40	1,526.00	1,140.30
Aug-13
Nov-13	1,437.00	1,500.10	1,114.20	1,483.50	1,546.60	1,151.30
Feb-14
May-14	1,454.10	1,515.80	1,123.00	1,502.50	1,564.20	1,161.70
Aug-14
Nov-14	1,477.00	1,542.40	1,128.70	1,528.40	1,593.90	1,168.30
Feb-15
May-15	1,483.10	1,541.50	1,136.90	1,537.30	1,595.70	1,179.00
Aug-15
Nov-15	1,500.50	1,560.50	1,145.70	1,556.50	1,616.50	1,188.90
Feb-16
May-16	1,516.00	1,573.30	1,160.90	1,568.30	1,625.60	1,202.10
Aug-16
Nov-16	1,533.40	1,595.50	1,163.50	1,584.30	1,646.40	1,203.10
Feb-17
May-17	1,543.20	1,605.60	1,179.00	1,594.10	1,656.50	1,218.80
Aug-17
Nov-17	1,569.60	1,632.10	1,191.50	1,615.30	1,677.70	1,227.10
Feb-18
May-18	1,585.30	1,650.60	1,207.40	1,631.10	1,696.40	1,243.50
Aug-18
Nov-18	1,605.50	1,668.10	1,225.30	1,651.30	1,713.90	1,261.60
Feb-19
May-19	1,634.80	1,695.10	1,237.90	1,681.60	1,741.80	1,275.60
Aug-19
Nov-19	1,658.40	1,722.80	1,257.00	1,706.20	1,770.60	1,295.40
Feb-20
May-20	1,713.90	1,768.90	1,304.70	1,762.20	1,817.10	1,343.40
Aug-20
Nov-20	1,711.60	1,769.90	1,280.30	1,757.20	1,815.60	1,316.60
Feb-21
May-21	1,737.10	1,797.00	1,305.80	1,783.70	1,843.50	1,343.50
Aug-21
Nov-21	1,748.40	1,813.00	1,328.90	1,794.60	1,859.30	1,366.60
Feb-22
May-22	1,769.80	1,835.30	1,344.70	1,816.10	1,881.60	1,382.30

Average weekly earnings (Original)

["","Full-time adult ordinary time earnings","Full-time adult total earnings","Total earnings","Full-time adult ordinary time cash earnings","Full-time adult total cash earnings","Total cash earnings"]

[["Nov-94","Feb-95","May-95","Aug-95","Nov-95","Feb-96","May-96","Aug-96","Nov-96","Feb-97","May-97","Aug-97","Nov-97","Feb-98","May-98","Aug-98","Nov-98","Feb-99","May-99","Aug-99","Nov-99","Feb-00","May-00","Aug-00","Nov-00","Feb-01","May-01","Aug-01","Nov-01","Feb-02","May-02","Aug-02","Nov-02","Feb-03","May-03","Aug-03","Nov-03","Feb-04","May-04","Aug-04","Nov-04","Feb-05","May-05","Aug-05","Nov-05","Feb-06","May-06","Aug-06","Nov-06","Feb-07","May-07","Aug-07","Nov-07","Feb-08","May-08","Aug-08","Nov-08","Feb-09","May-09","Aug-09","Nov-09","Feb-10","May-10","Aug-10","Nov-10","Feb-11","May-11","Aug-11","Nov-11","Feb-12","May-12","Aug-12","Nov-12","Feb-13","May-13","Aug-13","Nov-13","Feb-14","May-14","Aug-14","Nov-14","Feb-15","May-15","Aug-15","Nov-15","Feb-16","May-16","Aug-16","Nov-16","Feb-17","May-17","Aug-17","Nov-17","Feb-18","May-18","Aug-18","Nov-18","Feb-19","May-19","Aug-19","Nov-19","Feb-20","May-20","Aug-20","Nov-20","Feb-21","May-21","Aug-21","Nov-21","Feb-22","May-22"],[[630.10000000000002],[640.10000000000002],[648.20000000000005],[653.20000000000005],[661.20000000000005],[667],[673.79999999999995],[677.20000000000005],[686.10000000000002],[694.20000000000005],[696.29999999999995],[706.29999999999995],[710.60000000000002],[721.39999999999998],[725.70000000000005],[734.70000000000005],[739.5],[742.89999999999998],[748.5],[749.5],[760.79999999999995],[772.10000000000002],[779.10000000000002],[794.10000000000002],[798.10000000000002],[805.89999999999998],[818.79999999999995],[833],[842.60000000000002],[853.89999999999998],[860.10000000000002],[872.39999999999998],[882.10000000000002],[892.5],[912.79999999999995],[920.5],[929.10000000000002],[937.89999999999998],[939],[952],[965],[980.60000000000002],[993.79999999999995],[1009.2],[1011.8],[1023.3],[1025.8],[1037.0999999999999],[1044.0999999999999],[1058.5],[1076.8],[1093.0999999999999],[1098.5999999999999],[1113.0999999999999],[1119.5999999999999],[1144.5],[1158],[1175.5999999999999],[1187.8],[1204.2],[1226.8],[1243.9000000000001],[1250.0999999999999],[1258.8],[1275.2],[1291.3],[1304.7],[1324.9000000000001],[1330.0999999999999],[1348.0999999999999],[1349.2],[null],[1396],[null],[1420.9000000000001],[null],[1437],[null],[1454.0999999999999],[null],[1477],[null],[1483.0999999999999],[null],[1500.5],[null],[1516],[null],[1533.4000000000001],[null],[1543.2],[null],[1569.5999999999999],[null],[1585.3],[null],[1605.5],[null],[1634.8],[null],[1658.4000000000001],[null],[1713.9000000000001],[null],[1711.5999999999999],[null],[1737.0999999999999],[null],[1748.4000000000001],[null],[1769.8]],[[672.60000000000002],[681.10000000000002],[688.79999999999995],[692.70000000000005],[704.39999999999998],[708.5],[716.5],[717.79999999999995],[730.89999999999998],[733.20000000000005],[736.70000000000005],[746],[752.70000000000005],[761.5],[766.89999999999998],[774.89999999999998],[783.5],[782.10000000000002],[788.60000000000002],[787.5],[802.89999999999998],[808.60000000000002],[818.39999999999998],[833.20000000000005],[834.70000000000005],[840.10000000000002],[856.10000000000002],[867.60000000000002],[879.60000000000002],[891.39999999999998],[899.5],[911.60000000000002],[924.70000000000005],[933.10000000000002],[954.29999999999995],[964.70000000000005],[979.20000000000005],[985],[984],[999.79999999999995],[1017.2],[1034.4000000000001],[1047.0999999999999],[1056.7],[1066],[1072.0999999999999],[1073.5999999999999],[1084.3],[1093.8],[1105.0999999999999],[1124.0999999999999],[1141.8],[1151],[1164.9000000000001],[1171.5],[1195.2],[1210.8],[1222.7],[1234.9000000000001],[1250.3],[1276.7],[1290.7],[1300.3],[1309.7],[1328.5],[1343.7],[1357.9000000000001],[1376.2],[1390.5],[1406.8],[1413.0999999999999],[null],[1458],[null],[1482.5],[null],[1500.0999999999999],[null],[1515.8],[null],[1542.4000000000001],[null],[1541.5],[null],[1560.5],[null],[1573.3],[null],[1595.5],[null],[1605.5999999999999],[null],[1632.0999999999999],[null],[1650.5999999999999],[null],[1668.0999999999999],[null],[1695.0999999999999],[null],[1722.8],[null],[1768.9000000000001],[null],[1769.9000000000001],[null],[1797],[null],[1813],[null],[1835.3]],[[542.39999999999998],[549.20000000000005],[548.89999999999998],[548.89999999999998],[555.39999999999998],[563.79999999999995],[565.5],[567.39999999999998],[570.60000000000002],[582.20000000000005],[578.10000000000002],[582.39999999999998],[592.60000000000002],[597.70000000000005],[596],[602.70000000000005],[603.39999999999998],[607.89999999999998],[610.39999999999998],[604.79999999999995],[613],[625],[633.79999999999995],[645.39999999999998],[643.10000000000002],[658.39999999999998],[660.29999999999995],[670.20000000000005],[673.60000000000002],[684.60000000000002],[683.79999999999995],[694.10000000000002],[699.39999999999998],[713.89999999999998],[721.39999999999998],[728.79999999999995],[740.29999999999995],[749.79999999999995],[741.39999999999998],[754.79999999999995],[761.70000000000005],[783.20000000000005],[784.20000000000005],[799.5],[800.60000000000002],[816.5],[819.70000000000005],[830.20000000000005],[837.39999999999998],[857.10000000000002],[858.5],[871.10000000000002],[873.20000000000005],[886.60000000000002],[885],[901.79999999999995],[909.5],[921.10000000000002],[918.60000000000002],[940],[955],[973.79999999999995],[977.10000000000002],[978.39999999999998],[996.10000000000002],[1011.8],[1015.2],[1024.2],[1033.7],[1056.2],[1053.2],[null],[1081.3],[null],[1105],[null],[1114.2],[null],[1123],[null],[1128.7],[null],[1136.9000000000001],[null],[1145.7],[null],[1160.9000000000001],[null],[1163.5],[null],[1179],[null],[1191.5],[null],[1207.4000000000001],[null],[1225.3],[null],[1237.9000000000001],[null],[1257],[null],[1304.7],[null],[1280.3],[null],[1305.8],[null],[1328.9000000000001],[null],[1344.7]],[[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1301.4000000000001],[1310.5999999999999],[1327.8],[1344.2],[1357.4000000000001],[1377.7],[1381.4000000000001],[1400.7],[1401.5],[null],[1441],[null],[1464.4000000000001],[null],[1483.5],[null],[1502.5],[null],[1528.4000000000001],[null],[1537.3],[null],[1556.5],[null],[1568.3],[null],[1584.3],[null],[1594.0999999999999],[null],[1615.3],[null],[1631.0999999999999],[null],[1651.3],[null],[1681.5999999999999],[null],[1706.2],[null],[1762.2],[null],[1757.2],[null],[1783.7],[null],[1794.5999999999999],[null],[1816.0999999999999]],[[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1351.5],[1361.5],[1381],[1396.5999999999999],[1410.5999999999999],[1429],[1441.8],[1459.4000000000001],[1465.4000000000001],[null],[1503.0999999999999],[null],[1526],[null],[1546.5999999999999],[null],[1564.2],[null],[1593.9000000000001],[null],[1595.7],[null],[1616.5],[null],[1625.5999999999999],[null],[1646.4000000000001],[null],[1656.5],[null],[1677.7],[null],[1696.4000000000001],[null],[1713.9000000000001],[null],[1741.8],[null],[1770.5999999999999],[null],[1817.0999999999999],[null],[1815.5999999999999],[null],[1843.5],[null],[1859.3],[null],[1881.5999999999999]],[[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1016],[1017.5],[1035.5],[1051.9000000000001],[1055.0999999999999],[1063.5999999999999],[1072.3],[1096.9000000000001],[1093.5999999999999],[null],[1116.4000000000001],[null],[1140.3],[null],[1151.3],[null],[1161.7],[null],[1168.3],[null],[1179],[null],[1188.9000000000001],[null],[1202.0999999999999],[null],[1203.0999999999999],[null],[1218.8],[null],[1227.0999999999999],[null],[1243.5],[null],[1261.5999999999999],[null],[1275.5999999999999],[null],[1295.4000000000001],[null],[1343.4000000000001],[null],[1316.5999999999999],[null],[1343.5],[null],[1366.5999999999999],[null],[1382.3]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"$","axis_units":"","tooltip_units":"($)","table_units":"($)","axis_min":"500","axis_max":null,"tick_interval":null,"precision":"2","data_unit_prefix":"$","data_unit_suffix":"","reverse_axis":false}]

Source: Average Weekly Earnings, May 2022

Other estimates

Other sources of earnings level estimates provide extra detail beyond what is available from AWE.

Employee Earnings and Hours

Composition and distribution of weekly and hourly earnings, hours paid for and pay-setting methods.
Includes data by full-time/part-time status, industry, sex, state/territory, public/private sector, age, casual status and occupation.
Employee Earnings and Hours is sourced from the two-yearly Survey of Employee Earnings and Hours.

Employee earnings

Includes earnings data by sex, state/territory, occupation, industry and education qualifications.
Employee earnings is sourced from the annual Characteristics of Employment Labour Force supplementary survey.

Personal Income in Australia

Personal income estimates (including employee earnings) by age, sex, state/territory, and over 2,200 regions.
Personal Income in Australia is sourced from the Linked Employer-Employee Dataset (LEED), which is based on tax data.

See the Earnings page of the Labour Statistics Concepts, Sources and Methods for more information on earnings concepts and measures.

Average earnings guide

Learn about our average earnings measures and how to use them

Released

7/11/2022

Overview

Average earnings can be represented as either a median or mean value.

While the mean is the most commonly understood measure of average, median measures are most representative of an "average" employee’s earnings as earnings data has a positively skewed distribution. The mean is higher than the median value because of a small number of people with very high earnings.

The Earnings guide includes information about other earnings measures.

Median weekly earnings

Most representative measure of the "average" level of earnings.
Provides the "middle" earnings figure, where half of people earn more than the median earnings value and half earn less than the median earnings value.
Employee Earnings and Hours, Australia includes median earnings by age, method of setting pay, employment status, occupation and industry.
Employee earnings includes median earnings by education qualification, main and secondary jobs, and working arrangements.
Personal Income in Australia (and Jobs in Australia) includes median income estimates for small geographic areas.

Mean (average) weekly earnings

The arithmetic average, calculated by dividing total earnings by the total number of people (or employees).
Often just referred to as average earnings, however they do not represent the earnings of the "average" person.
Average Weekly Earnings, Australia includes mean weekly earnings by industry, state/territory and public/private sector.
Employee Earnings and Hours, Australia includes average hourly total earnings for non-managerial employees in addition to a range of weekly estimates.
- Managerial employees (more likely to have high earnings) are excluded so these EEH estimates are closer to median measures than estimates from AWE.
Employee earnings includes mean earnings by education qualification, main and secondary jobs, and working arrangements.
Personal Income in Australia includes average income estimates for small geographic areas.

Earnings distributions

Give more detail than average measures by providing information on the range of earnings of the population.
Refer to the level of earnings at which a certain percentage of people earn more or less than that value.
For example, 50% of people earn more and 50% earn less than the median (midpoint) value, 75% earn more than the 1st (of 4) quartile and 25% earn less, 10% earn more than the 9th (of ten) decile and 90% earn less.
Employee Earnings and Hours, Australia provides robust estimates by full-time/part-time status, method of setting pay, occupation and industry.
Employee earnings provides earnings distribution data by education qualification, working arrangements and main job.
Personal Income in Australia provides income distributions for small geographic areas.

Distribution of weekly total cash earnings (Original)

Visualisation showing distribution of weekly total cash earnings with mean and median points overlaid.

The image is a graph showing the distribution of weekly total cash earnings. Starting with under $200, the number of employees in each earning bracket increases, then peaks at $1000 to under $1200 bracket. After this, the number of employees drops off significantly, before showing an increase for employees earning $4000 and over. The graph also shows median weekly total cash earnings is $1209 and mean weekly total cash earnings is $1394.

Source: Microdata and TableBuilder: Employee Earnings and Hours, Australia, May 2021

Wages change and growth guide

Learn about our wages change (or growth) measures and how to use them

Released

7/11/2022

Overview

Wages change (or growth) over time can be measured in a few different ways:

wage inflation - changes in the price of wages and salaries unaffected by compositional factors
change in the earning levels of employees
change in total wages paid in the economy.

We have earnings estimates available to measure wages change in each of these ways. The right data source for you will depend on the purpose of your analysis.

The Earnings guide includes information about other earnings measures.

Wage inflation

The quarterly Wage Price Index (WPI) measures change in the price of wages and salaries (similar to earnings) in the Australian labour market over time. In a similar way to the Consumer Price Index (CPI), it follows changes in the hourly rate paid to a fixed group (or “basket”) of jobs.

The WPI measures pure price change by removing the effect of compositional factors including the quality or quantity of work performed or the composition of the workforce. This separates it from other ABS earnings measures.

WPI movements do not reflect changes in:

tasks or responsibilities
hours worked
job holder (for example junior rate, completion of trade certificate)
location where work is performed.

Use the WPI if your focus is wage inflation or inflationary pressures associated with wages and salaries. Estimates are available by industry, state/territory and public/private sector.

Annual wage inflation (Original)
	Total hourly rates of pay including bonuses (%)
Mar-20	2.0
Jun-20	1.7
Sep-20	1.0
Dec-20	1.3
Mar-21	1.8
Jun-21	1.9
Sep-21	2.1
Dec-21	2.8
Mar-22	2.4
Jun-22	3.1

Annual wage inflation (Original)

["","Total hourly rates of pay including bonuses"]

[["Mar-20","Jun-20","Sep-20","Dec-20","Mar-21","Jun-21","Sep-21","Dec-21","Mar-22","Jun-22"],[[2],[1.7],[1],[1.3],[1.8],[1.8999999999999999],[2.1000000000000001],[2.7999999999999998],[2.3999999999999999],[3.1000000000000001]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"Annual change (%)","axis_units":"","tooltip_units":"(%)","table_units":"(%)","axis_min":"0","axis_max":"4","tick_interval":"1","precision":"1","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

Source: Wage Price Index, June qtr 2022

Change in earnings levels

Average Weekly Earnings (AWE) measures average gross (pre-tax) weekly earnings paid to employees and is collected every six months. Movements in average weekly earnings levels provide an alternative view of wages growth to the WPI by reflecting real-world changes in both the level of earnings per employee and in the composition of employment.

This can include changes in the:

proportion of full-time, part-time, casual and junior employees
distribution of occupations within and across industries
distribution of employment between industries.

The Average Weekly Earnings, Australia methodology page includes information you will need to draw the correct conclusions about wages growth from this data.

Use AWE if your focus is on understanding changes in the level of average earnings over time, which reflects the influence of real-world changes in the composition of the labour market.

Average weekly total cash earnings (Original)
	Six monthly change (%)	Average weekly total cash earnings ($)
May-19	1.1	1,275.60
Nov-19	1.6	1,295.40
May-20	3.7	1,343.40
Nov-20	-2.0	1,316.60
May-21	2.0	1,343.50
Nov-21	1.7	1,366.60
May-22	1.1	1,382.30

Average weekly total cash earnings (Original)

["","Six monthly change","Average weekly total cash earnings"]

[["May-19","Nov-19","May-20","Nov-20","May-21","Nov-21","May-22"],[[1.1000000000000001],[1.6000000000000001],[3.7000000000000002],[-2],[2],[1.7],[1.1000000000000001]],[[1275.5999999999999],[1295.4000000000001],[1343.4000000000001],[1316.5999999999999],[1343.5],[1366.5999999999999],[1382.3]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"Average weekly total earnings ($)","axis_units":"","tooltip_units":"($)","table_units":"($)","axis_min":"0","axis_max":"1500","tick_interval":"500","precision":"2","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false},{"value":"1","axis_id":"1","axis_title":"Six monthly change (%)","axis_units":"","tooltip_units":"(%)","table_units":"(%)","axis_min":"-3","axis_max":"6","tick_interval":"3","precision":"1","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

Source: Average Weekly Earnings, May 2022

Change in total wages paid

The total wages index measures changes in the volume of wages and salaries paid each week. It is part of the Weekly Payroll Jobs and Wages in Australia estimates, which are released monthly. These estimates allow us to see week-to-week changes in the labour market for the first time.

Total wages index movements are more affected by compositional changes than other earnings measures, as they reflect changes in aggregate wages and salaries paid rather than average earnings per job or employee. Changes in the number of jobs being worked affect the total wages index. It is also affected by:

changes in hours worked
cyclical payments including bonuses, commissions or lump sum payment of leave loading
payment of penalty rates for public holidays
irregular payments including overtime, ad hoc or one off payments.

Use the total wages index if your focus is short term changes and understanding the effects on total (rather than job or employee) earnings.

Wages change including compositional factors (Original)
	WPJW - Total wages index (Index points)	AWE - All employee average weekly total earnings ($)
04-Jan-20	90.6
11-Jan-20	92.4
18-Jan-20	94
25-Jan-20	94.8
01-Feb-20	95.2
08-Feb-20	97.6
15-Feb-20	98
22-Feb-20	98.4
29-Feb-20	98.6
07-Mar-20	99.4
14-Mar-20	100
21-Mar-20	99.6
28-Mar-20	98.1
04-Apr-20	96.3
11-Apr-20	93.6
18-Apr-20	93.8
25-Apr-20	94.3
02-May-20	94.9
09-May-20	93.8
16-May-20	93.2	1,304.70
23-May-20	92.8
30-May-20	94
06-Jun-20	96.2
13-Jun-20	96.6
20-Jun-20	97.3
27-Jun-20	97.3
04-Jul-20	99.1
11-Jul-20	96.9
18-Jul-20	96.6
25-Jul-20	96.4
01-Aug-20	97.2
08-Aug-20	97.6
15-Aug-20	97.1
22-Aug-20	97.2
29-Aug-20	97.4
05-Sep-20	100
12-Sep-20	101.4
19-Sep-20	101.9
26-Sep-20	101.2
03-Oct-20	98.9
10-Oct-20	97.5
17-Oct-20	98.2
24-Oct-20	97.7
31-Oct-20	97.8
07-Nov-20	99
14-Nov-20	99.8
21-Nov-20	99.9	1,280.30
28-Nov-20	101.7
05-Dec-20	103.8
12-Dec-20	104.1
19-Dec-20	104.1
26-Dec-20	98.2
02-Jan-21	94.7
09-Jan-21	95.4
16-Jan-21	97.6
23-Jan-21	98
30-Jan-21	98.5
06-Feb-21	102.1
13-Feb-21	103.2
20-Feb-21	103.2
27-Feb-21	103.8
06-Mar-21	104.5
13-Mar-21	104.7
20-Mar-21	104.6
27-Mar-21	104.9
03-Apr-21	104.4
10-Apr-21	102.8
17-Apr-21	103
24-Apr-21	102.7
01-May-21	103.2
08-May-21	102.4
15-May-21	102.8
22-May-21	102.8	1,305.80
29-May-21	102.4
05-Jun-21	103.8
12-Jun-21	104.9
19-Jun-21	105.9
26-Jun-21	107.2
03-Jul-21	107.3
10-Jul-21	105.2
17-Jul-21	104.4
24-Jul-21	103
31-Jul-21	103.2
07-Aug-21	103.6
14-Aug-21	103.6
21-Aug-21	103.4
28-Aug-21	103.2
04-Sep-21	107.1
11-Sep-21	109.1
18-Sep-21	109.8
25-Sep-21	108.1
02-Oct-21	106.1
09-Oct-21	104.5
16-Oct-21	105.8
23-Oct-21	106.5
30-Oct-21	107.4
06-Nov-21	108.9
13-Nov-21	108.8
20-Nov-21	109.7	1,328.90
27-Nov-21	111.4
04-Dec-21	114
11-Dec-21	114.2
18-Dec-21	114.6
25-Dec-21	108.9
01-Jan-22	104
08-Jan-22	104
15-Jan-22	106
22-Jan-22	107
29-Jan-22	107.2
05-Feb-22	110.4
12-Feb-22	111.3
19-Feb-22	111.3
26-Feb-22	110.7
05-Mar-22	111.7
12-Mar-22	112.6
19-Mar-22	113.3
26-Mar-22	113.4
02-Apr-22	113.1
09-Apr-22	111.9
16-Apr-22	111.4
23-Apr-22	110.2
30-Apr-22	110.8
07-May-22	110.2
14-May-22	109.9
21-May-22	109.9	1,344.70
28-May-22	110.3
04-Jun-22	111.2
11-Jun-22	112.8
18-Jun-22	114.4
25-Jun-22	116.5
02-Jul-22	116.1
09-Jul-22	114.3
16-Jul-22	113.6
23-Jul-22	113.6
30-Jul-22	113.6
06-Aug-22	113
13-Aug-22	113
20-Aug-22	113.3
27-Aug-22	113.6
03-Sep-22	114.8
10-Sep-22	115.9
17-Sep-22	116.4

Wages change including compositional factors (Original)

["","WPJW - Total wages index","AWE - All employee average weekly total earnings"]

[["04-Jan-20","11-Jan-20","18-Jan-20","25-Jan-20","01-Feb-20","08-Feb-20","15-Feb-20","22-Feb-20","29-Feb-20","07-Mar-20","14-Mar-20","21-Mar-20","28-Mar-20","04-Apr-20","11-Apr-20","18-Apr-20","25-Apr-20","02-May-20","09-May-20","16-May-20","23-May-20","30-May-20","06-Jun-20","13-Jun-20","20-Jun-20","27-Jun-20","04-Jul-20","11-Jul-20","18-Jul-20","25-Jul-20","01-Aug-20","08-Aug-20","15-Aug-20","22-Aug-20","29-Aug-20","05-Sep-20","12-Sep-20","19-Sep-20","26-Sep-20","03-Oct-20","10-Oct-20","17-Oct-20","24-Oct-20","31-Oct-20","07-Nov-20","14-Nov-20","21-Nov-20","28-Nov-20","05-Dec-20","12-Dec-20","19-Dec-20","26-Dec-20","02-Jan-21","09-Jan-21","16-Jan-21","23-Jan-21","30-Jan-21","06-Feb-21","13-Feb-21","20-Feb-21","27-Feb-21","06-Mar-21","13-Mar-21","20-Mar-21","27-Mar-21","03-Apr-21","10-Apr-21","17-Apr-21","24-Apr-21","01-May-21","08-May-21","15-May-21","22-May-21","29-May-21","05-Jun-21","12-Jun-21","19-Jun-21","26-Jun-21","03-Jul-21","10-Jul-21","17-Jul-21","24-Jul-21","31-Jul-21","07-Aug-21","14-Aug-21","21-Aug-21","28-Aug-21","04-Sep-21","11-Sep-21","18-Sep-21","25-Sep-21","02-Oct-21","09-Oct-21","16-Oct-21","23-Oct-21","30-Oct-21","06-Nov-21","13-Nov-21","20-Nov-21","27-Nov-21","04-Dec-21","11-Dec-21","18-Dec-21","25-Dec-21","01-Jan-22","08-Jan-22","15-Jan-22","22-Jan-22","29-Jan-22","05-Feb-22","12-Feb-22","19-Feb-22","26-Feb-22","05-Mar-22","12-Mar-22","19-Mar-22","26-Mar-22","02-Apr-22","09-Apr-22","16-Apr-22","23-Apr-22","30-Apr-22","07-May-22","14-May-22","21-May-22","28-May-22","04-Jun-22","11-Jun-22","18-Jun-22","25-Jun-22","02-Jul-22","09-Jul-22","16-Jul-22","23-Jul-22","30-Jul-22","06-Aug-22","13-Aug-22","20-Aug-22","27-Aug-22","03-Sep-22","10-Sep-22","17-Sep-22"],[[90.599999999999994],[92.400000000000006],[94],[94.799999999999997],[95.200000000000003],[97.599999999999994],[98],[98.400000000000006],[98.599999999999994],[99.400000000000006],[100],[99.599999999999994],[98.099999999999994],[96.299999999999997],[93.599999999999994],[93.799999999999997],[94.299999999999997],[94.900000000000006],[93.799999999999997],[93.200000000000003],[92.799999999999997],[94],[96.200000000000003],[96.599999999999994],[97.299999999999997],[97.299999999999997],[99.099999999999994],[96.900000000000006],[96.599999999999994],[96.400000000000006],[97.200000000000003],[97.599999999999994],[97.099999999999994],[97.200000000000003],[97.400000000000006],[100],[101.40000000000001],[101.90000000000001],[101.2],[98.900000000000006],[97.5],[98.200000000000003],[97.700000000000003],[97.799999999999997],[99],[99.799999999999997],[99.900000000000006],[101.7],[103.8],[104.09999999999999],[104.09999999999999],[98.200000000000003],[94.700000000000003],[95.400000000000006],[97.599999999999994],[98],[98.5],[102.09999999999999],[103.2],[103.2],[103.8],[104.5],[104.7],[104.59999999999999],[104.90000000000001],[104.40000000000001],[102.8],[103],[102.7],[103.2],[102.40000000000001],[102.8],[102.8],[102.40000000000001],[103.8],[104.90000000000001],[105.90000000000001],[107.2],[107.3],[105.2],[104.40000000000001],[103],[103.2],[103.59999999999999],[103.59999999999999],[103.40000000000001],[103.2],[107.09999999999999],[109.09999999999999],[109.8],[108.09999999999999],[106.09999999999999],[104.5],[105.8],[106.5],[107.40000000000001],[108.90000000000001],[108.8],[109.7],[111.40000000000001],[114],[114.2],[114.59999999999999],[108.90000000000001],[104],[104],[106],[107],[107.2],[110.40000000000001],[111.3],[111.3],[110.7],[111.7],[112.59999999999999],[113.3],[113.40000000000001],[113.09999999999999],[111.90000000000001],[111.40000000000001],[110.2],[110.8],[110.2],[109.90000000000001],[109.90000000000001],[110.3],[111.2],[112.8],[114.40000000000001],[116.5],[116.09999999999999],[114.3],[113.59999999999999],[113.59999999999999],[113.59999999999999],[113],[113],[113.3],[113.59999999999999],[114.8],[115.90000000000001],[116.40000000000001]],[[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1304.7],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1280.3],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1305.8],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1328.9000000000001],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[1344.7],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null],[null]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"$","axis_units":"","tooltip_units":"($)","table_units":"($)","axis_min":"1150","axis_max":"1350","tick_interval":null,"precision":"2","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false},{"value":"1","axis_id":"1","axis_title":"Index points","axis_units":"","tooltip_units":"(Index points)","table_units":"(Index points)","axis_min":"80","axis_max":"120","tick_interval":null,"precision":"-1","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

Source: Average Weekly Earnings, May 2022 and Weekly Payroll Jobs and Wages in Australia, week ending 17 September 2022

Other total earnings measures

The Labour Account Payment quadrant measures costs to employers in employing labour and the income received by people for providing their labour. The Aggregate earnings guide includes more information about total earnings measures.

Weekly and hourly earnings guide

Learn about our weekly and hourly earnings measures and how to use them

Released

7/11/2022

Overview

Earnings measures can be derived for many time periods. Weekly and hourly measures are common across our various earnings sources. Measures with shorter time periods provide a common period for comparison of earnings levels, whereas measures with longer time periods are more affected by compositional or structural factors.

The Earnings guide includes information about other earnings measures.

Hourly earnings

Provide a common period for comparing earnings, removing the effect of differences in total hours worked.
For example, we can compare how much full-time and part-time workers receive for the same amount of time worked (that is, for each hour they worked).
Employee Earnings and Hours, Australia (EEH) is the best source for hourly earnings data.
EEH includes data for non-managerial employees by sex, occupation, industry, state/territory, public/private sector, and employer size.
Employee earnings includes hourly earnings data by education qualification, main and secondary jobs, and working arrangements every year.

Weekly earnings

Influenced by changes in the overall composition of the workforce over time.
Affected by changes in hours worked and work patterns, as well as changes in the level of earnings of employees.
Average Weekly Earnings, Australia includes weekly earnings estimates by industry, state/territory, and public/private sector every six months
Employee Earnings and Hours, Australia provides estimates by age, sex, occupation and employer size every two years.
Employee earnings includes estimates by education qualification, main and secondary jobs, and working arrangements every year.

Non-managerial employees, average cash earnings (Original)
	Weekly ($)	Hourly ($)
Full-time employees	1,766.50	45.00
Part-time employees	733.80	36.00

Non-managerial employees, average cash earnings (Original)

["","Weekly","Hourly"]

[["Full-time employees","Part-time employees"],[[1766.5],[733.79999999999995]],[[45],[36]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"Hourly ($)","axis_units":"","tooltip_units":"($)","table_units":"($)","axis_min":null,"axis_max":null,"tick_interval":null,"precision":"2","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false},{"value":"1","axis_id":"1","axis_title":"Weekly ($)","axis_units":"","tooltip_units":"($)","table_units":"($)","axis_min":null,"axis_max":null,"tick_interval":"400","precision":"2","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

Source: Employee Earnings and Hours, May 2021

Aggregate earnings guide

Learn about our total earnings and labour income measures and how to use them

Released

7/11/2022

Overview

Aggregate (total) earnings and labour income measures provide an economy wide view of the cost of labour. They measure total costs paid by employers and incomes received by people in return for working.

The Earnings guide includes information about other earnings measures.

Compensation of employees

Measures total wages and salaries and employers' social contributions (such as superannuation) paid by employers to employees.
Australian National Accounts, National Income, Expenditure and Product provides state/territory, public/private sector and industry estimates every quarter.
Australian National Accounts: State Account provides estimates for each state/territory by industry each year.
Labour Account, Australia provides quarterly industry estimates and annual industry sub-division estimates.

Total labour income

Measures the income received by people for working.
Total labour income includes compensation of employees (above) and labour income from self-employment.
Labour Account, Australia provides quarterly industry estimates and annual industry sub-division estimates.

Total labour income (Seasonally adjusted)
	Total labour income ($m)
Sep-19	259,725.5
Dec-19	261,984.2
Mar-20	263,481.9
Jun-20	262,795.9
Sep-20	268,699.3
Dec-20	270,863.4
Mar-21	273,951.2
Jun-21	277,231.3
Sep-21	279,526.2
Dec-21	286,903.6
Mar-22	290,947.8
Jun-22	300,609.8

Total labour income (Seasonally adjusted)

["","Total labour income"]

[["Sep-19","Dec-19","Mar-20","Jun-20","Sep-20","Dec-20","Mar-21","Jun-21","Sep-21","Dec-21","Mar-22","Jun-22"],[[259725.47279999999],[261984.15969999999],[263481.89270000003],[262795.91230000003],[268699.2977],[270863.43959999998],[273951.15950000001],[277231.27600000001],[279526.22340000002],[286903.63559999998],[290947.76049999997],[300609.7977]]]

[]

[{"axis_id":"0","tick_interval":"","axis_min":"","axis_max":"","axis_title":"","precision":-1,"axis_units":"","tooltip_units":"","table_units":"","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

[{"value":"0","axis_id":"0","axis_title":"Millions ($)","axis_units":"","tooltip_units":"($)","table_units":"($m)","axis_min":"250000","axis_max":null,"tick_interval":null,"precision":"1","data_unit_prefix":"","data_unit_suffix":"","reverse_axis":false}]

Source: Labour Account, Australia, June 2022

Other measures

Business Indicators, Australia provides quarterly estimates of employee wages and salaries for the private sector by industry.
Employment and Earnings, Public Sector, Australia provides annual estimates of cash wages and salaries for the public sector by level of government, state/territory, and industry.
Personal Income in Australia (and Jobs in Australia) provides total personal income estimates for more than 2,200 geographic areas.
Labour Costs, Australia provides estimates of main labour costs paid by employers, such as employee earnings and payroll tax.