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