Microdata and TableBuilder: Employee Earnings and Hours, Australia

The biennial Survey of Employee Earnings and Hours (EEH) provides detailed statistics on the composition and distribution of employee earnings, hours paid for and the methods used to set employee's pay. For the latest release of EEH see Employee Earnings and Hours, Australia. When performing analysis using EEH microdata, see the corresponding cycle's publication for summary results, methodology and other information.

You are able to access EEH data in: 

• TableBuilder - produce your own EEH tables and graphs
• DataLab - analyse detailed microdata

Microdata is currently available for the following cycles:

• Employee Earnings and Hours, Australia, May 2023
• Employee Earnings and Hours, Australia, May 2021
• Employee Earnings and Hours, Australia, May 2018
• Employee Earnings and Hours, Australia, May 2014
• Employee Earnings and Hours, Australia, May 2012

Compare data services to see what's right for you or Apply for access.

The Survey of Employee Earnings and Hours (EEH) microdata products include data items such as:

• Summation items
  • Weekly cash earnings (ordinary time, overtime, total)
  • Weekly hours paid for (ordinary time, overtime, total)
  • Hourly cash earnings (ordinary time, overtime, total)
• Employer characteristics
  • Employment size
  • Industry
  • Sector
  • State
• Employee characteristics
  • Age
  • Full-time / part-time status
  • Managerial status
  • Method of setting pay
  • Occupation
  • Rate of pay
  • Sex
  • Type of employee

The data items list in the Data downloads section is the definitive source of available data items and categorisations across EEH microdata products. Before purchasing your subscription, use the data items list to confirm the EEH microdata products fulfil the requirements for your research.

For general information relating to TableBuilder or instruction on how to use features of the TableBuilder product, please refer to TableBuilder. 

When tabulating data in TableBuilder, employee weights are automatically applied to the underlying sample counts for all summations. Weighting is the process of adjusting results from a sample survey to infer results for the total population. For more details on EEH methodology see Employee Earnings and Hours, Australia methodology.

The estimates in the EEH survey are based on information relating to a sample of employers and employees, rather than a full enumeration of the population. As a result, estimates are subject to sampling variability. Analysis undertaken on EEH estimates should incorporate appropriate quality measures which are available in the form of Relative Standard Errors (RSEs). The RSE is the expression of the standard error as a percentage of the estimate. See Confidentiality and relative standard error. 

Further information on the reliability of EEH estimates can be found in Employee Earnings and Hours, Australia methodology.

A confidentiality process called perturbation is applied to the data in TableBuilder to avoid releasing information that may lead to the identification of individuals, families, households, dwellings or businesses. See Confidentiality and relative standard error.

The Employee Earnings and Hours, Australia publication contains detailed data cubes, including distributional earnings statistics. For customised data requests that can't be created using TableBuilder, contact our Information Consultancy Service.

The DataLab environment allows real time access to detailed microdata files from the Survey of Employee Earnings and Hours (EEH) through a portal to a secure ABS environment. The level of detail provided within the DataLab exceeds that previously provided in the Expanded CURF and provides researchers greater access to the data.

For more information about the DataLab, see the DataLab page.

The DataLab is an interactive data analysis solution available for users to run advanced statistical analyses, for example, multiple regressions and structural equation modelling. The DataLab environment contains recent versions of R, SAS, Stata and Python analytical software. Controls in the DataLab have been put in place to protect the identification of individuals and organisations. All output from DataLab sessions must be cleared by an ABS officer before it can be released.

Users intending to purchase DataLab for the use of EEH microdata should ensure that the data and the associated level of detail they require is available in this product. The data item list for the microdata file, including relevant population and classification details, can be found in the Excel spreadsheet available from the Data downloads section. This should be used in conjunction with the survey information provided in the methodology for the chosen cycle of analysis.

In addition to the microdata files, DataLab also contains a README file which outlines some of the technical considerations to take into account when performing analysis. This includes preferred methods for calculating key statistics and considerations for data output requirements. It is highly recommended that this document is accessed prior to performing your analysis to ensure data and comparability limitations are understood.

EEH uses a two-stage selection approach which determines the final weight of each record. The first stage involves selecting a probability sample of employer units from the ABS Business Register. In the second stage, the selected employers are asked to select a random sample of employees from their payrolls using instructions provided by the ABS.

Care should be taken in the interpretation and use of employment estimates as EEH is not designed specifically to produce estimates on numbers of employees. Users are directed to Labour Force, Australia as the primary source for official ABS employment estimates.

Replicate weights will also be supplied within the DataLab microdata file. Replicate weights are used to calculate the standard error and relative standard error of the data using the 'Bootstrap' variance estimation method.

This release previously used catalogue number 6306.0.55.001.