Jobs in Australia methodology

This is not the latest release View the latest release
Reference period
2014-15 to 2018-19

Jobs in Australia provides annual information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. 

A job is a relationship between an employed person and their employing enterprise. This can be a relationship between an employee and an employer or between an owner-manager of an unincorporated enterprise and their own enterprise. Owner-managers of incorporated enterprises have not been identified in the underlying data and are included within the employee population. A person can have several jobs throughout the year with one or many employers, some of which may be held concurrently with others.

How data are collected

The Jobs in Australia statistics are compiled from the Linked Employer-Employee Dataset (LEED), which is built using Australian Tax Office (ATO) administrative data linked to ABS Business Longitudinal Analytical Data Environment (BLADE).


The LEED is a rich dataset that includes about 18 to 20 million job records each financial year since 2011-12 and contains over 150 million individual records over the period 2011-12 to 2018-19. 

The LEED covers all persons who either:

  • submitted an individual tax return (ITR); or
  • had a Pay As You Go (PAYG) payment summary issued by an employer and then remitted to the ATO.

Employees who did not submit a tax return and have not provided their Tax File Number to their employer will not appear in the LEED. Owner-managers of unincorporated enterprises (OMUEs) who did not submit an ITR are also excluded.

Data sources

The LEED incorporates:

  • employer level data that include the ABS’s BLADE data and the ABS Business Register data supplied by the Registrar of Australian Business Register (ABR) to the ABS under A New Tax System (Australian Business Number) Act 1999 - which requires that such data is only used for the purpose of carrying out functions of the ABS; and 
  • person level ITR data, job level PAYG payment summary data and Client Register (CR) data supplied by the ATO to the ABS under the Taxation Administration Act 1953 - which requires that such data is only used for the purpose of administering the Census and Statistics Act 1905.

The data limitations or weaknesses outlined below are in the context of using the data for statistical purposes, and not related to the ability of the data to support the ATO's core operational requirements.

The ABS acknowledges the continuing support of the ATO in compiling these statistics. 

How data are processed

Integration method

LEED links jobs to employers; hence employed persons are linked to employers via the jobs they hold.

Before the linkage takes place, an input job level file is created largely based on the PAYG payment summary file. This file is also enhanced with job records derived using ITR information, to cover jobs without payment summary information, such as OMUE jobs. Data quality of this file is also enhanced using occupation information from ITR, and the best available age, sex, and geographic information between the PAYG, ITR and CR data.      

Jobs are then integrated with the employer in one of two methods. The method used is dependent on which part of the business population on the ABS Business Register the employer is grouped into.

  • Non-profiled population (businesses with a simple structure): a deterministic approach using the Australian Business Number (ABN).
  • Profiled population (businesses with a complex structure): a more detailed approach to linking is used, detailed below. 

Where an employer is part of the profiled population, the relevant jobs are assigned to the type of activity units based on a logistic regression model developed using 2016 Census data. The model references independent variables common to both Census and personal income tax data, including sex, age, occupation, and region of usual residence. These are used to predict the industry of employment, which conceptually aligns to a type of activity unit. 

Where an employee has multiple job relationships with the same reporting ABN in an enterprise group, each job relationship is assigned to the same type of activity unit.

Based on the model, each job record is assigned a probability of being in any of the type of activity units present in the employing enterprise group. Iterative random assignment is undertaken using these probabilities until employment benchmarks are met. Benchmarks are based on Quarterly Business Indicators Survey (QBIS) data where unit is in scope. Otherwise, BLADE employment levels are substituted where possible, or no benchmarking is done.

The above process is applied to link the different input datasets for each financial year. Records have not been integrated across years and therefore, the LEED is a cross-sectional database and is not longitudinal.

ABS data integration practices comply with the High-Level Principles for Data Integration Involving Commonwealth Data for Statistical and Research Purposes. For further information see - Keeping integrated data safe

Component datasets

The LEED consists of three cross-sectional files: a person file, a job file and an employer file. The LEED is not longitudinal and each file is for a single financial year

The person file

The business file

The jobs file

Privacy and confidentiality

Legislative requirements to ensure privacy and secrecy of these data have been followed. In accordance with the Census and Statistics Act 1905, results have been confidentialised to ensure they are not likely to enable identification of a particular person or organisation. All personal information is handled in accordance with the Australian Privacy Principles contained in the Privacy Act 1988.

All personal income tax statistics were analysed in de-identified form with no home address or date of birth included in LEED input files. Addresses were coded to the Australian Statistical Geography Standard and date of birth was converted to an age at 30 June of the reference year prior to data provision.

To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts.

How data are released

The LEED has two releases, Jobs in Australia and Personal Income in Australia.  Both have detailed tables in data downloadable format.  LEED data are also available in the TableBuilder format in Microdata: Jobs in Australia. The TableBuilder product contains a broad range of data items covered in both Jobs in Australia and Personal Income in Australia. It is a rich source of information for data users interested in making customised analysis tables.

The Jobs in Australia release provides aggregate data for Australia, states and territories, and over 2,200 regions, as classified in the Australian Statistical Geography Standard (ASGS), including at the Statstical Area 4 (SA4), Statistical Area 3 (SA3), Statistical Area 2 (SA2), Local Government Area (LGA) and Greater Capital City Statistical Area (GCCSA) levels. It covers a wide variety of estimates including number of jobs, number of employed persons, median employment income per job, number of OMUEs etc. The estimates are also presented by person, job, or employer characteristics such as age, sex, occupation, industry, employment size, etc. 

The current release includes data for the five financial years between 2014-15 and 2018-19, while information for earlier years back to 2011-12 can be found in previous releases.

Data limitations

Jobs in Australia is 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 income tax item should be used to describe income standards, and in some cases the item can be a partial conceptual match. 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 aggregate series.
  • Measurement error. This is likely to be present in both person and employer information used. Most measurement error is unable to be determined or corrected; however, coherence with other similar statistics demonstrates that the error amount is small, and this has a low impact on aggregate series.
  • Incomplete information. Sometimes, Individual Tax Returns are not lodged, or not all items (e.g. occupation) are completed. The ABS advises caution when interpreting data subject to high rates of missing information.

Quality note for selected variables

Adjusted employee income per job

Employment income



Main job

Multiple job holders and concurrent jobs


Status in employment

Differences to other labour statistics

There are differences between Jobs in Australia statistics and other labour statistics produced by the ABS; these are due to differences in underlying concepts, scope, and methods.

Jobs in Australia provides annual insights into job relationships that have occurred during the reference financial year, at both the national level and for over 2,200 regions. It is a source of regional estimates on the number of jobs, number of job holders and employment income level.

The ABS receives ATO data approximately 16 months after the end of the financial year. This lag, in addition to the processing time required to construct LEED and produce the statistics for Jobs in Australia, currently results in a delay of approximately two years between the end of the reference financial year and the release.

Weekly Payroll Jobs and Wages

Labour Force

Labour Account

For more information on the range of different data sources, see ABS Labour Statistics: A broad range of information.


Show all


ABRAustralian Business Register
ABSBRAustralian Bureau of Statistics Business Register
ANZSCOAustralian and New Zealand Standard Classification of Occupations
ANZSICAustralian and New Zealand Standard Industrial Classification
ASGSAustralian Statistical Geography Standard
ATOAustralian Taxation Office
BLADEBusiness Longitudinal Analytical Data Environment
GCCSAGreater Capital City Statistical Area
ITRIndividual Tax Return
LEEDLinked Employer-Employee Dataset
LFSLabour Force Survey
OMUEOwner manager of unincorporated enterprise
PAYGPay as you go
PITPersonal Income Tax
SA2Statistical Area Level 2
SA3Statistical Area Level 3
SA4Statistical Area Level 4
SIHSurvey of Income and Housing
SESCAStandard Economic Sector Classifications of Australia
STPSingle Touch Payroll
TAUType of Activity Unit
TOLOType of Legal Organisation
TFNTax File Number
WPJWWeekly Payroll Jobs and Wages in Australia


Back to top of the page