Jobs in Australia methodology

Latest release
Reference period
2021-22 financial year

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 Taxation Office (ATO) administrative data linked to ABS Business Longitudinal Analysis Data Environment (BLADE).

Scope

The LEED is a rich dataset that includes about 18 to 22 million job records each financial year since 2011-12 and contains over 210 million individual records over the period 2011-12 to 2021-22. 

The LEED covers all people who either:

  • submitted an individual tax return (ITR); or
  • had an Income Statement (previously 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:

  • person level ITR data, job level Income Statement 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; and
  • 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.

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. 

Data on Migrants

The Migrant data used in LEED are sourced from the Person Level Integrated Dataset (PLIDA).

The Migrant data are a suite of administrative datasets (client information, visa grants, and visa applications) from the Department of Home Affairs. These data pertain to permanent migrants and temporary entrants to Australia, as well as Australian citizens who have travelled into or out of Australia. This data represents the most complete picture of migration and migrants available, providing information on a person’s visa information, citizenship status, and their movements into and out of Australia. 

The scope of the migrant data in this release includes:

  • Permanent migrants with an arrival date between 1 January 2000 and 30 June 2022;
  • Permanent migrants with an unknown arrival date and a visa granted between 1 January 2000 and 30 June 2022; 
  • Temporary visa holders with a visa granted between 1 January 2000 and 30 June 2022; and 
  • Permanent migrants who have become Australian citizens during this period.

Estimates produced during this reference period use 2023 Migrant data. Previous iterations were produced using the 2021 Migrant data.

How data are processed

Integration method

LEED links jobs to employers and 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 Income Statement file. This file is also enhanced with job records derived using ITR information, to cover jobs without Income Statement 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 Income Statement, ITR and Client Register (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 type of activity units (TAUs) based on a logistic regression model developed using 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 each 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. BLADE employment levels are substituted where QBIS data is not available, otherwise 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

Person file

Jobs file

Employer file

Integrating data for migrants

From 2022, migrant data were added to the LEED. Personal identifiers were used to first integrate the migrant data with the ATO's Client Register data and it is then integrated into LEED. This enables more detailed analysis of labour market and fiscal contributions of migrants to the economy, allowing policy makers and researchers to better understand the migrant experience and their economic contribution to Australia. 

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 Jobs and Income of Employed Persons. 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 nearly 2,500 regions, as classified in the Australian Statistical Geography Standard (ASGS) Edition 3, including at the Statistical Area Level 4 (SA4), Statistical Area Level 3 (SA3), Statistical Area Level 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. 

Summary tables in the current release present data for the five financial years between 2017-18 and 2021-22. Summary statistics for the full time series from 2011-12 to 2021-22 are presented in Table 15 in the Data download tab.

Data from LEED are also available in TableBuilder format Jobs and Income of Employed Persons. 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.

Differences between Jobs in Australia and Personal Income in Australia

Jobs in Australia (JIA) and Personal Income in Australia (PIA) present similar data on earners and income from the Linked Employee-Employer Dataset (LEED). However, there are a few small but important differences between JIA and PIA that should be taken into consideration when comparing them. 

The number of earners will be different. In PIA, anyone who earns income, whether from employment, superannuation, investment etc. is counted as an earner. This also includes individuals who only receive an employment termination payment without any regular income. In JIA, earners are restricted to those who receive payment from employment, which is either working as an employee (including as an owner manager of incorporated enterprise) or an owner-manager of unincorporated enterprise. JIA does not include people who only receive an employment termination payment. 

The median incomes reported in JIA are reported on a 'per job' and 'employed person' basis. However, people may work more than one job, either at the same time or throughout the financial year. For PIA, the income is reported on a 'per person' basis which includes all income types, not only employment income, received in that financial year.

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 (ITR) 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

Geography

Industry

Main job

Multiple job holders and concurrent jobs

Occupation

Status in employment

History of changes

A timeline of methodological changes are listed below for easy reference.

By release date

Glossary

Show all

Abbreviations

 
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
WPJWeekly Payroll Jobs

 

Back to top of the page