Retirement and Retirement Intentions, Australia methodology

Latest release
Reference period
2022-23 financial year


The two-yearly Retirement and Retirement Intentions (RaRI) survey was first conducted in 2004-05, as part of the Multi-Purpose Household Survey (MPHS). Similar data on retirement and retirement intentions were previously collected on an irregular basis between 1980 and 1997 in surveys conducted as supplementary to the Labour Force Survey (LFS), and also in the 2007 Survey of Employment Arrangements, Retirement and Superannuation (SEARS).

Data are used to examine changes in retirement trends over time, factors which influence retirement, and the income arrangements made by retirees and potential retirees for their retirement.

Additional information about survey design, scope, coverage and population benchmarks relevant to the monthly LFS, which also applies to supplementary surveys, can be found in Labour Force, Australia, Methodology.

Descriptions of the underlying concepts and structure of Australia’s labour force statistics, and the sources and methods used in compiling the estimates, are presented in Labour Statistics: Concepts, Sources and Methods.

Scope and coverage

The scope of the LFS is the civilian population aged 15 years and over, excluding:

  • Members of the permanent defence forces
  • Certain diplomatic personnel of overseas governments
  • Overseas residents in Australia 
  • Members of non-Australian defence forces (and their dependants) stationed in Australia.

The following additional exclusions apply to the MPHS:

  • People aged 15-17 years. The MPHS is collected via personal interview and restricted to persons aged 18 years and over 
  • Very remote parts of Australia and Aboriginal and Torres Strait Islander communities
  • People living in non-private households such as hotels, university residences, students at boarding schools, patients in hospitals, inmates of prisons and residents of other institutions (e.g. retirement homes, homes for people with disabilities).

People aged under 45 years are also excluded as out of scope for the Retirement and Retirement Intentions survey.

In the LFS, coverage rules are applied, which aim to ensure that each person is associated with only one dwelling, and hence has only one chance of selection in the survey. See Labour Force, Australia, Methodology for more details.

Collection Method

The Retirement and Retirement Intentions topic is collected within the Multi-Purpose Household Survey (MPHS), a supplement to the monthly Labour Force Survey (LFS).

Each month, a sample of households are selected for the MPHS from the responding households who are in the last of their 8 months in the LFS. In these households, after the LFS had been fully completed for each person, a usual resident aged 18 years and over is selected at random to complete the questionnaire.

Data are collected via personal interviews by either telephone or in person at selected households.

For more details, see the MPHS chapter in Labour Statistics: Concepts, Sources and Methods .


Sample Design

This survey is based on the new sample introduced into LFS in July 2018. The new sample design has adopted the use of the Address Register as the sampling frame for unit selection, and the sampling fractions for selection probabilities within each state have been updated to reflect the most recent population distribution based on results from the 2016 Census of Population and Housing. As with each regular sample design, the impacts on the data are expected to be minimal. For more information, see the Information Paper: Labour Force Survey Sample Design.

Sample Size

The sample is pooled from data collected each month across the whole financial year. In January 2023, the ABS increased the sample selections for the remaining 6 months of the year. The sample size of the 2022-23 RaRI survey (after taking into account the scope, coverage and sub-sampling exclusions) was approximately 11,000.

Weighting and estimation

Population benchmarks

Survey weights are calibrated against population benchmarks to ensure that the survey estimates conform to the independently estimated distribution of the population, rather than the distribution within the sample itself.

When calibrating the weights, the survey sample is grouped into categories based on the following characteristics:

  • State or territory
  • Capital city or rest of state
  • Sex
  • Age
  • Employed full-time, part-time, unemployed or not in the labour force.

The Labour Force Survey estimates are calculated in such a way as to sum to the independent estimates of the civilian population aged 15 years and over (population benchmarks). These population benchmarks are updated quarterly based on Estimated Resident Population (ERP) data. See Labour Force, Australia, Methodology for more information.

From August 2015, Labour Force estimates have been compiled using population benchmarks based on the most recently available release of ERP data, continually revised on a quarterly basis.

The RaRI benchmarks were based on a 12-month average of the LFS estimates for the June to July financial year, as reported in the November 2023 issue of Labour Force, Australia. This approach is used to remove the seasonality from the employed, unemployed and not in the labour force benchmarks and to improve coherence between the two publications.

Estimates from previous surveys back to 2014-15 have also been revised using this method, with benchmarks based on the same population series (as at November 2023). These estimates were calibrated to population benchmarks based on revisions to ERP that incorporated the results of the 2021 Census (introduced to LFS in the November 2023 issue).

Comparability with LFS

Due to differences in the scope and sample size of this MPHS and that of the monthly LFS, the estimates procedure may lead to some small variations between labour force estimates from this survey and those from the LFS.

Survey Output

A number of spreadsheets are available from Data downloads. They present tables of estimates and their corresponding relative standard errors (RSEs).

For users who wish to undertake more detailed analysis, the underlying microdata is available in DataLab and TableBuilder. For more details, refer to Microdata and TableBuilder: Retirement and Retirement Intentions.

Survey content

The survey is designed to provide a large range of statistics on retirees and retirement plans across the following conceptual groups:

  • Geography
  • Demographics
  • Cultural diversity
  • Families and children
  • Education and qualifications
  • Health and disability
  • Unpaid work and care
  • Participation and underemployment
  • Characteristics of employment
  • Characteristics of main job
  • Characteristics of last job
  • Wanting to work
  • Looking for work
  • Current income and housing
  • Partner's participation and income
  • Retirement status
  • Income at retirement
  • Current living costs in retirement
  • Superannuation
  • Factors influencing retirement decisions
  • Retirement intentions
  • Transition to retirement plans
  • Expected income at retirement
  • Returning to work after retirement

For more details, refer to the Data item list

Data item list

Accuracy and quality

Reliability of estimates

As the estimates are based on information obtained from occupants of a sample of households, they are subject to sampling variability. That is, they may differ from those estimates that would have been produced if all households had been included in the survey or a different sample was selected. Two types of error are possible in an estimate based on a sample survey - sampling error and non-sampling error.

  • sampling error is the difference between the published estimate and the value that would have been produced if all dwellings had been included in the survey.
  • non-sampling errors are inaccuracies that occur because of imperfections in reporting by respondents and interviewers, and errors made in coding and processing data. These inaccuracies may occur in any enumeration, whether it be a full count or a sample. Every effort is made to reduce the non-sampling error to a minimum by careful design of questionnaires, intensive training and effective processing procedures.

Some of the estimates contained in the tables have a relative standard error (RSE) of 50 per cent or greater. These estimates are marked as unreliable for general use. Estimates with an RSE of between 25 and 50 per cent are also marked and should be used with caution.

More on reliability of estimates


As estimates have been rounded, discrepancies may occur between sums of the component items and totals.


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History of changes


  • Estimates were rebenchmarked to a 12-month average of population estimates from the Labour Force Survey (as at Nov 2023).

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