Latest release

# Retirement and Retirement Intentions, Australia methodology

Reference period
2018-19 financial year
Released
8/05/2020
Next release Unknown
First release

## Explanatory notes

### ​​​​​​​Introduction

The two-yearly Retirement and Retirement Intentions (R&RI) survey was first conducted in 2004-05, as part of the Multi-Purpose Household Survey. 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.

Descriptions of the underlying concepts and structure of labour statistics, and the sources and methods used in compiling these estimates, are presented in Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001).

### Reference period

The reference period for the Retirement and Retirement Intentions survey is the 2018-19 financial year.

### Scope and coverage

The scope of this survey is people aged 45 years and over, excluding:

• members of the permanent defence forces
• certain diplomatic personnel of overseas governments, customarily excluded from census and estimated population counts
• members of non-Australian defence forces (and their dependants)
• overseas residents in Australia

The following exclusions also apply:

• people living in remote parts of Australia (including 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)

Coverage rules are applied which aim to ensure that each person is associated with only one household and hence has only one chance of selection in the survey. See the Explanatory Notes of Labour Force, Australia (cat. no. 6202.0) 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).

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 (cat. no. 6102.0.55.001).

### Sample design

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 is selected at random to complete the R&RI questionnaire.

For details on the sample design of the LFS, see the Explanatory notes in Labour Force, Australia (cat. no. 6202.0).

### Sample size

The sample size for the 2018-19 R&RI survey (after taking into account scope, coverage and sub-sampling exclusions) is approximately 8,000 people.

### Weighting, benchmarking and estimation

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 R&RI survey benchmarks were based on a 12 month average of the population estimates for the financial year July 2018 to June 2019, as reported in the December 2019 issue of Labour Force, Australia (cat. no. 6202.0). 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 2004-05 have also been revised using this method, with benchmarks based on the same population series (as at December 2019). The revised timeseries is available in Table 2 of this publication (in the Data downloads section). The format of Table 2 has been modified to accommodate extending the series back to the November 1997 survey (which has also been rebenchmarked).

### Survey output

Data on the retirement status and retirement intentions of persons aged 45 years and over, and includes:

• Socio-demographic information
• For people who have retired – information about age at retirement, sources of income, and superannuation
• For people who intend to retire – information about details of current job, retirement intentions, expected sources of income at retirement, superannuation, and transition to retirement plans

See the Retirement and Retirement Intentions data item list for more details (in the Data downloads section).

Data are also available in TableBuilder, see Microdata: Barriers and Incentives to Labour Force Participation, Retirement and Retirement Intentions (6238.0.55.001).

### ​​​​​​​Comparability with monthly LFS estimates

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

### Reliability of estimates

Estimates are subject to sampling and non-sampling errors:

• Sampling errors are the difference between the published estimate and the value that would have been produced if all households had been included in the survey. For more information see the technical note on Data Quality.
• Non-sampling errors are inaccuracies that occur because of, for example, 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 minimise non-sampling error by careful design of questionnaires, intensive training and supervision of interviewers and effective processing procedures

## Appendix - ABS labour statistics - a broad range of information

### Show all

Labour statistics are some of Australia’s most important economic and social statistics. Put simply, they provide information about people and their participation in the labour market, their success in finding employment, their earnings and other benefits, their type of work, their working hours and conditions.

Given the importance of high quality information on the Australian labour market, the ABS produces a broad range of labour statistics, drawn from a wide range of different sources. Some of these sources are very well known, such as the monthly Labour Force Survey, but others are less well known – particularly new collections like the annual Jobs in Australia and the quarterly Labour Account.

A simple way of visualising this is to consider that ABS labour statistics are drawn from four key “pillars” of data, each of which is a bit different, but which provide complementary insights into the labour market.

Each of these pillars – the two traditional sources of household and business surveys, and the two more recent pillars of administrative data based statistics and Labour Account - provides important and unique insights to enable Australians to better understand their labour market.

#### Figure 1 - The four pillars of ABS labour statistics

A simple way of visualising the key ABS labour statistics is under four pillars of data. Each of which is a bit different, but which provide complementary insights into the labour market. Each of these pillars – the two traditional sources of household and business surveys, and the two more recent pillars of administrative data based statistics and the Labour Account. These all provide important and unique insights to enable Australians to better understand their labour market.

#### Household surveys

A household survey approaches individual households to complete questions about their individual, family or household circumstances.

The key household survey that provides vital information about Australia’s labour market is the Labour Force Survey, and its related supplementary surveys.

#### Business surveys

Business surveys collect a broad range of information from businesses, including their performance, financial position or about jobs and employees.

Key business surveys with a labour market focus include Job Vacancies, Employee Earnings and Hours, Average Weekly Earnings and the Wage Price Index.

#### Administrative data

Administrative data refers to information maintained by governments and other entities that is made available to the ABS for statistical purposes. It includes data used for registrations, transactions and record keeping, usually during the delivery of a service.

The ABS publishes employment information from the Linked Employer Employee Dataset (LEED), using Australian Tax Office (ATO) information and ABS data. As a result, the LEED includes more than 100 million tax records over six consecutive years between 2011-12 and 2016-17, and provides information for over 2,200 different regions based on a person’s usual residence.

The ABS also publishes Weekly Payroll Jobs and Wages data derived from Single Touch Payroll (STP), which is provided by the ATO from businesses with STP-enabled payroll or accounting software. STP data includes both business and job level tax information and superannuation information. The data are combined with other administrative data from the Australian taxation system and provides indicative information on employees, including changes in paid employee jobs, changes in total wages paid, and changes in average weekly wages per job.

#### Labour Account

The Labour Account brings together data from separate administrative, business, and household sources, adjusting and confronting the various sources until a coherent picture of the labour market is established. It provides data on the number of employed persons, the number of jobs, hours worked and income earned for each industry. It provides the best labour market estimates for the 19 industry divisions each quarter and 86 industries annually.

#### Which data source should you be using?

Often there is only a single statistical data source on the ABS website that will include the information that you are after. However, for many labour market topics it is often the case that the ABS produces multiple statistics, each drawn from a different data source to enable different types of analysis. They provide important, complementary economic and social insights into the labour market, which is large, complex and dynamic.

It is therefore important to be guided by what you are looking to understand about the labour market. Is it to understand a topic where:

• demographic characteristics are important or it may related to an activity outside of employment? Household surveys are often useful for this.
• specific employer or payroll information is important? Business surveys are often useful for this.
• detailed sub-population or geographic information is important? This is usually best sourced from administrative data, or the five-yearly Census.
• a comprehensive ‘best estimate’ of key labour market indicators (based on reconciled information from all of the available data sources) is important? The Labour Account Is designed to provide this.

For example, in seeking to understand how many people are employed in jobs in Australia, you could use statistics from:

• Monthly Labour Force – which provides a timely indicator on changes in employment, unemployment and underemployment, including analysis by personal characteristics such as sex, age, occupation and employment status.
• The quarterly Labour Account – which is the best source of headline information on employment by industry. It provides an estimate of the number of jobs, hours worked, and associated labour income.
• The annual Jobs in Australia – which provides granular information on all the job relationship for more than 2,200 different regions across Australia. This rich dataset is based on more than 100 million individual records which allow for micro-data analysis of the Australian labour market.

Another common example is seeking to understand changes in wages over time, where you could use statistics from:

• Quarterly Wage Price Index - which measures changes in the price of labour in the Australian labour market. In a similar manner to the CPI, the WPI follows price changes in a fixed "basket" of jobs and is therefore not affected by changes in quality and quantity of work..
• The twice yearly Average Weekly Earnings - which provides data on average wages by industry, which provides insights into compositional changes in earnings over time.
• The two yearly Employee Earnings and Hours - which provides detailed data on methods of setting pay, hours paid for and detailed distributional earnings information.
• The annual Characteristics of Employment – which provides earnings by detailed socio-demographic and other characteristics.
• The quarterly Compensation of Employees measure in the National Accounts and quarterly measure of labour income in the Labour Account – which provide aggregate earnings measures.

#### Labour data sources

Below is a list of some of the key labour statistics collections, organised into the pillars. In addition to improving the visibility of all of the available labour statistics, the ABS is also exploring how to better organise labour market information around themes and topics. This is being actively explored as part of the design of its new website, which will be launched in June 2020.

#### Labour Account

Labour Account Australia (cat. no. 6150.0.55.003) - Quarterly

The ABS continues to strengthen the suite of labour market statistics, to ensure that Australia can effectively understand how its labour market, economy and society are changing over time and make informed decisions.

## Technical note - data quality

### Show all

#### Introduction

Since the estimates published in this publication 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. One measure of the likely difference is given by the standard error (SE), which indicates the extent to which an estimate might have varied by chance because only a sample of households (or occupants) was included.

There are about two chances in three (67%) that a sample estimate will differ by less than one SE from the number that would have been obtained if all households had been included, and about 19 chances in 20 (95%) that the difference will be less than two SEs.

Another measure of the likely difference is the relative standard error (RSE), which is obtained by expressing the SE as a percentage of the estimate.

$$\large R S E \% = (SE/estimate) \times 100$$

RSEs for Retirement and Retirement Intentions estimates have been calculated using the Jackknife method of variance estimation. This process involves the calculation of 30 'replicate' estimates based on 30 different subsamples of the original sample. The variability of estimates obtained from these subsamples is used to estimate the sample variability surrounding the main estimate.

The Excel spreadsheets in the Data downloads section contain all the tables produced for this release and the calculated RSEs for each of the estimates. The RSEs for estimates other than medians have been calculated using the Jackknife method, and RSEs for the medians have been calculated using the Woodruff method.

In the tables in this publication, only estimates (numbers, percentages, means and medians) with RSEs less than 25% are considered sufficiently reliable for most purposes. However, estimates with larger RSEs have been included. Estimates with an RSE in the range 25% to 50% should be used with caution while estimates with RSEs greater than 50% are considered too unreliable for general use. All cells in the Excel spreadsheets with RSEs greater than 25% contain a comment indicating the size of the RSE. These cells can be identified by a red indicator in the corner of the cell. The comment appears when the mouse pointer hovers over the cell.

#### Calculation of standard error and relative standard error

RSEs are routinely presented as the measure of sampling error in this publication and related products. SEs can be calculated using the estimates (counts or means) and the corresponding RSEs.

An example of the calculation of the SE from an RSE follows. An estimate of retired people is 118,300 and the RSE for this estimate is 12.0%. The SE is:

SE of estimate

$$= (RSE / 100) \times estimate$$

$$= 0.12 \times 118,300$$

$$= 14,200$$ (rounded to the nearest 100)

Therefore, there are about two chances in three that the value that would have been produced if all households had been included in the survey will fall within the range 104,100 to 132,500 and about 19 chances in 20 that the value will fall within the range 89,900 to 146,700. This example is illustrated in the following diagram.

The published estimate is 118,300. There are two chances in three that the true value is in the range of 104,100 to 132,500, and 19 chances in 20 that the true value is in the range of 89,900 to 146,700.

#### Proportions and percentage

Proportions and percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. A formula to approximate the RSEs of proportions not provided in the spreadsheets is given below. This formula is only valid when x is a subset of y.

$$\large R S E\left(\frac{x}{y}\right)=\sqrt{[R S E(x)]^{2}-[R S E(y)]^{2}}$$

Considering an estimate of 1,943,800 people retired from labour force, 898,300 or 46.2% were aged less than 55 years at retirement. The RSE of 898,300 is 3.9% and the RSE for 1,943,800 is 2.0%. Applying the above formula, the RSE for the proportion of people who retired aged less than 55 years is:

$$\large R S E=\sqrt{(3.9)^{2}-(2.0)^{2}}=3.3 \%$$

Therefore, the SE for the proportion who retired from the labour force aged less than 55 years is 1.5 percentage points (= (46.2/100) x 3.3). Therefore, there are about two chances in three that the proportion of people who retired from the labour force aged less than 55 years is between 44.7% and 47.7%, and 19 chances in 20 that the proportion is within the range 43.2% to 49.2%.

#### Sums or differences between estimates

Published estimates may also be used to calculate the sum of, or difference between, two survey estimates (of numbers, means or percentages) where these are not provided in the spreadsheets. Such estimates are also subject to sampling error.

The sampling error of the difference between two estimates depends on their SEs and the relationship (correlation) between them. An approximate SE of the difference between two estimates (x–y) may be calculated by the following formula:

$$\large S E(x-y)=\sqrt{[R S E(x)]^{2}+[R S E(y)]^{2}}$$

The sampling error of the sum of two estimates is calculated in a similar way. An approximate SE of the sum of two estimates (x+y) may be calculated by the following formula:

$$\large S E(x+y)=\sqrt{[R S E(x)]^{2}+[R S E(y)]^{2}}$$

An example follows. The estimated number of people aged 55–59 who retired from the labour force aged less than 55 years is 118,300 and the SE is 14,200. The estimate of people aged 60–64 who retired from the labour force aged less than 55 years is 124,700, the RSE is 7.9% and the SE is 9,900 (rounded to nearest 100). The estimate of people aged 55–64 who retired from the labour force aged less than 55 years is:

118,300 + 124,700 = 243,000

The SE of the estimate of people aged 55–64 who retired from the labour force aged less than 55 years is:

$$\large S E=\sqrt{\left(14,200)^{2}+(9,900)^{2}\right.}=17,300$$

Therefore, there are about two chances in three that the value that would have been produced if all households had been included in the survey will fall within the range 225,700 to 260,300 and about 19 chances in 20 that the value will fall within the range 208,400 to 277,600.

While these formulae will only be exact for sums of, or differences between, separate and uncorrelated characteristics or subpopulations, it is expected to provide a good approximation for all sums or differences likely to be of interest in this publication.

#### Significance testing

A statistical test for any comparisons between estimates can be performed to determine whether it is likely that there is a significant difference between two corresponding population characteristics. The standard error of the difference between two corresponding estimates (x and y) can be calculated using the formula detailed above. This standard error is then used to calculate the following test statistic:

$$\Large \left(\frac{x-y}{S E(x-y)}\right)$$

If the value of this test statistic is greater than 1.96 then there is evidence, with a 95% level of confidence, of a statistically significant difference in the two populations with respect to that characteristic. Otherwise, it cannot be stated with confidence that there is a difference between the populations with respect to that characteristic.

The imprecision due to sampling variability, which is measured by the SE, should not be confused with inaccuracies that may occur because of imperfections in reporting by respondents and recording by interviewers, and errors made in coding and processing data. Inaccuracies of this kind are referred to as non-sampling error, and they occur in any enumeration, whether it be a full count or sample. Every effort is made to reduce non-sampling error to a minimum by careful design of questionnaires, intensive training and supervision of interviewers, and efficient operating procedures.

## Glossary

### Show all

#### ​​​​​​​Employed

People who, during the reference week:

• worked for one hour or more for pay, profit, commission or payment in kind in a job or business, or on a farm (comprising employees, employers and own account workers); or
• worked for one hour or more without pay in a family business or on a farm (i.e. contributing family workers); or
• were employees who had a job but were not at work and were:

• away from work for less than four weeks up to the end of the reference week; or
• away from work for more than four weeks up to the end of the reference week and received pay for some or all of the four week period to the end of the reference week; or
• away from work as a standard work or shift arrangement; or
• on strike or locked out; or
• on workers' compensation and expected to return to their job; or

• were employers or own account workers who had a job, business or farm, but were not at work.

#### Employees

People who work for a public or private employer and receive remuneration in wages, salary, commission, tips, piece rates, or payment in kind.

People who operate their own incorporated enterprises can also be classified as employees, but are categorised in a separate category, see Owner managers of incorporated enterprises (OMIEs) and Status in employment

#### Employees with paid leave entitlements

Employees who were entitled to either paid sick leave or paid holiday leave (or both).

#### Employees without paid leave entitlements

Employees who were not entitled to, or did not know whether they were entitled to, paid sick and paid holiday leave.

#### Full-time workers (usual)

Employed people who usually work 35 hours or more a week in all jobs.

#### Fully self funded

Funded entirely from superannuation or any other income source, excluding any form of a government pension and/or allowance.

#### Government pension/allowance

Income support payments from government to people under social security and related government programs. Included are pensions and allowances received by aged, disabled, unemployed and sick people, families and children, veterans and their survivors, and study allowances for students. Payments made by overseas governments as well as the Australian government are included.

#### Industry

An industry relates to a group of businesses or organisations that perform similar sets of activities in terms of the production of goods and services. In this publication, industry is classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (Revision 2.0) (cat. no. 1292.0)

#### Intends to retire from the labour force

People who indicated that they intended to give up all labour force activity: working or looking for work.

#### Labour force

The civilian population can be split into two mutually exclusive groups: the labour force (employed and unemployed people) and not in the labour force.

#### Last job

Refers to the last job worked within the last 20 years.

#### Main job

The job in which most hours were usually worked.

#### Not employed

People who are either unemployed or not in the labour force.

#### Not retired from the labour force

People aged 45 years and over who have, at some time, worked and were not retired from the labour force. That is, either employed, unemployed or not in the labour force and intend to continue working or look for, or take up, work in the future.

#### Occupation

An occupation relates to a collection of jobs that are sufficiently similar in their title and tasks, skill level and skill specialisation which are grouped together for the purposes of classification. In this publication, occupation is classified according to ANZSCO – Australian and New Zealand Standard Classification of Occupations, 2013, Version 1.2 (cat. no. 1220.0).

#### Owner managers of incorporated enterprises (OMIEs)

People who work in their own incorporated enterprise, that is, a business entity which is registered as a separate legal entity to its members or owners (may also be known as a limited liability company).

An owner manager of an incorporated enterprise may or may not hire one or more employees in addition to themselves and/or other owners of that business. See Status in employment for more information.

#### Owner managers of unincorporated enterprises (OMUEs)

People who operate their own unincorporated enterprise or engage independently in a profession or trade.An owner manager of an unincorporated enterprise may or may not hire one or more employees in addition to themselves and/or other owners of that business. See Status in employment for more information.

#### Partially self funded

Funded by government pension and/or allowance and at least one other income source.

#### Part-time workers (usual)

Employed people who usually work less than 35 hours a week (in all jobs).

#### People in the labour force

People who were classified as being in the labour force, that is, either employed or unemployed.

#### People not in the labour force

People who were not classified as employed or unemployed.

#### Private health insurance

Includes hospital and/or extras cover only. People who reported ambulance cover only, or other health arrangements (eg Department of Veteran Affairs) are not considered to have private health insurance.

#### Relationship in household

The relationship of people who live in the same household.

#### Retired from the labour force

People who had previously worked and had retired from work or looking for work, and did not intend to look for, or take up, work in the future.

#### Status in employment

Status in employment is determined by an employed person's position in relation to their job, and is usually in respect of a person's main job if they hold more than one job.

Employed people are classified according to the reported relationship between the person and the enterprise for which they work, together with the legal status of the enterprise where this can be established. The groups include:

• Employees with leave entitlements
• Employees without leave entitlements
• Owner manager of incorporated enterprise (OMIEs) with employees;
• Owner manager of incorporated enterprise (OMIEs) without employees;
• Owner manager of unincorporated enterprise (OMUEs) with employees;
• Owner manager of unincorporated enterprise (OMUEs) without employees; and
• Contributing family workers.

#### Superannuation scheme

Any fund, association or organisation set up for the purpose of providing financial cover for members when they retire from work. For this survey, information about superannuation scheme membership was collected if the respondent indicated that contributions had been made to a scheme. Contributions could either have been made by the respondent, the respondent's partner or the respondent's employer.

#### Unemployed

People who were not employed during the reference week, and:

• had actively looked for full-time or part-time work at any time in the four weeks up to the end of the reference week and;
• were available for work in the reference week; or
• were waiting to start a new job within four weeks from the end of the reference week and could have started in the reference week if the job had been available then.

#### Usual number of hours

The number of hours usually worked in a week in all jobs.

## History of changes

### Show all

In order to provide a high degree of consistency and comparability over time, changes to survey methods, concepts, data item definitions, and frequency of collection are made as infrequently as possible. Changes affecting the LFS, which may also affect this survey, are outlined in Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001). Changes have included:

2018-19

• Estimates were benchmarked to a 12 month average of population estimates from the Labour Force Survey (as at December 2019). Estimates from previous surveys were also re-benchmarked using 12 month averages from the same LFS population series (as at December 2019) to improve coherence and consistency in the timeseries. The revised timeseries is available in Table 2 of this publications Data downloads section.
• The format of Table 2 has been modified to accommodate extending the series back to the November 1997 survey (which has also been rebenchmarked).
• The definition of retirement no longer requires people to have previously worked in a job for at least 2 weeks. The definition now only requires people to have previously worked in a job for any duration, including jobs that lasted for less than 2 weeks. This change was done to remain consistent with changes that were made to the LFS questionnaire in July 2014 regarding duration of job search.

2016-17

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• The reference period for benchmarks changed from March to December, which resulted in a minor impact on the comparison of level estimates between 2014-15 and 2016-17. This impact has since been removed in 2018-19, when both surveys were rebenchmarked to a 12 month average of the reference period instead of a single point in time.
• Enhancements were made to the previous job module, and new questions added on whether business owners have employees, and on housing tenure.
• Data now also released in TableBuilder.

2014-15

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• Questions on housing tenure, previous full-time job details and main source of current personal income were not collected.
• Addition of further age ranges ('65-69', '70-74', '75-79' and '80 and over') for questions on transitioning to retirement.
• To improve coherence with LFS estimates, survey benchmarking changed to include employed, unemployed and not in the labour force populations from the LFS alongside independent total population estimates from the Estimated Resident Population (ERP). Previously, benchmarks were based only on ERP. The reference period for the benchmarks were based on a single point in time (March 2015)

2012-13

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• New content added on satisfaction with current hours and current work arrangements, self-funded retirement, and transition to retirement plans.
• Additional content included for 2012-13 on self-assessed health status, private health insurance and housing tenure.
• Microdata not released.

2010-11

2008-09

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• In cases where people could not report an exact age they 'intend to permanently give up work', they were given the option of responding with an age range. These range responses were included in 'average age intends to retire' by substituting the low-point of the range into the calculation.
• New content added, including transition to retirement plans, sources of funds for meeting living costs, intentions for a healthy/active retirement, housing tenure, and self-assessed health.
• Additional content included for 2008-09 on self-assessed health status, private health insurance and housing tenure.
• Inclusion of 'all/main sources of funds for meeting living costs' data items.

April-July 2007

2006-07

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• Collected from the Multi-Purpose Household survey (MPHS) for the full financial year.
• Age intends to retire ‘don’t know’ category replaced with 'don't know age will retire' and 'don't know whether will retire'. People who don't know age will retire were included with the 'intends to retire' population, whereas people who reported 'did not know whether will retire' were excluded from this population. This change had the effect of slightly decreasing the number of people who intend to retire.
• An additional category of 'partner's income' was included in the following data items: 'all/main source of income at retirement', and 'all/main expected source of income at retirement' (in 2004-05 this was included in the 'other' or 'no income' category).

2004-05

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• Collected from the Multi-Purpose Household survey (MPHS) for August 2004 to June 2005.
• Retirement data expanded to include retirement from all kinds of work (full-time and part-time).

April-June 2000

November 1997

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• Collected from 6/8th of the Labour Force Survey.
• Retirement data expanded to include retirement from part-time work (excluding any part-time work of less than 10 hours per week).

November 1995

• Superannuation data collected in Superannuation, Australia (cat. no. 6319.0).
• Some limited retirement data for people aged under 75 years available.

November 1994

• Published in Retirement and Retirement Intentions, Australia (cat. no. 6238.0).
• Collected from 7/8th of the Labour Force Survey, previously collected from the whole sample.
• Includes people permanently unable to work. These people could be classed as retired if they had previously worked full-time at some point (before becoming permanently unable to work).

November 1993

October 1992

November 1991

November 1989

November 1988

November 1986

September 1984

September 1983

• Published as Persons Retired from Full-time Work, Australia (cat. no. 6238.0)
• Scope expanded to people aged 45 years and over.
• Retirement data expanded to include people who had retired more than 20 years ago.
• Retirement intentions data not collected.

September-November 1982

May 1980

• First retirement survey, published as Persons Aged 50-69 Years Ceasing Full-Time Work, Australia (cat. no. 6238.0).
• Retirement measured as retirement from full-time work.
• Scope originally limited to people aged 50 to 69 years.
• Age at retirement and other data items only asked when people had retired in the last 20 years.
• Excluded people permanently unable to work.

Feb 1974