# Barriers and Incentives to Labour Force Participation, Australia methodology

Latest release
Reference period
2020-21 financial year

## Introduction

The two-yearly Barriers and Incentives to Labour Force Participation (B&I) Survey was first conducted in 2004-05, as a topic on the Multipurpose Household Survey (MPHS). The MPHS is conducted by the Australian Bureau of Statistics (ABS) as a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics.

The Barriers and Incentives to Labour Force Participation survey provides a range of information about the people who are not participating, or not participating fully, in the labour force and the factors that influence them to join or leave the labour force.

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.

## Reference period

The reference period for the Barriers and Incentives to Labour Force Participation survey is the 2020-21 financial year.

## 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)

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 Barriers and Incentives to Labour Force Participation 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 .

Data files

### 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. The sample size of the 2020-21 B&I survey (after taking into account the scope, coverage and sub-sampling exclusions) was approximately 13,000.

## 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 B&I benchmarks were based on a 12-month average of the LFS estimates for the June to July financial year, as reported in the May 2022 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 May 2022).

## 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: Barriers and Incentives to Labour Force Participation.

### Survey content

The survey is designed to provide a large range of statistics on labour market dynamics 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
• Income and Housing
• Partner's participation and income
• Wanting to work or more hours
• Available for work or more hours
• Looking for work or more hours
• Difficulties finding work
• Barriers to participation
• Incentives to participate

For more details, refer to the Data item list

Data files

## Conceptual framework

To understand potential barriers to increased participation in the labour force, there are three groups who are of particular interest:

• unemployed;
• persons not in the labour force;
• employed persons who usually worked less than 35 hours.

These groups can be further broken down into:

• those who wanted a paid job or would prefer to work more hours
• those who were available (either in the previous week or within four weeks) to start a job or work more hours
• those who were looking (actively or passively) for a paid job or more hours.

This conceptual framework is represented diagrammatically in the 2018-19 issue of Barriers and Incentives to Labour Force Participation.

In 2020-21, the conceptual framework was revised to include the concept of job attachment, where there is a group of people who are not classified as employed but have a job that they about to start or can return to when available. This is consistent with the approach used in Participation, Job Search and Mobility.

In general, people who have a job to start or return to are excluded from populations of interest:

• The unemployed population of interest is now "Unemployed looking for work" where people who had already obtained a job and are waiting to start are excluded from the population (also known as future starters).
• The persons not in the labour force population of interest now excludes people who had a job to start or return to. This includes people who had obtained a job and were waiting to start, and also people who were away from work without pay for four weeks or longer and were not classified as employed or unemployed.

It is also worth noting that in cases where people who were reported as "permanently unable to work" in the LFS, but later indicated that they wanted a paid job during the personal interview of the MPHS, that these people are classified as potential supply in the population "PNILF who wanted a paid job."

## 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

#### Non-sampling error

Non-sampling error may occur in any collection, whether it is based on a sample or a full count such as a census. Sources of non-sampling error include non-response, errors in reporting by respondents or recording of answers by interviewers and errors in coding and processing data. Every effort is made to reduce non-sampling error by careful design and testing of questionnaires, training and supervision of interviewers, and extensive editing and quality control procedures at all stages of data processing.

#### Sampling error

Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if the total population (as defined by the scope of the survey) had been included in the survey. One measure of the sampling error 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 persons 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 surveyed, 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.

$$\large{RSE\%=(\frac{SE}{estimate})\times100}$$

RSEs for estimates have been calculated using the Jackknife method of variance estimation. This involves the calculation of 30 'replicate' estimates based on 30 different sub-samples of the obtained sample. The variability of estimates obtained from these subsamples is used to estimate the sample variability surrounding the main estimate. RSEs for median estimates have been calculated using the Woodruff method.

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.

Only estimates (numbers or percentages) with RSEs less than 25% are considered sufficiently reliable for most analytical 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.

Another measure is the Margin of Error (MOE), which shows the largest possible difference that could be between the estimate due to sampling error and what would have been produced had all persons been included in the survey with a given level of confidence. It is useful for understanding and comparing the accuracy of proportion estimates.

Where provided, MOEs for estimates are calculated at the 95% confidence level. At this level, there are 19 chances in 20 that the estimate will differ from the population value by less than the provided MOE. The 95% MOE is obtained by multiplying the SE by 1.96.

$$\large{MOE=SE\times1.96}$$

#### Calculation of standard error

Standard errors can be calculated using the estimates (counts or percentages) and the corresponding RSEs. Since the RSE is obtained by expressing the standard error as a percentage of the estimate, recalculating the standard error is obtained by multiplying the estimate by the RSE.

#### Proportions and percentages

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 RSE of a proportion is given below. This formula is only valid when x is a subset of y

$$\large{RSE(\frac{x}{y})\approx\sqrt{[RSE(x)]^2-[RSE(y)]^2}}$$

#### Differences

The difference between two survey estimates (counts or percentages) can also be calculated from published estimates. Such an estimate is 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

$$\large {SE(x-y)\approx\sqrt{[SE(x)]^2+[SE(y)]^2}}$$

While this formula will only be exact for differences between separate and uncorrelated characteristics or sub populations, it provides a good approximation for the differences likely to be of interest in this publication.

#### Significance testing

A statistical significance test for a comparison between estimates can be performed to determine whether it is likely that there is a difference between the corresponding population characteristics. The SE of the difference between two corresponding estimates (x and y) can be calculated using the formula shown above in the Differences section. This SE is then used to calculate the following test statistic

$$\LARGE{(\frac{x-y}{SE(x-y)})}$$

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 real difference between the populations with respect to that characteristic.

### Rounding

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

## Glossary

### Show all

#### Actively looking for work

Actively looking for work includes:

• written, telephoned or applied to an employer for work
• had an interview with an employer for work
• checked or registered with an employment agency
• advertised or tendered for work, and
• contacted friends or relatives in order to obtain work.

#### Available to start work

Refers to people who were available to start work or more hours either in the reference week, or in the four weeks subsequent to the interview.

#### Available to start work with more hours

Employed people who usually worked 0–34 hours per week in all jobs and were available to start work with more hours in the reference week or in the four weeks subsequent to the interview.

#### Barrier to participation

A "barrier to participation" is based on collating all of the reasons why people are not participating in the labour force and include:

• Reasons why not wanting to work or work more hours
• Reasons why not available to work or work more hours
• Reasons why not looking for work or more hours
• Difficulties looking for work
• Reasons why left or lost last job

For example, when childcare is regarded as a barrier to participation, it could be because caring for children was reported as a reason why not wanting to work, or a reason why not available for work, or a reason why not looking for work, etc.

#### Currently studying

People who were undertaking study for a trade certificate, diploma, degree or any other educational qualification at the time of the survey.

#### Did not prefer to work more hours

People who said 'no' or 'don't know' when asked 'would you prefer to work more hours than you usually work?'.

#### Did not want a paid job

People who were not classified as employed or unemployed who answered 'no' or 'don't know' when asked if they would like a paid job.

#### Duration of current main job/last job

Length of time worked in current main job or last job if not employed.

#### ​​​​​​​Employed persons

All people aged 15 years and over 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
• 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
• away from work as a standard work or shift arrangement
• on strike or locked out
• on workers' compensation and expected to return to their job; or
• were owner managers who had a job, business or farm, but were not at work.

#### Employees

An employed person who does not operate their own incorporated or unincorporated enterprise. An employee works for a public or private employer and receives remuneration in wages, salary, on a commission basis with a retainer, tips, piece-rates, or payment in kind.

#### 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.

#### Family

Two or more people, one of whom is at least 15 years of age, who are related by blood, marriage (registered or de facto), adoption, step or fostering; and who are usually resident in the same household. The basis of a family is formed by identifying the presence of a couple relationship, lone parent-child relationship or other blood relationship. Some households will, therefore, contain more than one family.

#### Full-time workers (usual)

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

#### Future starters

People who were not employed during the reference week, were waiting to start a 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.

People who were waiting to start a job already obtained. Also includes people who had a job but, up to the end of the reference week, had been away from work without pay for four weeks or longer and had not been actively looking for work.

People who are not in the labour force or are unemployed and have previously worked in the last 20 years

#### Industry

An industry is a group of businesses or organisations that undertake similar economic activities to produce goods and/or services. In this publication, industry refers to ANZSIC Division as classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (Revision 2.0) (cat. no. 1292.0).

#### 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.

#### Level of highest non-school qualification

A person's level of highest non-school qualification is the highest qualification a person has attained in any area of formal study other than school study. It is categorised according to the Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0) Level of education classification.

#### Looking for work with more hours

Looked for work with more hours at some time during the four weeks up to the end of the reference week.

#### Long-term health conditions

A person with a long-term health condition is anyone who reported one or more of the following condtions:

• Arthritis or osteoporosis
• Asthma
• Cancer
• Diabetes
• Heart disease
• Mental health condition
• Long-term injury
• Other long-term condition

#### Main job

The job in which most hours were usually worked.

#### Not employed

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

#### Occupation

An occupation is 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 refers to Major Group and Sub-Major Group as defined by 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 (also known as a limited liability company). These people are sometimes classified as employees. They can work alone or in a business with employees.

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

People who operate their own unincorporated enterprise, that is, a business entity in which the owner and the business are legally inseparable, so that the owner is liable for any business debts that are incurred. Includes those engaged independently in a trade or profession. They can work alone or in a business with employees.

#### 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.

#### Preferred to work more hours

Employed people who usually work less than 35 hours a week and would prefer to work more hours than they usually work.

#### Reference week

The week preceding the week in which the interview was conducted.

#### Relationship in household

The relationship of people who live in the same household.

#### Status of employment

Classifies employed persons according to the following categories on the basis of their current job:

• Employees
• with paid leave entitlements
• without paid leave entitlements
• Owner managers with employees (employer)
• Owner manager of incorporated enterprise with employees
• Owner manager of unincorporated enterprise with employees
• Owner managers without employees (own account worker)
• Owner manager of incorporated enterprise without employees
• Owner manager of unincorporated enterprise without employees
• Contributing family workers.

#### Time since last job

The elapsed time since ceasing last job.

#### 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.

#### Unpaid activities

Includes caring for own children or other people's children, including grandchildren. Also includes caring for the elderly or someone with a long-term illness or disability, or undertaking unpaid voluntary work. Respondents were asked whether they had undertaken any of these activities in the last four weeks.

#### Usual number of hours

Usual hours of work refers to a typical period rather than the hours worked in a specified reference period. The concept of usual hours applies both to people at work and to people temporarily absent from work, and is defined as the hours worked during a typical week or day. Actual hours worked (for a specific reference period) may differ from usual hours worked due to illness, vacation, strike, overtime work, a change of job, or similar reasons. It is possible for a person to usually not work any hours in a typical week (usually work 0 hours) but be classified as employed based on the hours worked during the specific reference period.

#### Wanted a paid job

People who are not in the labour force and would like a paid job of any kind. Includes people who answered 'Maybe/it depends'.

#### Wanted more hours

See 'Preferred to work more hours'.

## History of changes

### Show all

#### 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.