Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation

Enables detailed analysis of the factors that influence people to work more

Barriers and Incentives to Labour Force Participation microdata in DataLab

Barriers and Incentives to Labour Force Participation microdata is now available in ABS DataLab, released as a supplementary file for the Longitudinal Labour Force (LLFS) microdata. All existing users of the LLFS microdata will automatically get access to the additional file (use of the file may require an updated project proposal) and new users can apply for access to both files.

A detailed data item list for the Barriers and Incentives to Labour Force Participation microdata is available in Data downloads

Related microdata from the annual Participation, Job Search and Mobility survey is also available for the period February 2015 to February 2022. For more information, refer to Microdata and TableBuilder: Participation, Job Search and Mobility.

Barriers and Incentives to Labour Force Participation in Tablebuilder

The release of the 2020-21 Barriers and Incentives to Labour Force Participation microdata into Tablebuilder has been delayed until later in the year due to the release of the 2021 Census data in Tablebuilder. The previously released and unrevised issues of Barriers and Incentives to Labour Force Participation, Retirement and Retirement Intentions in Tablebuilder for the periods 2010-11, 2016-17, and 2018-19 will remain available during this time.


This product provides a range of information about the release of microdata relating to 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.

Microdata are the most detailed information available from a survey and are generally the responses to individual questions on the questionnaire or data derived from two or more questions.

Barriers and Incentives to Labour Force Participation

The Barriers and Incentives to Labour Force Participation survey is collected monthly as a module of the Multi-Purpose Household Survey (MPHS) with the sample pooled across a financial year. The survey has been run every second year since 2004-05.

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

Microdata from the Barriers and Incentives survey is released in both Tablebuilder and DataLab for the following years:

TableBuilder is an online tool for creating tables and graphs from underlying microdata. Refer to TableBuilder for more information.

DataLab is the analysis solution for high-end users who want to undertake real time complex analysis of detailed microdata in a secure environment. Refer to DataLab for more information.

Accessing the data

You can use this data in:

  • TableBuilder - online tool for creating tables and graphs.
  • DataLab - analyse detailed microdata

Compare data services to see what's right for you. Information on how to apply for access can be found in TableBuilder and DataLab.

Further information about these products, and other information to assist users in understanding and accessing microdata in general, is available from the Microdata and TableBuilder Entry Page.

Further information

Further information about the survey and the microdata can be found in the various pages associated with this product, including: 


For further support in the use of this product, please contact Microdata Access Strategies via microdata.access@abs.gov.au.

Data available on request

Data collected in the survey but not included in DataLab or TableBuilder may be available from the ABS, on request, as statistics in tabulated form.

Subject to confidentiality and sampling variability constraints, special tabulations can be produced incorporating data items, populations and geographic areas selected to meet individual requirements. These are available, on request, on a fee for service basis. For more information, contact the ABS by visiting www.abs.gov.au/about/contact-us or email the the Labour Statistics Branch at labour.statistics@abs.gov.au.


The ABS Privacy Policy outlines how the ABS handles any personal information that you provide to us.

Data and file structure

Survey methodology

General information about the Barriers and Incentives to Labour Force Participation (B&I) survey, including summary results, are available in Barriers and Incentives to Labour Force Participation.

Detailed information about the survey including scope and coverage, survey design, data collection methodology, weighting, estimation and benchmarking, estimate reliability and a glossary can be accessed from the Methodology page of the publication.

Data items

The data items included in the B&I TableBuilder are grouped under broad headings and subheadings as shown in the image below. A complete data items list can be found in Data downloads.

File structure image

File structure

The underlying format of the B&I file is structured at a single person level. This person level contains general demographic information such as age, sex, country of birth and status of employment as well details about underemployment, weekly income and qualifications.

When tabulating data from TableBuilder, person weights are automatically applied to the underlying sample counts to provide the survey's population estimates.

Not applicable categories

Most data items included in the TableBuilder file include a 'Not applicable' category. This category generally represents the number of people who were not asked a particular question or the number of people excluded from the population for a data item when that item was derived (e.g. Hours usually worked in main job is not applicable for unemployed persons or persons not in the labour force).

Table populations

The population relevant to each data item should be kept in mind when extracting and analysing data. The actual population count for each data item is equal to the total cumulative frequency minus the 'Not applicable' category.

Generally, some populations can be 'filtered' using other relevant data items. For example, if the population of interest is 'Employed', any data item with that population (excluding the 'Not applicable' category) could be used.

Zero value cells

Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfied the parameters of a particular cell in a table were in the survey. This is despite there being people in the general population with those characteristics. This is an example of sampling variability which occurs with all sample surveys. Relative Standard Errors cannot be generated for zero cells.

Using TableBuilder

For general information relating to the TableBuilder or instructions on how to use features of the TableBuilder product, please refer to TableBuilder and the TableBuilder, User Guide.

More specific information applicable to Barriers and Incentives to Labour Force Participation (B&I) survey TableBuilder, which should enable users to understand, interpret and tabulate the data, is outlined below.

Confidentiality features in TableBuilder

In accordance with the Census and Statistics Act 1905, all the data in TableBuilder are subjected to a confidentiality process before release. This confidentiality process is undertaken to avoid releasing information that may allow the identification of particular individuals, families, households, dwellings or businesses.

Processes used in TableBuilder to confidentialise records include the following:

  • perturbation of data; and
  • table suppression

Perturbation effects

To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves small random adjustments 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.

The introduction of these random adjustments result in tables not adding up. As a result, randomly adjusted individual cells will be consistent across tables, but the totals in any table will not be the sum of the individual cell values. The size of the difference between summed cells and the relevant total will generally be very small.

Please be aware that the effects of perturbing the data may result in components being larger than their totals. This includes determining proportions.

Table suppression

Some tables generated within TableBuilder may contain a substantial proportion of very low counts within cells (excluding cells that have counts of zero). When this occurs, all values within the table are suppressed in order to preserve confidentiality. The following error message below is displayed (in red) at the bottom of the table when table suppression has occurred.

ERROR: The table has been suppressed as it is too sparse
ERROR: table cell values have been suppressed

Counting units and weights

Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each record. The weight is the value that indicates how many population units are represented by each sample unit.

To produce estimates for the in-scope population you must use a weight field in your tables. In TableBuilder they can be found under the 'Summation Options' category in the left hand pane under the applicable level. If you do not select a weight field, TableBuilder will apply 'Person weight' by default. This will give you estimates of the number of persons.

If you are estimating the number of persons with certain characteristics (e.g. 'Number of non–school qualifications completed') the weight listed under the category heading 'Person level weighting' must be used.

Selecting data items for cross-tabulation

The Person level contains a range of data items detailing the characteristics of respondents including demographic, education, labour force, participation, job search, and population variables.

Populations and data items

When adding a data item to a table, it should be noted that not all respondents to the survey may be associated with that data item. For example, the data item “Main difficulty in finding work” only applies to people who looked for work. The “Not applicable” category is used to indicate people who did not look for work as only those who looked for work were asked about any difficulties in finding work.

Similarly, if users want to add multiple data items to a table they should ensure that these data items are applicable to the same population group.

For more information about data items, users should refer to the Data Items List available from Data downloads.

Cross-tabulating data items on the same level

Cross-tabulating data from the person level with other data items from the same level will produce data about people. For example, cross-tabulating the geographic variable 'State or territory of usual residence' by the 'Hours usually worked in all jobs' produces a table showing the number of people in each region by the hours that they usually work each week in all jobs.

Multi-response data items

A number of the survey's data items allow respondents to report more than one response. These are referred to as 'multi–response data items'. An example of such a data item is pictured below. For this data item respondents can report all of the reasons why they were not available to start work or work more hours.

Using tablebuilder image

When a multi–response data item is tabulated, a person is counted against each response they have provided (e.g. a person who responds 'Pregnancy' and 'Home duties' will be counted once in both of these categories).

As a result, each person in the appropriate population is counted at least once, and some persons are counted multiple times. Therefore, the total for a multi–response data item will be less than or equal to the sum of its components.

For more information on definitions and concepts that apply to the data items in this file, please refer to Barriers and Incentives to Labour Force Participation and Labour Force.

Using DataLab

DataLab allows real time access to detailed microdata files through a portal to a secure ABS environment. Using detailed microdata in DataLab allows users to run advanced statistical analyses using recent analytical software.

For information about the data items available on the detailed microdata files, see the Data Item Lists in Data downloads.

About DataLab

Detailed microdata files in DataLab can be accessed on-site at ABS offices or in a secure virtual environment from your own computer. All unit record data remains in DataLab, and any analysis results or tables are checked by the ABS before being provided to users.

Refer to DataLab for more information, including prerequisites for DataLab access.

Barriers and Incentives to Labour Force Participation microdata in DataLab, 2014-15 to 2020-21

Barriers and Incentives to Labour Force Participation (B&I) microdata is now available in ABS DataLab, released as a supplementary file for the Longitudinal Labour Force (LLFS) microdata.  All existing users of the LLFS microdata will automatically get access to the additional file (use of the file may require an updated project proposal) and new users can apply for access to both files.

This release of Barriers and Incentives microdata features financial year data for the years 2014-15, 2016-17, 2018-19 and 2020-21.

Record identifiers

The record identifiers used in the B&I and LLFS microdata are consistent across both files. This is to facilitate data linkage between the two files and enable further analysis.

The B&I survey is collected by personal interview from a random person aged 18 years and over in private dwellings from 1/8th of the Labour Force Survey (LFS) sample (selected from the 'outgoing rotation group' - people who are in their final month of selection in the LFS). This means that most records on the LLFS will not have a corresponding B&I record.

The B&I survey is collected monthly, with the sample pooled over a financial year. The survey month identifier (ABSMID), which indicates the month of collection, has been included to facilitate data linkage to the LLFS. While this can provide monthly sub-samples, it is recommended that in most cases the microdata should be analysed using the whole financial year sample, using the 'Reference year' (REFYEAR) identifier to mark different points in time.

More details on these records and the formatting of record identifiers can be found in the Data Item List in Data downloads.


Person level weights (and replicate weights for calculating standard errors) are provided on the B&I file. These differ from the weights provided on the LLFS file, as the weights are recalibrated for B&I due to the reduced sample size compared to the LFS. Aggregate estimates from both sets of weights will align closely, as the B&I survey data is benchmarked to match the corresponding 12-month average of estimates from the LFS, but care should be taken when performing micro analysis.

Weights and replicate weights have been calibrated for the surveys whole financial year sample and should be used in conjunction with the Reference year (REFYEAR) identifier.

B&I weights are recommended for cross-sectional analysis of B&I data items, but when linking B&I and LLFS data for longitudinal analysis, new weights should be calculated based on the population benchmarks provided on the LLFS file. Care should be taken to account for attrition bias by adjusting the weights appropriately (increasing the weights for those more likely to leave the LFS). More information on using benchmarks and weights for longitudinal analysis is provided in Longitudinal Labour Force.

Data downloads

Data item list

Data files

History of changes

04/11/2022 - First release

  • This is the first release of Microdata: Barriers and Incentives to Labour Force Participation. Data was previously published in conjunction with the Retirement and Retirement Intentions survey. Future releases will continue to improve and develop these surveys as separate titles.

Previous catalogue number

This release uses ABS catalogue number 6239.0.55.002.

Data from this release was previously published in Microdata: Barriers and Incentives to Labour Force Participation, Retirement and Retirement Intentions (6238.0.5.001)

Related microdata is also available in Microdata and TableBuilder: Participation, Job Search and Mobility (6226.0.00.001)

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