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# Barriers and Incentives to Labour Force Participation, Australia methodology

Reference period
2016-17 financial year
Released
19/12/2017

## Explanatory notes

### Introduction

1 This publication contains results from the Barriers and Incentives to Labour Force Participation Survey, a topic on the Multipurpose Household Survey (MPHS) conducted throughout Australia from July 2016 to June 2017. 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 topics collected in 2016–17 were:

2 For all topics, information on labour force characteristics, education, income and other demographics are available.

3 The publication Labour Force, Australia (cat. no. 6202.0) contains information about survey design, sample design, scope, coverage and population benchmarks relevant to the monthly LFS, which also apply to the MPHS. It also contains definitions of demographic and labour force characteristics, and information about the modes of data collection, which are relevant to both the monthly LFS and the MPHS.

### Concepts sources and methods

4 The conceptual framework used in Australia's LFS aligns closely with the standards and guidelines set out in Resolutions of the International Conference of Labour Statisticians. Descriptions of the underlying concepts and structure of Australia's labour force 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).

### Collection methodology

5 ABS interviewers conducted personal interviews by either telephone or in person at selected households during the 2016–17 financial year. Each month a sample of households were selected for the MPHS from the responding households in the LFS. In these households, after the LFS had been fully completed for each person, a usual resident aged 15 years and over was selected at random and asked the additional MPHS questions in a personal interview. Information was collected using Computer Assisted Interviewing (CAI), whereby responses are recorded directly onto an electronic questionnaire in a notebook computer.

### Scope

6 The scope of the LFS is restricted to persons aged 15 years and over and excludes the following:

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

7 In addition the 2016–17 MPHS excluded the following:

• households in Indigenous communities; and
• persons 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 persons with disabilities).

8 For the Barriers and Incentives to Labour Force Participation topic, the scope was further restricted to persons aged 18 years and over.

### Coverage

9 In the LFS, 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.

### Sample size

10 The initial sample for the MPHS 2016–17 consisted of approximately 26,000 private households. Of the 15,400 private households that remained in the survey after sample loss (e.g. households with LFS non-response, no residents in scope for the LFS, vacant or derelict dwellings and dwellings under construction), approximately 72% fully responded to the MPHS. The number of completed interviews obtained from these private households (after taking into account scope, coverage and sub-sampling exclusions) was 6,200 for the Barriers and Incentives to Labour Force Participation survey.

### Weighting, benchmarking and estimation

11 Weighting is the process of adjusting results from a sample survey to infer results for the total in scope population. To do this, a 'weight' is allocated to each sample unit, which, for the MPHS, can either be a person or a household. The weight is a value which indicates how many population units are represented by the sample unit. The first step in calculating weights for each unit is to assign an initial weight, which is the inverse of the probability of being selected in the survey. The initial weights are then calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks'. 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.

12 The survey was benchmarked to the Estimated Resident Population (ERP) in each state and territory at December 2016. Previously, March was used as the reference month for benchmarking. This is the first year that the reference month has been changed to December. This aligns MPHS with the weighting methodology generally adopted by other social surveys, whereby the middle month of the enumeration period is selected as the benchmark reference month. This will have a minor affect on the comparison of level estimates as there has only been 21 months of population growth accounted for between the 2014-15 publication (based on March 2015 benchmarks) and the 2016-17 publication (based on December 2016 benchmarks). There will be no effect on the analysis proportions.

### Reliability of the estimates

13 Estimates in this publication 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); and
• 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.

### Classifications used

14 Country of birth data are classified according to the Standard Australian Classification of Countries (SACC), 2011 (cat. no. 1269.0).

15 Occupation data are classified according to the ANZSCO – Australian and New Zealand Standard Classification of Occupations, 2013, Version 1.2 (cat. no. 1220.0).

16 Industry data are classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (Revision 2.0) (cat. no. 1292.0).

17 Education data are classified according to the Australian Standard Classification of Education (ASCED), 2001) (Cat. no. 1272.0)

### Notes on estimates

18 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 adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of information that could identify individual survey respondents while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. After perturbation, a given published cell will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals.

### Comparability with monthly LFS statistics

19 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.

### Previous surveys

20 The Barriers to Labour Force Participation survey was last conducted in the 2014–15 financial year. Results of this survey were published in:

### Changes in this issue

21 For the 2012–13 survey, questions were included on Previous full-time job details and Main source of current personal income. These were excluded from the 2014–14 survey.

22 For the 2014-15 survey, enhancements were made to the Previous job payment arrangements question, adding the response category of 'Unpaid trainee/work placement'. Enhancements were also made to survey questions on why not looking for work or more hours, trouble finding work or more hours and wanting more hours. The response categories of 'No need/satisfied with current arrangements/retired (for now)' and 'Visa requirements' were added to these questions.

23 For the 2016–17 survey, enhancements were made to Previous job module, a new question asking "Did you have employees in the business" was added.

24 For a more detailed list of available data items and their categories – Barriers & Incentives to Labour Force Participation and Retirement & Retirement Intentions 2016–17 Data Items List, is available in an Excel spreadsheet, on the ABS Website under the Data downloads section.

### Next survey

25 The ABS plans to conduct this survey again during the 2018–19 financial year.

### Acknowledgement

26 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act, 1905.

### Related publications

27 ABS publications which may also be of interest include:

## Technical note - data quality

### Show all

#### Introduction

1 Since the estimates in this publication are based on information obtained from occupants of a sample of dwellings, they are subject to sampling variability. That is, they may differ from those estimates that would have been produced if all dwellings 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 dwellings 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 dwellings had been included, and about 19 chances in 20 (95%) that the difference will be less than two SEs.

2 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.

RSE% = (SE/estimate ) x 100

3 RSEs for Barriers and Incentives to Labour Force Participation estimates have been calculated using the Jackknife method of variance estimation. This process involves the calculation of 30 'replicate' estimates based on 30 different sub-samples of the original sample. The variability of estimates obtained from these sub-samples is used to estimate the sample variability surrounding the main estimate.

4 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.

5 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

6 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.

7 An example of the calculation of the SE from an RSE follows. Datacube 1 shows that the estimated number of males who were unemployed was 300,800, and the RSE for this estimate was 6.6%. The SE is:

SE of estimate

= (RSE / 100) x estimate

= 0.066 x 300,800

= 19,900 (rounded to the nearest 100)

8 Therefore, there are about two chances in three that the value that would have been produced if all dwellings had been included in the survey would fall within the range 261,000 to 340,600 and about 19 chances in 20 that the value would fall within the range 68,800 to 93,200. This example is illustrated in the following diagram.

The published estimate is 300,800. There are two chances in three that the true value is in the range of 280,900 to 320,700, and 19 chances in 20 that the true value is in the range of 261,000 to 340,600.

#### Proportions and percentages

9 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.

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

10 Considering Datacube 8, of the 1,092,100 persons who were not in the labour and wanted a paid job, 352,200 or 32.2% were ages 55 years and over. The RSE of 352,200 is 7.3% and the RSE for 1,092,100 is 3.9%. Applying the above formula, the RSE for the proportion of males aged 55 years and over who were full-time workers:

$${R S E=\sqrt{(7.3)^{2}-(3.9)^{2}}=6.2 \%}$$

11 Therefore, the SE for the proportion of persons 55 years and over who were not in the labour force and wanted a paid job was 2.0 percentage points (= (32.2/100) x 6.2). Therefore, there are about two chances in three that the proportion of persons 55 years and over who were not in the labour force and wanted a paid job is between 30.2% and 34.0%, and 19 chances in 20 that the proportion was within the range 28.2% to 36.2%.

#### Sums or differences between estimates

12 Published estimates may also be used to calculate the sum of two or more estimates, or the 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.

13 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:

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

14 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:

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

15 Considering the example in paragraph 10, the estimated number who were not in the labour and wanted a paid job was 352,200, and the SE for this estimate was 25,700. From Datacube 8, the estimate of persons aged 45-54 years who were not in the labour force and wanted a paid job was 179,500 (or 67,300?) and the SE was 15,800. The estimate of persons aged 45 years and over who were not in the labour force and wanted a paid job is:

352,220 + 179,500 = 531,700

16 The SE of the estimate of persons aged 45 years and over who wanted a paid job is:

$${S E=\sqrt{(25,700)^{2}+(15,800)^{2}}=30,200}$$

17 Therefore, there are about two chances in three that the value that would have been produced if all dwellings had been included in the survey would fall within the range 506,900 to 567,300 and about 19 chances in 20 that the value would fall within the range 476,700 to 597,500.

18 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.

#### Standard errors of means and sums

19 The estimates of means and sums of continuous variables are subject to sampling variability and random adjustment. As for population estimates, the variability due to sampling and random adjustment is combined into the calculated Standard Error, and the Relative Standard Error is reported. The component of variability arising from sampling is calculated using the Jackknife method.

#### Standard errors of quantiles

20 The estimates of quantiles such as medians, quartiles, quintiles and deciles are subject to sampling variability and random adjustment. As for population estimates, the variability due to sampling and random adjustment is combined into the calculated Standard Error, and the Relative Standard Error is reported. The component of variability arising from sampling is calculated using the Woodruff method. This is also true for Equal Distribution Quantiles.

#### Significance testing

21 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 in paragraph 9. This standard error is then used to calculate the following test statistic:

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

22 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.

23 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.

## Appendix - populations

### Show all

#### Data available on request

The ABS has a range of data available on request from the Barriers and Incentives to Labour Force Participation topic. This section lists the populations which are used in the publication. Full details of the data items are available on the ABS website in an Excel spreadsheet, under the Data downloads section (B&I and R&RI 2016–17 Data Items List).

The population(s) for a particular data item refers to the persons in the survey to whom the data relates. Where alternative output categories are available for the same data item, these are shown and the data item name is followed by a bracketed numeral (e.g. Country of birth (2)).

Note: The populations for this topic are numbered from 1–15A. Populations 16–24A relate to the Retirement and Retirement Intentions topic (cat. no. 6238.0) alongside which this survey was run.

For more information about ABS data available on request, contact National Information and Referral Service in Canberra on 1300 135 070 or via email to client.services@abs.gov.au or contact Labour Markets Analytics Section by email to labour.statistics@abs.gov.au

#### Population 1

All persons aged 18 years and over

#### Population 2

Employed persons

#### Population 3

Unemployed persons (end note 1)

#### Population 4

Persons not in the labour force

#### Population 5

Persons not in the labour force who wanted a paid job

#### Population 6

Persons who were not in the labour force, wanted a paid job but were not available to start within four weeks

#### Population 7

Persons who were not in the labour force, wanted a paid job, were available to start within four weeks, but were not actively looking for a job

#### Population 8

Persons who were not in the labour force, wanted a paid job, were available to start within four weeks, and were actively looking for a job

#### Population 9

Persons who were not in the labour force and did not want a paid job or did not know

#### Population 9A

Persons aged 18–75 years, who were not in the labour force, excluding those permanently unable to work and permanently retired from the labour force

#### Population 10

Persons who usually worked 0–34 hours per week in all jobs

#### Population 11

Persons who usually work 0–34 hours, and preferred to work more hours

#### Population 12

Persons who usually work 0–34 hours, preferred to work more hours, but were not available to start within four weeks

#### Population 13

Persons who usually work 0–34 hours, preferred to work more hours, were available to start within four weeks, but were not looking for work with more hours

#### Population 14

Persons who usually work 0–34 hours, preferred to work more hours, were available to start within four weeks, and were looking for work with more hours

#### Population 15

Persons who usually work 0–34 hours, and did not prefer to work more hours

#### Population 15A

Persons aged 18–75 years, who usually work 0–34 hours per week in all jobs

#### End note

1. There are no unemployed persons aged over 75 years.

## 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 a Job Services Australia provider or any other employment agency;
• taken steps to purchase or start your own business;
• advertised or tendered for work; and
• contacted friends or relatives in order to obtain work.

#### Available to start work

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

#### Available to start work with more hours

Employed persons 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 within four weeks.

#### Currently studying

Persons 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

Persons 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

Persons 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/last job.

#### Employed

Persons 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

Persons who work for a public or private employer and receive remuneration in wages, salary, a retainer fee from their employer while working on a commission basis, tips, piece rates, or payment in kind, or persons who operate their own incorporated enterprise with or without hiring employees.

#### 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 persons, 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 persons who usually work 35 hours or more a week (in all jobs).

#### Future starters

Persons 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.

#### Had ever worked for two weeks or more

Persons who are not in the labour force or are unemployed and have previously worked for two weeks or more.

#### Had previously worked

Persons who are not in the labour force or are unemployed, who have previously worked for two weeks or more, less than 20 years ago.

#### 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).

#### Labour force

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

#### Last job

Refers to last job less than 20 years ago.

#### Level of highest non-school qualification

Non-school qualifications are awarded for educational attainments other than those of pre-primary, primary or secondary education. They include qualifications at the Postgraduate Degree level, Masters Degree level, Graduate Diploma and Graduate Certificate level, Bachelor Degree level, Advanced Diploma and Diploma level, and Certificates I, II, III and IV levels and not further defined. Non-school qualifications may be attained concurrently with school qualifications.

#### Looking for work with more hours

Refers to persons who indicated that they had done something in the last four weeks to obtain more hours of work.

#### Main job

The job in which most hours were usually worked.

#### Not employed

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

#### 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)

Persons 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)

A person who operates his or her own unincorporated enterprise or engages 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.

#### Part-time workers (usual)

Employed persons who usually worked less than 35 hours a week (in all jobs).

#### Persons in the labour force

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

#### Persons not in the labour force

Persons who were not classified as employed or unemployed.

#### Preferred to work more hours

Employed persons who usually work 0–34 hours each 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 persons who live in the same household.

#### Status of employment

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

Employed persons 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
• 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.

#### Time since last job

The elapsed time since ceasing last job.

#### Unemployed

Persons 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 persons children including grandchildren. Also includes caring for elderly or someone with 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 hours worked

The hours usually worked per week by an employed person.

#### Wanted a paid job

Persons who are not in the labour force and would like a paid job of any kind. Includes persons who said 'depends'.

#### Wanted more hours

See 'Preferred to work more hours'.

## Quality declaration - summary

### Institutional environment

For information on the institutional environment of the Australian Bureau of Statistics (ABS), including the legislative obligations of the ABS, financing and governance arrangements, and mechanisms for scrutiny of ABS operations, please see ABS Institutional Environment.

### Relevance

The Barriers and Incentives to Labour Force Participation survey provides data on persons aged 18 years and over who are either not employed or work less than 35 hours. The Barriers and Incentives to Labour Force Participation topic is designed to bring various aspects of factors which influence labour force participation into one data source for comparison. The survey provides information on the potential labour force and what is preventing these persons finding or taking up (more) work.

Full details of the data items are available on the ABS website in an Excel spreadsheet, under the Data downloads section (B&I and R&RI 2016–17 Data Items List).

### Timeliness

The Barriers and Incentives to Labour Force Participation survey is collected biennially, and was first conducted in 2004–05. The most recent Barriers and Incentives to Labour Force Participation survey was conducted throughout Australia during the 2016–17 financial year. It was a component of the 2016–17 Multipurpose Household Survey (MPHS), collected as a supplement to the Australian Bureau of Statistics (ABS) Labour Force Survey (LFS).

### Accuracy

The initial sample for the MPHS 2016–17 consisted of approximately 26,000 private households. Of the 15,400 private households that remained in the survey after sample loss (e.g. households with LFS non-response, no residents in scope for the LFS, vacant or derelict dwellings and dwellings under construction), approximately 72% responded to the MPHS. The number of completed interviews obtained from these private households (after taking into account scope, coverage and subsampling exclusions) was 6,200 for the Barriers and Incentives to Labour Force Participation survey.

Estimates from the survey are subject to sampling and non-sampling errors.

The MPHS was designed primarily to provide estimates at the Australia level. Broad estimates are available for states and territories, though users should exercise caution when using estimates at this level because of the presence of high sampling errors.

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 adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of information that could identify individual survey respondents while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. After perturbation, a given published cell will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals.

### Coherence

For the 2012–13 survey, questions were included on Previous full-time job details and Main source of current personal income. These were excluded from the 2014–15 survey.

For the 2014–15 survey, enhancements were made to the Previous job payment arrangements question, adding the response category of 'Unpaid trainee/work placement'. Enhancements were also made to survey questions on why not looking for work or more hours, trouble finding work or more hours and wanting more hours. The response categories of 'No need/satisfied with current arrangements/retired (for now)' and 'Visa requirements' were added to these questions.

For the 2016–17 survey, enhancements were made to Previous job module, a new question asking "Did you have employees in the business" was added.

The statistics presented in this survey have been benchmarked to the Estimated Resident Population for December 2016, independently produced according to the scope of the survey. This ensures that the survey estimates conform to person benchmarks by state, section of state, age and sex. The statistics have been further benchmarked to labour force survey estimates averaged over the 12 month MPHS reference period. This ensures that survey estimates are also consistent with the estimated in-scope population by state, section of state, sex, age and labour force status.

### Interpretability

The Barriers and Incentives to Labour Force Participation publication contains detailed Explanatory Notes, Technical Notes and a Glossary that provide information on the terminology, classifications and other technical aspects associated with these statistics.

The estimates are based on information collected over the financial year. Therefore, seasonally adjusted and trend estimates are not produced and seasonal weighting is not undertaken.

Further commentary is often available through articles and data published in other ABS products, including:

Australian Labour Market Statistics (cat. no. 6105.0).

Australian Social Trends (cat. no. 4102.0).

Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001).

### Data access

For the 2016–17 release, tables and associated RSEs are available in spreadsheet form on the ABS website.

Barriers and Incentives to Labour Force Participation, Australia (cat. no. 6239.0) is released electronically via the ABS website as Datacubes in spreadsheet format. Additional data may be available on request (subject to data quality). Note that detailed data can be subject to high relative standard errors. Full details of data items for this survey are available from the Data downloads section in Datacube: B&I and R&RI 2016-17 Data items list.

For users who wish to undertake a more detailed analysis of the data, the survey microdata will be released through the TableBuilder product. For more details, refer to the TableBuilder information, Microdata, Barriers and Incentives to Labour Force Participation, Australia (cat. no. 6238.0.55.001). For more information see About TableBuilder.

For more information about ABS data available on request, contact National Information and Referral Service in Canberra on 1300 135 070 or via email to client.services@abs.gov.au or contact Labour Markets Analytics Section by email to labour.statistics@abs.gov.au

## Abbreviations

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 '000 thousand ABS Australian Bureau of Statistics ANZSCO Australian and New Zealand Standard Classification of Occupations ANZSIC Australian and New Zealand Standard Industrial Classification ASCED Australian Standard Classification of Education ASCO Australian Standard Classification of Occupations DVA Australian Government Department of Veterans Affairs LFS Labour Force Survey MPHS Multipurpose Household Survey MPS Monthly Population Survey OMIE Owner manager of incorporated enterprise OMUE Owner manager of unincorporated enterprise RSE Relative standard error SACC Standard Australian Classification of Countries SE Standard error