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EXPLANATORY NOTES


INTRODUCTION

1 This publication presents results on Adult Learning from the 2006-07 Multi-Purpose Household Survey (MPHS). The MPHS is conducted throughout Australia as a supplement to the Labour Force Survey (LFS). The MPHS is usually conducted each month but in 2006-07 the survey was not conducted in August and September due to problems identified with the collection of another topic which required rectification. Adjustments were made to the sample in the subsequent months to achieve the target sample size. This is not expected to have an impact on the Adult Learning data.

2 The MPHS is designed to provide statistics annually for a small number of self-contained labour, social and economic topics. In 2006-07 the topics were:

• Adult Learning
• Barriers and Incentives to Labour Force Participation
• Retirement and Retirement Intentions
• Household Use of Information Technology
• Family Characteristics and Transitions

4 Data from other MPHS topics collected in 2006-07 will be released in separate publications.

5 The MPHS collected data on Adult Learning for persons aged 25 to 64 years. The topic focused on measuring three categories of learning: formal learning, non-formal learning and informal learning, as well as access to and opportunities for learning.

6 The Classification of Learning Activities developed by Eurostat (see <http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-BF-06-002/EN/KS-BF-06-002-EN.PDF> has been used to define these three categories of learning. The classification aims to operationalise the concept of learning by proposing simple, clear and understandable criteria which should be used when taking a decision on the allocation of education and learning activities according to the 3 categories. The relevant decision making flow chart is presented in Figure 1.

Figure 1: Classification of learning

8 Non-formal learning also refers to structured, taught learning, but differs from formal learning in that it does not lead to a qualification within the AQF. It includes non-accredited workplace training, that is, training that does not lead to a recognised qualification.

9 Informal learning refers to unstructured, non-institutionalised learning activities that are related to work, family, community or leisure. Activities may occur on a self-directed basis, but are excluded from scope if there is no specific intention to learn.

10 Formal and non-formal learning can be referred to as organised or 'course-based' forms of learning which together encompass what the OECD refers to as 'continuing education and training'.

11 The Adult Learning topic on the MPHS was based on an international survey, the Adult Education Survey, which was developed by Eurostat and conducted in European countries in 2006. The Adult Education Survey questions were adapted to suit an Australian sample. The Task Force report on the Adult Education Survey contains more information about the development and contents of the Adult Education Survey and is available on the Eurostat website at<http://epp.eurostat.cec.eu.int/cache/ITY_OFFPUB/KS-CC-05-005/EN/KS-CC-05-005-EN.PDF>.

12 The proposed core target population of the European Adult Education Survey was adults aged 25 to 64 years, which is designed to exclude people who are in the initial stages of education. Since the ABS Adult Learning is based on the European Adult Education Survey, the same population was chosen.

13 Selected questions from a previous ABS survey, the Adult Education and Training topic on the May 1995 Population Survey Monitor, were also included. See Population Survey Monitor, May 1995 (cat. no. 4103.0) for more information about the Adult Education and Training topic from the May 1995 Population Survey Monitor.

DATA COLLECTION

MPHS

14 The MPHS is conducted as a supplement to the monthly Labour Force Survey (LFS). One third of the dwellings in the outgoing rotation group (one eighth of the LFS sample is rotated out each month) are selected for the MPHS. In these dwellings, after LFS has been fully completed for each person in scope and coverage, a person (usual resident) aged 15 years and over is selected at random (based on a computer algorithm) and asked the additional MPHS questions in a personal interview. Data are collected using Computer Assisted Interviewing (CAI), whereby responses are recorded directly onto an electronic questionnaire in a notebook computer generally during a telephone interview.

15 The sample was accumulated during July 2006 to June 2007.

SCOPE

LFS and MPHS

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

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

• people living in private dwellings in very remote parts of Australia
• people living in non-private dwellings such as hotels, university residences, students at boarding schools, patients in hospitals, residents of homes (e.g. retirement homes, homes for persons with disabilities), and inmates of prisons.

COVERAGE

19 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 (cat. no. 6202.0) for more details.

SAMPLE SIZE

20 The initial sample for the 2006-07 MPHS consisted of approximately 19,800 private dwelling households. Of the 17,040 private dwelling households that remained in the survey after sample loss (for example, households selected in the survey which had no residents in scope for the LFS, vacant or derelict dwellings and dwellings under construction), approximately 14,190 or 83.3% fully responded to the MPHS.

WEIGHTING, BENCHMARKING AND ESTIMATION

21 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 be either 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.

Benchmarking

22 The estimation process for these surveys ensures that estimates of persons calibrate exactly to independently produced population totals at broad levels. The known population totals, commonly referred to as 'benchmarks', are produced according to the scope of the survey.

23 The survey was benchmarked to the estimated civilian population aged 25 to 64 years living in private dwellings in each state and territory, excluding persons out of scope (see Explanatory Notes 16 to 18). The process of weighting ensures that the survey estimates conform to person benchmarks by state, part of state, age and sex, and to household benchmarks by state, part of state and household composition. These benchmarks are produced from estimates of the resident population derived independently of the survey.

Estimation

24 Survey estimates of counts of persons or households are obtained by summing the weights of persons or households with the characteristic of interest.

IMPUTATION FOR NON RESPONSE

25 Approximately 36% of occupation and industry data for employed persons aged 25 to 64 years have been imputed from information collected in a previous month of the Labour Force Survey, because some persons were not asked their occupation and industry in some months of the survey. The following criteria were applied before imputation occurred:

• full-time or part-time status of employment was the same,
• status in employment (employee, employer, own account worker, contributing family worker) was the same, and
• hours usually worked in all jobs was different by no more than 10 hours.

INCOME LESS THAN ZERO

27 Some households reported negative income in the survey. This is possible if they incur losses in their unincorporated businesses or have negative returns from their investments. Studies of income and expenditure from the 1998-99 Household Expenditure Survey (HES) have shown that such households in the bottom income decile and with negative gross incomes tend to have expenditure levels that are comparable to those of households with higher income levels (and slightly above the average expenditures recorded for the fifth decile), indicating that these households have access to economic resources, such as wealth, or that the instance of low or negative income is temporary, perhaps reflecting business or investment start-up.

EQUIVALISED GROSS HOUSEHOLD INCOME QUINTILES

28 Quintiles are groupings of 20% of the total population when ranked in ascending order according to equivalised gross household income. The population used for this purpose includes all people living in private dwellings, including children and other persons under the age of 15 years. As the scope of this publication is restricted to only those persons aged 25 to 64 years, the distribution of this smaller population across the quintiles is not necessarily the same as it is for persons of all ages, i.e. the percentage of persons aged 25 to 64 years in each of these quintiles may be larger or smaller than 20%.

29 Equivalence scales are used to adjust the actual incomes of households in a way that enables the analysis of the relative wellbeing of people living in households of different size and composition. For example, it would be expected that a household comprising two people would normally need more income than a lone person household if all the people in the two households are to enjoy the same material standards of living. Adopting a per capita analysis would address one aspect of household size difference, but would address neither compositional difference (i.e. the number of adults compared with the number of children) nor the economies derived from living together.

30 When household income is adjusted according to an equivalence scale, the equivalised income can be viewed as an indicator of the economic resources available to a standardised household. For a lone person household, it is equal to income received. For a household comprising more than one person, equivalised income is an indicator of the household income that would be required by a lone person household in order to enjoy the same level of economic wellbeing as the household in question.

31 The equivalence scale used in this publication was developed for the Organisation for Economic Co-operation and Development and is referred to as the "modified OECD" equivalence scale. It is widely accepted among Australian analysts of income distribution.

32 The scale allocates 1.0 point for the first adult (aged 15 years or older) in a household; 0.5 for each additional adult; and 0.3 for each child. Equivalised household income is derived by dividing total household income by the sum of the equivalence points allocated to household members. For example, if a household received combined gross income of $2,100 per week and comprised two adults and two children (combined household equivalence points of 2.1), the equivalised gross household income would be calculated as $1,000 per week.

33 For more information on the use of equivalence scales, see Household Income and Income Distribution, Australia, 2005-06 (cat. no. 6523.0).

RELIABILITY OF ESTIMATES

34 The estimates provided in this publication are subject to sampling and non-sampling error.

Sampling error

35 Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if all persons in scope of the survey had been included. For more information refer to the Technical Note.

Non-sampling error

36 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-sample 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 the non-sampling error to a minimum by careful design of questionnaires, intensive training and supervision of interviewers and effective processing procedures.

CLASSIFICATIONS

Occupation

37 Occupation data are classified according to the ANZSCO - Australian and New Zealand Standard Classification of Occupations, First Edition, 2006 (cat. no. 1220.0).

Industry

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

Country of Birth

39 Country of birth data are classified according to the Standard Australian Classification of Countries (SACC), 1998 (cat. no. 1269.0).

Education

40 Level of Education and Field of Education are classified according to the Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0). The ASCED is a national standard classification which can be applied to all sectors of the Australian education system including schools, vocational education and training and higher education. ASCED replaces a number of classifications previously used in administrative and statistical systems, including the ABS Classification of Qualifications (ABSCQ), 1993 (cat. no. 1262.0). The ASCED comprises two classifications: Level of Education and Field of Education.

41 Level of Education is defined as a function of the quality and quantity of learning involved in an educational activity. There are nine broad levels, 15 narrow levels and 64 detailed levels. For definitions of these levels see the Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0).

42 The relationship between categories in the Level of Education classification should be essentially ordinal. In other words, educational activities at Broad Level 1 - Postgraduate Degree should be at a higher level than those at Broad Level 2 - Graduate Diploma and Graduate Certificate, and so on. However, when this is applied to educational provision in Australia, it is not always possible to assert that an ordinal relationship exists among the various levels of education.

43 Field of Education is defined as the subject matter of an educational activity. Fields of education are related to each other through the similarity of subject matter, through the broad purpose for which the education is undertaken, and through the theoretical content which underpins the subject matter.

44 There are 12 broad fields, 71 narrow fields and 356 detailed fields. For definitions of these fields see the Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0).

Level of highest educational attainment

45 Level of Highest Educational Attainment is derived from information on Highest Year of School Completed and Level of Highest Non-school Qualification. The derivation process determines which of the 'non-school' or 'school' attainments will be regarded as the highest. Usually the higher ranking attainment will be self-evident, but in some cases some Secondary Education is regarded, for the purposes of obtaining a single measure, as higher than some Certificate level attainments.

46 The following decision table is used to determine which of the responses to questions on Highest Year of School Completed (coded to ASCED Broad Level 6) and Level of Highest Non-school Qualification (coded to ASCED Broad Level 5) will be regarded as the highest. It is emphasised that this table was designed for the purpose of obtaining a single value for the output variable Level of Highest Educational Attainment and is not intended to convey any other ordinality.

CONFIDENTIALISED UNIT RECORD FILE

48 Confidentialised Unit Record Files (CURF) release confidentialised microdata from surveys, thereby facilitating interrogation and analysis of data. For all MPHS topics covered in the 2006-07 survey, an expanded CURF will be available in 2008. For more information on expanded CURFs refer to the ABS information paper Multi-Purpose Household Survey, Expanded Confidentialised Unit Record File, Technical Manual, 2005-06 (cat. no. 4100.0).

DATA COMPARISON

49 Since the MPHS is conducted as a supplement to the LFS, data items collected in the LFS are also available. However, there are some important differences between the two surveys. The MPHS sample is a small subset of the LFS sample collated over 12 months and the MPHS had a response rate of 83% which is lower than the average LFS response rate of around 96% during the same period. Due to these differences between the MPHS and LFS samples, the MPHS data are weighted as a separate process to the weighting of LFS data (see Paragraph 20 of these Explanatory Notes for further information on weighting). Differences may therefore be found in the estimates collected in the LFS and published as part of the MPHS, when compared with estimates published in Labour Force, Australia (cat. no. 6202.0).

50 As well as collecting information about Adult Learning and the other topics mentioned in Paragraph 2 of these Explanatory Notes, the MPHS collected other socio-demographic information that has been included in this publication, such as level of highest non-school qualification, highest year of school completed, occupation of current job and industry of current job. Standard ABS questions have been used to collect these data items to ensure comparability with other ABS collections. However, estimates resulting from the MPHS may differ from the estimates produced from other ABS collections, for several reasons. The MPHS is a sample survey and its results are subject to sampling error, as are the results from other sample surveys. Users should take account of the RSEs on MPHS estimates and those of other survey estimates where comparisons are made.

51 Differences may also exist in the scope and/or coverage of the MPHS compared to other surveys. Furthermore, the MPHS was collected over the period July 2006 to June 2007. Differences in MPHS data, when compared to the estimates of other surveys, may result from different reference periods reflecting seasonal variations, non-seasonal events that may have impacted on one period but not another, or because of underlying trends in the phenomena being measured.

52 Finally, differences can occur as a result of using different collection methodologies. This is often evident in comparisons of similar data items reported from different ABS collections where, after taking account of definition and scope differences and sampling error, residual differences remain. These differences are often the result of the mode of the collections, such as whether data is collected by an interviewer or self-enumerated by the respondent, whether the data is collected from the person themselves or from a proxy respondent, and the level of experience of the interviewers. Differences may also result from the context in which questions are asked, i.e. where in the interview the questions are asked and the nature of preceding questions. The impacts on data of different collection methodologies are difficult to quantify. As a result, every effort is made to minimise such differences.

53 Appendix 2 contains a table, Comparison of Data from the 2006-07 MPHS and Other ABS Sources, which presents comparisons between a number of key MPHS data items and similar data items from other ABS sources. The comparison shows that, the 2006-07 MPHS data is broadly consistent with other ABS sources.

COMPARISON WITH OTHER COUNTRIES

54 The international data presented in Table 4 is from a Life Long Learning survey that was conducted as an ad-hoc module to the European Union Labour Force Survey in selected European countries in 2003. While survey methodology varied from country to country, the aim of the survey was the same in each country; to measure the participation and volume of lifelong learning in persons aged 25 to 64. Detailed information on the survey methodology is available at the following website:<http://circa.europa.eu./Public/irc/dsis/edtcs/library?l=/public/education_labour/lfs_2003_ahm_lll>. For RSEs of estimates provided in Table 4 and response rates, please contact the representative for the relevant country as listed on the United Nations Statistics Division website at <http://unstats.un.org/unsd/methods/inter-natlinks/sd_natstat.asp>.

FUTURE SURVEYS

55 The ABS will conduct the MPHS again during the 2007-08 financial year. The topics included in the 2007-08 MPHS are:

• Household Use of Information Technology
• Attitudes Towards the Environment
• Personal Fraud

RELATED PUBLICATIONS

57 Other ABS publications which may be of interest include:

• A Directory of Education and Training Statistics (cat. no. 1136.0)
• Aspects of Literacy: Assessed Skill Levels, Australia (cat. no. 4228.0)
• Aspects of Literacy: Profiles and Perceptions, Australia (cat. no. 4226.0)
• Education and Training Experience, Australia (cat. no. 6278.0)
• Education and Training Indicators, Australia (cat. no. 4230.0)
• Education and Work, Australia (formerly Transition from Education to Work, Australia) (cat. no. 6227.0)
• Employer Training Expenditure and Practices, Australia (cat. no. 6362.0)
• General Social Survey: Summary Results, Australia (cat. no. 4159.0)
• Information Paper: Measuring Learning in Australia - A Framework for Education and Training Statistics (cat. no. 4213.0)
• Information Paper: Measuring Learning in Australia - Dictionary of Standards for Education and Training Statistics (cat. no. 4232.0.55.001)
• Information Paper: Measuring Learning in Australia - Plan to improve the Quality, Coverage and Use of Education and Training Statistics (cat. no. 4231.0)
• Labour Force, Australia (cat. no. 6202.0)
• Schools, Australia (cat. no. 4221.0)
• Adult Literacy and Life Skills Survey, Summary Results, Australia, 2006 (cat. no. 4228.0)