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EXPLANATORY NOTES


INTRODUCTION

1 This publication presents results from household use of information technology (HUIT) data collected from the Multi-Purpose Household Survey (MPHS) for 2006-07 by the Australian Bureau of Statistics (ABS).

2 The MPHS, conducted each year throughout Australia from July to June as a supplement to the Monthly Labour Force Survey (LFS), is designed to collect statistics for a number of small, self-contained topics. These include both labour topics and other social and economic topics. The topics collected in 2006-07 were:

• Education, personal and household income (core)
• Household use of information technology
• Barriers and incentives to labour force participation
• Retirement and retirement intentions
• Family characteristics and transitions
• Adult learning

4 The 2005-06 HUIT included results from the 2006 Children's Participation in Cultural and Leisure Activities (CPCLA) survey, conducted throughout Australia in April 2006 and also a supplement to the Monthly Labour Force Survey (LFS). It was designed to collect information about children's use of information technology, and to identify characteristics of children who participated in organised sport and cultural activities and a range of other activities outside of school hours primarily for recreation and leisure. The ABS has not conducted a CPCLA since the last publication.

5 Data on household use of information technology has been previously collected by the ABS in the Population Survey Monitor (1996, 1998, 1999 and 2000), the Survey of Education, Training and Information Technology (2001), the General Social Survey (2002), the National Aboriginal and Torres Strait Islander Survey (2002), the Survey of Disability, Ageing and Carers (SDAC - 2003), the CPCLA Survey (2003 and 2006), and the MPHS (2004-05 and 2005-06). The MPHS will be the vehicle for collection of HUIT data for the 2007-08 reference period.

6 The publication Labour Force, Australia (Cat. no. 6202.0) contains information about survey design, sample redesign, scope, coverage and population benchmarks relevant to the monthly LFS, which also apply to supplementary surveys. It also contains definitions of demographic and labour force characteristics, and information about telephone interviewing relevant to both the monthly LFS and supplementary surveys.

DATA COLLECTION

7 The MPHS is conducted as a supplement to the monthly LFS. One third of the dwellings in the outgoing rotation group (one eighth of the 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 or 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.

8 The sample was accumulated over a ten month period (July 2006, October 2006 to June 2007).

HISTORICAL COMPARISONS

9 Due to the difference in the scope of previous surveys, household use of information technology (HUIT) data from the 2005-06 MPHS onwards are not comparable with data from several of the surveys listed in paragraph 7. For example, the HUIT data for 2003 were obtained from the SDAC, where person level data only relates to those with a disability aged 15 years or over. Data are not comparable with results from MPHS which covers all persons 15 years or over. However, SDAC and MPHS data are comparable at the household level.

10 The 2002 HUIT data were obtained from the GSS using a face-to-face randomly selected person methodology. MPHS questions were asked using a telephone interview. The ABS has taken reasonable steps during the survey development process to ensure that this change in collection methodology does not affect the quality of the data, however, a small impact on responses for the more complex questions cannot be ruled out.

SCOPE

11 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

14 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

15 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

16 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 Survey 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.

17 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. The same is true for estimates of households produced in this survey. However, in these cases the household benchmarks are actually estimates themselves and not strictly known population totals.

18 The survey was benchmarked to the estimated civilian population aged 15 years and over living in private dwellings in each state and territory excluding persons out of scope (refer Explanatory Notes 11-12).

ESTIMATION

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

IMPUTATION FOR NON RESPONSE

20 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

22 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 HOUSEHOLD INCOME QUINTILES

23 These 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 15 years and over, 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 15 years and over in each of these quintiles may be larger or smaller than 20%.

24 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.

25 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.

26 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.

27 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 for each household member would be calculated as $1,000 per week.

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

REMOTENESS

29 Remoteness Areas (RA) are the spatial units that make up the ASGC Remoteness Classification. There are six classes of Remoteness Area in the Remoteness Structure; Major Cities of Australia, Inner Regional Australia, Outer Regional Australia, Remote Australia, Very Remote Australia and Migratory. Remoteness Areas are aggregations of Collection Districts (CD) which share common characteristics of remoteness

30 The purpose of the RA structure is to classify Collection Districts (CD) which share common characteristics of remoteness into broad geographical regions called RAs. The remoteness structure includes all CDs thereby covering the whole of geographic Australia. Where relevant, statistics in this publication have been produced using the ASGC Remoteness Classification.

31 Remoteness is calculated using the road distance to the nearest Urban Centre in each of five classes based on population size. The Remoteness classification divides Australia into six RAs: Major Cities of Australia; Inner Regional Australia; Outer Regional Australia; Remote Australia; Very Remote Australia; and Migratory. The glossary accompanying this publication provides definitions of RAs used. For further information see Statistical Geography: Volume 1 - Australian Standard Geographical Classification (ASGC), 2006 (cat. no. 1216.0).

32 The key element in producing the structure is the preparation of the Accessibility/Remoteness Index of Australia (ARIA+) grid. ARIA+ scores are first calculated for each Urban Centre and are then interpolated to create a 1 km grid covering the whole of Australia. Each grid square carries a score of remoteness from an index of scores ranging from 0 (zero) through to 15. The data custodian of the grid remains the National Key Centre for Social Applications of Geographic Information System (GISCA), Adelaide University, South Australia. ABS Remoteness Areas are created by averaging the ARIA+ scores within Census Collection Districts (CDs), then aggregating the CDs up into the 6 ABS Remoteness Area categories based on the averaged ARIA+ score.

33 RA categories are defined in the ASGC Remoteness Classification as follows:

• Major Cities of Australia: CDs with an average Accessibility/Remoteness Index of Australia (ARIA) index value of 0 to 0.2
• Inner Regional Australia: CDs with an average ARIA index value greater than 0.2 and less than or equal to 2.4
• Outer Regional Australia: CDs with an average ARIA index value greater than 2.4 and less than or equal to 5.92
• Remote Australia: CDs with an average ARIA index value greater than 5.92 and less than or equal to 10.53
• Very Remote Australia: CDs with an average ARIA index value greater than 10.53

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.

CONFIDENTIALISED UNIT RECORD FILE

37 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. The expanded CURF for MPHS 2005-06 topics are available. For more information on expanded CURFs refer to ABS information paper Multi-Purpose Household Survey 2005-06, Expanded Confidentialised Unit Record File (Cat. no. 4100.0)

COMPARABILITY WITH MONTHLY LFS STATISTICS

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

COMPARISON WITH OTHER COUNTRIES

39 Tables 5.1 and 5.2 data for other countries have been provided courtesy of the OECD and were originally sourced from individual country reports to the OECD. With the exception of Australian data, all other data have been published in the OECD Science, Technology and Industry Scoreboard 2005- Towards a knowledge based economy and the OECD Key ICT Indicators.

40 There are important differences in definitions, scope, coverage and reference periods for the international comparison data included for selected indicators in the above tables, and thus the figures should be used with caution.

41 The ABS defines broadband as an 'always on' Internet connection with an access speed equal to or greater than 256 kbps. Most other OECD countries define broadband in terms of technology (e.g. ADSL, cable etc) rather than speed.

42 The metadata for OECD Countries' ICT Collections site available at <www.oecd.org/sti/ictmetadata> provides detailed information on the reference period and survey scope for each country.

FUTURE SURVEYS

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

• Education and household income (core)
• Household use of information technology
• Attitudes towards the environment
• Personal fraud

RELATED PUBLICATIONS

45 Other ABS publications on the production and use of information and communication technologies and telecommunication goods and services in Australia are:

• Business Use of Information Technology, 2005-06 (Cat. no. 8129.0)
• Government Technology, Australia, 2002-03 (Cat. no. 8119.0)
• Household Use of Information Technology, Australia, 2006-07 (Cat. no. 8146.0)
• Patterns of internet access in Australia, 2006 (Cat. no. 8146.0.55.001)
• Information and Communication Technology, Australia, 2004-05 (Cat. no. 8126.0)
• Use of Information Technology on Farms, Australia, 2004-05 (Cat. no. 8150.0)
• Internet Activity, Australia, June 2006 (Cat. no. 8153.0)
• Children's Participation in Cultural and Leisure Activities, April 2006 (Cat. no. 4901.0)

ABS DATA AVAILABLE ON REQUEST

47 As well as statistics included in this and related publications, the ABS may have other relevant data available on request. Inquiries should be made to Siddhartha De, Canberra, (02) 6252 6519 or the National Information Referral Service on 1300 135 070.