8146.0 - Household Use of Information Technology, Australia, 2010-11 Quality Declaration 
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 15/12/2011   
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1 This release presents results from Household Use of Information Technology (HUIT) data collected from the Multipurpose Household Survey (MPHS) for 2010–11 and the 2009 Survey of Disability, Ageing and Carers (SDAC) 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 2010–11 were:

    • Household use of information technology
    • Crime victimisation
    • Attendance at selected cultural venues and events
    • Patient experience
    • Adult learning
    • Barriers and incentives to labour force participation
    • Retirement and retirement intentions.
3 Data for other MPHS topics collected in 2010–11 are released in separate publications.


4 The SDAC was conducted throughout Australia from April to December 2009. The primary objective of the survey was to collect information about three population groups:
    • people with a disability
    • older people (i.e. those aged 60 years and over)
    • people who provide and assistance to older people and people with disabilities.
Data from the 2009 SDAC were released in Disability, Ageing and Carers, Australia, 2009 (cat. no. 4430.0).

5 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 Labour Force Survey (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.



6 The MPHS is conducted as a supplement to the monthly LFS. A portion 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 years 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.

7 The sample was accumulated over a twelve month period (July 2010 to June 2011).


8 Different data collection methods were used for the household and cared-accommodation components of SDAC. Data presented in this release relates to the household component only, which covered persons in:
    • private dwellings such as houses, flats, home units and townhouses
    • non-private dwellings such as hotels, motels, boarding houses, short-term caravan parks and self care components of retirement villages.
Smaller disability homes (with fewer than six persons) were considered to be private dwellings.

9 Data are collected by trained interviewers, who conduct computer-assisted personal interviews.



10 Due to the difference in the scope of previous surveys, Household Use of Information Technology (HUIT) data from the 2005-06 MPHS onwards (the scope of which is persons aged 15 years and over) are not directly comparable with data from previous years, which was limited to persons aged 18 years and over.


11 Much of the content of the six disability surveys conducted by the ABS between 1981 and 2009 is comparable. There are differences, however, as later surveys have attempted to obtain better coverage of disability and of specific tasks and activities previously considered too sensitive for a population survey. Survey questions collected in regard to the use of computers and the internet are unchanged between the 2003 and 2009 surveys.



12 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).
13 In addition, the 2010-11 MPHS excluded the following:
    • people living in very remote parts of Australia (as defined by the ASGC remoteness classification)
    • 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.

14 The 2010–11 MPHS was conducted in both urban and rural areas in all states and territories, but excluded people living in very remote parts of Australia. The exclusion of these people is expected to have only a minor impact on any aggregate estimates that are produced for individual states and territories, except in the Northern Territory where such people account for around 23% of the population.

15 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.

16 Coverage rules are the same as that for the monthly LFS with the exception that all visitors to private dwellings are excluded from process scope (and process coverage) in the MPHS.


17 The scope of SDAC was persons in both urban and rural areas in all states and territories, living in both private and non-private dwellings (including persons in cared-accommodation), but excluding:
    • diplomatic personnel of overseas governments
    • persons whose usual residence was outside Australia
    • members of non-Australian defence forces (and their dependents) stationed in Australia
    • persons living in very remote areas.
18 The coverage of SDAC was the same as the scope except that the following (small) populations were not enumerated for operational reasons:
    • persons living in Indigenous communities in non-very remote areas
    • persons living in boarding schools
    • persons living in goals or correctional institutions.
19 Rules were applied to maximise the likelihood that each person in coverage was associated with only one dwelling and thus had one chance of selection. See Disability, Ageing and Carers, Australia: Summary of Findings 2009 (cat. no. 4430.0) for more details.



20 The initial sample for the 2010–11 MPHS Household Use of IT topic consisted of approximately 31,800 private dwelling households. Of the approximately 27,000 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; were vacant; or were under construction), 21,309 households (79%) fully responded to the MPHS.

21 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. For further information on the sample size of the LFS, refer to the ABS information paper Labour Force Survey Sample Redesign, Nov 2007 (Third Edition) (cat. no. 6269.0).


22 Multi-stage sampling techniques were used to select the sample for the survey. After sample loss, the household sample included approximately 27,600 private dwellings and 200 non-private dwellings. After exclusions due to scope and coverage, the final sample comprised 64,213 persons for the household component.


23 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. Weights for the SDAC are for persons only. 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.

24 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.

25 Survey estimates are benchmarked to persons within the scope of the survey - for example, the MPHS 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. Survey estimates of counts of persons or households are obtained by summing the weights of persons or households with the characteristics of interest.

26 Certain data items in the MPHS such as estimates of income had significant non-response for 2010–11. The ABS has not applied any imputation methodology for estimation of values for non-responses.


27 Some households reported negative income in the survey. This is possible if they incur losses in their unincorporated business or have negative returns from their investments. Studies of income and expenditure from the Household Expenditure Survey, Australia (cat. no. 6530.0) have shown that such households in the bottom income decile and with negative gross incomes tend to have expenditure levels that are comparable with 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.


28 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.

29 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.

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

31 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.

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


33 These are groupings of 20% of the total population when ranked in ascending order according to equivalised 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%.


34 Country of birth data are classified according to the Standard Australian Classification of Countries (SACC) (Second Edition) (cat. no. 1269.0).

35 Educational attainment is classified according to Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0).

36 Remoteness areas are classified according to the Statistical Geography: Volume 1 - Australian Standard Geographical Classification (ASGC), 2006 (cat. no. 1216.0).

37 Section of State (SOS) areas are also classified according to the Statistical Geography: Volume 1 - Australian Standard Geographical Classification (ASGC), 2006 (cat. no. 1216.0).

38 In each state, the SOS categories of:
    • 0 - Major Urban: urban areas with a population of 100,000 and over
    • 1 - Other Urban: urban areas with a population of 1,000 to 99,999
are regarded as Urban.

39 The SOS categories of:
    • 2 - Bounded Locality: small towns with a population of 200 to 999
    • 3 - Rural balance
are regarded as Rural.

40 Occupation data are classified according to the ANZSCO - Australian and New Zealand Standard Classification of Occupations, First Edition, Revision 1, 2009 (cat. no. 1220.0).


41 Estimates have been rounded and discrepancies may occur between sums of the component items and totals.


42 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.


43 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.

44 The 2010-11 HUIT was supplemented by additional funding from the Department of Broadband, Communications and the Digital Economy (DBCDE) to increase content and sample size. This funding has enabled the ABS to collect a broader range of questions relating to internet use and release data at a finer geographic level than would be possible with ABS resources for HUIT.


45 Other ABS publications on the production and use of information and communication technologies and telecommunication goods and services in Australia are:
46 Publications and other products to be released within the next six months by the ABS are listed in the ABS release calendar. The calendar is available from the ABS website <https://www.abs.gov.au>.


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 Paul Schollum on (08) 9360 5933 or the National Information Referral Service on 1300 135 070.