8146.0 - Household Use of Information Technology, Australia, 2008-09 Quality Declaration
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 16/12/2009
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3 Data for other MPHS topics collected in 2008–09 will be released in separate publications.
4 The CPCLA survey, conducted throughout Australia in April 2009 as a supplement to the Monthly Labour Force Survey (LFS), was designed to collect information about children's participation in cultural and leisure activities. This supplementary topic is made up of the following sub-topics:
5 This publication will cover the topics of internet and mobile phone use. Data for other CPCLA survey topics will be released in a separate publication.
6 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 Children's Participation in Cultural and Leisure Survey (2003 and 2006), the Time Use Survey (2006) and the MPHS (2004–05 onwards). The MPHS will be the vehicle for collection of HUIT data for the 2010-11 reference period and thereafter HUIT data will be collected biennially in the MPHS.
7 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.
8 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 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.
9 The sample was accumulated over a twelve month period (July 2008 to June 2009).
10 Information was collected in interviews conducted over a two week period during April 2009.
11 Information was collected from any responsible adult in the household who was asked to respond on behalf of the children in the household.
12 In each selected household, information on cultural, sporting and selected other activities was sought for a maximum of three children. In households with four or more children aged 5–14 years, three children were randomly selected for the survey. For the additional children in these households only selected demographic information was collected.
13 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.
14 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.
15 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.
16 The Children's Participation in Cultural and Leisure Activities Survey was previously conducted in 2000, 2003 and 2006 as supplements to the Labour Force Survey. Computer assisted telephone interviewing was introduced during 2003 and while information was collected using a paper form for the majority of households in 2003, computer assisted interviewing was used for all survey interviews in the 2006 survey. This change in the methodology is not expected to impact on the comparability of the data between the surveys.
17 Data collected about information technology have changed between each iteration of this survey. In previous surveys questions were asked about general computer access but in 2009 the focus changed to Internet access and mobile phone use. This was the first of these surveys to ask about children's use of mobile phones.
SCOPE AND COVERAGE
18 The scope of the LFS is restricted to people aged 15 years and over and excludes the following persons:
20 The 2008–09 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.
21 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.
22 Visitors to private dwellings are not included in the coverage of the MPHS.
23 The scope of the supplementary survey was all children aged 5–14 years who were usual residents of private dwellings except:
24 This supplementary survey was conducted in both urban and rural areas in all states and territories, but excluded children living in very remote parts of Australia who would otherwise have been within the scope of the survey. The exclusion of these children will have a minor impact on any aggregate estimates that are produced for states and territories, with the exception of the Northern Territory where such children account for 28% of the total number of children in the population.
25 The estimates in this publication relate to children covered by the survey in April 2009. For all intents and purposes, the population coverage of the April 2009 survey is the same as its scope, with the following exceptions:
26 In the LFS, coverage rules are applied which aim to ensure that each child is associated with only one dwelling, and hence have only one chance of selection in the survey. See Labour Force, Australia (cat.no.6202.0) for more details.
27 The initial sample for the 2008–09 MPHS Household Use of IT topic consisted of approximately 18,023 private dwelling households. Of the 15,233 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 13,035 or 86% fully responded to the MPHS.
28 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 (Second Edition) (Cat. no. 6269.0).
29 In total, information was collected about the activities of 5,825 children living in the selected households.
WEIGHTING, ESTIMATION AND BENCHMARKING
30 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 CPCLA survey 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.
31 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.
32 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.
33 Certain data items in the MPHS such as estimates of income had significant non-response for 2008–09. The ABS has not applied any imputation methodology for estimation of values for non-responses.
INCOME LESS THAN ZERO
34 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
35 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.
36 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.
37 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.
38 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.
39 For more information on the use of equivalence scales, see Household Income and Income Distribution, Australia (cat. no. 6523.0).
40 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.
41 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.
42 Remoteness is calculated using the road distance to the nearest Urban Centre in each of five classes based on population size. 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).
43 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.
44 RA categories are defined in the ASGC Remoteness Classification as follows:
RELIABILITY OF ESTIMATES
45 The estimates provided in this publication are subject to sampling and non-sampling error.
46 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.
47 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.
EFFECTS OF ROUNDING
48 Estimates have been rounded and discrepancies may occur between sums of the component items and totals.
CONFIDENTIALISED UNIT RECORD FILE
49 Confidentialised Unit Record Files (CURF) release confidentialised microdata from surveys, thereby facilitating interrogation and analysis of data.
50 For all MPHS topics covered in the 2008–09 survey, an expanded CURF will be released in 2010. The expanded CURF for MPHS 2007–08 topics is available through the ABS' Remote Access Data Laboratory. For more information on expanded CURFs refer to Technical Manual: Multi-Purpose Household Survey, Expanded CURF, Australia (Cat. no. 4100.0).
COMPARABILITY WITH MONTHLY LFS STATISTICS
51 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
52 In tables 7.1 to 7.3 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 Key ICT Indicators.
53 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.
54 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.
55 The metadata for OECD Countries' ICT Collections site available at <http://www.oecd.org/countrylist/0,3349,en_2649_34449_34336071_1_1_1_1,00.html> provides detailed information on the reference period and survey scope for each country.
56 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.
57 Other ABS publications on the production and use of information and communication technologies and telecommunication goods and services in Australia are:
58 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>.
ABS DATA AVAILABLE ON REQUEST
59 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.
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