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EXPLANATORY NOTES


INTRODUCTION

1 This publication presents results compiled from household use of information technology (HUIT) data collected from two different surveys conducted by the Australian Bureau of Statistics (ABS), the Multi-Purpose Household Survey (MPHS) for 2005-06 and the 2006 Children's Participation in Cultural and Leisure Activities (CPCLA) survey.

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 2005-06 were:

• Household use of information technology
• Sports attendance
• Attendance at selected culture and leisure venues and events
• Participation in sport and physical activity
• Work related injuries

4 The CPCLA survey, conducted throughout Australia in April 2006 and also a supplement to the Monthly Labour Force Survey (LFS), 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.

5 This supplementary topic is made up of the following sub-topics:

• Home Computers;
• Computer & Internet Use;
• Participation in Organised Sports;
• Participation in Cultural Activities;
• Attendance at Cultural Venues and Events; and
• Participation in Recreational and Other Activities.

7 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 (2000 and 2003), and the MPHS (2004-05). The MPHS will be the vehicle for collection of HUIT data for the 2006-07 and 2007-08 reference periods in the future.

8 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.

HISTORICAL COMPARISONS

MPHS data

9 Due to the difference in the scope of previous surveys, household use of information technology (HUIT) data from the 2005-06 MPHS 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, but a small impact for the more complex questions cannot be ruled out.

CPCLA data

11 The CPCLA survey was previously conducted in 2000 and 2003 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 entirely used in the 2006 survey. These changes in the methodology and the questionnaire are not expected to impact on the comparability of the data between the three surveys.

12 Some changes were made to the survey's content between 2000 and 2003. In 2000, detailed data was collected for a maximum of six children per household, and selected demographic data for up to three more. In 2003 and 2006, detailed data was collected for a maximum of three children, per household, and selected demographic data was collected for up to ten more.

13 There were also some changes to the data items. These are:

• In 2003, involvement in Internet activities and emailing was collected as a single response. In 2006, these activities were separately identified. Similarly, emailing and accessing chat rooms were combined in 2003 but separately collected in 2006.
• In 2003, the category 'Playing games' on a computer included Internet based activities such as downloading games information. In 2006, computer activities relating to playing games using the Internet have been included in the category 'Internet based activities'. In 2006, the Internet activity 'Playing games' has been relabelled 'Playing on-line or Internet based games'.
• In 2003, the category 'other' activities relating to computer usage included downloading information (e.g. music, pictures, recipes) from the Internet. In 2006, computer activities relating to the Internet have been included in the category 'Internet based activities'.
• In 2003, the category 'other' activities relating to Internet usage included downloading music. In 2006, downloading music has been included in the separate category 'Downloading music from Internet sites'.

15 The sample was accumulated over a twelve month period (July 2005 to June 2006).

CPCLA

16 Information was collected through interviews conducted over a two week period during April 2006.

17 Information was collected from any responsible adult in the household who was asked to respond on behalf of the children in the household. About 75% of the interviews were conducted by telephone with the remainder being face-to-face interviews.

18 In each selected household, information relating to computer and Internet use was sought for a maximum of three children. In the 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.

SCOPE

LFS AND MPHS

19 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 special dwellings such as hotels, university residences etc
• students at boarding schools, patients in hospitals, residents of homes (e.g. retirement homes, homes for persons with disabilities), and inmates of prisons
• visitors to private dwellings
• people living in very remote Indigenous communities.

CPCLA

22 The scope of the supplementary survey was all children aged 5-14 years who were usual residents of private dwellings except:

• children in households where all persons aged 15 years and over were members of the Australian permanent defence forces
• children of certain diplomatic personnel of overseas governments, customarily excluded from censuses and surveys
• children of overseas residents in Australia
• children of members of non-Australian defence forces stationed in Australia.

COVERAGE

24 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

MPHS

25 The initial sample for the 2005-06 MPHS was 18,846 private dwelling households. Of the 16,212 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 14,219 or 88% fully responded to the MPHS.

CPCLA

26 In total, information was collected about the activities of 8,682 children living in the selected households.

WEIGHTING, BENCHMARKING AND ESTIMATION

27 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 and the CPCLA 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.

Benchmarking

28 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.

29 Since these surveys were last conducted, the process for producing household benchmarks has been refined. Whilst this process is still under review, it represents a significant improvement to the previous method and household benchmarks produced using the new method are considered sufficient quality for use in household survey estimation. In addition, measures of the variability in household benchmarks have been incorporated into household estimates for the first time. These changes may result in unexpected movements in total households (at some broad levels) due to revised benchmark methodology.

30 A paper describing these issues in detail is currently being developed and is due for release in early 2007 with catalogue number 3107.0.55.007

31 The surveys were benchmarked to the estimated civilian population aged 15 years and over living in private dwellings in each state and territory in non-sparsely settled areas.

Estimation

32 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

33 Certain data items such as estimates of income had significant non-response for 2005-06. 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 GROSS HOUSEHOLD INCOME QUINTILES

35 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%.

36 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.

37 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.

38 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.

39 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.

40 For more information on the use of equivalence scales, see Household Income and Income Distribution, Australia, 2003-04 (cat. no. 6523.0)

REMOTENESS

41 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

42 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.

43 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).

44 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.

45 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

47 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

48 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

49 Confidentialised Unit Record Files (CURF) release confidentialised microdata from surveys, thereby facilitating interrogation and analysis of data. For all MPHS topics covered in the 2005-06 survey, an expanded CURF will be available in 2007. The expanded CURF for MPHS 2004-05 topics are available. For more information on expanded CURFs refer to ABS information paper Multi-Purpose Household Survey 2004-05, Expanded Confidentialised Unit Record File (Cat. no. 4100.0)

COMPARABILITY WITH MONTHLY LFS STATISTICS

50 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

51 Tables 6.1 and 6.2 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.

52 There are important differences in definitions, scope, coverage and reference periods for the international comparison data included for selected indicators in the above tables. Significant differences are:

Reference Period and scope

53 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.

54 Generally, data from the European Union (EU) Community Survey on Household Use of ICT, which covers EU countries as well as Norway and Iceland, relate to the first quarter of the reference year. Australian data from MPHS relate to the financial year.

55 In table 6.1, data for Korea are sourced from the Survey on the "Computer and Internet usage" conducted by the National Internet Development Agency of Korea and include Internet access via computer and mobile phone. The scope for Mexico includes persons aged 6 years or over. New Zealand information is based on households in private occupied dwellings with access to the Internet with visitor only dwellings such as hotels excluded. For Switzerland, figures refer to sample based on individuals and private data from the organisation of Arbitsgruppe fur Werbemedienforschung. Data for Turkey relate to households in urban areas only.

56 For table 6.2, generally data from the EU Community Survey on household use of ICT, which covers EU countries plus Iceland, Norway and Turkey, relate to the first quarter of the reference year. For the Czech Republic, data relate to the fourth quarter of the reference year. For Korea, data include broadband access modes such as xDSL, cable and other fixed and wireless broadband via computers and mobile phone access. For Luxembourg, data include wireless access. For Mexico, data relate to households with Internet access via cable, ADSL or fixed wireless. For Turkey, data relate to households in urban areas only.

Definition of Broadband

57 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. However, Iceland only includes connections with a bandwidth equal to or greater than 2Mbps.

FUTURE SURVEYS

58 The ABS will conduct the MPHS again during the 2006-07 financial year. The topics included in the 2006-07 MPHS are:

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

ACKNOWLEDGEMENT

60 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

61 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, 2004-05 (Cat. no. 8129.0)
• Government Technology, Australia, 2002-03 (Cat. no. 8119.0)
• Household Use of Information Technology, Australia, 2004-05 (Cat. no. 8146.0)
• 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

63 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 Afroza Rahman, Canberra, (02) 6252 6365 or the National Information Referral Service on 1300 135 070.