• Summary
• Downloads
• Explanatory Notes
• Related Information
• Past Releases

INTRODUCTION

1 This release presents results for Household Use of Information Technology (HUIT) collected from the Multipurpose Household Survey (MPHS) for 2012–13 by the Australian Bureau of Statistics (ABS).

2 The MPHS is conducted each year as a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics. In 2012–13 these topics were:

• Household use of information technology
• Crime victimisation
• Family characteristics and family transitions and history
• Patient experience
• Barriers and incentives to labour force participation
• Retirement and retirement intentions.

• Children's use of the Internet and mobile phones in Children's Participation in Culture and Leisure Activities, Australia, Apr 2012 (cat. no. 4901.0); and
• Disabled and older persons use of computers and the internet in Disability, Ageing and Carers, Australia: Summary of Findings, 2012 (cat. no. 4430.0).
  

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

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

11 The LFS applies coverage rules that aim to ensure each person is associated with only one dwelling and hence has only one chance of selection in the survey. MPHS coverage rules are the same as those for the monthly LFS with the exception that people living in Indigenous Communities in very remote areas were not enumerated for operational reasons. Nationally, less than 1% of people in-scope of the MPHS live in Indigenous Communities in very remote areas. The majority are in Northern Territory where approximately 16% of the in-scope population are in very remote Indigenous Communities.

SAMPLE SIZE

12 The initial sample for the household use of information technology topic was 23,016 private dwellings, from which one randomly selected person per household was asked about their household's access to (and their own use of) the internet. Of the 19,632 private dwellings that remained in the survey after sample loss, 15,433 private dwellings (79%) fully responded to the questions on the household use of information technology.

WEIGHTING, ESTIMATION AND BENCHMARKING

13 Weighting is the process of adjusting data from a sample survey to infer data for the total in-scope population. To do this a 'weight' is allocated to each sample unit, which can be either a person or a household for the MPHS. The weight is a value which indicates how many population units are represented by the sample unit. For the MPHS, the first step in calculating weights for each unit was to assign an initial weight, which is the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (i.e. they represent 600 people). The initial weights were then calibrated to align with independent estimates of the population of interest, referred to as benchmarks.

14 The 2012–13 survey was benchmarked to the projected civilian population aged 15 years and over, living in private dwellings in each state and territory. 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. The estimation procedure ensures estimates of persons calibrate exactly to independently produced population totals at broad levels. The known population totals 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 as this population is not known.

15 The person benchmarks used for the 2012–13 MPHS were based on the projected population for March 2013. These benchmarks were based on the published figures for the December 2012 quarter (Australian Demographic Statistics, Dec 2012 (cat. no. 3101.0)). Therefore, the benchmarks used in this survey will differ slightly from the actual estimates produced for the March 2013 quarter.

INCOME LESS THAN ZERO

16 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.

EQUIVALISED HOUSEHOLD INCOME

17 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.

18 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.

19 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.

20 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.

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

EQUIVALISED HOUSEHOLD INCOME QUINTILES

22 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%.

CLASSIFICATIONS USED

23 Country of birth data are classified according to the Standard Australian Classification of Countries (SACC), 2011 (cat. no. 1269.0).

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

25 Occupation data are classified according to the ANZSCO - Australian and New Zealand Standard Classification of Occupations, Version 1.2, 2013 (cat. no. 1220.0).

26 Remoteness Areas and Section of State (SOS) are classified according to the Australian Standard Geographical Classification (ASGC), July 2011 (cat. no. 1216.0).

27 In each state, Urban includes the SOS categories of:

• 0 - Major Urban: urban areas with a population of 100,000 and over; and
• 1 - Other Urban: urban areas with a population of 1,000 to 99,999.

• 2 - Bounded Locality: small towns with a population of 200 to 999; and
• 3 - Rural balance .
  

• Internet Activity, Australia, June 2013 (cat. no. 8153.0)
• Disability, Ageing and Carers, Australia: Summary of Findings, 2012 (cat. no. 4430.0)
• Children's Participation in Cultural and Leisure Activities, Australia, Apr 2012 (cat. no. 4901.0)
• Business Use of Information Technology, 2011–12 (cat. no. 8129.0)
• Summary of IT Use and Innovation in Australian Business, 2011–12 (cat. no. 8166.0)