1 This publication presents a summary of the findings from the 2017–18 Survey of Income and Housing (SIH). The survey collected detailed information about the income, wealth and household characteristics of persons aged 15 years and over in private dwellings throughout Australia (excluding very remote areas).
2 The Survey of Income and Housing, User Guide, Australia, 2017–18 (6553.0), here on referred to as the User Guide, will assist users to understand and utilise results from the SIH.
3 The SIH was conducted continuously from 1994–95 to 1997–98, and then in 1999–2000, 2000–01 and 2002–03. From 2003–04 the SIH has been conducted every two years. The 2017–18 SIH collected information from a sample of 14,060 households over the period July 2017 to June 2018.
4 Previous surveys of household income were conducted by the Australian Bureau of Statistics (ABS) in 1979, 1982, 1986 and 1990. These surveys were generally conducted over a two-month period, compared to a twelve-month period for the SIH. The SIH also included improvements to the survey weighting and estimation procedures, changes to the scope and coverage of household income and changes to interviewing methods from 1994–95 onwards.
5 In 2003–04, 2009–10 and 2015–16 the SIH was integrated with the Household Expenditure Survey (HES). In 2005–06, 2007–08, 2011–12, 2013–14 and 2017–18, the SIH was run as a stand-alone survey.
Changes in this issue
6 Key changes in 2017–18 compared with 2015–16 include:
- additional questions to have been asked to collect further information about the living arrangements of usual residents aged under 20 years of age who live in the household some of the time, but also spend time living with a parent/guardian elsewhere. Further to that questions have also been asked to determine the living arrangement of children (aged under 20 years) who spend time at the household but are not considered a usual resident.
- superannuation balances are no longer disseminated based on whether it is a government or non-government fund
- child care imputation was improved in the 2017–18 cycle
- credit card and HECS debt information is now collected at the person level and aggregated to the household level
- changes in Government payments and allowances categories to reflect Department of Social Security reporting (such as the removal of Baby Bonus, School Kids Allowance and Utilities Allowance)
- removal of question regarding supplement amount as it is now estimated by the eligibility based model designed by the Department of Social Security (model introduced in 2015–16)
- previous financial year income is no longer collected, except for business income
- business income question wording was improved to ensure franking credits were excluded from responses
- module on smoking status was included (output as part of National Health Survey) will be available on the SIH CURF, Tablebuilder and detailed file in the DataLab
7 To protect the confidentiality of individuals, a technique called perturbation is used to randomly adjust cell values. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.
8 After perturbation, a given published cell value will generally be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals.
9 The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as Table Builder.
Concepts and definitions
10 The concepts and definitions relating to income statistics are described in the following section of this publication. Other definitions are included in the ‘Glossary’ section of this publication.
Person and household data
11 Income is a major determinant of economic wellbeing for most people and households. While income is usually received by individuals, it is normally shared between partners in a couple relationship and, often, with dependent children. To a lesser extent, it may be shared with other children, other relatives and possibly other people living in the same household, for example through the provision of free or reduced accommodation costs. Even when there is no transfer of income between members of a household, and no provision of free or reduced accommodation costs, household members are still likely to benefit from some economies of scale that arise from sharing dwellings.
12 Income and wealth have a collective effect at the household level. As a result, households are the main unit of analysis in this publication. However, it is the number of people who belong to households with particular characteristics, rather than the number of households with those characteristics, that is of primary interest in measuring income distribution and leads to the preference for the equal representation of those persons in such analysis. For example, if the person is used as the unit of analysis rather than the household, then the representation in the income distribution of each person in a household comprising four persons is the same as that for each person in a two person household. In contrast, if the household were to be used as the unit of analysis, each person in the four person household would only have half the representation of each person in the two person household.
13 In this publication, the income distribution measures are all calculated with respect to persons, including children. Such measures are sometimes known as person weighted estimates. They are described in more detail in the User Guide. Nevertheless, as most of the relevant characteristics of persons relate to their household circumstances, data cubes available from the Data downloads section of this publication primarily describe the households to which people belong.
14 Household income consists of all current receipts, whether monetary or in kind, that are received by the household or by individual members of the household, and which are available for, or intended to support, current consumption.
15 Income includes receipts from:
- employee income (whether from an employer or own incorporated enterprise), including wages and salaries, salary sacrificed income, non-cash benefits, bonuses and termination payments
- government pensions and allowances
- profit/loss from own unincorporated business (including partnerships)
- net investment income (interest, rent, dividends, royalties)
- private transfers (e.g. superannuation, workers' compensation, income from annuities, child support, and financial support received from family members not living in the same household).
16 Receipts of Family Tax Benefit are treated as income, regardless of whether they are received fortnightly or as a lump sum. The Newborn Supplement and Newborn Upfront Payment replaced the Baby Bonus on 1 March 2014 and those eligible receive it as part of their Family Tax Benefit Part A payments for a period of 13 weeks or with their lump sum. The Paid Parental Leave payment has also been included as income.
17 The Energy Supplement is included in income from government pensions or allowances. This tax-exempt, indexed payment is paid to pensioners, other income support recipients, families receiving Family Tax Benefit payments and Commonwealth Seniors Health Card holders, provided they meet eligibility requirements.
18 In 2007–08, the ABS revised its standards for household income statistics following the adoption of new international standards in 2004 and review of aspects of the collection and dissemination of income data. The income estimates from 2007–08 onwards apply the new income standards, and are not directly comparable with estimates for previous cycles. The change in income level in 2007–08 is partly due to the change in methods but also partly due to real change in income. To the extent possible, the estimates for 2003–04 and 2005–06 shown in the time series tables also reflect the new treatments.
19 For more detail on the nature and impact of the changes on the income data see Appendix 4 of Household Income and Income Distribution, Australia, 2007–08.
20 Gross income is the sum of income from all sources before income tax and the Medicare levy have been deducted.
21 Disposable income better represents the economic resources available to meet the needs of households. It is derived by deducting estimates of personal income tax and the Medicare levy from gross income. Medicare levy surcharge was also calculated and deducted from gross income while calculating disposable income (as it was for the first time in 2007–08).
22 Income tax liability is estimated for all households using taxation criteria for the relevant financial year and the income and other characteristics of household members reported in the survey (such as private health insurance fund membership).
23 Prior to 2005-06 the derivation of disposable income also included the addition of Family Tax Benefit (FTB) paid through the tax system or as a lump sum by Centrelink. For practical reasons it was not included in the gross income estimates. From 2005-06 to 2013-14, FTB amounts were modelled for some households where amounts were not reported by the respondents. These amounts are not included in gross or disposable income from 2015-16. The introduction of a new model in 2015-16 for micro-editing government payments includes modelling of FTB values. These have been utilised where the reported amount was missing, significantly above the maximum eligible amount or where other payments, related to FTB, were reported by survey respondents, such as single parents with children under 8 years who receive Parenting Payment. More information about the effect of this change is available in the User Guide.
Equivalised disposable income
24 Most analyses in this publication use equivalised disposable household income rather than gross or disposable income. Using an equivalising factor for household income enables the direct comparison of the relative economic wellbeing of households of different size and composition (for example, lone person households, families and group households of unrelated individuals).
25 Equivalised disposable household income is calculated by adjusting disposable income by the application of an equivalence scale. The scale is based on the principle that larger households require a higher level of income to achieve the same standard of living as a smaller household. However, there are economies of scale, so each additional person does not equally add to the income needed to support household consumption.
26 Whereas disposable income includes negative values, these are adjusted to zero for the purpose of equivalised disposable household income
27 After 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.
28 For more information on equivalised income, see the User Guide.
Lowest income decile
29 Throughout the next few paragraphs, the terms quintile, decile and percentile are used. If a distribution, such as household income, is put in order from lowest to highest, and then divided into 100 equal groups, each group is a percentile. Ten percentiles make up a decile (ten equal groups) and twenty percentiles make up a quintile.
30 Equivalised income generally provides a useful indicator of economic wellbeing. However, some households report extremely low and even negative income in the survey, which places them well below the safety net of income support provided by government pensions and allowances. Households may under report their incomes in the survey at all income levels, including low income households. Households may also correctly report low levels of income if they have incurred losses in their unincorporated business or have negative returns from other investments.
31 Studies of income and expenditure reported in HES surveys 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 income decile). This suggests 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. Other households in the lowest income decile in past surveys had average incomes at about the level of the single pension rate, were predominantly single person households, and their main source of income was largely government pensions and allowances. However, on average, these households also had expenditures above the average of the households in the second income decile, which is not inconsistent with the use of assets to maintain a higher standard of living than implied by their incomes alone.
32 Other households in the lowest income decile in past surveys:
- had average incomes at about the level of the single pension rate
- were predominantly single person households
- their main source of income was largely government pensions and allowances.
However, on average, these households also had expenditures above the average of the households in the second income decile, which may be because these households are using assets to maintain a higher standard of living than their income alone could allow.
33 Some of the households included in the lowest income decile are unlikely to be suffering extremely low levels of economic wellbeing. Income distribution analysis may lead to inappropriate conclusions if such households are used as the basis for assessing low levels of economic wellbeing.
34 For this reason, in previous surveys, tables showing statistics classified by income quintiles included a supplementary category comprising the second and third income deciles, which were used as an alternative to the lowest income quintile.
35 More recent analysis suggests that this approach may have over-estimated the economic wellbeing of low income households, and unnecessarily excluded some of the most vulnerable households in the lowest income decile. The 2017–18 SIH uses the adjusted lowest income quintile that was introduced for the 2013–14 SIH cycle. The adjusted lowest income quintile is made up of the lowest two deciles, excluding the first and second percentiles, and has been calculated for previous cycles to create a time series of these data, available from the Data downloads section of this publication.
36 Income is collected using a number of different reporting periods. The reporting period is the whole financial year for own unincorporated business and investment income. In contrast, for wages and salaries, other sources of private income and government pensions and allowances, the reporting period is the most recent or usual payment, close to the time of interview. The income reported is divided by the number of weeks in the reporting period. Estimates of weekly income in this publication do not therefore refer to a given week within the reference period of the survey.
37 The tables in the main body of this publication refer to 'current' weekly income, that is, income being received at the time the data were collected from respondents. Previous financial year information is now only available for business income. The User Guide explains how current income differs from annual income, notes some of the advantages and disadvantages of the two types of measure and presents some 'annual' income estimates.
38 Imputed rent is an estimate of the amount of money that owner occupiers would have spent on housing if they were renting. The ABS estimates imputed rent to be able to compare household characteristics such as income across tenure types (owners, renters, non-market renters). Imputed rent may be understood as an adjustment to the income which takes into account the savings made by owning the household home or renting it at a subsidised rate.
39 Gross imputed rent is an estimate of how much it would cost to rent the household home.
40 Net imputed rent is gross imputed rent with housing costs (such as repairs and insurance) deducted, as these costs are incurred by owner occupiers, but generally not incurred by market renters.
41 Imputed rent is included in income on a net basis.
42 Base rental yields used in the estimation of gross imputed rent for individual owner-occupied dwellings have been updated in the 2017–18 SIH to include data from Census 2016 and CoreLogic RP Data from 2015–16 and 2016–17. Census medians used in the estimation of gross imputed rent for other tenure types have also been updated in the 2017–18 SIH to include data from Census 2016. Information on detailed methodology used to produce base rental yields and Census medians, and their use in calculations of gross imputed rent, can be found in Estimates of Imputed Rent, 2015–16.
Child care payments
43 Child care subsidies assist families with dependent children with the costs of childcare. Two subsidies are collected and modelled in the 2017–18 SIH. These are the Child Care Benefit and Child Care Rebate.
44 Child Care Benefit (CCB) is a payment from the Australian Government that assists families with the costs of registered or approved child care. The scheme is means-tested and allocates an hourly amount that can either be provided to child care consumers after child care has been paid, or directly paid to child care providers, thereby reducing the upfront child care fees payable by the consumer.
45 Child Care Rebate (CCR) is also an Australian Government payment that, like CCB, assists families with the cost of child care. Each child care consumer is entitled to CCR, which is 50% of their net child care costs. That is, a child care consumer is entitled to 50% of their child care costs after CCB has been deducted from the cost if they receive it, or else 50% of the whole cost. CCR payments accrue up to a per child, per year limit ($7,613 per child per year in 2017–18). CCR, like CCB, may be paid either to the consumer in a lump sum or directly to child care providers, thereby further reducing the upfront cost of child care.
46 Estimates of CCB and CCR are collected from the child care questions, however there has been a substantial gap between the reported number of households receiving child care subsidies and the total value of that assistance, compared to administrative records. CCB and CCR have been modelled to improve the accuracy of estimates of these payments. The output data is made up of both reported and modelled data. Child care assistance is conceptually treated as social transfers in kind, including administrative overhead as part of the value of the transfer.
Social transfers in kind
47 Social transfers in kind consist of goods and services provided free or at subsidised prices by the government. The allocation of social transfers in kind presented in this publication is restricted to government expenditure that is relatable to particular types of households. Information reported in the 2017–18 SIH was used as the basis for allocating social transfers in kind for the provision of education, health, housing, child care, electricity concessions and other social security and welfare services.
48 The total value of social transfers in kind was defined as Commonwealth, state or territory and local government expenses, net of intra-government transfers, minus government pensions and allowances paid in cash minus government revenue from the sale of goods and services.
49 The User Guide provides estimates of social transfers in kind and outlines the methodologies used to allocate the social transfers in kind to individual households in 2017–18.
50 Net worth, often referred to as wealth, is the value of a household's assets less the value of its liabilities.
51 Assets can take many forms including:
- produced tangible fixed assets that are used repeatedly and for more than one year, such as dwellings and their contents, vehicles, and machinery and equipment used in businesses owned by households
- intangible fixed assets such as computer software and artistic originals;
- business inventories of goods
- non-produced assets such as land
- financial assets such as bank deposits, shares, superannuation account balances, and the outstanding value of loans made to other households or businesses.
52 Liabilities are primarily the value of loans outstanding including:
- credit card debt
- investment loans
- borrowings from other households
- debt on other loans such as personal loans to purchase vehicles, and study loans.
53 In the 2017–18 SIH, some asset and liability data were collected on a net basis rather than collecting for each component listed above. In particular, if a survey respondent owned or part owned a business, they were asked how much they would receive if they sold their share of the business and paid off any outstanding debts.
Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA)
54 The Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA) is a geographic index which quantifies service accessibility within metropolitan areas. The index reflects the ease or difficulty people face accessing basic services within metropolitan areas, derived from the measurement of road distances people travel to reach different services, and covers five different service themes:
- public transport
- financial/postal services.
55 Metro ARIA covers 2011 Greater Capital City Statistical Area (GCCSA) by 2011 Statistical Area 1. Areas outside GCCSAs are defined as non-metropolitan. Non-metropolitan should not be interpreted as lower accessibility; it is simply that the region is located outside the capture area detailed Metro ARIA. Further information regarding Metro ARIA and maps can be found via the following link: https://data.aurin.org.au/dataset/ua-hcmpr-adh-hcmpr-sa1-metro-aria-2014-australia-sa1
56 The survey collects information by personal interview from usual residents of private dwellings in urban and rural areas of Australia (excluding very remote areas), covering about 97% of the people living in Australia. Private dwellings are houses, flats, home units, caravans, garages, tents and other structures that were used as places of residence at the time of interview. Long-stay caravan parks are also included. These are distinct from non-private dwellings which include hotels, boarding schools, boarding houses and institutions. Residents of non-private dwellings are excluded.
57 'Usual residents' excludes:
- households which contain members of non-Australian defence forces stationed in Australia
- households which contain diplomatic personnel of overseas governments
- households in areas defined as very remote - this has only a minor impact on aggregate estimates, except in the Northern Territory where such households account for about 23% of the population.
58 Information for each household was collected using:
- a household level computer assisted interview questionnaire which collected information on household characteristics
- an individual level computer assisted interview questionnaire which collected information on income, wealth, child care costs and other personal characteristics from each usual resident aged 15 years and over;
59 Sample copies of the above collection tools are included in the User Guide.
60 The sample was designed to produce reliable estimates for broad aggregates for households resident in private dwellings aggregated for Australia, for each state and for the capital cities in each state and territory. More detailed estimates should be used with caution, especially for Tasmania, the Northern Territory and the Australian Capital Territory.
61 For the 2017–18 SIH, dwellings were selected through a stratified, multistage cluster design from the private dwelling framework of the ABS Population Survey Master Sample. Selections were distributed across a twelve month enumeration period so that the survey results are representative of income patterns across the year.
62 Of the selected dwellings there were 23,049 households in the scope of the survey. Of this initial sample, 3,967 dwellings (17%) were excluded as no contact was able to be made (e.g. vacant dwelling, holiday homes). A further 5,022 (22%) did not respond at all to the questionnaire, or did not respond adequately. Most of these were not able to take part in the survey during the collection period. Other reasons included:
- households affected by death or illness of a household member
- households which did not respond due to communication barriers or because they refused to participate.
63 357 households were excluded because the main income earners in the household did not adequately respond to questions about income sources and amounts.
Partial response and imputation
64 Partial imputation is completed for all households with missing data items. Donor records are selected by finding fully responding persons with matching information on various characteristics (such as state, sex, age, labour force status and income) as the person with missing information. As far as possible, the imputed information is an appropriate proxy for the information that is missing. Depending on which values are to be imputed, donors are randomly chosen from the pool of individual records with complete information for the block of questions where the missing information occurs
65 The final SIH sample includes 3,745 households (27% of households) and 9,946 person records (30% of persons aged 15 years or over) which had at least one imputed value. Of all the relevant items (continuous variables), 4.1% of values were imputed. This is slightly higher than SIH 2015–16 where HES was jointly collected (3.5%) and similar to the last SIH only cycle 2013–14 (3.9%).
66 Of the selected dwellings (19,082) that were contacted and in scope of the survey, 14,060 (74%) households were included as part of the final estimates.
|GREATER CAPITAL CITY||REST OF STATE||TOTAL|
|NSW||1 321||2 818||1 030||1 929||2 351||4 747|
|Vic.||1 333||2 712||1 113||2 064||2 446||4 776|
|Qld||965||1 856||1 030||1 878||1 995||3 734|
|SA||1 121||2 150||1 045||1 830||2 166||3 980|
|WA||1 019||2 031||1 149||2 147||2 168||4 178|
|Tas.||589||1 058||1 031||1 902||1 620||2 960|
|ACT(b)||773||1 522||. .||. .||773||1 522|
|Aust.||7 549||14 968||6 511||11 953||14 060||26 921|
. . not applicable
a. Number of persons aged 15 years and over
b. Greater Capital City counts for the ACT relate to total ACT
Survey of Income and Housing, final sample, 2017–18
67 Weighting is the process of adjusting results from a sample survey to infer results for the total in scope population whether that be persons or households. To do this, a weight is allocated to each sample unit (e.g. 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. For example, if the probability of a household being selected in the survey was 1 in 600, then the household would have an initial weight of 600 (that is, it represents 600 households). The initial weights are then calibrated to align with independent estimates of the population of interest, referred to as benchmarks. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than to the distribution within the sample itself.
68 Most of the independent person and household benchmarks are based on demography estimates of numbers of persons and households in Australia. The benchmarks are adjusted to include persons and households residing in private dwellings only and to exclude persons living in very remote areas, and therefore do not, and are not intended to, match estimates of the Australian resident population published in other ABS publications. The demography estimates of persons (estimated resident population - ERP) and households used in SIH 2017–18 are built up from the 2016 Census.
69 In the 2017–18 SIH, as in 2007–08, 2009–10, 2011–12, 2013–14 and 2015–16, all persons in each household were assigned a weight. This differs from the 2005–06 SIH where children aged 0–14 years were not given separate weights, but household counts of the number of children were benchmarked to population totals.
70 The benchmarks used in the calibration of the final weights for the 2017–18 SIH were:
- number of persons
- by state or territory by age by sex
- in five year age groups up to 80+ years for all states and territories (excluding NT)
- in five year age groups up to 70+ years for the NT
- by state or territory by labour force status ('Employed', 'Unemployed' and 'Not in the labour force') (except NT which does not use labour force status)
- by state or territory by age by sex
- numbers of households
- by state, by indexation quarter by capital city/balance of state (except NT and ACT which only use state)
- by state, by household composition (number of adults (1, 2 or 3+) and whether or not the household contains children) (except NT which only uses whether or not the household contains children)
71 Estimates produced from the survey are usually in the form of averages (e.g. average weekly income of couple households with dependent children), or counts (e.g. total number of households that own their dwelling or total number of persons living in households that own their own dwelling). For counts of households, the estimate was obtained by summing the weights for the responding households in the required group (e.g. those owning their own dwelling). For counts of persons, the household weights were multiplied by the number of persons in the household before summing. The SIH collects data on the number of people, including children, in each household but separate records with income and most detailed data were only collected for people 15 years and older.
72 Average income values are obtained in two different ways, depending on whether mean gross household income or mean equivalised disposable household income is being derived. Estimates of mean gross household income are calculated on a household weighted basis. They are obtained by multiplying the gross income of each household by the weight of the household, summing across all households and then dividing by the estimated number of households. For example, the mean gross household income of couple households with dependent children is the weighted sum of the gross income of each such household divided by the estimated number of those households.
73 Estimates of mean equivalised disposable household income are calculated on a person weighted basis. They are obtained by multiplying the equivalised disposable income of each household by the number of people in the household (including children) and by the weight of the household, summing across all households and then dividing by the estimated number of people in the population group. The User Guide illustrates the differences between mean gross household income calculated on a household weighted basis and mean equivalised disposable household income calculated on a person weighted basis.
Reliability of estimates
74 The estimates provided in this publication are subject to two types of error, non-sampling and sampling error.
75 Non-sampling error can occur in any collection, whether the estimates are derived from a sample or from a complete collection such as a census. Sources of non-sampling error include non-response, errors in reporting by respondents or recording of answers by interviewers and errors in coding and processing the data.
76 Non-sampling errors are difficult to quantify in any collection. However, every effort is made to reduce non-sampling error to a minimum by careful design and testing of the questionnaire, training of interviewers and data entry staff and editing and quality control procedures during data processing.
77 One of the main sources of non-sampling error is non-response by persons selected in the survey. Non-response occurs when people cannot or will not cooperate or cannot be contacted. Non-response can affect the reliability of results and can introduce a bias. The magnitude of any bias depends upon the level of non-response and the extent of the difference between the characteristics of those people who responded to the survey and those who did not.
78 The following methods were adopted to reduce the level and impact of non-response:
- Primary Approach Letters (PALs) were posted to selected SIH households prior to enumeration
- document cards were provided to respondents to suggest having financial statements and similar documents handy at the time of interview to assist with accurate responses
- face-to-face interviews with respondents
- the use of interviewers who could speak languages other than English, where necessary
- proxy Interviews conducted when consent is given, with a responsible person answering on behalf of a respondent incapable of doing so themselves
- follow-up of respondents if there was initially no response
- imputation of missing values
- ensuring that the weighted data is representative of the population (in terms of demographic characteristics) by aligning the estimates with population benchmarks.
79 The estimates are based on a sample of possible observations and are subject to sampling variability. The estimates may therefore differ from the figures that would have been produced if information had been collected for all households. A measure of the sampling error for a given estimate is provided by the standard error, which may be expressed as a percentage of the estimate (relative standard error). In this publication, estimates with an RSE of 25% to 50% are preceded by an asterisk (e.g. *3.4) to indicate that the estimate has a high level of sampling error relative to the size of the estimate, and should be used with caution. Estimates with an RSE over 50% are indicated by a double asterisk (e.g. **0.6) and are generally considered too unreliable for most purposes.
80 Another measure is the Margin of Error (MoE), which are provided for proportions to assist users in assessing the reliability of these data. Estimates of proportions with an MoE more than 10% are annotated to indicate they are subject to high sample variability and particular consideration should be given to the MoE when using these estimates. Depending on how the estimate is to be used, an MoE greater than 10% may be considered too large to inform decisions. In addition, estimates with a corresponding standard 95% confidence interval that includes 0% or 100% are annotated with a # to indicate that they are usually considered unreliable for most purposes.
81 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.
Products and services
82 Summary results from the SIH are available in spreadsheet form from the Data downloads section in this release.
83 For users who wish to undertake more detailed analysis you can access SIH microdata products. These include:
- TableBuilder (available July 2019) - an online tool for creating tables from ABS survey data, where variables can be selected for cross-tabulation.
- Detailed file available via the DataLab (available July 2019) - approved users can access a remote desktop environment for in-depth analysis using a range of statistical software packages
- Basic confidentialised unit record file (CURF) (available August 2019) - allows approved users interactive access in the user’s own computing environment
Further information about ABS microdata, including conditions of use, and access is available via the Microdata section on the ABS website.
84 The ABS offers specialist consultancy services to assist clients with more complex statistical information needs. Clients may wish to have the unit record data analysed according to their own needs, or require tailored tables incorporating data items and populations as requested by them. Tables and other analytical outputs can be made available electronically or in printed form. However, as the level of detail or disaggregation increases with detailed requests, the number of contributors to data cells decreases. This may result in some requested information not being able to be released due to confidentiality or sampling variability constraints. All specialist consultancy services attract a service charge, and clients will be provided with a quote before information is supplied.
86 The Survey of Income and Housing, User Guide, Australia, 2017–18 includes information about the purpose of the survey, the concepts and contents, and the methods and procedures used to collect the data and derive the estimates. It also outlines the differences between the 2017–18 survey and earlier SIH surveys. Its purpose is to help users of the data understand the nature of the survey, and its potential to meet user needs.