Household Income and Wealth, Australia methodology

Latest release
Reference period
2019-20 financial year

How the data is collected


This publication presents a summary of the findings from the 2019–20 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.

The Survey of Income and Housing, User Guide, Australia, 2019–20, referred to as the User Guide, is intended to assist users ability to understand and utilise results from the SIH.

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 was conducted every two years. The 2019–20 SIH collected information from a sample of 15,011 households over the period July 2019 to June 2020.

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.

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, 2017–18 and 2019–20, the SIH was run as a stand-alone survey.

Changes in this issue

Key changes in 2019–20 compared with 2017–18 include:

  • collection methodology for 2019–20 included the introduction of an online form (formally; computer assisted web interview, or CAWI), where the respondent could self report (without interviewer assistance). As a result, estimates may not be directly comparable to previous cycles (See collection Method section for more information).
  • a general review of the questions, populations and sequencing was undertaken to optimise survey content for online collection
  • the Household Form was redesigned as part of the Integrated Household Surveys Program to produce common content across various household surveys
  • cyclical housing content was collected this cycle, including changes in rent payments which was last collected in 2007–08
  • the child care module was largely restructured for online collection and to address payment changes. The Child Care Rebate (CCR) and Child Care Benefit (CCB) were no longer collected for children aged 12 and under. The Child Care Subsidy (CCS) replaces the CCR and CCB and is now collected for children aged 13 and under. 
  • superannuation: use of lump sum payments is not collected
  • financial stress indicators have been altered comparative to what was collected in the combined SIH and HES from 2015-16 (HIES) ie. the $500 emergency funds, heat cool home, dental treatment. Additional content on financial behaviours and resilience have been included, in line with the General Social Survey
  • Additional content on financial behaviours and resilience have been included, in line with the General Social Survey
  • Social transfers in kind (STIK) data is no longer collected in cyclical housing years
  • changes in Government payments and allowances categories to reflect Department of Social Security reporting (such as Newstart allowance changed to JobSeeker allowance)
  • family changes and smoking status modules were not collected for this cycle.

Data Collection


The scope of the survey includes:

  • all usual residents in Australia aged 15 years and over living in private dwellings
  • both urban and rural areas in all states and territories

 The survey excludes the following:

  • visitors to private dwellings
  • overseas visitors who have not been working or studying in Australia for 12 months or more, or do not intend to do so
  • members of non-Australian defence forces stationed in Australia and their dependants
  • non-Australian diplomats, diplomatic staff and members of their households
  • people who usually live in non-private dwellings, such as hotels, motels, hostels, hospitals, nursing homes and short-stay caravan parks
  • households in very remote areas
  • households in discrete Aboriginal and Torres Strait Islander communities.

The exclusion of very remote areas is unlikely to impact on national estimates and will only have a minor impact on any aggregate estimates that are produced for individual states and territories, except the Northern Territory where the excluded population accounts for around 21% of the population. 

The 2019–20 SIH was carried out from July 2019 to June 2020. During this time, Australians were impacted by bushfires and COVID-19. The data collection design for this survey was optimised to meet operational objectives. As a result, the sample design and collection of 2019-20 SIH does not accurately reflect the household impacts of the bushfires nor COVID-19. 

Collection method

SIH 2019-20 introduced a change in collection methods to allow for online collection. This change gave respondents the option to complete the survey online or face-to-face with an ABS interviewer. Due to COVID-19 restrictions from late March 2020, telephone interviewing replaced face-to-face interviewing.

The survey interview commenced with one adult (aged 18 years and over) who acted as the household's representative and answered questions about the household's financial situation (for example rent, rates, and loan payments) on behalf of the whole household. Each person aged 15 years and over, then completed a personal interview, answering questions about their education, employment, income, and wealth.

Analysis of survey results by enumeration method is not available due to the sample design restricting comparability. However, a post-collection data review found some differences in how a typical online respondent reports information compared to respondents with an interviewer. Online enumeration data provided an insight into concepts that some respondents had difficulties answering. Rigorous data checks were undertaken by the ABS to ensure sample coverage, estimation methods and survey weighting are accurate. However, this fundamental change in collection methodology may impact survey cycle comparability against previous cycles.

Comparability with preliminary estimates

Preliminary results from SIH 2019-20 were released in December 2020 (see Household financial resources, Methodology, Australia, June 2020). The preliminary estimates involved similar but less extensive coding and editing checks than those which are performed on these annual estimates. This includes treatment of statistical outliers and removal of households that did not provide sufficient principal information. Some more intensive processing tasks were also not performed in producing preliminary estimates. This resulted in more of the sample being excluded from preliminary estimates, when compared to annual estimates.  As such, final estimates and data movements may not directly align with preliminary findings.

Sample design

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.

For the 2019–20 SIH, dwellings were selected through a stratified, multi-stage 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.

Non-Responding households

Of the selected dwellings there were 23,552 households in the scope of the survey. Of this initial sample, 3,458 dwellings (17%) were excluded as no contact was able to be made (e.g. vacant dwelling, holiday homes). A further 4,580 (19%) 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.

A further 68 households were excluded because the main income earners in the household did not adequately respond to questions about income sources and amounts.

Final sample

Of the selected dwellings (19,263) that were contacted and in scope of the survey, 15,011 (78%) households were included as part of the final estimates.

Survey of Income and Housing, Final sample, 2019–20
Households no.Persons(a) no.Households no.Persons(a) no.Households no.Persons(a) no.

. . not applicable
(a) Number of persons aged 15 years and over
(b) Greater Capital City counts for the ACT relate to total ACT

How the data is processed


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 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.

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 are the weighted sum of the gross income of each such household divided by the estimated number of those households.

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.


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.

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 2019–20 are built up from the 2016 Census.

In the 2019–20 SIH, as previous cycles since 2007–08, 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.

The benchmarks used in the calibration of the final weights for the 2019–20 SIH were categorised into two groups:

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 and ACT)
  • in five year age groups up to 70+ years for the ACT
  • in five year age groups up to 65+ 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 2016 SEIFA Index for Relative Socioeconomic Disadvantage decile of household (state level).

Numbers of households:

  • 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).

Partial response and imputation

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). Where possible, the imputed information is used as an appropriate proxy for the missing information.

The final SIH sample includes 2,178 households (15% of households) and 11,421 person records (39% of persons aged 15 years or over) which had at least one imputed value.

How the data are released


The Census and Statistics Act 1905 authorises the ABS to collect statistical information and requires that information is not published in a way that could identify a particular person or organisation. The ABS must make sure that information about individual respondents cannot be derived from published data.

To minimise the risk of identifying individuals in aggregate statistics, a technique called perturbation is used to randomly adjust cell values. Perturbation involves small random adjustment of the statistics which have a negligible impact on the underlying pattern. This is considered the most satisfactory technique for avoiding the release of identifiable data while maximising the range of information that can be released. 


Concepts and definitions

The concepts and definitions relating to income statistics are described within this section of this publication. Other definitions are included in the ‘Glossary’ section of this publication.

Person and household data

Income is a major determinant of economic well-being for most people and households. While income is usually received by individuals, it is assumed to be 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 shared dwellings.

Income and wealth have a collective effect at the household level. As a result, households are the main unit of analysis in this publication. 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.

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 and are described in more detail in the User Guide. As most of the relevant characteristics of persons relate to their household circumstances, data cubes are available from the Data downloads section of this publication primarily describe the households to which people belong.


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.

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).

Receipts of Family Tax Benefit are treated as income, regardless of whether they are received fortnightly or as a lump sum. Payments of the Newborn Supplement and Newborn Up-front Payment are received as part of the 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.

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.

Income measures

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.

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.

Gross income

Gross income is the sum of income from all sources before income tax and the Medicare levy have been deducted.

Disposable income

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 is also calculated and deducted from gross income while calculating disposable income (as it was for the first time in 2007–08).

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).

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

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 well-being of households of different size and composition (for example, lone person households, families and group households of unrelated individuals).

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.

Whereas disposable income includes negative values, these are adjusted to zero for the purpose of equivalised disposable household income

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 well-being as the household in question. 

For more information on equivalised income, see the User Guide.

Lowest income decile

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.

Equivalised income generally provides a useful indicator of economic well-being. 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.

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. 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.

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.

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.

Some of the households included in the lowest income decile are unlikely to be suffering extremely low levels of economic well-being. Income distribution analysis may lead to inappropriate conclusions if such households are used as the basis for assessing low levels of economic well-being.

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.

More recent analysis suggests that this approach may have over-estimated the economic well-being of low-income households, and unnecessarily excluded some of the most vulnerable households in the lowest income decile. The 2019–20 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 in this publication.

Current income

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.

Annual income

The tables in 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.

Imputed rent

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.

Gross imputed rent is an estimate of how much it would cost to rent the household home.

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.

Imputed rent is included in income on a net basis.

Base rental yields used in the estimation of gross imputed rent for individual owner-occupied dwellings have been updated in the 2019–20 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 2019–20 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

The Child Care Subsidy (CCS) is the main way the Australian Government financially supports families with child care fees. The CCS replaced two previous payments: the Child Care Benefit and the Child Care Rebate. CCS is generally paid directly to care providers who pass the subsidy on to families through a fee reduction. Families therefore pay the difference between the provider’s fee and the subsidy amount. 

Unless an exemption applies, to be eligible for CCS a child must be aged 13 or less and must not be attending secondary school. The level of CCS a family receives depends on three factors: family income, the service type used and parent activity. The combined income of both parents in a two parent household, or the sole income in a single parent household is used to determine the applicable rate of CCS. The rate of CCS is then applied to either the hourly fee charged or the relevant hourly rate cap, whichever is lower. The relevant hourly rate cap is differs according to which type of approved child care service is used. Lastly, the activity test determines how many hours of child care can be subsidised by the CCS per fortnight. The activity test is determined using the parent with the lowest level of recognised activity (e.g. work hours).

A supplementary payment was introduced at the same time as the CCS, the Additional Child-Care Subsidy (ACCS). The ACCS provides top up assistance in addition to the CCS for children at risk of abuse or neglect, families experiencing financial hardship, families transitioning to work from income support and grandparent carers on income support. The ACCS replaced a number of previous payments including the Special Child-Care Benefit, Grandparent Child-Care Benefit and the Jobs, Education and Training Child-Care Fee Assistance payment.

Net worth

Net worth, often referred to as wealth, is the value of a household's assets less the value of its liabilities.

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.

Liabilities are primarily the value of loans outstanding including:

  • credit card debt
  • mortgages
  • investment loans
  • borrowings from other households
  • debt on other loans such as personal loans to purchase vehicles, and study loans. 

In the 2019–20 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.

Quality declaration

Institutional environment

For information on the institutional environment of the Australian Bureau of Statistics (ABS), including the legislative obligations of the ABS, financing and governance arrangements, and mechanisms for scrutiny of ABS operations, please see ABS Institutional Environment.


The Survey of Income and Housing (SIH) collects detailed information on income, wealth, housing, characteristics of individuals, income units and households from a sample of private dwellings throughout Australia.

The survey collects information by personal interview from usual residents of private dwellings in urban and rural areas of not Very Remote Australia, covering approximately 97% of the people living in private dwellings in Australia.

The survey facilitates the analysis and monitoring of the social and economic welfare of Australians in private dwellings. The main users are government and other social and economic analysts involved in the development, implementation and evaluation of social and economic policies.

Income and wealth data are used by economic and social analysts and policy makers to:

  • understand the distribution of economic resources among private households in Australia
  • identify households most at risk of experiencing economic hardship
  • understand the effects of taxation and welfare payments on people and families.

Housing data are used for:

  • housing affordability studies
  • analysis of housing conditions and occupancy, including levels of home ownership and housing utilisation
  • tracking changes in housing costs by tenure type over time.


The SIH is conducted every two years. The 2019–20 SIH collected information over the period early July 2019 to late June 2020.

The first results from the 2019–20 survey was released on 28 April 2022. Subsequent outputs, including other publications and microdata products will be released from May 2022 onwards.


Reliability of the estimates

The estimates provided from the Survey of Income and Housing (SIH) are subject to two types of error: 

  • non-sampling error    
  • sampling error

Non-sampling error

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.

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.

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.

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
  • official guide to complete the survey online
  • face-to-face, online and telephone 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.

Sampling error

Sampling error is the expected difference that can occur between the published estimates and the value that would have been produced if the whole population had been surveyed. Sampling error is the result of random variation and can be estimated using measures of variance in the data.

Standard error

One measure of sampling error is the standard error (SE). There are about two chances in three that an estimate will differ by less than one SE from the figure that would have been obtained if the whole population had been included. There are about 19 chances in 20 that an estimate will differ by less than two SEs.

Relative standard error

The relative standard error (RSE) is a useful measure of sampling error. It is the SE expressed as a percentage of the estimate:

\(R S E \%=\left(\frac{S E}{e s t i m a t e}\right) \times 100\)

Only estimates with RSEs less than 25% are considered reliable for most purposes. Estimates with larger RSEs, between 25% and less than 50% have been included in the publication, but are flagged to indicate they are subject to high SEs. These should be used with caution. Estimates with RSEs of 50% or more have also been flagged and are considered unreliable for most purposes. RSEs for these estimates are not published.

Margin of error for proportions

Another measure of sampling error is the Margin of Error (MOE). This describes the distance from the population value that the sample estimate is likely to be within and is particularly useful to understand the accuracy of proportion estimates. It is specified at a given level of confidence. Confidence levels typically used are 90%, 95% and 99%.

For example, at the 95% confidence level, the MOE indicates that there are about 19 chances in 20 that the estimate will differ by less than the specified MOE from the population value (the figure obtained if the whole population had been enumerated). The 95% MOE is calculated as 1.96 multiplied by the SE:

\(MOE = SE \times 1.96\)

The RSE can also be used to directly calculate a 95% MOE by:

\({MOE}(y) \approx \frac{R S E(y) \times y}{100} \times 1.96\)

The MOEs in this publication are calculated at the 95% confidence level. This can easily be converted to a 90% confidence level by multiplying the MOE by:

\({1.615 \over 1.96}\)

or to a 99% confidence level by multiplying the MOE by:

\({2.576 \over 1.96}\)

Depending on how the estimate is to be used a MOE of greater than 10% may be considered too large to inform decisions. For example, a proportion of 15% with a MOE of plus or minus 11% would mean the estimate could be anything from 4% to 26%. It is important to consider this range when using the estimates to make assertions about the population.


Confidence intervals

A confidence interval expresses the sampling error as a range in which the population value is expected to lie at a given level of confidence. A confidence interval is calculated by taking the estimate plus or minus the MOE of that estimate. In other terms, the 95% confidence interval is the estimate +/- MOE. 


Calculating measures of error

Proportions or percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. A formula to approximate the RSE of a proportion is given below. This formula is only valid when the numerator (x) is a subset of the denominator (y):

\({RSE}\left(\frac{x}{y}\right) \approx \sqrt{[R S E(x)]^{2}-[R S E(y)]^{2}}\)

When calculating measures of error, it may be useful to convert RSE or MOE to SE. This allows the use of standard formulas involving the SE. The SE can be obtained from RSE or MOE using the following formulas:

\(SE = {RSE\%\times estimate \over 100}\)

\(SE = {MOE \over 1.96}\)

Comparison of estimates

The difference between two survey estimates (counts or percentages) can also be calculated from published estimates. Such an estimate is also subject to sampling error. The sampling error of the difference between two estimates depends on their SEs and the relationship (correlation) between them. An approximate SE of the difference between two estimates (x - y) may be calculated by the following formula:

\(S E(x-y) \approx \sqrt{[S E(x)]^{2}+[S E(y)]^{2}}\)

While this formula will only be exact for differences between unrelated characteristics or sub-populations, it provides a reasonable approximation for the differences likely to be of interest in this publication. 

Significance testing

When comparing estimates between surveys or between populations within a survey, it is useful to determine whether apparent differences are 'real' differences or simply the product of differences between the survey samples. 

One way to examine this is to determine whether the difference between the estimates is statistically significant. This is done by calculating the standard error of the difference between two estimates (x and y) and using that to calculate the test statistic using the formula below:

\(\left(\frac{x-y}{S E(x-y)}\right)\)


\(S E(y)=\frac{R S E(y) \times y}{100}\)

If the value of the statistic is greater than 1.96, we can say there is good evidence of a statistically significant difference at 95% confidence levels between the two populations with respect to that characteristic. Otherwise, it cannot be stated with confidence that there is a real difference between the populations.


The SIH provides baseline income and wealth information which provides a comparison point for the Census, and other ABS and external surveys. Selected comparisons with other ABS sources and a comparison between items collected in the SIH and the Australian System of National Accounts will be provided on the Data downloads section of the User Guide. There are some differences between the SIH and these other sources for various reasons, including scope, coverage, period and definitional differences (standardised where possible), non-response, and potential under- and over-estimates of some items in the SIH.

Each cycle of the SIH collects comparable information to allow for analysis of changes over time.

Various statistics can be utilised to make comparisons between 2019–20 SIH data and data from previous SIH cycles. These include the Gini coefficient (a summary measure of income and wealth distribution and inequality), proportions (e.g. proportional share of income and wealth), means and medians. Wherever comparisons of prior cycles are made in the data cubes, CPI adjusted data has been provided to allow for analysis of real change after inflation is taken into account.

The ABS seeks to maximise consistency and comparability over time by minimising changes to the survey. Sound survey practice, however, requires ongoing development and maintenance to maintain the integrity of the data and the efficiency of the collection. The change in survey collection methodology for SIH 2019-20 affects cycle-to-cycle comparability. Current income and wealth standards are available on the ABS website and more information is available in the Methodology section of this publication and the User Guide publication.


Detailed information on the terminology, classifications and other technical aspects associated with the SIH are listed throughout this Methodology section. Additional information can be found in the Glossary included with this publication and the Survey of Income and Housing, User Guide, Australia.



Tabulated data and associated relative standard errors are freely available in Excel spreadsheets which can be accessed from the Data downloads section.

A Basic microdata product will be produced from the SIH, subject to the approval of the Australian Statistician. For further details, refer to the Microdata Entry Page on the ABS website. It is expected that the Basic microdata unit record files will be available in June 2022.

Customised data are also available on request. Note that detailed data can be subject to high relative standard errors which in some cases may result in data being regarded as unfit for release. A data item list is available from the Data downloads section of the Survey of Income and Housing, User Guide, Australia.

For inquiries about these and related statistics, contact the Customer Assistance Service via the ABS website Contact Us page. The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us. 



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

Summary results from the SIH are available in spreadsheet form from the Data downloads section in this release.

For users who wish to undertake more detailed analysis you can access SIH microdata products. These include:

  • Detailed file accessible via the DataLab (available June 2022) - approved users can access a remote desktop environment for in-depth analysis using a range of statistical software packages
  • Basic microdata unit record files (available June 2022) - 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.

The ABS offers specialist consultancy services to assist data users with more complex statistical information needs. Users 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. 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.

For inquiries about these and related statistics, contact the Customer Assistance Service via the ABS website Contact Us page. The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.


User guide

The Survey of Income and Housing, User Guide, Australia, 2019–20 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 2019–20 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. 


A glossary is located in the Survey of Income and Housing User Guide.

Additional terms referenced in this release include:

Coronavirus supplement

A $550 per fortnight supplement payment for new and existing recipients of JobSeeker, Parenting Payment, Youth Allowance for job-seekers, Farm Household Allowance and Special Benefit, paid from 27 April 2020.


Economic Support Payments

Two separate 'Economic Support' payments of $750 were being paid to social security, veteran and other income support recipients and eligible concession card holders. The first payment made from 31 March, and the second from around 13 July. The second payment was not made to those eligible for the Coronavirus supplement. 


COVID-19 early access superannuation scheme

Eligible individuals adversely financially affected by COVID-19 were able to apply to access of up to $10,000 of their superannuation in the financial year 2019–20 between 20 April 2020 and 30 June 2020. 


Dissaving action

Any action where spending is greater than income, thereby reducing already accumulated savings or leading to borrowing to finance the expenditure. Examples of dissaving actions include any of the following actions because money was needed for basic living expenses:

  • reducing home loan repayments 
  • drawing on savings or term deposits 
  • increasing balance owed on credit cards by $1,000 or more 
  • entering into a loan agreement with family or friends 
  • taking out a personal loan
  • selling household goods or jewellery
  • selling shares or other assets.

Financial stress

A range of items which provide a subjective measure of the household's economic well-being. One person in each household was asked to provide assessments of the current household's circumstances. Items include management of household income, present standard of living compared with two years ago, ability to raise emergency money, and a range of cash flow problems.

JobKeeper payment

The JobKeeper payment scheme is a subsidy for businesses significantly affected by Coronavirus (COVID-19). It was introduced in April 2020 to help employers with the costs of their employees’ wages. 

JobSeeker payment

The JobSeeker payment scheme provides financial help for working aged Australians (aged between 22 and Age Pension age) who are looking for work or sick or injured and can’t do usual work or study for a short time. The JobSeeker payment was introduced on 20 March 2020 as the main payment for people aged 22 years to pension age.

Socio-Economic Indexes for Areas (SEIFA)

Socio-Economic Indexes for Areas (SEIFA) is a product developed especially for those interested in the assessment of the welfare of Australian communities. The ABS has developed a set of indexes to allow ranking of regions/areas, providing a method of determining the level of social and economic well-being in each region. For further information about the SEIFAs, see Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA) 2016 (cat. no. 2033.0.55.001).


A list of abbreviations is located in the Survey of Income and Housing User Guide.

Back to top of the page