This section presents a summary of the methodology used to create individual data points; a summary of the steps undertaken to enable the presentation of the data points in a time series, including a discussion on demographic shifts; and the strengths and weaknesses of the data presented in the publication.
Overview of methodology for individual data point
The methodology used to compile the individual data points in this publication is based on the methodology described in the Information Paper: Australian National Accounts, Distribution of Household Income, Consumption and Wealth, 2009-10 (cat. no. 5204.0.55.009). A summary of the methodology is as follows:
Current price household estimates for income, consumption and wealth from the Australian System of National Accounts, 2017-18 (cat. no. 5204.0), for biennial years 2003-04 to 2017-18 were distributed for five household distributional indicators based on data from the ABS Survey of Income and Housing (biennial years starting from 2003-04 to 2015-16) and ABS Household Expenditure Survey (2003-04, 2009-10 and 2015-16).
Estimates for non-profit institutions serving households (NPISH) included in the household sector in the cat. no. 5204.0 were removed from the household national accounts in this release.
The household national accounts estimates for a particular year (macro) and the corresponding ABS household survey estimates (micro) were compared and coverage ratios (micro/macro) calculated. For some items, the macro and/or micro estimates were adjusted to derive the most relevant common scope for comparison. The corresponding micro household items were sub sectored into the following household groups: main source of income; equivalised income quintiles; household composition; age of household reference person; and equivalised net worth quintiles.
The Australian System of National Accounts (ASNA) household components and aggregates were distributed to the five household groups:
- directly using the distribution of the equivalent micro component when the coverage ratio was considered adequate, for example, social assistance benefits;
- indirectly by a related micro distribution when there was no direct micro distribution information for the national accounts item, for example the national accounts item non-life insurance claims were distributed using the micro distribution for total insurance premiums paid;
- indirectly by creating a micro distribution ('synthesised') based on related micro distribution, for example, synthesised micro distribution was created for the national accounts item financial intermediation services indirectly measured (FISIM) for consumer loans; and
- by the corresponding aggregate distribution for income (disposable income), consumption (final consumption expenditure), assets (total assets) and liabilities (total liabilities), when micro distributions either directly or indirectly are not available. For these national accounts items, the inclusion or exclusion of the item did not impact on the distribution of the national accounts aggregates.
The very remote communities (VRC) and people living in non-private dwellings (NPD) populations that were out of scope of the micro surveys were excluded from the ASNA estimates and distributed separately using data from the 2006, 2011 and 2016 ABS Census of Population and Housing. These distributions were then added to the ASNA distributions based on the micro surveys to obtain the final distribution of the ASNA household income, consumption and wealth estimates.
For detail information regarding the methodology described above, please refer to Information Paper: Australian National Accounts, Distribution of Household Income, Consumption and Wealth, 2009-10 (cat. no. 5204.0.55.009), Chapter 4 - "Data Sources and Methodology: Distribution Methodology for Household National Accounts Estimates". Improvements to the original methodology were made in the October 2014 and November 2015 releases of this publication.
The methodology to construct data point for 2017-18 is discussed below in the section, Time Series Presentation.
Time series presentation
The time series presented in this release for distribution of the household income, consumption and wealth is biennial from 2003-04 to 2017-18. The decision to start the time series in 2003-04, and compile the estimates biennially up to 2017-18 was based on:
- the availability of income and wealth modules from the ABS Survey of Income and Housing (SIH) for all seven data points from 2003-04 to 2015-16 for income, and 6 data points (excluding 2007-08) for wealth;
- the availability of the improved income data collected through the SIH starting from 2003-04;
- distributed data points being a minimum of two years from the 2006, 2011, 2016 ABS Census;
- distributed data points being a minimum of two years from the 2003-04, 2009-10 and 2015-16 ABS Household Expenditure Survey (HES); and
- availability of the micro Social Transfer in Kind (STiK) data for five data points from 2003-04 to 2015-16 (excluding 2005-06 and 2007-08).
Due to feedback from users for more timely household distributional data, this release includes extrapolated estimates for household distributional data for income, consumption and wealth for 2017-18. All distributional data points in the publication are benchmarked to the most recent issue (released 26 October 2018) of the Australian System of National Accounts, 2017-18 (cat. no 5204.0) and as a result the distributional data set for the 2017-18 data point is available approximately 5 months after the end of the reference year.
Models used to estimate data gaps in micro distributional data
The two options of linear interpolation (extrapolation) were applied in this release:
- three data point linear trend interpolation (extrapolation); and
- two data point average growth rate of the total household micro estimate, with the average growth applied to the average share over three data points of the household indicator (e.g. quintiles).
Both option (1) and (2) are simple methodologies, and work effectively if the historical data is stable over time and in particular if there are not large fluctuations between shares of the various indicators over time.
Improvements to the original methodology (October 2014 release) used to estimate data gaps in the micro distributional data were made in the November 2015 release, including a feasibility study of the extrapolation of the most recent year estimate from the SIH data.
Models used for current release
Option (1) was applied to interpolate (extrapolate) the micro distributional indicators for consumption for the years 2005-06, 2007-08, 2011-12, 2013-14, and 2017-18 from HES. In general, it is assumed that consumption patterns of household tend to be fairly stable over time, and this method has the advantage of capturing the systematic pattern (i.e. movements up or down) of distributional information over time.
Option (2) was applied to SIH to interpolate (extrapolate) the micro distributional indicators for income in 2017-18; wealth for the years 2007-08 and 2017-18; and STiK for the years 2005-06, 2007-08 and 2017-18. This method has the advantage of not generating negative vales, works adequately for when the distributed pattern is not linear over time and assumes that the shares of the distributional indicators are stable over time. The assumption regarding the stability of the shares is more than likely to be valid as the availability of the actual survey data used in the method is between 2 years from the interpolated (extrapolated) data point.
Option (1) was applied to interpolate (extrapolate) Census data that is used to construct the distributional data for the VRC and NPD populations. The total disposable income, total consumption and total net worth estimates for the NPD and VRC populations were approximately 1% of the total Australian aggregates of income, consumption and net worth for all data points. The impact of the methodology chosen to interpolate (extrapolate) would be minimal on the final Australian National Accounts distributional estimates.
Changing demographics over time
When distributional data across different years is compared, it is important to note that the change in the estimate is impacted by (a) changes in the household's income (consumption and wealth) and (b) change due to more households in the distributional group.
In order to separate changes due to (a) and (b), the ABS applied a number of different methods to control for the demographic shift, that is item (b). For detail information regarding the different methods applied, see, Australian National Accounts, Distribution of Household Income, Consumption and Wealth, 2003-04 to 2011-12 (cat. no. 5204.0.55.011), Methodology - Changing Demographics Over Time. In this release, dollars per household were applied to account for demographic shifts. It should be noted that the ideal methodology to capture demographic shifts accurately is to undertake longitudinal (panel) surveys such as the Melbourne Institutes 'Household, Income and Labour Dynamics in Australia' (HILDA). However, it should be noted these types of surveys would be extremely expensive to undertake with the sample size required to produce robust detail distributional information such as what is produced by the current ABS micro surveys.
To assist users in understanding the size of the demographic shift, the tables below provide the proportion of households in each household distributional indicator.
|Total Number of Households||7 954 585||8 160 856||8 327 818||8 664 856||8 912 566||9 150 897||9 246 191||9 275 076|
|Main Source of Income (%)|
|Wages and salaries||56.0||57.6||60.1||59.5||59.8||59.8||59.3||59.8|
|Income from Unincorporated Business||8.1||8.0||8.2||7.8||7.3||7.3||7.7||7.3|
|Property income & Superannuation||8.6||8.8||8.4||7.9||8.5||8.5||7.7||7.0|
|Government pensions & allowances||25.9||24.3||22.0||23.7||23.3||23.2||24.0||24.7|
|Household Composition (%)|
|Lone person under 65||16.4||16.6||16.1||16.1||15.7||15.7||15.0||15.3|
|Lone person 65 and over||10.7||10.8||10.6||10.3||10.8||10.7||11.5||12.6|
|One parent with dependent children||6.7||6.7||6.0||6.2||5.7||5.7||5.5||5.6|
|Couple only, reference person under 65||17.2||16.8||17.2||16.9||16.2||16.2||15.1||15.9|
|Couple only, reference person 65 and over||8.3||8.3||8.6||8.6||9.0||9.0||9.8||8.8|
|Two adults or more with dependent children||27.2||26.4||26.8||26.8||26.8||26.8||28.2||26.2|
|Age of Reference Person (years) (%)|
|Equivalised Disposable Income Quintiles (%)||20.9||20.9||20.9||20.9||21.0||21.0||20.9||20.9|
|Equivalised Disposable Net Worth Quintiles(%)|
Table 4.1 Proportion of households, by household indicator, 2003-04 to 2017-18
The number of households in the equivalised income and net worth quintiles when distributed to the in scope micro survey population was 20% of households for each quintile. However, when the VRC and NPD populations (out of scope for the micro surveys) are included, the proportion of households in each quintile marginally moves away from 20% as illustrated in the table above.
Time series analysis included in the release
The release includes the following tables to:
- analyse how household distributional groups have contributed to total growth of income, consumption and wealth - electronic table 9. This table includes demographic shifts such as the increase in the number of households in a particular household group, as they are an important driver to total growth;
- remove demographic shifts, the method used in this release is dollars per household - electronic table 3 and 4;
- analyse household groups per household growth in income, consumption and wealth - electronic table 10;
- analyse contributions by component (income, consumption and net worth) to a household group's growth per household of gross disposable income, house final consumption expenditure, net worth and actual final consumption - electronic table 5 to 8; and
- analyse the impacts of redistribution policies such as income tax, social assistance benefits and social transfers in kind; and the effectiveness of the policies over time - electronic table 11.
Strengths and weaknesses of time series
To enable users to interpret the data of the time series, the strengths and weaknesses of the time series are presented below.
The time series of the distributed household income, consumption and wealth data:
- is benchmarked to the aggregates published in Australian System of National Accounts, 2017-18, (cat. no. 5204.0), which enables users to interpret household distributional data within the broader context of published estimates on the Australian economy such as gross domestic product (GDP);
- includes household distributional data for 2017-18, available five months from the end of the reference year, and therefore is the most up to date distributional data on households publicly available;
- is complete and consistent for the years presented, where data was missing linear interpolation and extrapolation modelling techniques have been implemented;
- is based on and expands upon work undertaken in an Organisation for Economic Cooperation and Development (OECD) and Eurostat (European Union statistical commission) expert group for measuring disparities in a national accounts framework. As a result, the data set produced for this publication should be comparable with the distribution of household income, consumption and wealth in a national accounts framework performed by members of this expert group; and
- may be extended with future data points and revised with new source data, enabling a more accurate and longer time series. The time series is based on robust methodology formulated through an international expert group, with the availability of new source data from ABS micro surveys (Survey of Income and Housing and Household Expenditure Survey) and revised aggregate data from the ASNA, the data presented in this release may be easily revised and updated with future data points.
A major weakness of this data set are the relatively long intervals between collection years for the Household Expenditure Survey (HES) and, to a lesser extent, the Census of Population and Housing (Census). As a result:
- due to the availability of only three time periods for the HES (2003-04, 2009-10 and 2015-16) and the unavailability of proxies for the time periods in between, the missing source data had to be interpolated or extrapolated. While linear movements were assumed for the purpose of interpolation and extrapolation, care should be taken when looking at the distributions of household consumption items for 2005-06, 2007-08, 2011-12, 2013-14 and 2017-18, as this assumption may not be accurate. An additional limitation on extrapolation is the estimates are based on past observations, increasing the possibility of error caused by the actual movement deviating from the past movement; and
- due to the unavailability of data on the distribution of household income, consumption and wealth items for populations living in Very Remote Communities and in Non-Private Dwellings, estimates had to be made for these items using ABS Census data. However, as this issue only affected about 2% of households the impact of the missing source data is assumed to be very small.
The unavailability of the 2007-08 (wealth only) and 2017-18 SIH data, means that the missing micro data points are modelled. Similar to the model used for the missing years of HES data, the models to estimate the SIH data are based on past observations, increasing the possibility of error caused by the actual movement deviating from the past movement.
Due to the inclusion of the VRC and NPD populations into the distributed estimates from the surveyed population, the number of households in each of the income and net worth quintiles does not equal 20%. After the addition of the distributed estimates for VRC and NPD, the quintile proportion ranges from 19.6% to 21.0%. Please see Table 4.1 above for more detail.
It could be argued that the time series (electronic Table 1, 2, 9 and 11) represents static points of cross sectional data and therefore falls short of a strictly defined time series such as a time series from a longitudinal study (e.g. Melbourne Institute HILDA survey). That is, the data in these electronic tables do not account for demographic shifts in the time series which a longitudinal study would capture. Please refer to section above on "Changing Demographic Over Time " for the method used to capture demographic shifts in this release.
Finally, users are encouraged to read Chapter 4, "Methodological Issues", in the Information Paper: Australian National Accounts, Distribution of Household Income, Consumption and Wealth, 2009-10 (cat. no. 5204.0.55.009), to understand the issues in constructing a household distributional data set for a single time point.
Revisions of estimates from the previous release are due to:
- the implementation of revised national accounts aggregates from Australian System of National Accounts, 2017-18 (cat. no. 5204.0);
- the implementation of revised national accounts data from Australian National Accounts: Finance and Wealth, June Quarter 2018, used to construct detail components for the national accounts net worth aggregates; and
- new 2015-16 SIH, HES and Census data points impacting on linear interpolation methodology.