Australian Bureau of Statistics
6530.0 - Household Expenditure Survey, Australia: Summary of Results, 2009-10
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 06/09/2011
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Changes to the survey sample
7 For the 2009-10 HES there was an additional sample of metropolitan households whose main source of income was a government pension, benefit and/or allowance. These pensioner households were enumerated using a separate sample design, but the fully responding in-scope households from this sample were included in the final SIH and HES samples. The main purpose of the inclusion of this additional sample was for the development of a Pensioner and Beneficiary Living Cost Index (PBLCI), which is part of the revised process for indexing age and other pensions. The pensioner sample supports improved commodity weighting for the PBLCI to better reflect the different expenditure patterns of pensioner households compared with the general population.
8 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 changes that have been made since 2003-04 include:
9 For more detail on the nature and impact of the changes on the income data see Appendix 4 of Household Income and Distribution, Australia, 2007-08 (cat. no. 6523.0)
10 To ensure consistency with the conceptual treatment of income introduced by the revision of household income standards, the 2009-10 HES includes some improvements to the treatment of non-cash benefits and salary sacrifice in household expenditure estimates. Non-cash benefits used by employees are incorporated to improve the coverage of consumption expenditure, and improvements to the inclusion of expenditures via salary sacrifice for vehicles have been implemented.
11 Most employee remuneration is in a monetary form. However a substantial number of employees receive other benefits in the form of goods and services i.e. non-cash benefits. Examples include the use of motor vehicles, provision of a computer, subsidised child care, housing rent free or at less than normal market rent, car parking, superannuation (employer contributions above the minimum compulsory contributions) and low interest loans. Information on non-cash benefits provided by employers has been collected from wage and salary earners and owners of incorporated businesses, commencing in 2003-04, and were included for the first time in the estimates of income in 2007-08. Items provided free or at a reduced cost by employers to employees for their own private use are regarded as expenditure in-kind. These estimates of expenditure in-kind have been included in the expenditure estimates for the first time in 2009-10.
12 More detailed information was collected for salary sacrifice on motor vehicles in the 2009-10 HES to improve the expenditure estimates for this type of expenditure. The additional information captured within the questionnaire was used to model the value of expenditure on motor vehicles and associated running costs such as fuel, insurance, registration, servicing and tyres.
13 The following table shows the estimated impact of these changes on the HES 2009-10 expenditure estimates.
14 The commodity codes for the Household Expenditure Classification (HEC) are largely the same as in 2003-04 with a small number of changes, particularly to address emerging technologies between the survey cycles. The list of commodity codes for 2009-10 HES will be released in Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia, 2009-10 (cat. no. 6503.0) which is expected to be released in September 2011. The expenditure estimates have also been derived for the Classification of Individual Consumption by Purpose (COICOP) for the first time in 2009-10. The total expenditure estimates differ between the two classifications due to scope differences, in particular the COICOP includes estimates of imputed rent which are out of scope for the HEC.
CONCEPTS AND DEFINITIONS
15 The concepts and definitions relating to income, expenditure, net worth and households are described in the following section. Other definitions are included in the glossary.
16 The household is the basic unit of analysis in the HES. It is defined as a group of related or unrelated people who usually live in the same dwelling and make common provision for food and other essentials of living; or a lone person who makes provision for his or her own food and other essentials of living without combining with any other person.
17 Households therefore have the following characteristics:
18 The household is adopted as the basic unit of analysis because it is assumed that sharing of the use of goods and services occurs at this level. If smaller units, say persons, are adopted, then it is difficult to know how to attribute to individual household members the use of shared items such as food, accommodation and household goods.
19 The HES aggregate estimates of expenditure on goods and services refer to:
20 Estimates of selected other payments (income tax, mortgage repayments (selected dwelling) and superannuation and life insurance) are also provided.
21 Estimates of average weekly expenditure do not refer to a given week. Average weekly expenditure was calculated by dividing expenditure by the number of weeks in the recall period or reporting period over which it was collected.
22 Household expenditure is compared to household income to help explain variations in expenditure levels and patterns and to identify groups of special interest (e.g. households with low incomes).
23 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.
24 Income includes receipts from:
25 Income is collected using a number of different reporting periods, such as the whole financial year for own unincorporated business and investment income, and the usual payment for a period close to the time of interview for wages and salaries, other sources of private income and government pensions and allowances. The income reported is divided by the number of weeks in the reporting period. Estimates of weekly income in this publication therefore do not refer to a given week within the reference period of the survey.
Equivalised disposable income
26 In most tables in this publication, gross household income is presented along with expenditure estimates. However, when using income as an approximate means of ranking households according to the relative standards of living, it is more appropriate to use equivalised disposable household income.
27 Income tax payments were estimated for all households using taxation criteria for 2009-10 and the income and other characteristics of household members reported in the survey.
28 Disposable income is derived by deducting estimates of personal income tax and the Medicare levy from gross income. Disposable income better represents the economic resources available to meet the needs of households. Disposable income is then adjusted by the application of an equivalence scale to facilitate comparison of income levels between households of differing size and composition, reflecting the requirement of a larger household to have a higher level of income to achieve the same standard of living as a smaller household. Where disposable income is negative, it is set to zero equivalised disposable income. For more information on equivalised income see Appendix 3 of Household Income and Income Distribution, Australia, 2009-10 (cat. no. 6523.0).
Lowest income decile
29 While equivalised income generally provides a useful indicator of economic wellbeing, there are some circumstances which present particular difficulties. 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. However, households can correctly report low levels of income if they incur losses in their unincorporated business or have negative returns from their other investments.
30 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.
31 It can therefore be reasonably concluded that many 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. For this reason, tables showing statistics classified by income quintiles include a supplementary category comprising the second and third income deciles, which can be used as an alternative to the lowest income quintile. For an explanation of quintiles and deciles, see Appendix 1, Household Income and Income Distribution, Australia, 2009-10 (cat. no. 6523.0).
32 Whenever a HES is conducted, analysis of households in the lowest income decile can be improved through direct observation of the expenditure and net worth of these households. An examination of households with low economic resources (income and wealth) is expected to be included as a feature article in Household Wealth and Wealth Distribution, Australia, 2009-10 (cat. no. 6554.0) to be released in October 2011.
33 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:
34 Liabilities are primarily the value of loans outstanding including:
35 In the 2009-10 HES, 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.
36 While this publication provides some household net worth statistics, principally to aid expenditure analysis, a more comprehensive range of household asset and liability information will be released in October 2011 in Household Wealth and Wealth Distribution, 2009-10 (cat. no. 6554.0).
Difference between income and expenditure
37 The HES provides information about both the income and the expenditure of households, but it would be misleading to regard the difference between average weekly income and the sum of the items of average weekly expenditure as shown in the tables in this publication as a measure of savings.
38 First, to be properly understood, the concept of household saving needs to be articulated along with the concept of household wealth (assets and liabilities), and all forms of income and expenditure need to be measured and classified consistently with these concepts. The HES does not attempt to do this. It focuses on usual income being received at the time the data was collected; estimates of personal income tax; expenditure on current consumption of goods and services; and two major items of expenditure which can be regarded as investment ('mortgage repayments - principal (selected dwelling)' and 'superannuation and life insurance'). The two items of investment expenditure are included in the HES because they are a significant regular commitment of many households which have to be financed from income.
39 Second, there are significant timing differences between the different components of income and expenditure collected:
40 HES income and expenditure estimates therefore do not balance for individual households or groups of households and the difference between income and expenditure cannot be considered to be a measure of saving.
Scope and coverage
41 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.
42 Usual residents excludes:
43 Information for each household was collected using:
44 Sample copies of the above documents are included in the Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia, 2009-10 (cat. no. 6503.0) to be released in September 2011.
45 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 (see Appendix 2).
46 The HES sample was designed in conjunction with the SIH. In the combined sample, some dwellings were selected to complete both the SIH questionnaire and the HES questionnaire, while other dwellings were selected to complete the SIH questionnaire only. 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 and expenditure patterns across the year.
47 For the 2009-10 HES there was an additional sample of metropolitan households whose main source of income was government pensions, benefits and/or allowances. These households were enumerated using a separate sample design.
48 In the pensioner sample, dwellings were selected via two phase sampling to complete the HES questionnaire. To target the pensioner households the 2006 Census information was used to identify the areas where the number of households that were more likely to belong to the target population were higher. This frame prediction was then updated for known deficiencies and changes to the Australian population since 2006. Selections of small geographic (meshblock) first stage units were made to avoid overlap with the population master sample and distributed across a ten month enumeration period from September 2009 to July 2010.
49 Of the 8,786 households selected in the main HES sample, 2,219 did not respond at all to the questionnaire, or did not respond adequately. Such households included:
50 For the additional pensioner sample, 42,913 dwellings were approached to screen for inclusion in the sample.
Partial response and Imputation
51 Some households did not supply all the required information but supplied sufficient information to be retained in the sample. Such partial response occurs when:
52 In the first two cases, the data provided are retained and the missing data are imputed by replacing each missing value with a value reported by another person (referred to as the donor).
53 For the third type of partial response, the data for the persons who did respond are retained, and data for each missing person are provided by imputing data values equivalent to those of a fully responding person (the donor). Non-significant respondents who did not sufficiently complete either week one or two diaries, had their diary data imputed from a fully responding donor. If all significant persons within the households failed to supply either diaries, then the household was converted to a SIH household for sample retention.
54 For the fourth type of partial response, the diary information provided is used to represent the missing information. For example, if the first week of diary entries is provided but not the second week then the first week of expenditure is used to represent expenditure for the second week.
55 Donor records are selected by finding fully responding persons with matching information on various characteristics, such as state, sex, age, labour force status, income and expenditure, 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.
56 The final sample includes 3,353 households which had at least one imputed value in either income, assets and liabilities or expenditure reported in the household questionnaire. For 49.9% of these households, only a single value was missing, and most of these were for superannuation assets or a minor source of income for the household.
57 The final sample on which estimates were based is composed of households for which all necessary information is available. The information may have been wholly provided at the interview (fully-responding) or may have been completed through imputation for partially responding households. Of the selected dwellings, there were 8,786 in the scope of the survey, of which 6,567 (75%) were included as part of the final HES estimates. For the additional pensioner sample, 4,804 dwellings identified as being in scope, of which 3,207 dwellings (67%) were included on the final file. The final combined HES sample consists of 9,774 households, comprising 17,955 persons aged 15 years and over.
58 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).
59 An adjustment is then made to the initial weights to account for changes in the sample across the four quarters of survey enumeration; the sum of the weights after this initial adjustment of households in each quarter is equal.
60 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.
61 In the 2009-10 HES, all persons in each household were assigned a weight. This differs from the 2003-04 HES where children aged 0-14 years were not given separate weights, but household counts of the number of children were benchmarked to population totals.
62 The HES survey was benchmarked to the in scope estimated resident population (ERP) and the estimated number of households in the population, and to a number of estimates produced from the SIH. The 2009-10 HES used population and household benchmarks based on the 2006 Census.
63 The population benchmarks used in the calibration of the final weights for the 2009-10 HES were:
64 In addition to the population benchmarks presented above, the following SIH estimates were used as benchmarks at the state level in weighting the HES sample:
65 More detailed age groupings have been used where possible in benchmarking 2009-10 HES results.
66 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.
67 In weighting the pensioner sample, independent initial probability weights were assigned to the pensioner sample as it was selected separately from the SIH and HES sample. The initial probability weights were then adjusted by the results of the first phase screening results with respect to the observed proportion of identified screened pensioner households. This pensioner sample was only able to be collected in three of the four quarters of HES enumeration and the initial probability weights were adjusted accordingly.
68 The pensioner weighted estimates for person and households were calibrated to the main SIH sample estimates for persons, households and total weekly household income.
69 Composite estimation was used to obtain the optimal proportions for combining the pensioner sample and main SIH and HES samples for age pensioner households and other pension beneficiary households at a state by quarter of enumeration level. For more details see Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia, 2009-10 (cat. no. 6503.0) to be released in September 2011.
70 After the main HES sample and the pensioner sample were combined through composite estimation the SIH estimates were included again as final benchmarks to increase the comparability between the surveys and to improve the reliability of income estimates produced from the HES. The following SIH estimates were used as benchmarks:
71 This means that estimates produced using the HES sample for the aggregates used as benchmarks will be the same as the estimates produced using the SIH sample.
72 Although the HES and the SIH are integrated, the estimates for common items published in both this publication and the SIH publication Household Income and Income Distribution, Australia, 2009-10 (cat. no. 6523.0) are unlikely to have exactly the same values, unless calibrated to do so. All estimates in this publication are taken from the HES subsample (except in the feature article which includes some SIH estimates). They are therefore subject to greater sampling variability than the full SIH estimates, but have been included here because it is considered that they are more appropriate for comparisons with the expenditure data items, which are only available for the HES subsample.
73 Estimates produced from the survey are usually in the form of averages (e.g. average weekly household expenditure on clothing and footwear), or counts (e.g. total number of households that own their dwelling). For counts of households, the estimate was obtained by summing the weights for the responding households in the required group (e.g. those households that own their dwelling).
74 Averages are obtained by adding the weighted household values, and then dividing by the estimated number of households. For example, average weekly expenditure on clothing and footwear by Victorian households is the weighted sum of the average weekly expenditure of each selected household in Victoria who reported such expenditure, divided by the estimated number of households in Victoria. Note that the denominator is the total number of households and not just the number of households which reported expenditure on a particular item.
RELIABILITY OF ESTIMATES
75 The estimates provided in this publication are subject to two types of error, non-sampling and sampling error.
76 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.
77 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 extensive editing and quality control procedures at all stages of data processing.
78 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.
79 The following methods were adopted to reduce the level and impact of non-response:
80 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). Further information on sampling error is given in Appendix 2.
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.
PUBLICATION AND DISSEMINATION OF DATA
82 Information about the range of data, including special data services and unit record files, to be made available from the 2009-10 HES is given in Appendix 1.
83 Users may also wish to refer to the following related ABS products:
Household Wealth and Wealth Distribution, Australia, 2009-10, (cat. no. 6554.0), to be released in October 2011
Housing Occupancy and Costs, Australia, 2009-10 (cat. no. 4130.0), to be released in November 2011
Government Benefits, Taxes and Household Income, Australia, 2009-10, (cat. no. 6537.0), to be released mid 2012
Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia, 2009-10 (cat. no. 6503.0) to be released in September 2011
Microdata: Household Expenditure Survey and Survey of Income and Housing - Basic and Expanded CURF, Australia 2009-10 (cat. no. 6540.0) to be released in September 2011
Labour Force, Australia, (cat. no. 6202.0) - issued monthly
Average Weekly Earnings, Australia, (cat. no. 6302.0) - issued quarterly
Measuring Wellbeing: Frameworks for Australian Social Statistics, 2001, (cat. no. 4160.0)
Measures of Australia's Progress, 2010, (cat. no. 1370.0)
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This page last updated 5 September 2011