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7 The commodity codes for the Household Expenditure Classification (HEC) are largely the same as in 2009-10 with a small number of changes, particularly to address emerging technologies and industries between the survey cycles. Estimates for previous cycles have been recompiled to reflect these changes at a broad expenditure level. The list of commodity codes for 2015-16 HES will be released in the User Guide (cat. no. 6503.0) which is expected to be released in October 2017. The expenditure estimates have also been derived for the Classification of Individual Consumption by Purpose (COICOP). 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.
8 To protect the confidentiality of individuals, a technique called perturbation is used to randomly adjust cell values. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.
9 After perturbation, a given published cell value will generally be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals.
10 The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as Table Builder.
CONCEPTS AND DEFINITIONS
11 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 and more detail will be forthcoming in the User Guide.
12 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.
13 Households therefore have the following characteristics:
14 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.
15 The HES aggregate estimates of expenditure on goods and services refer to:
16 Estimates of selected other payments (income tax, mortgage repayments (selected dwelling) and superannuation and life insurance) are also provided.
17 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.
18 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).
19 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.
20 Income includes receipts from:
21 Receipts of Family Tax Benefit are treated as income, regardless of whether they are received fortnightly or as a lump sum.
22 The Newborn Supplement and Newborn Upfront Payment replaced the Baby Bonus on 1 March 2014 and those eligible receive it as part of their Family Tax Benefit Part A payments for a period of 13 weeks or with their lump sum. The Paid Parental Leave payment has also been included as income.
23 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.
24 The twice-yearly Schoolkids bonus payment that was paid to eligible families, carers and students from January 2013 to July 2016 has been included in income from government pensions and allowances. This payment, paid in January and July, was made payable to families receiving Family Tax Benefit Part A. Young people enrolled in school who were receiving Youth Allowance and other specific income support or receiving an education allowance from Department of Veteran's Affairs are also entitled to this payment, providing that they meet the age and education requirements.
25 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.
26 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 (cat. no. 6523.0).
Equivalised disposable income
27 Most analyses in this publication use equivalised disposable household income rather than gross or disposable income. Using an equivalising factor for household income enables the direct comparison of the relative economic wellbeing of households of different size and composition.
28 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.
29 Whereas disposable income includes negative values, these are adjusted to zero for the purpose of equivalised disposable household income.
30 After household income is adjusted according to an equivalence scale, the equivalised income can be viewed as an indicator of the economic resources available to a standardised household. For a lone person household, it is equal to income received. For a household comprising more than one person, equivalised income is an indicator of the household income that would be required by a lone person household in order to enjoy the same level of economic wellbeing as the household in question.
31 For more information on equivalised income, see the User Guide.
Lowest income decile
32 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.
33 Equivalised income generally provides a useful indicator of economic wellbeing. However, some households report extremely low and even negative income in the survey, which places them well below the safety net of income support provided by government pensions and allowances. Households may under report their incomes in the survey at all income levels, including low income households. Households may also correctly report low levels of income if they have incurred losses in their unincorporated business or have negative returns from other investments.
34 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.
35 Other households in the lowest income decile in past surveys:
However, on average, these households also had expenditures above the average of the households in the second income decile, which may be because these households are using assets to maintain a higher standard of living than their income alone could allow.
36 Some of the households included in the lowest income decile are unlikely to be suffering extremely low levels of economic wellbeing. Income distribution analysis may lead to inappropriate conclusions if such households are used as the basis for assessing low levels of economic wellbeing.
37 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.
38 More recent analysis suggests that this approach may have over-estimated the economic wellbeing of low income households, and unnecessarily excluded some of the most vulnerable households in the lowest income decile. The 2015–16 SIH uses an adjusted lowest income quintile instead, which is made up of the lowest two deciles, excluding the first and second percentiles. This adjusted lowest income quintile has been calculated for previous cycles to create a time series of these data, available from the ‘Downloads’ tab of this publication.
39 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:
40 Liabilities are primarily the value of loans outstanding including:
41 In the 2015-16 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.
42 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 Household Income and Wealth Distribution, 2015-16 (cat. no. 6523.0).
Difference between income and expenditure
43 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.
44 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.
45 Second, there are significant timing differences between the different components of income and expenditure collected:
46 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.
Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA)
47 The Metropolitan Accessibility/Remoteness Index of Australia (Metro ARIA) is a geographic index which quantifies service accessibility within metropolitan areas. The index reflects the ease or difficulty people face accessing basic services within metropolitan areas, derived from the measurement of road distances people travel to reach different services, and covers five different service themes:
48 Metro ARIA covers 2011 Greater Capital City Statistical Area (GCCSA) by 2011 Statistical Area 1. Areas outside GCCSAs are defined as non-metropolitan. Non-metropolitan should not be interpreted as lower accessibility; it is simply that the region is located outside the capture area detailed Metro ARIA. Further information regarding Metro ARIA and maps can be found via the following link: https://aurin.org.au/projects/data-hubs/metro-aria/
Scope and coverage
49 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.
50 Usual residents excludes:
51 Information for each household was collected using:
Sample copies of the above documents are included in the User Guide (cat. no. 6503.0).
52 The simultaneous collection of information from the Survey of Income and Housing and the Household Expenditure Survey allows for expenditure to be placed in the context of the households' economic resources (income and wealth). Estimates of income, wealth and housing should be directed to the larger sample in the SIH (17,768 households). These estimates are drawn from the HES only where expenditure information is required.
53 The sample was designed to produce reliable estimates for broad aggregates for households resident in private dwellings aggregated for Australia, for each state/territory and for capital cities and the rest of state in each state and territory (based on Greater Capital City Statistical Area). More detailed estimates should be used with caution, especially for Tasmania, the Northern Territory and the Australian Capital Territory.
54 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.
55 For the 2015-16 HES there was an additional sample of households in Greater Capital City areas, designed to collect information specifically from households whose main source of income was government pensions, benefits and/or allowances. These households were enumerated using a separate sample design, and received the combined SIH and HES questionnaire.
56 In this additional sample, dwellings were targeted using information from the previous HES (2009-10), and information from the Socio-Economic Indexes for Areas (SEIFA). Households were screened using a short questionnaire to identify whether pensions and benefits were likely to be the main source of income for the household. 23,870 households were screened. One in four households were selected to complete the combined SIH and HES questionnaire and diaries regardless of the screening outcome. Information from this sample were used to assess the outcomes from the screening questionnaire for the whole sub-sample.
57 Of the selected dwellings for HES there were 17,873 households in the scope of the survey. Of this initial sample, 2,579 dwellings (14%) were excluded as no contact was able to be made (e.g, vacant dwelling, holiday homes). A further 5,220 (29%) 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. The remainder were:
58 110 households were excluded because the main income earners in the household did not adequately respond to questions about income sources and amounts. 229 households that were collected as part of the HES sample but did not have sufficient expenditure diary information were retained as part of the SIH sample. 74 households were retained after repair to an instrument error.
Partial response and imputation
59 237 partially responding households were retained in the final sample after full record imputation of person(s) in the household who were not the main income earners. For these households, any missing values were imputed by replacing each missing value with a value reported by another person (referred to as the donor).
60 Partial imputation is completed for all households with missing data items. Donor records are selected by finding fully responding persons with matching information on various characteristics (such as state, sex, age, labour force status and income) as the person with missing information. As far as possible, the imputed information is an appropriate proxy for the information that is missing. Depending on which values are to be imputed, donors are randomly chosen from the pool of individual records with complete information for the block of questions where the missing information occurs.
61 The final HES sample includes 3,487 households (35% of households) and 4,762 person records (25% of persons aged 15 years or over) which had at least one imputed value. 154 full records were imputed (0.5% of all HES person level records).
62 Of the selected dwellings (15,294) that were contacted and in scope of the survey, 10,046 (66%) households were included as part of the final estimates.
63 Household Expenditure Survey, Final Sample, 2015-16
64 The HES sample is not evenly balanced over the course of the year. Due to under-performance of the sample design in the first half of the collection year, a top-up sample was selected and collected from January - July 2016. The fully responding households by quarter are provided in the table below.
65 Weights adjust by quarter to ensure representativeness across the year.
BALANCE OF FULLY RESPONDING HOUSEHOLDS, 2015-16 collection year
66 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 i.e. 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).
67 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.
68 In the 2009-10 and 2015–16 HES, all persons in each household were assigned a weight. The final SIH weights were used as the initial weights for the HES, with a sub-sampling adjustment being applied to incorporate the additional pensioner sample. This differs from the method used in 2009-10, where the base HES and additional pensioner samples were combined using composite estimation after weighting each component separately.
69 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 and the Monthly Population Survey. ERP benchmarks were preliminary, based on the 2011 Census. An additional benchmark using administrative payment data was applied for households that received government payments.
70 The population benchmarks used in the calibration of the final weights for the 2015-16 HES were:
71 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:
72 The independent person and household benchmarks are based on demography estimates of numbers of persons and households in Australia, except for the labour force benchmarks which are based on the Monthly Population Survey. 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.
73 Composite estimation was used to obtain the optimal proportions for combining the targeted sample and main HES sample of pensioner households at a state level.
74 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 Wealth, Australia, 2015-16 (cat. no. 6523.0) are unlikely to have exactly the same values, unless calibrated between the surveys. 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 for comparisons with the expenditure data items.
75 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).
76 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
77 The estimates provided in this publication are subject to two types of error, non-sampling and sampling error.
78 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.
79 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.
80 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.
81 The following methods were adopted to reduce the level and impact of non-response:
82 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 the User Guide.
83 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.
SPECIAL DATA SERVICES
84 The ABS offers specialist consultancy services to assist clients with more complex statistical information needs. Clients may wish to have the unit record data analysed according to their own needs, or require tailored tables incorporating data items and populations as requested by them. Tables and other analytical outputs can be made available electronically or in printed form. However, as the level of detail or disaggregation increases with detailed requests, the number of contributors to data cells decreases. This may result in some requested information not being able to be released due to confidentiality or sampling variability constraints. All specialist consultancy services attract a service charge, and clients will be provided with a quote before information is supplied.
UNIT RECORD FILE
86 A confidentialised unit record file (CURF) from the 2015-16 HES will be released on CD-ROM and through the ABS Remote Access Data Laboratory in late 2017. All clients wishing to access the HES 2015-16 CURF should refer to the How to Apply for Microdata web page. Clients should familiarise themselves with the User Manual: Responsible Use of ABS CURFs and other related microdata information which are available via the Microdata web pages, before applying for access through MiCRO.
87 The ABS/Universities Australia Agreement provides participating universities with access to a range of ABS products and services. This includes access to CURF data. For further information, university clients should refer to the ABS/Universities Australia Agreement web page.
88 The Microdata Entry page on the ABS website contains links to microdata related information to assist users to understand and access microdata. For further information users should contact the microdata access team by email: email@example.com or telephone (02) 6252 7714.
89 The Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia, 2015–16 (cat. no. 6503.0) 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 2009–10 survey and earlier HES surveys. Its purpose is to help users of the data understand the nature of the survey, and its potential to meet user needs. It also contains information for users of the HES confidentialised unit record files (CURFs). The 2015–16 User Guide is expected to be released in October 2017.
90 Users may also wish to refer to the following related ABS products:
Government Benefits, Taxes and Household Income, Australia (cat. no. 6537.0) - 2009-10
Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia (cat. no. 6503.0) - 2009-10
Household Income and Wealth, Australia (cat. no. 6523.0) - 2015-16
Housing Occupancy and Costs (cat. no. 4130.0) - 2013-14
Labour Force, Australia (cat. no. 6202.0) - issued monthly
Microdata: Household Expenditure Survey and Survey of Income and Housing, Australia (cat. no. 6540.0) - 2009-10 Third Edition
Microdata: Income and Housing, Australia (cat. no. 6541.0.30.001) - 2013-14
Survey of Income and Housing, User Guide, Australia (cat. no. 6553.0) - 2013-14
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