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Weekly household energy expenditure
10 Estimates of weekly household energy expenditure were derived for each source of energy used by a household at the time of interview. A variety of reference periods were used to best capture expenditure across the range of energy sources. Estimates of weekly expenditure do not refer to any given week, but are weekly equivalents based on the reported amount and reference period.
11 Energy expenditure estimates presented in this publication reflect net 'out of pocket' private expenditure, that is with any refunds, deductions or amounts charged to a business removed.
12 Further detailed information was sought on expenditure on particular aspects of energy. These included solar electricity feed-in tariffs, GreenPower, fixed payment plans and electricity and mains gas supply and consumption charges. All items except solar electricity feed-in tariffs were asked only if a household had their most recent energy bill available to refer to for this information.
Energy expenditure and household income
13 Energy expenses are usually a significant and recurrent component of total living costs. Therefore energy expenditure may be analysed as a proportion of total income. It should be noted that the difference between household energy costs of a larger household and a smaller household would not be expected to be as great as the difference for other household expenses, such as food or clothing. In other words, larger households can be expected to experience economies of scale in the supply of household energy. This means that if a larger household and a smaller household both have the same standard of living, it could be expected that on average the larger household will have a lower value for energy costs when expressed as a proportion of total income. Therefore relatively high household energy costs as a proportion of income are more of a concern with respect to larger households than smaller households. This should be borne in mind when comparing ratios across different household sizes.
14 Households with nil or negative income have been excluded from calculations of energy expenditure as a proportion of gross household income. These households make up 0.6% of all households.
15 Energy consumption information was collected from households who used electricity, mains gas, LPG/ bottled gas and who had their most recent bill or statement available at interview. Consumption information was not collected for firewood, other sources of energy, or for energy sources where households were unable to refer to their most recent bill or statement. Weekly estimates of energy consumption were derived using the consumption amount and coverage period provided on the bill or statement. Information on the number of kWh related to feed-in tariffs was also collected.
16 Dwelling characteristics are useful for understanding variations in household energy expenditure and consumption. A range of energy related characteristics from households about their dwelling were collected, including:
17 A self-complete paper form was provided to households to collect detailed information about selected heating, cooling, lighting and other appliances used in the dwelling.
18 The climate zone classifications used for HECS is based on the eight climatic zones defined by the Australian Building Codes Board (ABCB). Each zone is based on humidity, temperature and rainfall characteristics and are as follows:
19 To concord the ABCB climate zones, HECS used 2006 Collection Districts (CDs) from the Australian Standard Geographical Classification (ASGC). There are some small differences between climate zones using the HECS and ABCB versions due to differences in the CD and climate zone boundaries. When a CD contains two or more climate zones, the climate zone was assigned based on the centre point of the CD. HECS estimates for Zone 8 (alpine) are included in estimates for the climate zone which mostly surrounds the area. In most cases this is Zone 7 (cool temperate).
Energy behaviours and perceptions
21 During the household interview, several items regarding the behaviours and perceptions of the household (or household members) were collected.
22 Owner households (with or without a mortgage) and households who lived rent free who were asked if they had made any energy efficient modifications to the dwelling in the past 2 years (or if all members were resident less than 2 years, since first residing in the dwelling). Modifications included such as installing solar systems, insulation, window treatments or replacing an electric hot water system for a gas hot water system. All households (including renters) were asked if any heaters, coolers or major whitegoods had been replaced in the past 2 years for more energy efficient models (if resident less than two years, since occupying the dwelling). Major whitegoods may include such appliances as refrigerators, freezers, dishwashers, washing machines and clothes dryers. Owner households or those households who lived rent free who did not make energy efficient modifications to their dwelling or upgraded any heaters, coolers or major whitegoods were asked for the main reason why they did not perform any of these actions.
23 Households were also asked a variety of energy efficient behaviours performed by the majority of household members, such as those featured in HECS tables within this publication. Households who performed less than five energy efficient behaviours were asked for the main reason why they had not performed more actions.
24 All households were asked their intention in the next 12 months to replace any heaters, coolers or major whitegoods for more energy efficient models. Owner households (with or without a mortgage) and households who lived rent free were asked for their intention to make energy efficient modifications to their dwelling in the 12 months following the interview. For owner households and households who lived rent free who did not intend to make any energy efficient modifications or upgrade any heaters, coolers or whitegoods, the main reason for not intending to make improvements was collected.
25 Several items relating to instances financial stress experienced by the household in the last 12 months were collected. These consisted of both energy related and other experiences of financial stress.
26 Households were asked if they were willing to participate in up to four rounds of follow-up questions, asked every three months following their household interview, up until January to March 2013. Questions included basic demographic characteristics of the household, dwelling characteristics, energy expenditure and consumption, and energy behaviours and perceptions during the previous three months. For more information on the longitudinal component and methodology, please refer to the Household Energy Consumption Survey, User Guide, Australia, 2012 (cat. no. 4671.0). Households who participated in four rounds of follow-up questions are the focus of the feature article contained in this product.
27 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.
28 Income includes receipts from:
29 Receipts of family tax benefit are treated as income, regardless of whether they are received fortnightly or as a lump sum. Baby Bonus payments and Paid Parental Leave payment are also included as income.
30 The one-off Clean Energy Advance payment paid in May 2012 and June 2012 is also included as current income for households interviewed in the first half of 2012. This one-off payment was paid to pensioners, other income support recipients, families receiving Family Tax Benefit payments and Senior Supplement recipients, provided they met eligibility requirements.
31 Also included as income is the one-off Education Tax Refund that was paid to eligible families in June 2012. This one-off payment was made payable to families receiving Family Tax Benefit Part A, plus young people in school receiving Youth Allowance and some other income support and veterans' payments, providing they met the age and education requirements.
Current weekly income
32 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 do not therefore refer to a given week within the reference period of the survey.
33 Gross income is the sum of the income from all sources before income tax and the Medicare levy have been deducted.
34 Disposable income better represents the economic resources available to meet the needs of households. It is derived by deducting estimates of personal income tax and the Medicare levy from gross income. Medicare levy surcharge was also calculated and deducted from gross income while calculating disposable income.
35 Income tax is estimated for all households using taxation criteria for 2011-12 (if interviewed between January and June 2012) and 2012-13 (if interviewed between July and December 2012) and the income and other characteristics of household members reported in the survey.
Equivalised disposable income
36 Analysis in this publication features equivalised disposable household income rather than gross or disposable income since it enables comparison of the relative economic wellbeing of households of different size and composition. Equivalised disposable household income is calculated by adjusting disposable income by the application of an equivalence scale. This adjustment reflects the requirement for 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.
37 When 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.
38 For more information on equivalised income see Appendix 3 of Household Income and Income Distribution, Australia, 2011-12 (cat. no. 6523.0) and Appendix 2 'Equivalised disposable household income' of the Survey of Income and Housing, User Guide, Australia, 2011-12 (cat. no. 6553.0).
Lowest income decile
39 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.
40 Studies of income and expenditure reported in Household Expenditure Surveys (HES) 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.
41 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).
Low economic resources
42 Low economic resources is a measure that simultaneously considers a household's level of equivalised income and wealth. Household energy characteristics are supplied for these households in the Additional tables for Economic Resources, available as a datacube in the "Downloads" tab. People with low economic resources are those in households in the lowest two quintiles (i.e. 40%) of both equivalised disposable household income (including private imputed rent) and equivalised household net worth. Net imputed rent is an estimate of the value of housing services that household receives from home ownership or by households paying subsidised rent or occupying their dwelling rent free (for more information on imputed rent see the section of the Household Energy Consumption Survey, User Guide, Australia, 2012 (cat. no. 4671.0)).
43 Low economic resource households exclude those people who live in households with either relatively high incomes or relatively high wealth, and as a result is more likely to correctly classify people most likely to be at risk of experiencing economic hardship compared to measures using income or wealth alone.
44 An examination of the characteristics and economic circumstances of people living in households with low economic resources is included in feature articles in Household Wealth and Wealth Distribution, Australia, 2009-10 (cat. no. 6554.0) and Household Income and Income Distribution, Australia, 2011-12 (cat. no. 6523.0) publications.
45 Tables of this publication refer to 'current' weekly income, that is, income being received at the time the data were collected from respondents. The survey also produces measures of 'annual' income that reflect total incomes for the previous financial year. Appendix 2 of Household Income and Income Distribution, Australia, 2011-12 (cat. no. 6523.0) 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.
46 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:
47 Liabilities are primarily the value of loans outstanding including:
48 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.
49 While this publication provides some household net worth statistics, principally to aid household energy analysis, a more comprehensive range of household asset and liability information (based on the 2011-12 Survey of Income and Housing) is available in Household Wealth and Wealth Distribution, Australia, 2011-12 (cat. no. 6554.0).
50 The survey collected information 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. Households provided information by personal interview and self-complete paper form, and could participate in the voluntary longitudinal component via a web form or telephone interview. 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.
51 Usual residents excludes:
52 Information for each household was collected using:
53 Sample copies of the above documents are included in the Household Energy Consumption, User Guide, Australia, 2012 (cat. no. 4671.0).
54 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 the twelve months of 2012 so that the survey results are representative of energy consumption and income patterns across the year, and any seasonal patterns in temperature.
55 Both HECS and SIH follow the same sample design principles. More information on the SIH sample design can be located in the Survey of Income and Housing, User Guide, Australia, 2011-12 (cat. no. 6553.0) product.
56 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 'Sampling Variability').
57 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 the twelve months of 2012 so that the survey results are representative of income patterns across the year.
58 Of the selected dwellings there were 18,665 households in the scope of the survey. Of these, 3,819 did not respond at all to the questionnaire, or did not respond adequately. Of these 3,819 households, 47.2% were not able to be contacted during the survey enumeration and 16.1% were contacted but either refused to respond or were not able to respond. The remainder of these households included:
59 Some households did not supply all the required information but supplied sufficient information to be retained in the sample. Such partial response occurs when:
60 In the first two cases, the data provided are retained and some missing data are imputed by replacing each missing value with a value reported by another person (referred to as the donor).
61 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).
62 The HECS did not impute data for the following types of items:
63 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.
64 The final sample includes 545 households which had at least one imputed value in household energy expenditure.
65 The final sample on which estimates were based is composed of persons 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 15,797 in the scope of the survey, of which 11,978 (75.8%) were included as part of the final estimates.
HECS FINAL SAMPLE, 2012
- nil or rounded to zero
(a) Number of persons aged 15 years and over.
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 (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).
67 An adjustment is then made to the initial weights to ensure that seasonal variation is appropriately represented in survey estimates. After this initial adjustment, the sum of the weights of households in each quarter is in proportion to the length of the quarter (which align across the financial year with pension indexation dates rather than calendar quarters).
68 The quarterly adjusted 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.
69 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 HECS are built up from the 2006 Census.
70 Each household, and all persons in each household were assigned a weight. Weighting was not performed to account for the non-response bias in the longitudinal component of HECS. This means separate longitudinal weights were not produced for households in the longitudinal sample. However, responding households to the longitudinal still had weights as part of the full sample weighting process.
71 The benchmarks used in the calibration of the final weights for the HECS were:
72 Estimates produced from the survey are usually in the form of averages (e.g. average energy expenditure of couple households with dependent children), or counts (e.g. total number of households that use particular sources of energy). For counts of households, the estimate was obtained by summing the weights for the responding households in the required group (e.g. those owning their own dwelling). For counts of persons, the household weights were multiplied by the number of persons in the household before summing. The HECS 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.
73 Average expenditure values are obtained on a household weighted basis, that is by multiplying the expenditure 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 energy expenditure of couple households with dependent children is the weighted sum of the energy expenditure of each such household divided by the estimated number of those households.
74 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, similar to average expenditure, are also calculated on a household weighted basis.
75 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.
RELIABILITY OF ESTIMATES
76 The estimates provided in this publication are subject to two types of error, non-sampling and sampling error.
77 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.
78 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.
79 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.
80 The following methods were adopted to reduce the level and impact of non-response:
81 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 Appendix 'Sampling Variability'.
82 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
83 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. For further information, contact ABS information consultants on 1300 135 070 from 9:00am to 4:30pm AEST Monday to Friday (International callers +61292684909).
UNIT RECORD FILE
84 A basic confidentialised unit record file (CURF) from the HECS will be released on CD-ROM after the release of the summary of results product. A more detailed (expanded) SIH CURF will also be available through the ABS Remote Access Data Laboratory. All clients wishing to access the HECS basic and expanded CURFs 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.
85 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.
86 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
87 The User Guide, Household Energy Consumption, User Guide, Australia, 2012 (cat. no. 4671.0), 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 HECS and other Household Energy surveys and collections. Its purpose is to help users of the data understand the nature of the survey, and its potential to meet user needs. It will also contain important information about the survey for users of the survey microdata.
88 In addition to this publication, users may wish to refer to the following ABS products which relate to income, wealth, housing and household expenditure. All publications can be downloaded free of charge from the ABS website.
Household Income and Income Distribution, Australia, 2011-12 (cat. no. 6523.0)
Household Wealth and Wealth Distribution, Australia 2011-12 (cat. no. 6554.0)
Housing Occupancy and Costs, Australia, 2011-12 (cat. no. 4130.0)
Household Expenditure Survey, Australia: Summary of Results, 2009-10 (cat. no. 6530.0)
Government Benefits, Taxes and Household Income, Australia 2009-10 (cat. no. 6537.0)
Survey of Income and Housing, User Guide, Australia, 2011-12 (cat. no. 6553.0)
Microdata: Survey of Income and Housing - Australia, 2011-12 (cat. no. 6541.0.30.001)
89 Other ABS publications relevant to household energy statistics are listed below. These publications can also be downloaded free of charge from the ABS website.
Household Water and Energy Use, Victoria, October 2011 (cat. no. 4602.2)
Queensland Water and Energy Use and Conservation, Oct 2009 (cat. no. 4602.3)
Household Choices Related to Water and Energy, WA, October 2009 (cat. no. 4656.5)
Environmental Views and Behaviour, 2011-12 (cat. no. 4626.0.55.001)
Environmental Issues: Energy Use and Conservation, March 2011 (cat. no. 4602.0.55.001).
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