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Changes to the survey sample
7 The May 2009 Budget funded an expansion in the SIH sample for an extra 4,200 households, located outside capital cities. This expansion was to better support Council of Australian Governments (COAG) performance indicator reporting, particularly in regard to housing affordability and home ownership measures required under COAG intergovernmental agreements.
8 For the 2009-10 SIH and 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 sample. 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.
9 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 2007-08 and 2009-10 income estimates apply the new income standards.
10 To the extent possible, the estimates for 2003-04 and 2005-06 shown in the time series tables in this publication also reflect the new treatments.
11 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)
12 Errors in processing the 2007-08 income estimates have been corrected, resulting in an average increase of $3 for mean equivalised disposable household income across all households. This was reflected largely in a 1.3% increase in the mean equivalised disposable household income of households in the highest quintile. The income estimates for 2007-08 shown in this publication have been revised.
CONCEPTS AND DEFINITIONS
13 The concepts and definitions relating to statistics of income are described in the following section. Other definitions are included in the glossary.
Person and household data
14 A major determinant of economic wellbeing for most people is the level of income they and other family members in the same household receive.
15 While income is usually received by individuals, it is normally shared between partners in a couple relationship and with dependent children. To a lesser extent, it may be shared with other children, other relatives and possibly other people living in the same household, for example through the provision of free or reduced accommodation costs. This is particularly likely to be the case for children other than dependants and other relatives with low levels of income of their own. Even when there is no transfer of income between members of a household, nor provision of free or reduced accommodation costs, members are still likely to benefit from the economies of scale that arise from the sharing of dwellings.
16 Household characteristics, including household income, are therefore the main information required for analysing income distribution. However, it is the number of people who belong to households with particular characteristics, rather than the number of households with those characteristics, that is of primary interest in measuring income distribution and leads to the preference for the equal representation of those persons in such analysis. For example, if the person is used as the unit of analysis rather than the household, then the representation in the income distribution of each person in a household comprising four persons is the same as that for each person in a household comprising two persons. In contrast, if the household were to be used as the unit of analysis, each person in the four person household would only have half the representation of each person in the two person household.
17 In this publication, the income distribution measures are all calculated with respect to persons, including children. Such measures are sometimes known as person weighted estimates. They are described in more detail in Appendix 1. Nevertheless, as most of the relevant characteristics of persons relate to their household circumstances, Tables 6 to 17 primarily describe the households to which people belong.
18 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.
19 Income includes receipts from:
20 Receipts of family tax benefit are treated as income, regardless of whether they are received fortnightly or as a lump sum. The aged persons' savings bonus and self-funded retirees' supplementary bonus, paid as part of the introduction of The New Tax System in 2000-01 are regarded as capital transfers as they were designed to help retired people maintain the value of their savings and investments following the introduction of the GST. However, the one-off payment to older Australians paid in 2000-01, 2005-06 and 2007-08, the one-off payment to families paid since 2003-04, and the one-off payments to carers paid since 2003-04, are included as income as they were primarily a supplement to existing income support payments. The maternity payment introduced in July 2004, now referred to as the Baby Bonus, is also included as income.
21 The one-off stimulus payments paid in 2008-09 and 2009-10 based on 2007-08 taxable income are also included as income. These stimulus payments include the one off payments from the Family Assistance Office of the single income family bonus, back to school bonus and the additional FTB Part A payment of $1,000 per child. These also include the stimulus payments from the Australian Taxation Office which were one-off income based payments of $250, $600 or $900 and the Centrelink assistance payments to health care card holders, carers, farmer hardship payment and the training and learning bonus.
22 Gross income is the sum of the income from all sources before income tax and the Medicare levy have been deducted. Prior to 2005-06 family tax benefit paid through the tax system or as a lump sum was excluded from gross income for practical reasons but deducted in deriving disposable income. Since 2005-06 these payments have been included in gross income.
23 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 (as it was for the first time in 2007-08).
24 Income tax is estimated for all households using taxation criteria for 2009-10 and the income and other characteristics of household members reported in the survey.
25 Prior to 2005-06 the derivation of disposable income also included the addition of family tax benefit paid through the tax system or as a lump sum by Centrelink since for practical reasons it was not included in the gross income estimates.
Equivalised disposable income
26 Most analyses in this publication use 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.
27 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.
28 For more information on equivalised income see Appendix 3.
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.)
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 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.
34 The tables in the main body 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 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.
35 In May 2008 the ABS released household level estimates of imputed rent, derived from data reported in the 2003-04 and 2005-06 SIH for the first time (Experimental Estimates of Imputed Rent, Australia, 2003-04 and 2005-06 (cat. no. 6525.0)). The availability of imputed rent estimates allows the analysis of household income to be extended to include the imputed rental incomes that flow to people living in homes owned by the occupant and those paying subsidised rent.
36 Such imputations allow for more meaningful comparison of the income circumstances of people living in different tenure types, and to understand changes over time in income levels and the distribution of income when tenures may be changing over time. Including imputed rent as part of household income and expenditure conceptually treats owner-occupiers as if they were renting their home from themselves, thus simultaneously incurring rental expenditure and earning rental income. Imputed rent is included in income on a net basis i.e. the imputed value of the services received less the value of the housing costs incurred by the household in their role as a landlord.
37 Hedonic regression is used to estimate the market value of the rental equivalent of an owner-occupied dwelling. Data from the SIH on reported rents paid by private market renters is regressed on the characteristics of their rented dwellings e.g. location and dwelling structure. The estimated coefficients are then applied to the corresponding characteristics of owner-occupied and other dwellings to produce imputed values of the gross rental equivalence for these dwellings.
38 Net imputed rent is estimated as gross imputed rent less reported housing costs. For owner occupiers, the housing costs subtracted are those which would normally be paid by landlords i.e. rates, mortgage interest, insurance, repairs and maintenance. For households paying subsidised rent (e.g. tenants of an employer or of a state/territory housing authority) and households occupying their dwelling rent-free, the housing costs that are subtracted are largely made up of the reported rent paid, but other housing costs incurred, such as rates, are also subtracted for some tenure types. In the case of tenants of state/territory housing authorities, the net imputed rent estimates have been benchmarked to administrative data on the mean weekly rental subsidy.
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 2009-10 SIH, some asset and liability data were collected on a net basis rather than collecting for each component listed above. In particular, if a survey respondent owned or part owned a business, they were asked how much they would receive if they sold their share of the business and paid off any outstanding debts.
42 While this publication provides some household net worth statistics, principally to aid income analysis, a more comprehensive range of household asset and liability information will be released in October 2011 in Household Wealth and Wealth Distribution, Australia, 2009-10 (cat. no. 6554.0).
43 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.
44 Usual residents excludes:
45 Information for each household was collected using:
46 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.
47 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 4).
48 The SIH sample was designed in conjunction with the HES. 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.
49 For the 2009-10 SIH and 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.
50 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 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.
51 For the SIH (excluding the additional pensioner sample) there were 18,285 households in the scope of the survey. Of these, 3,421 did not respond at all to the questionnaire, or did not respond adequately. Of these 3,421 households, 33% were not able to be contacted during the survey enumeration and 49% were contacted but either refused to respond or were not able to respond. The remainder of these households included:
52 For the additional pensioner sample 42,913 dwellings were approached to screen for inclusion in the sample.
Partial response and imputation
53 Some households did not supply all the required information but supplied sufficient information to be retained in the sample. Such partial response occurs when:
54 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).
55 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).
56 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.
57 The final sample includes 5,419 households which had at least one imputed value in income or child care expenses. For 53.7% of these households only a single value was missing, and most of these were for income from interest and investments or information relating to household loans.
58 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 18,285 in the scope of the survey, of which 14,864 (81%) were included as part of the final estimates. For the additional pensioner sample 4,804 dwellings identified as being in scope, of which 3,027 dwellings (67%) were included on the final file. The final combined sample consists of those 18,071 households, comprising 33,999 persons aged 15 years old and over.
59 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).
60 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.
61 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.
62 In the 2009-10 SIH, as in 2007-08, all persons in each household were assigned a weight. This differs from the 2005-06 SIH where children aged 0-14 years were not given separate weights, but household counts of the number of children were benchmarked to population totals.
63 The SIH survey was benchmarked to the in scope estimated resident population (ERP) and the estimated number of households in the population. The 2009-10 SIH used population and household benchmarks based on the 2006 Census.
64 The benchmarks used in the calibration of the final weights for the 2009-10 SIH were:
65 More detailed age groupings have been used where possible in benchmarking 2009-10 SIH results.
66 The benchmark for the value of government benefit cash transfers was used for 2009-10 because, without it, the survey estimates of the number of people receiving income from government benefit cash transfers were lower (81% coverage) than the expected 85% coverage of payments reported by the Department of Family and Community Services, the Department of Veterans' Affairs and the Department of Education, Employment and Workplace Relations. This benchmark was last used in compiling results from the 2000-01 SIH. The benchmark is intended to address likely differences between the characteristics of people who responded to the survey and the characteristics of those who did not respond. The economic circumstances between the 2007-08 and 2009-10 SIH collections saw strong growth in the numbers of recipients for the age pension and disability support pensions. Introducing an additional benchmark is a means of addressing this. The benchmark ensured that the survey estimate of government benefit cash transfers is maintained at a proportion of aggregate benefit cash transfers that is consistent with previous SIH cycles.
67 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.
68 In weighting the pensioner sample, independent initial probability weights were assigned to the pensioner sample as it was selected separately from the SIH 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 SIH enumeration and the initial probability weights were adjusted accordingly.
69 The pensioner weighted estimates for persons and households were calibrated to the main SIH sample estimates of persons, households and total weekly household income.
70 Composite estimation was used to obtain the optimal proportions for combining the pensioner sample and main SIH 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.
71 Estimates produced from the survey are usually in the form of averages (e.g. average weekly income of couple households with dependent children), or counts (e.g. total number of households that own their dwelling or total number of persons living in households that own their own dwelling). For counts of households, the estimate was obtained by summing the weights for the responding households in the required group (e.g. those owning their own dwelling). For counts of persons, the household weights were multiplied by the number of persons in the household before summing. The SIH collects data on the number of people, including children, in each household but separate records with income and most detailed data were only collected for people 15 years and older.
72 Average income values are obtained in two different ways, depending on whether mean gross household income or mean equivalised disposable household income is being derived. Estimates of mean gross household income are calculated on a household weighted basis. They are obtained by multiplying the gross income of each household by the weight of the household, summing across all households and then dividing by the estimated number of households. For example, the mean gross household income of couple households with dependent children is the weighted sum of the gross income of each such household divided by the estimated number of those households.
73 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. Appendix 3 illustrates the differences between mean gross household income calculated on a household weighted basis and mean equivalised disposable household income calculated on a person weighted basis.
RELIABILITY OF ESTIMATES
74 The estimates provided in this publication are subject to two types of error, non-sampling and sampling error.
75 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.
76 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.
77 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.
78 The following methods were adopted to reduce the level and impact of non-response:
79 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 4.
80 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
81 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
82 It is expected that a basic confidentialised unit record file (CURF) from the 2009-10 SIH will be released on CD-ROM in September 2011. It is also expected that a more detailed (expanded) SIH CURF will be available through the ABS Remote Access Data Laboratory. All clients wishing to access the SIH 2009-10 basic and expanded CURFs should refer to the ABS Website <https://www.abs.gov.au> (see Services, ABS Microdata) and read the Microdata Entry Page, and other linked information, before downloading the appropriate Guide, Application and Undertaking forms and applying for access.
83 University clients should refer to the ABS web site <www.abs.gov.au> (see Services, Services for Universities). The SIH 2009-10 basic and expanded CURFs can be accessed by universities participating in the ABS/Universities Australia Agreement for research and teaching purposes.
84 Other prospective CURF clients should contact the Microdata Access Strategies Section of the ABS at <firstname.lastname@example.org> or on (02) 6252 7714.
85 Users may wish to refer to the following ABS products which relate to income. All can be downloaded free of charge from the ABS website.
Microdata: Household Expenditure Survey and Survey of Income and Housing - Basic and Expanded CURF, Australia (cat. no. 6540.0) is expected to be released in September 2011
Household Expenditure Survey, Australia: Summary of Results, 2009-10 (cat. no. 6530.0) is expected to be released in September 2011
Housing Occupancy and Costs, Australia, 2009-10 (cat. no. 4130.0) is expected to be released in November 2011
Household Wealth and Wealth Distribution, Australia 2009-10 (cat. no. 6554.0) is expected to be released in October 2011
Government Benefits, Taxes and Household Income, Australia 2009-10 (cat. no. 6537.0) is expected to be released mid 2012
86 The earlier publications relating to the SIH are listed below. These publications can also be downloaded free of charge from the ABS website.
Estimates of Personal Income for Small Areas, 2001-02 to 2005-06 (cat. no. 6524.0.55.002)
Government Benefits, Taxes and Household Income, Australia, 2003-04 (cat. no. 6537.0)
Household Expenditure Survey, Australia: Summary of Results, 2003-04 (cat. no. 6530.0)
Household Expenditure Survey, Detailed Expenditure Items, 2003-04 (cat. no. 6535.0.55.001)
Housing Occupancy and Costs, Australia, 2007-08 (cat. no. 4130.0)
Household Wealth and Wealth Distribution, Australia, 2005-06 (cat. no. 6554.0)
87 The other ABS publications relevant to income statistics are listed below. These publications can also be downloaded free of charge from the ABS website.
Average Weekly Earnings, Australia (cat. no. 6302.0) - quarterly
Measuring Wellbeing: Frameworks for Australian Social Statistics, 2001 (cat. no. 4160.0)
Measures of Australia's Progress, 2010 (cat. no. 1370.0)
Estimates of Personal Income for Small Areas, Time Series, 2003-04 to 2007-08 (cat. no. 6524.0.55.002)
Information paper: Changes to ABS Measures of Employee Remuneration, Australia, 2006 (cat. no. 6313.0)
Standards for Income Variables, 2010 (cat. no. 1287.0) - this is only available electronically and cannot be downloaded.
88 Users may also wish to refer to the following non-ABS products which relate to income.
(Australian Tax Office) link: under > Corporate > Our statistics centre > Taxation Statistics
Statistical Paper No. 3: Income support customers: A statistical overview 2010
(Department of Families, Community Services and Indigenous Affairs)
link: under FaHCSIA Internet > About FaHCSIA > Publications & Articles > Research Publications > Statistical Paper series
Household, Income and Labour Dynamics in Australia (HILDA) Survey, Annual Report 2010 (Department of Families, Housing, Community Services and Indigenous Affairs)
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