# Estimates of imputed rent

Methodologies to produce imputed rent estimates for dwellings receiving subsidised housing in ‘Income and Housing’ & ‘Household Expenditure’ surveys

Released
23/03/2018

## Introduction

Note: this paper was formerly known as 6525.0 - Experimental Estimates of Imputed Rent, Australia, 2013-14.

This information paper presents a detailed explanation of the final methodologies implemented for estimates of imputed rent in the 2015–16 Survey of Income and Housing (SIH) and Household Expenditure Survey (HES). These include imputed rent estimates for owner-occupied dwellings and the imputed benefit to tenants not paying market rents.

The ABS first released experimental household level estimates of imputed rent for owner-occupied dwellings and other tenure types not paying market rents in May 2008, derived from data reported in the 2003–04 and 2005–06 Surveys of Income and Housing (SIH). The same methodologies were used for each subsequent SIH up to 2011–12. For the 2013–14 SIH, new experimental methodologies for estimating gross imputed rent were developed to address limitations of the previous methodologies. For the 2015–16 SIH, further refinements to the experimental methodologies were applied.

Estimates of imputed rent for 2003–04 to 2015–16 are presented in Household Income and Wealth, Australia, 2015–16 (cat. no. 6523.0). Estimates between 2003–04 and 2013–14 have been revised to be consistent with the new method outlined in this paper.

### Background

Household income statistics compiled for individual households are critical to analysis and modelling that supports understanding the socio-economic circumstances of different household types. They are also important in developing and evaluating policies on income support, income distribution and income taxation.

The ABS regularly collects detailed information on household income, expenditure and wealth in SIH and HES. SIH is conducted every two years, with the latest results published with respect to 2015–16. The HES is conducted every six years, with the latest survey relating to 2015–16. The SIH and HES were conducted on an integrated basis in 2003–04, 2009–10 and 2015–16.

The ABS releases summary statistics on household income in Household Income and Wealth, Australia (cat. no. 6523.0). Microdata from the surveys, such as the Confidentialised Unit Record Files (CURFs) and access to files via the DataLab (restricted to authorised users), are also available to users to support comprehensive and detailed analyses.

The most restricted concept of income used in income analysis is the gross private income of individuals. While this measure is useful for certain purposes, it is generally of limited use when trying to understand people’s broader economic wellbeing. Published ABS household income analysis, in accordance with international statistical standards, extends this income measure by:

• adding government transfers (both cash and in kind),
• deducting direct and indirect taxes,
• equivalising household income to adjust for household size, and
• adding an imputed rent value for the net benefits of home ownership and subsidised rent payments.

Imputed rent is included in both household income and expenditure. This 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 generally incurred by the household in their role as a landlord. Gross imputed rent is added to the expenditure of owner-occupiers, and any housing costs generally borne by a landlord are deducted (e.g. general and water rates, building insurance).

Including imputed rent in income for people living in different tenure types enables more meaningful analysis to be undertaken on their economic wellbeing and enables better analysis of changes over time in income levels and income distribution if tenures change. International standards for household income and expenditure statistics also recommend the inclusion of imputed rent to support different types of analyses.

### References

International Conference of Labour Statisticians 2003, Final Report of the 17th International Conference of Labour Statisticians, Geneva, 24 November to 3 December 2003.

UNECE (2011), Canberra Group Handbook on Household Income Statistics, Second Edition, ECE/CES/11, Geneva.

System of National Accounts, 2008 (2008 SNA).

## Final methodology

### Introduction

Different methodologies are used to produce household level estimates of gross and net imputed rent for:

• owner-occupied dwellings, and
• other tenure types.

This section provides a step by step explanation of how household level estimates of gross and net imputed rent have been created for these tenure types.

The market value of the rental equivalent for owner-occupied dwellings can be estimated in a number of ways (e.g. self-report, stratification and regression approaches). The statistical office of the European Union, Eurostat, has reviewed rental equivalence methods and recommended regression or stratification techniques in countries where representative market rates can be obtained (Eurostat 2006). Australia has a well-established private rental market, and this data is the basis for both the previous and new methodologies. A non-parametric stratification technique is used to estimate the market value of the rental equivalent in the new methodology for owner-occupied dwellings. The stratification method replaces the previously used hedonic regression method. A stratification method was first adopted for the 2013-14 Survey of Income and Housing (SIH) outputs and has undergone further refinement for the 2015–16 SIH outputs to improve these methodologies (see the 'Changes to methodology over time' section).

The net imputed rent for owner-occupied dwellings has been estimated as:

• the market value of the rental equivalent (referred to as gross imputed rent); less
• the housing costs normally paid by landlords i.e. general rates, water and sewerage rates, mortgage interest, building insurance, repairs and maintenance.

The imputation of gross and net imputed rent includes other housing tenures in order to value the in-kind benefit conferred to 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 gross imputed rent for these housing tenures has been estimated using the same stratified rental data from the Census of Population and Housing as used for owner-occupiers. In deriving net imputed rent for these tenure types, actual rent paid is the major housing cost deducted.

### Overview

The methodology for estimating gross imputed rent for individual owner-occupied dwellings uses the relationship between dwelling price (available from Valuers General data) and the market rent that a dwelling would receive (available from Census data).

By merging aggregated Valuers General (VG) data and Census dwelling data for the smallest available geographic area, rental yields based on average dwelling prices and reported rents have been calculated for each rental dwelling in the Census. These rental yields (termed base rental yields) underpin the new methodology.

The methodology takes account of differences in the value of dwellings and market rents due to location, type of dwelling and Socio-Economic Indexes for Areas Index of Relative Socio-Economic Advantage and Disadvantage (SEIFA IRSAD), to produce an estimate of a market rent for each owner-occupied dwelling in the SIH.

Appendix 2 summarises the detailed steps described below to produce gross imputed rent estimates for owner-occupied dwellings.

### Produce base rental yields for owner-occupied dwellings

Census data was used to provide market rents paid by households by type of dwelling for each SA1 in Australia in scope of the SIH.

VG data was used to provide an average (mean) dwelling price for each SA1 in Census 2011. To ensure there were sufficient dwelling sales to produce reliable estimates, VG dwelling sales prices for the financial year before and after the Census were used i.e. 2010–11 and 2011–12 for the 2011 Census. To ensure the dwelling sales prices were representative of the region, an average price was only calculated if there were at least five dwelling sales in the SA1 in the two year period. For the 2011 Census, approximately 16% of SA1’s were excluded due to an insufficient number of dwelling sales. This has negligible impact due to the broader stratifications applied to the data, as explained in Step 1.2 below.

To produce historical imputed rent estimates using the new methodology, CD Census 2006 data and VG dwelling sales data from 2005–06 and 2006–07 were also used. Estimates for 2015–16 will be reviewed based on 2016 Census data and 2015–16 and 2016-17 VG dwelling sales data in due course.

The following three steps were used to calculate a base rental yield to produce gross imputed rent estimates for individual dwellings in the SIH.

### Step 1.1 ‒ Calculate a preliminary rental yield for each SA1 or CD

The first step was to pool VG dwelling sales and Census rental data. A preliminary rental yield was allocated to each Census rental dwelling by dividing its reported rent by the mean VG dwelling price from sales in the SA1 or CD where the Census dwelling was located. If no mean dwelling price was available because there were less than five dwelling sales in the relevant SA1/CD, the rental records for that region were excluded.

### Step 1.2 ‒ Stratify Census rental records

Census rental records, with the preliminary rental yield added to each record, were then stratified using the following variables:

• State/territory (eight categories)
• Section of state (four categories)
• Dwelling type (up to two categories)
• SEIFA IRSAD quintiles (five categories).

The final strata were determined based on analysis that there were sufficient dwellings to support the estimates. Strata created for each of the states and territories can be found in the 'Data access' section of this product.

Table 2 in the 'Data access' section shows the 25 strata created in each of the six states. Five categories based on different combinations of section of state and dwelling type were created for each of the five SEIFA IRSAD quintiles.

The territories have fewer strata. In the Northern Territory there were 15 strata because section of state was reduced to two categories (major/other urban and bounded locality/ rural balance) (see Table 3 in 'Data access'). In the Australian Capital Territory, there were 10 strata because section of state was not used (see Table 4 in 'Data access').

The total number of strata for the entire SIH population was therefore 175.

### Step 1.3 ‒ Estimate a final base rental yield for each stratum

The third step was to create a final base rental yield for each of the 175 strata. The preliminary rental yields for the Census rental records in each stratum (from Step 1.2), were ranked from highest to lowest. The final base rental yield for each stratum was the median preliminary rental yield for that stratum.

To ensure rental yields were representative for each stratum a median was only calculated if there were at least five Census rental records in the stratum. If there were insufficient records, the rental yield was imputed using a rental yield from an adjacent SEIFA IRSAD quintile with the same dwelling characteristics.

### Estimate gross imputed rent for dwellings in base SIH cycles

Base SIH cycles are those enumerated at around the same time as the Census i.e. SIH 2005–06 (2006 Census) and SIH 2011–12 (2011 Census).

As the SIH contains all of the stratification variables listed in Step 1.2, each owner-occupied dwelling in the sample can be matched to a unique stratum. The gross imputed rent for each owner-occupied dwelling in the base SIH cycles was calculated as the final base rental yield for the relevant stratum of the dwelling, multiplied by the estimated sale price of the dwelling reported in the SIH.

Dwellings with an extremely low estimated sale price reported in the SIH, resulted in an unreasonably low estimate of gross imputed rent. A minimum value was therefore applied, equal to the market rent at the top of the first percentile for the relevant state in the Census. This ensured the gross imputed rent estimate reflected reasonable market costs associated with renting a property.

### Produce intercensal rental yields for owner-occupied dwellings

The relationship between rents and dwelling prices can vary over time as prices change at different rates. To reflect the relative differences between the change in dwelling prices compared to rents, an adjustment factor was created using data reported in the intercensal SIH cycles for which gross imputed rent was to be calculated (SIHs 2003–04, 2007–08, 2009–10 and 2013–14). An intercensal adjustment factor was also used for SIH 2015–16 due to updated VG data not being available at the time of compilation (this will be updated in due course).

As there is significant variation in the change in rents and house prices between states and territories, separate adjustment factors were created for greater capital city area and rest of state for each of the six states. Adjustment factors were created for each territory at the territory level. Appendix 2 and the 'Changes to methodology over time' chapter provide further analysis underpinning the development of the intercensal adjustment factors.

There were three steps to produce the intercensal rental yields.

### Step 2.1 ‒ Calculate mean rental yields for each state/territory using SIH data

For each SIH from 2003–04 to 2015-16, a mean rental yield was calculated for each state/territory as the mean rent reported by market renters divided by the mean value of owner-occupied dwellings.

### Step 2.2 ‒ Calculate rental yield adjustment factors for intercensal SIH cycles

A rental yield adjustment factor was calculated for each of the non-base SIH cycles as its mean rental yield divided by the mean rental yield for the relevant base SIH cycle (2005–06 or 2011–12) (from Step 2.1).

SIH 2005–06 is the base cycle for SIHs 2003–04, 2007–08 and 2009–10. For SIH 2013–14 and 2015–16, the base cycle was SIH 2011–12. Updated VG data was not available at the time of SIH 2015–16 compilation therefore the SIH 2011–12 base cycle was used. It is expected that new base rental yields will be implemented for SIH 2017–18 to include updated Census and VG data.

### Step 2.3 ‒ Calculate strata rental yields for intercensal SIH cycles

An adjusted rental yield was calculated for each stratum in each intercensal SIH, as the final base rental yield of the stratum (from the process outlined in step 1) multiplied by the rental yield adjustment factor (step 2.2) for the relevant state/territory of the stratum.

### Estimate gross imputed rent for intercensal SIH cycles

Gross imputed rent for the intercensal SIH cycles was calculated for each owner-occupied dwelling as the adjusted rental yield (Step 2.3) for the relevant stratum of the dwelling, multiplied by the estimated sale price of the dwelling reported in the SIH.

### Net imputed rent for owner-occupied dwellings

To calculate the net imputed rent for owner-occupied dwellings, the following housing costs normally paid by landlords were subtracted from the gross imputed rent:

• body corporate payments
• general and water rates
• the interest component of repayments of loans that were obtained for the purposes of purchasing or building the dwelling
• house insurance, and
• repair and maintenance costs.

All housing costs were net of refunds or subsidies received from outside the household.

All of the relevant housing costs are collected in the SIH except for expenditure information on house insurance and repairs and maintenance. Household Expenditure Survey (HES) 2003–04, 2009–10 and 2015–16 data were used to estimate these expenditures.

Average repair and maintenance costs were calculated for owner-occupiers, stratified by the number of bedrooms. The relevant average expenditure was allocated to each owner-occupied dwelling in the SIH. In non-HES years, these costs were extrapolated using the published ABS Consumer Price Index for 'House repairs and maintenance'.

Stratification by number of bedrooms was also used to calculate an average cost of house insurance using HES data. Average house insurance costs for the relevant number of bedrooms were allocated to all owner-occupiers in the SIH based on HES data. Where house insurance costs were combined with home contents insurance costs, a factor was applied to the total expenditure to estimate the amount for excluding home contents insurance costs. In non-HES years, expenditure was estimated by inflating the most recent HES data using the published Consumer Price Index for 'Insurance services'.

### Gross imputed rent for other tenure types

Methodologies for calculating gross imputed rent and net imputed rent for other tenure types remain unchanged. The methodologies implemented in SIH 2013–14 were used in SIH 2015–16 and will continue to be used in future cycles. The current methodologies still in use are detailed below.

### Overview

Some renters do not pay a market rent, effectively receiving a subsidy for their living costs. Typically, the subsidised rent is made available by government state and territory housing authorities, employers or a family or friend, collectively termed, ‘Other tenure types’.

The value of this subsidy can be estimated by calculating the gross imputed rent (i.e. market rent) for the property and then deducting the actual rent paid by the tenant (reported in the SIH).

The methodology for calculating gross imputed rent for owner-occupied dwellings is not suitable for other tenure types as there is no estimate in the SIH of the value of these dwellings. Therefore, a different approach has been developed that uses the strata developed for imputing the rent for owner-occupied dwellings.

Appendix 2 summarises the steps described below to produce gross imputed rent estimates for other tenure types.

### Estimate gross imputed rent for other tenure types

An imputed market rent value was calculated for other tenure types using the median Census rent for the relevant stratum of the subsidised rental dwelling.

For intercensal SIHs, the estimates have been indexed to account for changes in rent over time. The indexation method is similar to that used for owner-occupied dwellings i.e. the percentage difference between the mean rent from the SIH conducted at the time of the last Census and the mean rent for the SIH cycle in question.

Not all households identified in the SIH as potentially living in a subsidised rental dwelling actually receive any discount on their rent. Therefore, if the estimated gross imputed rent was lower than the actual reported rent, the reported rent was used for the gross imputed rent estimate.

This methodology has been applied to SIH 2013–14 and SIH 2015–16 and will be used for subsequent surveys. For all cycles up to SIH 2011–12, the gross imputed rent for other tenure types remains unchanged from previously published estimates that used the hedonic regression model. For these other tenure types, the current methodology has minimal impact on the estimates (2% in 2011–12).

### Net imputed rent for other tenure types

For other housing tenure types, the housing costs subtracted from gross imputed rent to derive net imputed rent are outlined in Table 1.

Table 1. Housing costs subtracted from gross imputed rent, other tenure types
Housing tenureHousing costs (net of refunds)
Subsidised renter(a)Reported rent paid.
Occupied rent-freeBody corporate fees; and general and water rates payments.
Rent-buy/shared equity schemeReported rent paid; body corporate fees; general and water rates payments; the interest component of repayments of loans that were obtained for the purposes of purchasing or building the dwelling; house insurance; and repair and maintenance costs.
Life tenure schemeBody corporate fees and general and water rates payments.
1. Includes households renting from: a state/territory housing authority; a parent or other relative not living in the same household; an employer; a housing cooperative or community/church group.

For each of the housing tenures described in Table 1, any refunds or subsidies received for rent payments were implicitly accounted for in the estimation of net imputed rent. For consistency across all housing tenures, the reported values of any rental refunds or subsidies received by private market renters have been included in the estimates of net imputed rent.

For tenants of state/territory housing authorities, the mean difference between the initial gross imputed rent estimates and the reported rent paid were compared with the mean weekly rental subsidy published in the Report on Government Services (RoGS) for each state. Where initial net imputed rent estimates underestimate the mean benefit for public tenants, net imputed rents are benchmarked to the RoGS published state mean weekly rental subsidies using a multiplicative adjustment.

### References

ABS, Socio-Economic Indexes for Areas (SEIFA), Australia (cat. no. 2033.0.55.001)

RoGS, Report on Government Services 2017, Housing and Homelessness

Eurostat 2006, 'HBS and EU-SILC Imputed Rent', Meeting of the Working Group on Living Conditions, Luxembourg, 15–16 May 2006

## Changes to methodology over time

The ABS developed and implemented new experimental methodologies of gross imputed rent for owner-occupied dwellings and other tenure types for the Survey of Income and Housing (SIH) 2013–14.

Following peer review and coherence investigations with National Accounts imputed rent estimates and Census data, further refinements have been made to the gross imputed rent methodology for owner-occupied dwellings. Methodologies have now been finalised and implemented for the 2015–16 SIH and Household Expenditure Survey (HES).

Gross imputed rent methodology for other tenure types remains unchanged and is consistent with the experimental methodology implemented in SIH 2013–14.

### Review findings

Investigations suggested that an upward bias may be present in the experimental estimates for owner-occupied dwellings, particularly for dwellings with four or more bedrooms. For strata of a similar location and dwelling type (e.g. separate houses in Sydney), experimental rental yields were observed to increase with the number of bedrooms. This observation does not align with the general expectation of higher rental yields for lower value dwellings, and vice versa. Investigations also suggested that imputed rents were slightly underestimated for one and two bedroom dwellings.

For example, the rental yield for a two bedroom house in a given region was 0.00059113 under the experimental method. For houses with additional bedrooms in the same areas, yields increased to 0.00089476 for a five bedroom house. Continuing on with this example, a two bedroom house valued at $500,000 and a five bedroom house valued at$900,000 would receive $296 and$805 in gross imputed rent respectively. Note that the latter amount is likely to exceed market rents for a five bedroom in the same area. Additionally, depending on market conditions, rent for a two bedroom house could easily exceed the $296 calculated. The inclusion of number of bedrooms as a stratification variable was the main cause for this trend. Within the experimental method strata, the composition of rental properties compared to owner-occupied dwellings appeared very different. There are far more owner-occupied properties that were separate dwellings with three or more bedrooms when compared to rental properties (particularly in higher SEIFA quintile areas). Therefore in calculating final base rental yields, the rent paid for rental dwellings (the numerator) tended to be for a smaller number of bedrooms in each strata, while dwelling value based on the Valuers General (VG) sales data (the denominator) related to all dwellings sold in the relevant SA1. As a result, the experimental estimates are likely to have overestimated the rental yields for owner-occupied dwellings, such as in the example above, particularly those with four or more bedrooms, and underestimate the rental yield for one or two bedroom units. Removing the number of bedrooms as a stratification variable, reduces cases of very high imputed rents for dwellings with a higher number of bedrooms and increases imputed rents for dwellings with fewer bedrooms. Using the same houses from the example above, the rental yield for both dwellings is 0.0007598 under the revised method, which for our two and five bedroom houses would estimate gross imputed rents of$380 and \$684 respectively. While the latter imputed rent value may be higher than current market rents for a similar property for the area (based on type and number of bedrooms), it is still plausible. It is often difficult to find a rental market equivalent which reflects the additional features of owner-occupied dwellings. Aspects such as solar panels, insulation and improved heating/cooling and other appliances more prevalent in owner-occupied dwellings can contribute to higher gross imputed rents for these dwellings compared to market alternatives.

This limitation may be addressed if the VG dataset provided dwelling characteristics information such as number of bedrooms or dwelling type, which are currently not available on the dataset. The review did not identify the absence of dwelling type from the VG dataset as a significant limitation. Investigations into Census data revealed that most strata were relatively homogenous for type of dwelling. Similarities between yields for semi-detached dwellings and flats, units and apartments were noted.

### Stratification changes

The final methodologies remove the number of bedrooms as a stratification variable, allowing type of dwelling and rental yield for each region to determine the gross imputed rent for the dwelling. Strata for semi-detached dwellings were also combined with flats, units and apartments due to very similar rental yields.

The overall impact of these changes served to reduce derived rental yield for dwellings in major urban areas with four or more bedrooms, and increase the yield for one and two bedroom units, apartments and semi-detached dwellings.

The distribution of gross imputed rent has remained mostly unchanged between the experimental and final methodologies. Graph 1 below outlines the change in the distribution for owner-occupied dwellings between the experimental methodology implemented in SIH 2013–14 and the finalised methodology, using data for 2013–14 as a comparison. Graph 1 shows that the new final methodology has removed the upward bias for larger dwellings (higher end of the distribution) and the downward bias for one bedroom units (lower end of the distribution).

### Graph 1. Distribution of gross imputed rent for owner-occupied dwellings, 2013-14

As outlined in the Final Methodology section of this publication, an adjustment factor is used to improve the estimation of changes in gross imputed rent over time. The relative change in mean market rents and the mean value of owner-occupied dwellings between each SIH cycle are used for the adjustment factor. The experimental method adjusted estimates at a state level only. Further analysis revealed that the survey data can support an adjustment that includes a Capital City and Rest of state split for the six states. The final methodology implements this change to intercensal adjustment factors to better account for different patterns of change in house prices and rents across regions.

The revised adjustment factors were validated by comparing the gross imputed rent estimates for the SIH 2011–12 when they were calculated using 2011 Census data and those calculated using Census 2006 data extrapolated forward. As shown in Graph 2, the two results for the 2011–12 period remain consistent in the current method.

### References

Household Income and Wealth, Australia, 2015–16 (cat. no. 6523.0)

Census of Population and Housing, 2006 and 2011.

## Data access

For the Survey of Income and Housing (SIH) 2015–16 imputed rent estimates have been produced using only the new final methodologies.

Revised household level historical estimates for each SIH between 2003–04 and 2013–14 have also been produced. There are three ways by which data analysts can access these new estimates of imputed rent for owner-occupied dwellings.

Imputed rent estimates for each Survey of Income and Housing (SIH) and Household Expenditure Survey (HES) between 2003–04 and 2013–14 using the methodology outlined in this paper are available in following ways:

• Aggregate estimates using the new methodology have been published in Data cube 13 - Imputed Rent, available from the Data downloads section of Household Income and Wealth, Australia, 2015–16 (cat. no. 6523.0).
• Estimates are available via customised data requests from the ABS for each SIH and HES between 2003–04 and 2013–14. This is a charged service.
• The ABS publishes Confidentialised Unit Record Files (CURFs) for each SIH and HES. For more information on the SIH and HES CURF files see Microdata: Income and Housing, Australia 2013–14 (cat. no. 6541.0.30.001) and Microdata: Household Expenditure, Income and Housing 2015–16 (cat. no. 6540.0).
• SIH and HES data may also be accessed via the DataLab.

### Historical estimates

For each SIH and HES from 2003–04 to 2013–14, CURF and DataLab users can derive a modified estimate of gross imputed rent for individual owner-occupied dwellings using the methodology outlined in this paper.

A data cube is available under the Data downloads section of this publication that provides rental yields for strata created only using data items available on the relevant CURFs. It also provides a minimum market rent estimate for each state for each SIH year.

### Strata for gross imputed rent on detailed microdata files

For detailed microdata files, for each of the six Australian states, 25 strata were used (Table 2) using SEIFA IRSAD, Section of State and dwelling type. For the two Australian territories, the detailed Section of State classification was not used. Two groupings were used for the Northern Territory resulting in 15 strata (Table 3). Only one grouping was used for the Australian Capital Territory resulting in 10 strata (Table 4).

Table 2. Strata for NSW, Vic., Qld, SA, WA and Tas. for each SEIFA IRSAD quintile(a)
Section of stateDwelling
Major UrbanSeparate house
Major UrbanSemi-detached; flat, unit or apartment; other dwellings
Other Urbanna
Bounded Localityna
Rural Balancena

a. Total of 25 strata in each state
na not applicable

Table 3. Strata for NT for each SEIFA IRSAD quintile(a)
Section of stateDwelling
Major Urban and Other UrbanSeparate house
Major Urban and Other UrbanSemi-detached; flat, unit or apartment; other dwellings
Bounded Locality and Rural Balancena

a. Total of 15 strata in NT
na not applicable

Table 4. Strata for ACT for each SEIFA IRSAD quintile(a)
Section of stateDwelling
naSeparate house
naSemi-detached; flat, unit or apartment; other dwellings

a. Total of 10 strata in ACT
na not applicable

### Strata for gross imputed rent on Confidentialised Unit Record Files (CURFs)

Detailed geographical items are not included on historical CURFs, therefore gross imputed rent estimates can only be calculated using available data items. To calculate gross imputed rent estimates for owner-occupied dwellings using the the current method for historical SIHs, CURF users must use the stratification variables available (outlined in Tables 5 and 6 below) from the relevant CURF to identify the rental yield, which is published in the data cube in the Data downloads section of this product.

The gross imputed rent estimate is calculated as the estimated sale price of the individual owner-occupied dwelling multiplied by the rental yield for that SIH cycle. Estimates produced that are below the state minimum should be imputed with the minimum market rent for the relevant state/territory (also available in the data cube described above).

Table 5. NSW, Vic., Qld, SA, WA and Tas. (total 4 strata per state)
Area of usual residenceDwelling
Capital CitySeparate house
Capital CitySemi-detached; flat, unit or apartment; other dwellings
Balance of Statena

na not applicable

Table 6. NT and ACT (Expanded CURF), and combined NT and ACT (Basic CURF) (total 2 strata per territory)
Area of usual residenceDwelling
naSeparate house
naSemi-detached; flat, unit or apartment; other dwellings

na not applicable

For example, to calculate CURF estimates of gross imputed rent for separate houses in Sydney in 2003–04 using the final methodology, users can:

• stratify records by:
• state/territory of usual residence - to get New South Wales (STATEHBC)
• area of usual residence - to get Capital City (AREAHCF)
• dwelling structure - to get Separate House (DWELTCF)
• locate the rental yield for Sydney in the data cube published in the Data downloads section of this product (i.e. 0.0005493)
• multiply the Estimated sale price of dwelling item (HVALUECH) by rental yield provided to get the gross imputed rent estimates.

Gross imputed rent estimates for CURFs have been aligned with estimates derived from more detailed microdata files for the relevant state and territory in each SIH by adjusting the rental yields for each stratum by the amount necessary to achieve alignment. This adjustment helps minimise the effect of using limited data items on the CURF to stratify and calculate the estimates, when compared to those calculated from the detailed microdata files. The resulting difference between estimates produced using detailed microdata and CURF microdata is small (less than 10% difference).

### Net imputed rent

The housing costs deducted from gross imputed rent to calculate net imputed rent estimates for owner-occupied dwellings have not changed. Therefore, revised estimates of net imputed rent using the new methodology can be calculated by deducting the original housing costs for each dwelling from the revised gross imputed rent estimate for that dwelling.

### Imputed rent for other tenure types

Gross and net imputed rent estimates for other tenure types will not be revised for SIH 2003–04 to 2011–12 because the impact of the new final methodology is minimal on these estimates e.g. 2% in 2011–12. Methodologies implemented in 2013–14 for other tenure types remain unchanged and are consistent with the methodologies used in SIH 2015–16.

### References

UNECE (2011), Canberra Group Handbook on Household Income Statistics, Second Edition, ECE/CES/11, Geneva.

## Appendix 1 - data sources

### Show all

The major data sources used to produce household level estimates are:

• the ABS Survey of Income and Housing (SIH)
• the 2006 and 2011 Censuses of Population and Housing, and
• state and territory Valuers General (VG) dwelling sales data.

The ABS Household Expenditure Survey (HES) is also used for estimating some housing costs.

#### Survey of Income and Housing

The SIH collects detailed information about the income, assets, liabilities and household characteristics of households in private dwellings throughout Australia.

Information reported in the SIH on the estimated value of owner-occupied dwellings, the actual rent paid by private market renters, as well as other dwelling and household characteristics, are used in estimating the gross imputed rent for owner-occupied dwellings and other households not paying market rents. Housing costs reported in the SIH are also used in the estimation of net imputed rent.

#### Censuses of Population and Housing

The Census of Population and Housing counts the number of people in Australia on Census night as well as collecting information on their key characteristics, including information about the dwellings in which they live and rents paid.

Summary information on median rent by Collection District (CD) from the 2006 Census and Statistical Area 1 (SA1) from the 2011 Census are used in the estimation of gross imputed rent, as well as other dwelling characteristics and quintiles based on the Socio-Economic Index for Areas - Index of Relative Socio-Economic Advantage and Disadvantage.

2016 Census data will be applied when State and Territory VG dwelling sales data becomes available.

#### State and territory valuers general dwelling sales

Aggregated dwelling sales data from the state and territory VG departments has been used to provide an average (mean) dwelling price for the same geographical regions as the respective Census (CD or SA1). To ensure there were sufficient dwelling sales to produce reliable estimates, VGs dwelling sales prices for the financial year before and after each Census were used i.e. sales from 2005–06 and 2006–07 for the 2006 Census and 2010–11 and 2011–12 for the 2011 Census.

#### Household Expenditure Survey

HES data has been used in the compilation of net imputed rent estimates. The HES is conducted for a subset of households in the SIH sample in every third cycle of the SIH (that is, six yearly). Households selected to participate in the HES complete both the SIH and HES questionnaires. In the HES a personal diary is used, in which usual residents aged 15 years and over record their expenditure over two weeks.

Information reported in the 2003–04, 2009–10 and 2015–16 HES has been used to estimate average household expenditure on repairs and maintenance and house insurance costs for owner-occupiers, which are used to derive net imputed rent estimates.

#### Gross imputed rent

The data items used for estimating gross imputed rent in the new methodology are listed below. For each of the Census and VG data items, there is an equivalent data item available from the SIH. These data items are described below.

#### Table 1: Data items by data source

Data itemData item descriptionData source
Dwelling priceAggregate dwelling price data from actual dwelling salesVGs
Dwelling priceEstimated sale price of owner-occupied dwellingsSIH
Landlord typeType of landlord from whom the dwelling was rented, e.g. through
a real estate agent, from an unrelated person not living in the same household, from a family member, or from a state/territory housing authority
Census and SIH
Market rentRents paid to real estate agents or an unrelated person not living in the same household (excludes owner/managers of a caravan park for imputed rent purposes)Census and SIH
Dwelling sizeTotal number of bedrooms (used in the absence of a measure of the total floor area of the dwelling)Census and SIH
Type of dwellingWhether the dwelling was: a detached house; a semi-detached house or other dwelling; or a flat, unit or apartmentCensus and SIH
StateThe state/territory where the dwelling is locatedVGs, Census and SIH
Section of stateSection of state: major urban, other urban, bounded locality, and rural balanceCensus and SIH
LocationStatistical Area 1 (SA1) for data from the 2011 Census
Collection District (CD) for data from the 2006 Census

These equate to regions with between 200 and 800 people
VGs and Census
Socio-Economic Index for Areas (SEIFA)The Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) is used to indicate the socio-economic condition of the area where the dwelling is located. A higher score indicates that an area has attributes such as a relatively high proportion of people with high incomes or a skilled workforce. SEIFA IRSAD quintiles have been derived using the SEIFA index scores for each 2006 Census CD and 2011 Census SA1Census and SIH

#### Net imputed rent

Most housing costs required to estimate net imputed rent for individual households are collected in the SIH. House insurance and repairs and maintenance costs are estimated from data collected in the 2003–04, 2009–10 and 2015–16 HES.

#### References

Socio-Economic Indexes for Areas (SEIFA), Australia (cat. no. 2033.0.55.001), and

National Statistics, Census Data, Census Reference and Information.

All references are available on the ABS website http://www.abs.gov.au.

## Appendix 2 - summary of steps to produce gross imputed rent

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#### Step 1.1 Calculate a preliminary rental yield for each SA1

This section summarises the methodology for producing base rental yields from the 2011 Census based on SA1. This process was repeated for the 2006 Census except that the geographical region was the Collection District (CD) instead of the SA1.

#### (a) Prepare Valuers General (VG) dwelling sales data

Pool two years VG data (2010–11, 2011–12)

Let $$i$$ = dwelling in VG data

$$P S A_{i}$$ = sales price of ith dwelling in an SA1

$$N S A$$ = total number of dwellings in an SA1

Then – Discard any SA1 where $$N S A$$ < 5

– Calculate mean dwelling sales price ($$\overline{P S A}$$) for each remaining SA1 as:

$$\overline{P S A}=\left(\sum_\limits{i=1}^{N S A} P S A_{i}\right) / N S A$$

#### (b) Prepare Census rental records

– Retain Census market rental records, discarding the dwellings for:

• owner-occupiers;
• residents living in caravan parks; and
• rental records out of scope of SIH (in very remote regions).

#### (c) Merge VG and Census record dataset

– Attach respective $$\overline{P S A}$$ [from (a)] to each Census rental record [from (b)]

– Discard any Census records with no $$\overline{P S A}$$

#### (d) Calculate preliminary rental yield

Let $$j$$ = rental dwelling in Census

$$R_{j}$$ = weekly rent paid for $$j$$th dwelling

$$\overline{P S A}_{j}$$ = mean VG dwelling price for SA1 of $$j$$th dwelling [from (c)]

Then – For each Census rental record, calculate preliminary rental yield ($$R Y_{j}$$ ) as:

$$R Y_{j}=R_{j} / \overline{P S A}_{j}$$

#### Step 1.2 Stratify Census rental records

– Define strata ($$s$$): state × section of state × dwelling type × Socio Economic Index for Areas, Index of Relative Socio Economic Advantage and Disadvantage (SEIFA IRSAD) quintile

– 25 strata created for each state; 15 strata for NT; and 10 strata for ACT; 175 in total across Australia (see 'Data access' section)

#### Step 1.3 Estimate a final base rental yield for each stratum

Let $$R Y_{s}$$ = final base rental yield for a stratum $$s$$
$$Ns$$ = total number of dwellings paying rent in a stratum $$s$$

Then – Calculate final base rental yield as median of preliminary rental yields for a stratum $$s$$,i.e.

$$R Y_{s}=median\left(R Y_{s 1}, R Y_{s 2}, R Y_{s 3}, \ldots . R Y_{s N s}\right)$$

Note: If $$N_{s}$$ < 5 for any stratum, then the $$R Y_{s}$$ for another stratum with similar characteristics and geographic location is used

#### Produce base rental yields for owner-occupied dwellings in SIH 2005-06

– Repeat the same procedure outlined above for the Census 2006 file
– Smallest geographical area is Collection District (CD) instead of SA1

#### Estimate gross imputed rent for dwellings in base SIH cycles

Note: Base SIH cycles are those SIH conducted at around the same time as a Census, i.e. SIH 2005–06 and SIH 2011–12. The next base cycle will be SIH 2015–16 for the 2016 Census which will be implemented for the 2017–18 SIH when all required data becomes available.

Let $$G I R O D_{k}$$ = gross imputed rent for owner-occupied dwelling $$k$$

$$P O D_{k}$$ = SIH estimated sale price of owner-occupied dwelling $$k$$

Then – Calculate GIR for $$k$$th owner-occupied dwelling as its corresponding stratum rental yield ($$R Y_{s}$$) multiplied by the SIH estimated sale price of $$k$$th dwelling belonging to stratum, i.e.

$$G I R O D_{k}=R Y_{s} \times P O D_{k}$$

#### Step 2.1 Calculate mean rental yields for each state/territory using SIH data

Let $$\overline{R M}_{t}$$ = mean rent paid by market renters in state/territory $$t$$in SIH

$$\overline{P O D}_{t}$$ = mean estimated sale price of owner-occupied dwellings in state/territory $$t$$in SIH

– SIH 2005–06: base cycle for SIHs 2003–04, 2007–08 and 2009–10

– SIH 2011–12: base cycle for SIH 2013–14 and SIH 2015–16

Then – Calculate mean rental yield ($$\overline{R Y}_{t}$$) for each state/territory t in intercensal SIH cycles (1) and base SIH cycles (0) as:

$$\large{\overline{R Y}_{t^{(1)}}=\frac{\overline{R M}_{t^{(1)}}}{\overline{P O D}_{t^{(1)}}}}$$ and $$\large{\overline{RY}_{t^{(0)}}=\frac{\overline{RM}_{t^{(0)}}}{\overline{POD}_{t^{(0)}}}}$$

#### Step 2.2 Calculate rental yield adjustment factors for intercensal SIH cycles

– Calculate a rental yield adjustment factor ($$A R Y_{t}$$) for each state/territory $$t$$and SIH cycle (from 2003–04 to 2015–16) as:

$$\large{A R Y_{t^{(1)}}=\frac{\overline{R Y}_{t^{(1)}}}{\overline{R Y}_{t^{(0)}}}}$$

#### Step 2.3 Calculate strata rental yields for intercensal SIH cycles

– Calculate an adjusted rental yield ($$R Y A$$) for each SIH stratum ($$s$$) using final base rental yields ($$R Y_{s}$$ from step 1.3) and corresponding state/territory adjustment factor ($$A R Y_{t}$$) (from step 2.2) as:

$$\large{R Y A_{t, s^{(1)}}=R Y_{s^{(0)}} \times A R Y_{t^{(1)}}}$$

#### Estimate gross imputed rent for intercensal SIH cycles

– Calculate gross imputed rent estimates for  $$k$$th owner-occupied dwelling ($$G I R O D_{k}$$) using adjusted rental yields ($$R Y A_{t, s}$$) (from step 2.3) as:

$$\large{G I R O D_{k^{(1)}}=R Y A_{t, s^{(1)}} \times P O D_{k^{(1)}}}$$

#### (a) Base SIH cycles

For the base SIH cycles, SIH 2005–06 and 2011–12:

Let $$G I R O T$$ = gross imputed rent for other tenure type dwellings in each SIH

$$R M_{s}$$= rent paid by market renters in a given stratum ($$s$$) from Census

$$Ns$$ = total number of market renters in a given stratum ($$s$$) from Census

– Using the same strata defined for owner-occupied dwellings ($$s$$) (see 'Data access' section), impute market rent values for base cycles (0) by calculating the median market rent in stratum $$s$$ from Census data, i.e.

$$\large{G I R O T_{(0)}=median\left(R M_{s 1}, R M_{s 2}, R M_{s 3}, \ldots R M_{s Ns}\right)}$$

#### (b) Intercensal SIH cycles

Let $$\overline{R M}_{t}$$ = mean rent paid by market renters in state/territory $$t$$ in SIH
$$A R M_{t}$$= market rent adjustment factor in state/territory $$t$$ in SIH

Then – Calculate a market rent adjustment factor ($$A R M_{t}$$) for state/territory $$t$$ in each intercensal SIH cycle (1) as:

$$\large{A R M_{t^{(1)}}=\overline{R M}_{t^{(1)}}/ \overline {R M}_{t^{(0)}}}$$

– Estimate intercensal gross imputed rent for other tenure type dwellings in SIH as:

$$\large{G I R O T_{(1)}=G I R O T_{(0)} \times A R M_{t^{(1)}}}$$

## Glossary

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#### Assets

An entity of a financial or non-financial nature, owned by the household or its members, and from which economic benefits may be derived by holding or use over a period of time.

#### Australian Statistical Geography Standard (ASGS)

The ASGS came into effect in July 2011 to replace the Australian Statistical Geographical Classification (ASGC). The ASGS provides a common framework of statistical geography used by the ABS to enable the publication of statistics that are comparable and spatially integrated. Its purpose is to outline the conceptual basis of Mesh Blocks, the regions of the main structure and the Greater Capital City Statistical Areas and their relationships to each other. For more information refer to Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2011 (cat. no. 1270.0.55.001) and http://www.abs.gov.au/geography

#### Australian Standard Geographical Classification (ASGC)

The ASGC was replaced by the Australian Statistical Geography Standard (ASGS) in July 2011. For more information refer to Australian Standard Geographical Classification (ASGC) (cat. no. 1216.0) and http://www.abs.gov.au/geography

#### Balance of State

Under the Australian Standard Geographical Classification (ASGC), Balance of State represents each state or territory not defined as Capital City.

#### ​​​​​​​Body corporate fees

Payments to a registered corporate body for the maintenance of strata title properties (e.g. flats, town houses).

#### Capital city

Capital city under the Australian Statistical Geography Standard (ASGS) refers to Greater Capital City Statistical Areas (GCCSAs) as defined in the Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2011 (cat. no. 1270.0.55.001). For the Australian Capital Territory, the estimates relate predominantly to urban areas. All of the Australian Capital Territory is defined as capital city for this publication.

Capital city under the Australian Standard Geographical Classification (ASGC) refers to Australia's six State capital city Statistical Divisions and the Darwin Statistical Division as defined in the Australian Standard Geographical Classification (ASGC) (cat. no. 1216.0). For the Australian Capital Territory the estimates relate predominantly to urban areas, and all of the Australian Capital Territory is defined as a capital city for this publication. Capital city estimates for the Northern Territory are not available on the CURF.

#### Collection District

Census Collection District (CD) is the smallest geographic area defined in the Australian Standard Geographical Classification (cat. no. 1216.0).

#### Consumer Price Index (CPI)

A general measure of price inflation for the household sector in Australia. Specifically, it provides a measure of changes, over time, in the cost of a constant basket of goods and services acquired by capital city households in Australia.

#### Disposable income

Gross income less income tax, the Medicare levy and the Medicare levy surcharge i.e. remaining income after taxes are deducted, which is available to support consumption and/or saving. Income tax, Medicare levy and the Medicare levy surcharge are imputed based on each person's income and other characteristics as reported in the survey. Disposable income is sometimes referred to as net income.

#### Dwelling

Defined as a suite of rooms contained within a building which are self-contained and intended for long-term residential use. To be self-contained the suite of rooms must possess cooking and bathing facilities as building fixtures. Examples of types of dwelling include: separate house; semi-detached, row or terrace house or townhouse; flat, unit, or apartment; and other dwelling, including caravan, cabin, houseboat, and house or flat attached to a shop.

#### Dwelling structure

The dwelling structure type is determined by the structure of the building that contains the dwelling. Households belong to one of four dwelling categories:

• separate house
• semi-detached, row or terrace house or townhouse
• flat, unit, or apartment and
• other dwelling, including caravan or cabin in a caravan park, houseboat in a marina, caravan not in a caravan park, houseboat not in a marina and house or flat attached to a shop

#### Equivalised disposable household income

Disposable household income adjusted using an equivalence scale. For a lone person household it is equal to disposable household income. For a household comprising more than one person, it is an indicator of the disposable household income that would need to be received by a lone person household to enjoy the same level of economic wellbeing as the household in question. For more information on the process of equivalisation, see the Household Expenditure Survey and Survey of Income and Housing, User Guide, Australia (cat. no. 6503.0).

#### Flat, unit or apartment

Includes all self-contained dwellings in blocks of flats, units or apartments. These dwellings do not have their own private grounds and usually share a common entrance foyer or stairwell. This category includes houses converted into flats and flats attached to houses such as granny flats. A house with a granny flat attached is regarded as a separate house.

#### Gross imputed rent

The estimated market rent that a dwelling would attract if it were to be commercially rented.

#### Gross income

Income from all sources, whether monetary or in kind, before income tax, the Medicare levy and the Medicare levy surcharge are deducted.

#### Gross private income

Current receipts from private organisations and other households, including wages and salaries, income from own business, superannuation, workers' compensation, income from annuities, interest, dividends, royalties, income from rental properties, scholarships and child support.

#### Household

A person living alone or a group of related or unrelated people who usually live in the same private dwelling.

#### Housing costs

Housing costs for the purposes of calculating net imputed rent for owner-occupiers in this study comprise:

• rates payments (general and water)
• body corporate fees
• the interest component of mortgage and unsecured loan repayments, where the loan was obtained for the purposes of purchasing or building
• rent payments
• house insurance costs
• repair and maintenance costs.

#### Income

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. Income includes receipts from:

• wages and salaries and other receipts from employment (whether from an employer or own incorporated enterprise), including income provided as part of salary sacrificed and/or salary package arrangements
• profit/loss from own unincorporated business (including partnerships)
• net investment income (interest, rent, dividends, royalties)
• government pensions and allowances (includes pensions and allowances from Commonwealth and State and Territory governments as well as pensions from overseas)
• private transfers (e.g. superannuation, workers' compensation, income from annuities, child support, and financial support received from family members not living in the same household).

Gross income is the sum of the income from all these sources before income tax, the Medicare levy and the Medicare levy surcharge are deducted. Other measures of income are Disposable income and Equivalised disposable household income.

Note that child support and other transfers from other households are not deducted from the incomes of the households making the transfers.

#### Landlord type

For renters, the type of entity to whom rent is paid or with whom the tenure contract or arrangement is made. Renters are classified to one of the following categories:

• state/territory housing authority-where the household pays rent to a state or territory housing authority or trust
• private landlords-where the household pays rent to a real estate agent or to another person not in the same household
• person in the same household-where the unit pays rent to a person who resides in the same household
• other-where the household pays rent to the owner/manager of a caravan park, an employer (including a government authority), a housing cooperative, a community or church group, or any other body not included elsewhere.

#### Life tenure

A lease arrangement in which the tenant has the right to occupy the dwelling for an indefinite or unspecified period.

#### Market rent

The rent that a dwelling would attract if it was commercially rented.

#### Market renter

For the purpose of this study, a market renter is a household that rents its dwelling from a real-estate agent, an unrelated person not living in the same household, or the owner/manager of a caravan park.

#### Mortgage

A mortgage is a loan taken out using the usual residence as security. An owner with a mortgage must still owe money from such a loan.

#### Net imputed rent

Gross imputed rent less housing costs. Net imputed rent is an estimate of the value of housing services that households receive from home ownership or by households paying subsidised rent or occupying their dwelling rent free. Housing costs for the purpose of calculating net imputed rent for owner-occupiers comprise:

• rates payments (general and water)
• body corporate fees
• the interest component of repayments of loans that were obtained for the purposes of purchasing or building
• rent payments
• house insurance costs
• repair and maintenance costs.

#### Net worth

Net worth is the value of a household's assets less the value of its liabilities. Net worth may be negative when household liabilities exceed household assets.

#### Owner (of dwelling)

A household in which at least one member owns the dwelling in which the household members usually reside. Owners are divided into two classifications - owners without a mortgage and owners with a mortgage. If there is any outstanding mortgage or loan secured against the dwelling the household is an owner with a mortgage. If there is no mortgage or loan secured against the dwelling the household is an owner without a mortgage.

#### Owner-occupied dwelling

A dwelling usually inhabited by its owner.

#### Public renter

A household paying rent to a state or territory housing authority/trust.

#### Quintiles

Groupings that result from ranking all households or people in the population in ascending order according to some characteristic such as their household income and then dividing the population into five equal groups, each comprising 20% of the estimated population.

#### Rent-free

Rent-free is a tenure arrangement where the unit (i.e. household, income unit or person) exchanges no money for lodging and is not an owner of the dwelling.

#### Renter

A household that pays rent to reside in the dwelling. See 'Landlord type' for further classification.

#### Salary sacrifice

An arrangement under which an employee agrees contractually to forgo part of their remuneration, which the employee would otherwise receive as wages and salaries, in return for the employer or someone associated with the employer providing benefits of a similar value.

#### State/territory housing authority

A state/territory government authority which, under the Housing Assistance Act 1996 (Cwlth) and in accordance with a Commonwealth-State Housing Agreement, is charged with the provision of housing assistance.

#### Statistical Area Level 1

Statistical Areas Level 1 (SA1s) have been designed as the smallest unit for the release of Census data. SA1s generally have a population of 200 to 800 persons, and an average population of about 400 persons. They are built from whole Mesh Blocks and there are approximately 55,000 SA1s covering the whole of Australia.

#### Subsidised renter

A household renting its dwelling for less than it would be expected to pay in a commercial market. For the purpose of this study, subsidised renters are those households renting from a parent or other relative not living in the same household, an employer, or a housing cooperative or community/church group. However, some households in these categories were judged to be paying commercial rents; net imputed rent for such households was zero.

#### Tenure type

The nature of a household's legal right to occupy the dwelling in which the household members usually reside. Tenure is determined according to whether the household owns the dwelling outright, owns the dwelling but has a mortgage or loan secured against it, is paying rent to live in the dwelling, or has some other arrangement to occupy the dwelling.

#### Value of dwelling

The estimated sale price of dwelling and its land, at the time of the respondent's interview, as estimated and reported by the respondent.

See Net worth.

## Abbreviations

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The following symbols and abbreviations are used in this publication:

 ABS Australian Bureau of Statistics ASGC Australian Standard Geographical Classification ASGS Australian Statistical Geography Standard ACT Australian Capital Territory AIHW Australian Institute of Health and Welfare Aust. Australia cat. catalogue CD Collection District Census Census of Population and Housing CURF confidentialised unit record file EDHI equivalised disposable household income HES Household Expenditure Survey incl. including ICLS International Conference of Labour Statisticians IRSAD Index of Relative Socio-Economic Advantage and Disadvantage MURF main unit record file no. number NSW New South Wales NT Northern Territory Qld Queensland RSE relative standard error SA South Australia SA1 Statistical Area 1 SEIFA Socio-Economic Indexes for Areas SIH Survey of Income and Housing Tas. Tasmania UNECE United Nations Economic Commission for Europe VG Valuers General Vic. Victoria WA Western Australia