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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:
GROSS IMPUTED RENT FOR OWNER-OCCUPIED DWELLINGS
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:
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 1 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 2 in 'Data access'). In the Australian Capital Territory, there were 10 strata because section of state was not used (see Table 3 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:
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.
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
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.
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
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