Skip navigation

Assumptions and Methodology

Summary of the modelling approach and assumptions which underpin the Low-income Housing Upgrade Benefit Analysis tool developed by Springmount Advisory for ACOSS.

Modelling approach

  • The low-income household upgrade analysis tool calculates the estimated bill savings, job creation, and emissions reductions from household upgrades at an electorate and state level.
  • The tool utilises primary modelling inputs from:
    • ABS 2021 Census - housing and income statistics including the number of house types (standalone, townhouse, apartment, social housing) per electorate and the number of households per income bracket per electorate.
    • Climateworks Centre, Renovation Pathways program state-level research findings (unpublished) on the upgrade costs and benefits from home energy upgrades for detached homes, townhouses and apartments.
    • Australian Institute of Health and Welfare data on social housing stock per state. AIHW data on public housing statistics is more accurate than ABS census data, however is only available at state level, but not the electorate level.
    • National Greenhouse Accounts Factors 2022, Table 1, to calculate expected emissions savings from solar installation.

Upgrades modelled tool

  • The tool models the expected benefits from upgrading households in line with the “Quick-fix” thermal upgrade levels, plus electrification, developed by Climateworks Centre, Renovation Pathways. Note Climateworks Centre developed three upgrade levels typologies, we have focused only on the first one.
  • The Quick-fix upgrade includes the installation of ceiling insulation (R3.0); infiltration /draught proofing (0.5 ACH); heavy drapes; roller shutters; efficient electric heat pump; efficient electric hot water heating and cooking.
  • Climateworks Centre also modelled the addition of rooftop solar to the thermal upgrades to bring homes as close to zero emissions as possible.
  • The benefits for each state vary due to differences in climate and energy costs.
  • The most significant benefits are typically identified for upgrades to detached housing, while the least is typically identified in apartments due to better thermal performance.

Bill savings from Home Energy upgrades

The bill savings data was derived from Climateworks Centre Renovation Pathway program state and territories data (unpublished) which underpins their published national report. To estimate the bill savings in each state Climateworks Centre:

  • Identified 16 building archetypes representing the majority of homes and modelled  the housing stock nationally, including the share of each archetype per state.
  • Defined a ‘low-performance’ home (equivalent to around 3.5 NatHERS star rating depending on archetypes).
  • Quick-fix thermal upgrade was compared against the ‘low-performance’ case determining annual space conditioning energy savings (GJ/dwelling)
  • The appliance electrification upgrade was also compared to the ‘low-performance’ case determining energy consumption savings (GJ/dwelling)
  • Considered theoretical energy required for heating and cooling loads to maintain a building within a defined comfort band.
  • Sourced gas (Canstar 2023) and electricity prices (ACCC 2021/22 or Jurisdictional Government) for each state and territory.
  • Calculated energy savings for 397 unique combinations of archetypes across the Australian climate zones in each state and territory. 

Income brackets

  • Households earning an equivalised income of <$800 per week were classified as the lowest quintile of earners (representing 21.2% of all households), the second lowest quintile was defined as households earning $800-<$1499 per week in the Census.

Social housing

  • Electorate level calculations use the reported number of public housing dwellings in that electorate from the 2021 Census to inform the modelling.
  • State level social housing figures utilise AIWH data as this is a more accurate source of data, however it is unavailable at an electorate level.

Modelling methodology

  • The modelling utilises granular electorate level census data to determine the quantity of each of the three housing types in the electorate (stand alone, townhouse, or apartment) as well as the reported number of social housing dwellings.
  • The calculated savings and emissions reductions are then applied to each electorate based on the quantity of each housing type in that electorate.
  • The percentage of households in the lowest quintile were calculated for every electorate and this is then is used to determine the expected benefits from a program aimed at either upgrading low income households (lowest quintile) or social housing upgrades.


  • The model assumes that the mix of house types in each electorate is evenly distributed among income brackets. Ie if 10% of the electorate is apartments, then it assumes that 10% of Q1 households live in apartments.
  • The model also assumes that the mix of household types is evenly distributed for social housing in each electorate. 
  • The model assumes that every household in the target demographic will require an upgrade as detailed for the specific housing type in Climateworks Centre’s research. 
  • The model assumes cost savings per household will be equivalent in all areas of each state. In practice, cold regions of each state will likely derive higher savings due to greater electrification benefits.
  • Due to smaller sample sizes of all household types in the Northern Territory and apartments in South Australia, the national average for each housing type has been used in those jurisdictions to calculate expected savings.


  2. Climateworks Centre, 2023, Climate-ready homes: Building the case for a renovation wave in Australia.