The Extra Cost of Energy

The Extra Cost of Energy campaign estimates the full household energy costs that young adults (aged 18–29) contribute while living at home. Our analysis combines product-level energy consumption data, average household usage patterns, and state-based electricity pricing to build a clear picture of how lifestyle and location influence energy bills.

Data sources:
– 19 year old’s were living with their parents and this had increased to 72% in 2021 – Young people living with parents | Australian Institute of Family Studie–
Household appliances: Appliance energy consumption data was drawn from the Energy Rating Calculator. For each appliance, the top three brands with the highest energy ratings were reviewed, and the most popular 2–3 products were selected. 
– Electronic and gaming devices: Energy usage estimates were collated from multiple publicly available sources (e.g., manufacturer specifications, independent testing reports). These values were averaged across common product models. 
– Essential household activities: Estimates for daily essentials like showers, lighting, and kitchen appliances were derived from existing averages for the target demographic, based on both water/energy physics (e.g., heating water) and reported usage patterns. 
– Product adoption and usage rates: Data on the proportion of Australians aged 18–29 living at home who use each device or appliance was sourced from Statista. This dataset informed the weighting of each product’s impact in the model — ensuring the results reflect real-world usage among young adults living with their parents. 
– The Statista data was incorporated alongside appliance-level consumption figures, forming the baseline for calculating how common each energy behaviour is across Australia. 

Usage assumptions:
– Shower consumption: A typical 6–8 minute shower was assumed to use around 80 litres of water, with energy requirements calculated at ~2 kWh per shower once heating and inefficiencies are factored in. This aligns with reported averages in Australia.
– Device usage rates: Product adoption rates (e.g. % of young adults using laptops, gaming consoles, air fryers, etc.) were sourced from national-level survey data of 18–29-year-olds living with their parents. These proportions were then applied consistently across all states.
– Low, medium, and high usage tiers: To capture behavioural differences, three usage profiles were created. Each profile scales consumption by frequency and duration of use.
– Low usage: Minimal daily usage of devices, shorter shower times, and limited appliance operation.
– Mid usage: Average frequency of use reflecting a “typical” young adult.
– High usage: Heavy reliance on multiple devices, longer showers, and more frequent appliance cycles.
– Weighting by adoption rates: Statista data provided percentage adoption figures for each product among 18–29-year-olds living at home. These proportions were applied across states when calculating average household impact — for example, only 49% of respondents reported using a clothes dryer, so the cost of that appliance was weighted accordingly.

Cost Calculations:
– State electricity rates: Per-kWh costs were sourced from state averages, ensuring that the regional price differences are reflected in total household cost estimates. South Australia, for example, carries a higher cost burden due to its higher average rate per kWh, compared with Victoria, which sits at the lower end.
– Annual consumption: Each product’s estimated kWh/year was multiplied by its relevant state rate. Household totals were then aggregated by category (Essentials, Household Appliances, Electronic Devices, and Gaming Devices).
Australian average: A national benchmark was calculated to compare state deviations from the average cost.
– Integration with Statista data: Weighted cost estimates were produced by multiplying each product’s annual energy cost by its adoption rate from the Statista dataset. This created more realistic averages that reflect the typical household composition of young Australians living at home, rather than assuming every home uses every device.

Key considerations
– While appliance adoption proportions were based on national survey data, they were applied uniformly across states due to the absence of state-level breakdowns. 
– Estimates are intended to highlight broad trends and relative comparisons between states and usage levels rather than provide precise household bills. 
– Actual household energy bills will vary depending on factors such as family size, building insulation, and individual behaviour.
– Appliance adoption proportions were based on Statista’s national survey data of 18–29-year-olds living with their parents. Although state-level breakdowns weren’t available, these national proportions were applied consistently across states to maintain comparability. Data available on request.

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