When shopping for appliances, people can find it difficult to weigh up the advertised cost of an appliance against its long-term running costs. This is sometimes referred to as the ‘energy‑efficiency gap’.
BETA joined forces with the Australian Government Department of the Environment and Energy and Appliances Online to see if we could encourage consumers to buy more energy‑efficient appliances—helping them to save money.
Drawing on behavioural insights, we designed an alternative energy label and ran a trial to test whether it – or the existing Australian Energy Rating Label – helped people to choose more energy‑efficient appliances online.
We found energy labels have positive effects on consumer behaviour compared to no labels. These effects are large enough to warrant consideration by policy makers interested in the twin policy goals of reducing carbon emissions and household energy costs. We did not find any difference between the impact of the existing label and the alternative label.
Pre-registration information
When combined, relatively small inefficiencies in Australia’s household appliances market have the potential to generate large welfare losses for individuals and significant damage to the environment. Reducing household energy consumption is a key component to boosting Australia’s energy productivity.
The Australian Government employs a range of strategies to reduce household energy use and emissions, one of which is the Australian Energy Rating Label. These labels provide consumers with information on energy-efficiency in a standardised format (energy consumption calculated by kWh per year). Evidence suggests that consumer understanding and interpretation of the label could be enhanced.
The study aims to provide evidence to maximise the alignment of consumer preferences with their choice in household appliances. In particular, the study aims to test the impact of a new behavioural economics-informed energy rating label on customer engagement in relation to higher energy efficient household appliances, in an online environment.
The trial is expected to run for approximately 30-days. We expect to have 13,000 unique observations over this period. This means approximately 4,333 individuals will be randomised into each of the experimental groups.