Use Case 5: Investigate and exploit energy demand curves


In the energy efficiency space, many utilities provide rebates to their customers that purchase energy efficient appliances. An important finding is that individuals use different discount rates for different types of goods in different contexts. In the case of domestic energy technologies, revealed discount rates were found to be clustered in the 5% to 40% range, but higher rates were applied to refrigerators and water heaters than to heating equipment and weatherization measures. Other studies have found short-term discount rates as high as 300% for air-conditioning technologies. This marked variability suggests that discount rates are influenced by many elements of the decision context, including perceived risk, framing, and social arrangements. Again, financial literacy can play here an important role in this case study in understanding the determinants of energy demand curves.

Research questions

Does providing more salient financial information impact implicit discount rates and willingness to purchase more efficient home appliances?

What impact do factors such as financial information, risk reduction, energy discounts and loans have on implicit discount rates for home appliances?

What impact do financial literacy, energy literacy, environmental concern have on implicit discount rates?

For consumers who choose to purchase more efficient appliances, what impact do direct rebound rates have when choosing an appliance?

Design and impact

Using experimental approaches, we can allow for different choices to be varied across consumers, by mapping the demand curves for energy efficient devices. Designing relative surveys, we will try to estimate possible nonlinearities of the demand curve. In these experiments, each surveyed customer will be presented with several hypothetical offers by energy suppliers and will be asked to identify the offer that he/she would choose and other attributes that consumers face in real life scenarios. These experiments have the advantage of being able to include service attributes that have not been offered in real world markets or have not varied sufficiently in markets to allow estimation. Surveys are expected to be conducted in several countries using a large number of participants for maximizing estimation of consumers’ heterogeneity. Discrete choice models would be used to assess the effectiveness of different types of attributes in influencing consumers’ preferences.

Socio-demographic information

Residence characteristics

House appliance Factors

Energy related financial literacy

Discount rate

Rebound effect

Behavioural intention and attitude

Environmental literacy