Understanding households’ investment behaviour

In the CHEETAH project, the micro level investigation concerns households (see project overview here). A large demographically representative survey in eight EU member states will provide deeper insights into households’ responses to various energy efficiency policy measures such as energy labels or subsidies.

The energy used by households depends (beside the households’ energy consumption patterns) on the decisions that households make when purchasing energy-related technologies ranging from lightbulbs over household appliances to heating systems and building retrofits. When deciding about an energy-related purchase, one typically faces the trade-off between paying a higher purchase price now and saving money on the energy bill in the future. Various policy measures are in place in order to raise consumers´ awareness of energy cost savings, to increase accessibility of capital and to direct choices towards more efficient technologies.

CHEETAH will explore how households respond to energy efficiency policies, accounting for differences in household characteristic, technology characteristics and countries. CHEETAH will conduct demographically representative household surveys in eight EU Member States. Policy responses will be elicited using discrete choice experiments. Relying on the survey data, econometric methods will be employed to estimate the influence of policy on energy efficiency technology adoption.

Key results from the micro- and meso analysis

• Rebates for A⁺⁺⁺-labelled refrigerators are an effective measure to boost the adoption of A⁺⁺⁺-labelled refrigerators in all countries (except the UK)
  But: providing a rebate for energy-efficient refrigerators may be regressive; rebates could be offered to low-income households only [result from choice experiment on refrigerators]
  It is more efficient to focus rebates on low-income groups. The cost for rebates is lower per saved kWh if rebates are directed to lowincome households only than for rebates directed to all income groups. From a public spending perspective it is therefore more efficient to target low income households directly (this limits e.g. freerider effects) [result from modeling on refrigerators]
• Labelling schemes are more effective for customers with a higher energy literacy.
  -> Raising the level of energy literacy via education and information programs (e.g., brochures, or online or on-site courses) may be an effective means [result from choice experiment on refrigerators]
• Promotion of smart thermostats (i.e. a fairly new technology) should be coupled with external advise/recommendations, ideally by experts [result from choice experiment on smart thermostats]
• More trust in energy providers than in governments. Respondents react more positively to rebates if they are offered by an energy provider rather than the government [result from choice experiment on heating systems]
• Governments can build support for future measures by introducing financial support before the measures take effect. Results on trust in government, experience with rebates for energy-efficient investments and green identity point to where policy-makers might focus in building support for future energy efficiency measures, for example, by introducing financial support measures in advance of more coercive or costly measures [Result from choice experiment on policy acceptance]
• Other quality aspects also matter, especially consumer ratings. Communicate positive consumer ratings by peers.

Limitations of the choice experiments

Methodological limitations

• Hypothetical character of stated preferences Choice Experiments.
• Limitation to at most 5 or 6 attributes of technologies (otherwise too complex).
• Actual choice situation in the survey is a bit artificial compared to actual decision environment.
  -> But: CE allow testing new attributes which are not yet on the market.

Limitations due to the high effort of choice experiments (in terms of expenditure and high burden on respondents)

• Limited number of technologies → method was developed to transfer the results to other energy efficiency technologies (building renovation, other appliances)
• Limited number of countries → method was developed to transfer the results to other MS

Further reading from the library

• Draft report on policy implications from the micro-level analysis (see report)
• Working paper on energy demand projections for buildings (see report)
• Scientific working paper on factors driving household acceptance of energy-efficiency policies (see report)
• Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies (see article)
• Working Paper on the role of policies and key factors for household stated adoption of energy-efficient technologies in the EU (see report)
• Changing energy efficiency technology adoption in households - Documentation for first expert workshop (see report)
• Changing energy efficiency technology adoption in households – Working paper on policies (see report)
• Changing energy efficiency technology adoption in households – Working paper on modelling and survey (see report)