Energy Sector Behavioural Insights Platform

Although technologies are important determinants of energy demand, people’s decisions about which technologies they use, and how they use them, ultimately determine energy use. This is true for all sectors. Identifying ways to influence human behaviour will therefore be an important ingredient in clean energy transitions globally.

However, in many cases when designing and implementing energy policy, policy makers resort to “rules of thumb” about human behaviour, often based on orthodox economic theory. While these can be useful, they are not always good predictors of actual human behaviour and policies based on them can sometimes be ineffectual – a policy performance gap.

Building on existing knowledge and experience to incorporate evidence from behavioural science (or Behavioural Insights) throughout the policy cycle should help ensure that energy policies are designed to work with people’s likely behaviours, reducing the policy performance gap.

To some extent, all energy policy is designed to change behaviour: From congestion taxes to discourage people from driving in certain parts of the city, to labelling schemes that encourage people to purchase more energy efficient appliances.

However, in many countries policy makers observe a disconnect between the expected outcomes of a policy and the actual outcomes – a policy performance gap. Often, this gap is because people behave differently than the way policy makers had expected.

Energy policy makers—like policy makers in many other fields—often use “rules of thumb” when making policy, which implicitly involve assumptions about human behaviour. A typical example is this:

While this rule of thumb may work in many cases, it is based an assumption about how people respond to prices and ignores other ways people make purchasing decisions. For example, for some people, higher-priced goods might signify better quality. For these people, lowering a product’s price may make it unattractive, the opposite impact intended by the policy.

Examples such as this suggest policy makers should carefully consider evidence from the behavioural sciences when designing policy, to minimise the risk of policy performance gaps.

What are Behavioural Insights?

Behavioural Insights (BI) are designed to help make better and more effective public policies based on evidence on human behaviour drawn from the fields of behavioural economics, psychology and other behavioural sciences.

Research from these fields has shown that behaviour is often not “rational” and that habits are often guided by cognitive “short cuts” which, while useful in many situations, sometimes result in behaviours that differ from expectations.

BI is designed to help policy makers take such factors into account when designing policies, offering a data-driven and nuanced approach to policy making based on what actually drives citizens’ decisions rather than relying on assumptions about how they should act.

The emergence of Behavioural Insights in government and the need for collaboration

Over the last decade, several countries have set up specialised teams to incorporate BI within energy policy development and implementation processes. In some countries, dedicated BI teams have been established within energy or environment departments. In others, BI teams are established in central agencies to apply BI across a portfolio of issues, including energy. In others still, BI analysis has been conducted by private or semi-private organisations, with government as the primary client.

While some countries have been applying BI to energy policy for years, others are just beginning to experiment with it. International collaboration can help ensure that countries share lessons learned and pool their efforts to improve the efficacy of energy policy globally.

1. Overall objective: Improve the efficacy of demand-side energy policies by ensuring that human behaviour is accounted for at all stages of the policy cycle.
2. Build an international network of energy policy makers that use or are interested in using BI for energy policy.
3. Identify benefits and drawbacks of different institutional governance models for incorporating BI into policy: From in-house models (including both centralised models placing BI teams within a central agency and decentralised models which embed BI teams in line agencies), to outsourced models.
4. Share lessons learned and identify best practices, from inside and outside the energy sector, in applying BI throughout the policy cycle and in both advanced and emerging economies.

For Subtask 1

Through desktop research, a survey, and interviews, evidence will be compiled on which countries have established BI teams for the purpose of informing the design and delivery of energy policy and regulations.

The following organisations will be within scope:

• Central policy agencies (e.g., Cabinet offices)
• Line agencies responsible for energy and related policy areas (e.g. transport)
• Energy regulators responsible for regulating energy markets

Case studies from beyond government will also be examined where relevant.

To assess how BI are being used, a BI policy typology will be developed to categorise the use of BI in energy policy making. Dimensions assessed could include: policy type, policy stage, scale, behaviour targeted, intervention type, impacts, evaluation methods and institutional/cultural settings amongst others.

The primary benefit of participation is gaining access to a network of policy makers with a joint aim: making better energy policy by incorporating human behaviour at all stages of the policy cycle.

Participants in the Task directly shape the direction of the research and decide what form the outputs of the research take.

While there will be a strong focus on the use of BI in participating countries, the scope of the research will extend well beyond participating countries.

Subtask 1: Environment scanning

Duration: ~9 months

The purpose of the sub-task is to assess where and how BI is being used to inform energy policy around the world.

Subtask 2: [TBC]

Based on the analysis from Sub-task 1, and the results of Deliverables 1.3 and 1.4, the topic for the next phase of work will be identified. A range of ideas are presented below:

• Workshops and training sessions with policy makers (in both advanced and emerging economies).
• Webinar series: A series of webinars from policy makers could be delivered via the UsersTCP Academy. Each webinar could be focused on a different aspect of applying BI for energy policy.
• Guidance reports for energy policy makers on various topics. For example:
  • How-to establish a BI team for energy policy
  • How to conduct field trials in the energy sector
  • From field trials to actual policy
  • Using BI to optimise policies in different sectors
• Online case study database: A searchable online database of case studies, cataloguing the types of interventions tested, impacts, etc.

For more information on these deliverables please refer to the full proposal

Phase I: Australia, Canada, Ireland, the Netherlands, United Kingdom and Switzerland.

Annex duration: 1 December 2019 to 1 December 2020.

Latest publications:

• Policy Brief (March 2021)- Improving demand-side energy policy outcomes using behavioural insights https://doi.org/10.47568/1PB106
• UsersTCP and IEA Report (December 2020) – Behavioural insights for demand-side energy policy and programmes: An environment scan https://doi.org/10.47568/6OR105

Previous publications:

• Project proposal (as agreed by the UsersTCP ExCo)
• Proposal slides