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Behavioural Response to Investment Risks in Energy Efficiency

Periodic Reporting for period 2 - BRISKEE (Behavioural Response to Investment Risks in Energy Efficiency)

Reporting period: 2016-06-01 to 2017-12-31

BRISKEE – Behavioural Response to Investment Risks in Energy Efficiency – is a Horizon 2020 project that provides evidence-based input to the design and evaluation of energy efficiency policy in the EU residential sector.

With the residential sector representing 27% of the EU final energy demand, households' investment in energy efficiency is a key issue for meeting energy and climate policy targets. When assessing the costs and benefits of insulating their homes, or purchasing energy-saving appliances, households wonder what will be the future value of these investments. Owing to constraints on time, attention, and individuals’ ability to process information, the evaluation of investments may lead to biased choices.

Discount rates are key parameters in energy-economic models used by policy makers in designing and evaluating energy efficiency policies. In energy demand models, the investment evaluation is currently typically represented using a net present value method (NPV). The net present value being positive indicates whether the investment has a positive monetary return over its lifetime. A main variable in the calculation of NPV of the decision model is the respective implicit discount rates. Such implicit discount rates provide a highly aggregated picture of the consumers’ time and risk preferences as well as all barriers to the adoption of energy efficiency measures. Consequently, these implicit discount rates largely exceed market discount rates.

BRISKEE addresses household decision-making and its implications at three levels: The micro, meso and macro level. At the micro level, factors influencing individual decision-making are elicited in a representative survey. At the meso level, the impact of policies addressing decision-making on medium- and long-term energy demand is investigated using the energy demand models FORECAST and Invert/EE-Lab. At the macro-level, BRISKEE assesses the effects of energy efficiency improvements on the economy using the macroeconomic model ASTRA.
Work package (WP) 1: Within the first reporting period, a project management guide (D 1.1) and a quality assurance and risk management plan (D 1.2) were developed.

WP2: Within the first periodic reporting period, the BRISKEE team surveyed the conceptual and empirical literature on household adoption of energy efficient technologies. This also included a survey and discussion of the literature on methods of how preferences may be elicited via online questionnaires. As part of the conceptual work, a framework was developed which allowed disentangling the various components of the implicit discount rate and, in particular, clarifying the role of policy intervention. The outcome of this work fed into Deliverable 2.1. (Draft Literature survey). The BRISKEE team developed a questionnaire, which is fielded in eight EU Member States and which was extensively pretested.

WP3: Within the first reporting period, the input data structure, model algorithms and output structures were enhanced to allow them to cope with the extended parameter set and more complex algorithms which calculate the market shares of technology options (Task 3.1). In the course of Task 3.3 the project team agreed on the basic settings and data sources (time series of GDP, population, number of households, energy prices) and overall directions of the three policy scenarios: (1) scenario with current polices while including more detailed modelling of actors; (2) scenario with current policies, yet intensified and a (3) scenario mainly with new instruments affecting actors (actor-relevant policies increased). Within Task 3.4 and 3.5 we furthermore started to update the country specific input data of the Invert/EE-Lab Model and FORECAST model.
WP 4: In the first reporting period, the format and timelines for the data transfer from survey to models were established.

WP 5: Within the first reporting period, an analysis of both national and European energy efficiency policy measures in each of the countries selected for our survey was carried out. The analysis was followed by an in-depth discussion of national policy approaches with stakeholders from each country at the first BRISKEE expert workshop in June 2015, focusing in particular on behavior-related policy measures. First insights from the BRISKEE project regarding the role of discount rates for policy-making were contributed to a workshop on discount rates organized by eceee and Ecofys. At the micro-level, the findings from the literature review (see WP 2) were communicated to and discussed with policy makers at an exchange meeting at the European Commission on 20 January 2016. Furthermore, general aspects to maximize the project’s policy impact were discussed in the exchange meeting on 27 March 2015. At all levels, the first reporting period involved the development of research designs that will allow for deriving insights to support evidence-based policy design.

WP 6: Within the first reporting period, the project website (briskee.eu) was designed and implemented. The first public deliverable D2.1 “Draft literature review on time and risk preferences and energy efficiency technology adoption” has been published on the project website. The communication and dissemination strategy further includes expert workshops in order to exchange expertise with national experts, policy makers and evaluators, as well as stakeholders form the research community. The first expert workshop was organised as a side-event of the ECEEE summer study in June 2015.
The BRISKEE project is expected to have a positive impact on energy efficiency policy development, evidenced for instance by its reference into impact assessments, strategy papers or other policy documents. The project focuses on energy efficiency in the residential sector, addressing multiple benefits at the micro-, meso and macro-level. BRISKEE addresses the challenge of understanding household energy-efficiency decision-making, focusing on time-preferences, risk- attitudes and non-monetary barriers and derives policy recommendations on how to effectively design policy instruments to increase the market uptake of energy efficiency technologies. The project is expected to significantly improve the representation of individual household decision-making behaviour in energy demand models. Energy demand models are used widely in policy making and ex-ante evaluations of policies, such that increasing their accuracy and validity is expected to provide a positive impact on policy making.

Within the first reporting period, a literature review on empirical evidence regarding household investment decisions was provided and presented to policy makers. The relevance of these findings for energy demand modelling and policy design and evaluation was analysed and strategies to include such findings in energy demand models were developed. A survey has been developed in order to provide insights going well beyond the state of the art, and approaches to include the survey results in energy demand models FORECAST and Invert/EE-Lab were defined.