There is an urge for policymakers and citizens to take action to tackle global warming and climate change, as emphasised by the Intergovernmental Panel on Climate Change (IPCC) last October in Seoul, South Korea. At the EU level, initiatives have already been put in place, such as the 2021-2027 Multiannual Financial Framework, where 30% of the budget is allocated to a low-carbon economy, climate change, and resource efficiency, among others. In parallel, the 2030 Climate and Energy Framework aims for at least a 32.5%-increase in energy efficiency by 2030.
One of the measures to reach this goal is to boost firm-level investments in energy-efficiency improvements, as these considerably contribute to reducing greenhouse gas emission (Stamatiou and Dritsakis 2017, International Energy Agency 2018). However, these investments will not happen at a sufficient scale on their own. This is because market failures triggered by imperfect information, positive externalities, and split incentives, among others, prevent investments at a socially optimal level (Allcott and Greenstone 2012, Gerarden et al. 2015, Jaffe and Stavins 1994, Sutherland 1996).
This raises the question from a policy perspective: what is the most effective way to boost firm investment in energy efficiency? In a recent paper, we shed some light on this question by using new experimental data from EU firms (Brutscher and Ravillard 2019a). The basic idea of the experiment is to test how firms’ stated willingness to invest in different types of energy-efficiency projects varies with changes in the financing offer attached to these projects, as well as the availability (or not) of technical assistance when it comes to implementing the energy-efficiency project in question.
The online experiment
Each year, the European Investment Bank (EIB) carries out a telephone-based survey amongst EU firms, known as the EIB Group Survey on Investment and Investment Finance (EIBIS). At the end of the interview, firms are asked to participate in a separate online survey. This year’s online survey topic was investment in energy efficiency. Firms that agreed to participate were first asked about their annual energy cost. They were then shown a series of investment scenarios, detailing investment characteristics and a financing offer accompanying the investment, and then asked whether they would go ahead with the investment under these conditions.
A total of 1,614 firms participated in the experiment.1 Figure 1 shows an example of a screen presented to a British firm with an annual energy spend of £1,500. Each firm would see eight screens.
Figure 1 Design of the experiment
Characteristics of the project, financing, as well as the availability (or not) of technical assistance, which each firm saw on the screen were determined at random (from a series of underlying distributions).2 This ensured that the scenarios with which firms were confronted were completely independent of their characteristics, such as their location, type of activity, performance, environmental sensitivity, etc. It thus allows us to exclude the possibility of ‘omitted variable bias’ or ‘reverse causality’ when it comes to linking project and financing characteristics to firms’ stated willingness to invest in a project and to infer the causal effect of the former on the latter.
Using the online experiment results, we first deduct how the probability that firms are willing to invest in a project changes with the internal rate of return (IRR) of a project, as shown in Figure 2. When the IRR is equal to 4%, the probability that firms invest is 39%, ceteris paribus. If the IRR increases to 20%, this probability goes up to 77%. The rate above which firms are indifferent between investing and not investing, also known as the hurdle rate, is slightly above 8%.
To put these IRR values in a comparative perspective, the existing literature shows that the IRR for energy-efficiency investments varies from 10% to 25%, with a calculated average of 17% (EnergyStar, Farrell & Remes, Intelligent Energy Europe), meaning that the implied investment probability ranges between 54% and 88%.
Figure 2 The relationship between the internal rate of return and investment probabilities of adopting energy-efficiency technologies based on different sources
A more favourable financing offer can boost the probability to invest by more than a third
One policy measure to boost firms’ incentive to invest in energy-efficiency projects with a particular IRR is to match them with favourable financing terms. The advantage of this approach, as opposed to grant funding, for instance, is that the money can be recycled and that it provides an incentive for firms to invest in the best possible technology. Our experiment shows what happens to firms’ willingness to invest in energy-efficiency projects if the linked funding characteristics change.
Figure 3 summarises our results by showing how a change in each financing term can increase the probability that a firm is willing to invest in an energy efficiency project. If the fixed interest rate decreases by 100 basis points, the probability increases by 8 percentage points (or 13% for a typical investment project),3 in contrast to 5 percentage points (or 8%) if it were floating. This shows that firms are more sensitive to changes in the fixed interest rate than in the floating one, which has to do with the fact that firms care more about the long run and are more risk-averse. Another term that matters is the collateral requirement coming with the funding offer. For each 20% decrease in the collateral assets’ value, the probability of investing increases by 2.5 percentage points (or 4%).
Taken together, our results suggest that a favourable financing offer situation where the interest rate is fixed and 100 basis points less than the mid-market offer, and where the collateral requirement is 20% as opposed to 60%, can boost investment probabilities by more than a third (i.e. 33%).
Providing technical assistance for project implementation also increases the probability that firms invest
Assisting in the implementation of the project with technical expertise is also effective in increasing the probability that firms invest in energy efficiency. If provided, it increases the probability that firms invest in the project by 3 percentage points (or 5%), other things held constant. Technical assistance can mean establishing baseline studies or simply helping in project implementation.
Figure 3 Effects of changes in financing-offer characteristics on the probability that firms invest in energy-efficiency projects
The experiment we carried out is based on the assumption that firms are aware of the savings associated with different investment projects. In reality, however, this is not always the case. For this reason, it is necessary to complement the use of financing terms and technical assistance by ensuring greater transparency on the costs and benefits of investments in energy efficiency. One way to do so is by encouraging firms to carry out energy audits. In the EU, there is already a directive on energy audits since 2012, under which it is compulsory for large firms to have carried one out by 2015 and at least every four years thereafter (Brems et al. 2016, Torregrossa 2015).
Audits can promote energy efficiency investments by overcoming imperfect information
A series of studies suggest that carrying out energy audits increases the likelihood of investing in energy efficiency, especially as they help overcome imperfect information and hence close the ‘energy efficiency gap’ – the disconnect between potential investments in energy-efficiency improvements and those actually carried out (Kalantzis et al. 2018, Schleich et al. 2015).
In a separate study also relying on the online experiment of the EIBIS, we suggest policy interventions that can help promote energy audits amongst EU firms (Brutscher and Ravillard 2019b). We confronted firms with different scenarios of policy interventions on energy audits and asked whether they would go ahead with carrying out an energy audit under those conditions. Findings revealed that for a 50 percentage point increase in the level of support for the energy audit, coming in the form of a grant, the chances that firms would go ahead with the audit increased by 27 percentage points (or 45%). This 50 percentage point support level increase is based on existing support schemes for large firms in Portugal, Sweden, Luxembourg, and Germany, where support schemes cover between 40% and 60% of total energy audits’ costs (Brems et al. 2016, Hirzel and Behling 2016).
This column comes at a time when tackling climate change and global warming are central to governments and to policymakers’ agendas. One of the ways to confront global warming is by increasing investments in energy efficiency. The EU, for its part, has already allocated some of its annual budget to this type of activity and set an energy efficiency target for 2030. However, little is known about effective ways to meet the target.
This is where our work aims to add value. By using EU firm-level data from a new online experiment, we are able to capture firms’ preferences in financial instruments and technical assistance in the context of investments in energy efficiency. By doing so, we measure and quantify the effectiveness of these instruments in increasing the probability that firms invest, which in turn allows us to provide important insights on how to optimally design these instruments. We find a favourable financing offer can increase the likelihood that firms are willing to invest in energy efficiency by as much as 33%. These findings have important implications for both policymakers and for lending institutions, such as the EIB, and support better tailoring of financial products and projects, as well as promoting more policy interventions.
Allcott, H, and M Greenstone (2012), “Is there an energy efficiency gap?”, NBER Working Paper 17766.
Anderson, ST, and RG Newell (2004), “Information programs for technology adoption: The case of energy-efficiency audits”, Resource and Energy Economics 26.
Brems, A, E Steele and A Papadamou (2016), “A study on energy efficiency in enterprises: Energy audits and energy management systems library of typical energy audit recommendations, costs and savings”, European Union.
Brutscher, P, and P Ravillard (2019a), “Can favourable financing improve energy efficiency investments in the EU? Evidence from new experimental data”, in press.
Brutscher, P, and P Ravillard (2019b), “Experiment-based evidence on the effectiveness of policy interventions in promoting energy audits”, in press.
Intelligent Energy Europe (2013), “Energy Efficiency Policies in the EU: Lessons from the Odyssee-Mure Project”.
Farrell, D, and JK Remes (2008), “How the world should invest in energy efficiency”, The McKinsey Quarterly Economic Studies.
Gerarden, TD, RG Newell and RN Stavins (2015), “Assessing the energy-efficiency gap”, NBER Working Paper 20904.
Hirzel, S, and I Behling (2016), “A study on energy efficiency in enterprises: Energy audits and energy management systems”, European Union.
International Energy Agency (2008), “Promoting energy efficiency investments: Case studies in the residential sector”.
EnergyStar (2007), “Investment Analysis”, in Building Manual.
Jaffe, AB, and RN Stavins (1994), “The energy paradox and the diffusion of conservation technology”, Resource and Energy Economics 16.
Kalantzis, F, P Brutscher and P Ravillard (2018), “Investment in climate change mitigation”, in Investment report 2018-9: Retooling Europe’s economy, Luxembourg: European Investment Bank.
Schleich, J, T Fleiter, S Hirzel, B Schlomann, M Mai and E Gruber (2015), “Effect of energy audits on the adoption of energy-efficiency measures by small companies”, European Council for an Energy-Efficient Economy.
Stamatiou, P, and N Dritsakis (2017), “Dynamic modeling of causal relationship between energy consumption, CO2 emissions, and economic growth in Italy”, in N Tsounis and A Vlachvei (eds.), Advances in applied economic research, 2016 International Conference on Applied Economics.
Sutherland, RJ (1996), “The economics of energy conservation policy”, Energy Policy 24(4).
Torregrossa, M (2015), “Energy-efficiency investment with special regard to the retrofitting of buildings in Europe”, in B Galgóczi (ed.), Europe’s energy transformation in the austerity trap, Brussels: European Trade Union Institute.
 This is an estimate, as not all firms went to the end of the module.
 Cost saving percentage was drawn from a uniform distribution ranging from 5% to 25%. This, along with firm-stated energy costs, allowed to derive the total cost saving from the energy-efficiency project. A second variable was the internal rate of return (IRR, ranging uniformly from 4% to 20%), which, together with the cost saving, allowed to derive an overall project cost. The payback period was calculated directly from the total project cost and the cost saving.
 A typical investment project is one where all variables are set to their mid-points. The average investment probability equals 60% under these conditions.