Annex D: Defining Cost Effectiveness
In the EES Route Map in 2018, we proposed that an EPC C should be reached where cost effective and technically feasible. Following this, we commissioned a literature review through ClimateXChange to survey definitions of cost effectiveness used for energy efficiency upgrades in buildings.
The research found that there is no single approach that is universally applied. In addition to a straightforward cap on the costs of upgrading a property (which will be used in the Energy Efficient Scotland private rented housing regulations in the initial stages), the review identified at least nine methods of evaluating cost effectiveness which have been used in different contexts.
These definitions are best understood as a continuum, becoming more complex as various costs and benefits, and more sophisticated methods of calculation, are added. Three broad categories of defining cost effectiveness are set out in the box below.
Cost Cap: The simplest is a cost cap approach, which focuses entirely on the cost of upgrading the dwelling, and is also the easiest definition to calculate and communicate.
Simple Payback Test: A simple payback test, which the review found was the most widely used method for domestic properties, takes into the account the benefit of the upgrade in terms of fuel bill savings as well as its cost, and tests whether the savings are expected to exceed the cost of the upgrade over the life of the measure, or within a set maximum period. This definition requires calculation of the fuel bill savings, most likely through an application of the SAP methodology to calculate the expected savings for the particular dwelling in question. It may also require a decision to be made on the expected lifetimes of different types of upgrades.
Net present value: Further refinements can be made to the simple payback test. For example, future energy prices can be assumed to grow at a particular rate rather than remaining constant, maintenance costs can be included, and discounting can be applied to future costs and benefits, so that the definition increasingly resembles a full net present value calculation. In turn, this requires a decision about the appropriate discount rate. Business as usual costs could potentially also be taken into account.
Deciding which parameters to use in the cost effectiveness definition will require trade-offs between the ease of calculation and communication, the sophistication of the test and the level of energy efficiency and low carbon attainment in the housing stock.
For example, setting a maximum upgrade cost is relatively easy to communicate. However, it may mean that more expensive measures, such as external wall insulation and renewables, will be less likely to fall within the cap, even if they are expected to pay back over their lifetimes. This limitation also applies to a simple payback test if it sets a maximum payback period which is significantly shorter than the lifetime of longer-lasting measures.
Definitions which focus on the payback to the individual household from fuel bill savings can also fail to recognise wider benefits to society from reducing carbon emissions, since these are not factored into the market price of fuels, particularly fossil fuels (such as gas and oil) which have a high carbon content contributing to pollution and climate change.
The cost effectiveness calculation could attempt to include the wider social benefits from reduced greenhouse gas emissions, although this would require quantification. An alternative approach is to factor in public sector incentive schemes, e.g. payments for the energy generated from renewables, or a contribution towards the capital cost of installing renewables or insulation, since the rationale for this public funding is to close the gap between what is individually optimal and what is socially optimal. This could add complexity to the calculation, particularly as the level of support can fluctuate between years, and budgets may run out during a year.
A further decision that is required is whether the cost effectiveness test applies to a package of measures, or to each measure on its own. A test based on a package of measures is likely to result in more dwellings meeting the target than a measure-by-measure test.
For example, the final measure of a package of measures which is required to meet the target may not pay back when considered on its own, even though the package of measures as a whole pays back because the negative payback on the final measure is more than offset by the positive payback on the other measures.
If the cost effectiveness calculation applies to a package of measures, this would require setting a time period to determine whether previous work undertaken by the owner should be considered as part of the package; in contrast, with a measure-by-measure approach, there is no need to consider previous work.
It will also be important that the cost effectiveness test works effectively alongside the assessment methodology. For example, the assessment methodology may allow for tailoring of the recommendations to the needs of the particular household in question to give them the best advice for their own needs. However, to decide whether the regulatory standard has been met, standard assumptions will need to be applied, because the regulations need to cover the situation where the occupants of the dwelling change.
The assessment process may allow greater flexibility to choose a more sophisticated cost effectiveness definition, since the complexities can be offset to some extent by ensuring that the assessment tool automatically calculates whether the cost effectiveness test has been met, although the drawback would be the household may have less understanding of what the calculation means.
To help inform these considerations, we have commissioned modelling work to explore the impacts of different cost effectiveness definitions on attainment rates. This work is focussing on the three main approaches set out above;
- a cost cap,
- a simple payback test,
- and a net present value calculation.
It is also undertaking sensitivity testing of the impact of factoring public sector incentives for upgrades. We expect the results to be published in early 2020.
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