Robert Hill, Robert Pfeifer & Miriam Steurer
In 2021, the Government set out its ambitious Net Zero Strategy to reach net zero carbon emissions by 2050. As buildings account for nearly 40% of the UK’s energy consumption, increasing the energy efficiency of residential properties needs to be an essential part of this strategy. This paper evaluates the market incentives for homeowners to invest in energy-saving property improvements and investigates how these incentives differ across regions and property types.
Multiple studies have shown that properties with higher energy efficiency ratings sell at higher prices (other things equal). So far, what has been less clear is how these price effects compare with the associated costs of these energy efficiency improvements and how the results differ across property types and regions. We provide this analysis by comparing the net effect of implementing EPC recommendations on property values and costs in different markets.
Since 2008, residential properties must obtain an Energy Performance Certificate (EPC) when being sold. These EPCs not only evaluate the property’s current energy efficiency performance but also provide homeowners with a list of recommendations to improve their property’s energy efficiency, including an estimate of the expected energy efficiency if these improvements were implemented. We use both the actual and the potential EPC ratings in our study.
The hedonic models we run to estimate the impact of improving a property’s energy performance on market prices require detailed descriptions of property characteristics. We establish such a detailed dataset by matching each sales record from the HM Land Registry with its corresponding EPCs. We can describe each transaction with a wide range of characteristics, including price, size, age, building type, window type, heating system, and current and potential energy efficiency values. These characteristics help us to minimise any bias from unobserved quality differences in our model estimation.
Although our merged dataset describes each property in detail, one important variable is missing: plot size. To overcome this omission, we construct a proxy variable for plot size using an innovative approach based on the distances between neighbouring properties. Incorporating plot size in the hedonic model can explain some apparent anomalies in the literature concerning the impact of energy efficiency on property prices in the UK.
We then compute separate hedonic models for the three main property types (flats, semis/terraces, and detached houses) and the ten ITL-1 regions in England and Wales.
We calculate the capitalisation rate of energy efficiency improvements (CREEI) for each property in our dataset. The CREEI is defined here as the percentage of EPC-suggested home improvement costs that are covered by the estimated increase in property value. A CREEI of 100% implies that the estimated increase in property value exactly covers the costs of the EPC-suggested energy improvements. A CREEI value of less than 100% indicates that the costs are higher than the estimated value increases, while a CREEI of above 100% suggests that the costs of the energy-efficiency improvements are more than covered.
Even though our data describe properties in quite some detail, there will always be some missing variable bias in the hedonic estimation. As a robustness check for our hedonic method, we construct a sample of properties that sold at least twice during the estimation period and underwent energy-performance improvements but no change in overall size. These repeat-sales properties allow us to estimate an alternative impact of the effect of energy-improving estimates on house price values. We compare the price ratios of these repeat-sales properties with those obtained from our hedonic models (for these same properties) and find that the estimates vary only slightly, thus validating our results.
In terms of findings, we can state the following for the period 2014-2022:
- We find that the capitalisation rate of energy efficiency improvements varies significantly across types of properties and regions.
- For flats, the capitalisation rate varies between 72% (East) and 103% (East Midlands) of the costs of energy-efficiency improvements recommended by the EPCs.
- The capitalisation rates are lower for semis/terraces and detached houses. For semis/terraces, they range between 47% (North East) and 65% (North West). For detached houses, they range between 24% (London) and 88% (North East).
- Over time the capitalisation rates trend upwards for semis/terraces and detached houses but not for flats. The capitalisation rates for detached houses in London (irrespective of their initial energy efficiency level) are particularly low. We hypothesise that this is due to the crucial role of location and plot size in London in determining property prices. Given the high land prices in London, these factors tend to dominate other quality characteristics, such as energy efficiency.
Our finding that energy efficiency improvements are not entirely capitalised in property prices suggests the need for government intervention. Government subsidies, such as the recently announced “Help to Heat” scheme, could play an essential role in encouraging owners to invest in energy efficiency improvements of their homes. Moreover, government support schemes should consider regional differences to ensure that subsidies are targeted where they are most needed. Our study can provide meaningful input toward reaching this goal.
Figure 1 below illustrates how building age correlates with a property’s energy efficiency rating. Improvements in energy efficiency have been particularly marked for detached houses. While in the older property cohorts, flats are more energy efficient than semis/terraces, which are more energy efficient than detached houses, these differences no longer exist for properties built after 2007.
Figure 2 indicates how the energy efficiency ratings of detached houses differ across ITL-1 regions. London has the lowest percentage of properties with energy efficiency classes A, B, and C.
ESCoE blogs are published to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the ESCoE, its partner institutions or the Office for National Statistics.