Regional differences in the capitalisation of energy efficiency improvements in the housing market

We match Energy Performance Certificates (EPCs) with Land Registry data to create a micro-level dataset for England and Wales on residential transaction prices and property characteristics. We then develop a hedonic model to predict the impact of proposed energy improvements on the price of each property. A crucial element of this model is a proxy measure for plot size (which is missing in the UK data). This proxy is needed to generate meaningful results for London. By comparing the price impacts of energy improvements with the costs (from the EPCs), we can examine how private incentives to make energy improvements vary by ITL-1 region and property type. Our results suggest that the private incentives to increase energy efficiency are weakest for detached houses in London. More generally, our findings could help design more cost-effective government subsidy schemes to help the UK reach its Net-Zero carbon emissions target by 2050.

Improving the energy efficiency of residential housing must be a key element of any plan for the UK to reach its Net-Zero carbon emissions target by 2050. An important part of this plan should be to improve property owners’ incentives to increase their homes’ energy efficiency. This project aims to establish for what types of properties and in which regions of England and Wales these incentives are weakest. We use matching algorithms to construct detailed micro-level datasets by combining Land Registry and Energy Performance Certificate (EPC) data. We then estimate hedonic models to determine how energy efficiency improvements affect property prices. By comparing these price increases with the estimated costs of these improvements from the EPCs, we can assess the private incentives to undertake such improvements at the level of individual properties.

First, we developed algorithms to match properties in the Land Registry dataset with properties in the Energy Performance Certificate (EPC) dataset. We constructed a proxy measure of plot size (which is missing in the UK data) based on the distance between adjacent properties using the entire UPRN dataset (40 million addresses). We then worked on the estimation of a hedonic model to model how property prices depend on property characteristics (such as age, floor area, energy efficiency, and location).

Using the hedonic model, we predicted the impact of changes in energy efficiency on property prices. We compared the predicted price impact of energy improvements with the estimated costs given in the EPCs to determine where the private incentives to improve energy efficiency are weakest. We then used a sample of repeat sales properties to construct an alternative measure of how energy improvements increase property prices. These repeat-sales estimates serve as a benchmark against which to compare our hedonic results.

We found that the inclusion of a proxy for plot size in the hedonic model is crucial for obtaining meaningful results for detached houses in London. The variable has little effect on the results for semi-detached/terrace houses or flats. The capitalisation rates for energy improvements are reasonably similar across ITL-1 regions and over time. The capitalisation rates are higher for flats than for semis-terraces and detached houses.

The most striking result we found was the very low capitalisation rate of energy improvements for detached houses in London. This is due to the crucial role played by location in London in determining property prices. For London, location dominates other considerations, such as energy efficiency. Our hedonic results are very similar to those obtained using repeat sales. This confirms that the hedonic model is generating plausible results.

The UK has committed to achieving a Net-Zero carbon emissions target by 2050. Buildings account for almost 40% of the UK’s energy consumption and carbon emissions. Hence increasing the energy efficiency of housing must be a key element of the Net-Zero strategy. This project seeks to identify the property types and regions of the UK where the private incentives to undertake energy improvements are weakest. This information will help the government design more cost-effective initiatives (including subsidies) for reaching the Net-Zero goal by 2050.

Hill, R., Pfeifer, N. and Steurer, M. (2023) ‘Property Values: A Hedonic Analysis of Market Incentives in England and Wales‘ ESCoE Discussion Paper Series, ESCoE DP 2023-12, July 2023.

Hill, R. ‘The capitalisation rate of energy efficiency improvements in the housing market: a micro-level analysis for England and Wales’ Business Analytics and Data Science Center Lecture, University of Graz, 29 March, 2023

Hill, R., Pfeifer, N. and Steurer, M. ‘The Capitalisation of Energy Efficiency Improvements in the Housing Market: A Micro-Level Hedonic Comparison for England and Wales’ Workshop Residential Housing Markets: Connecting Housing Researchers in Austria, Vienna University of Economics and Business, 30 January 2023

Steurer, M. ‘Do Energy Improvements Pay for Themselves in the Housing Market? A Micro-level Hedonic Comparison across England and Wales‘ ESCoE Economic Measurement Webinar, 23 March 2023

Hill, R.,  Pfeifer, N. and Steurer, M. ‘Do Energy Improvements Pay for Themselves in the Housing Market?  A Micro-level Hedonic Comparison across England and Wales’ Economic Statistics Centre of Excellence: The Next Five Years, poster exhibition, 12 December 2022, One Birdcage Walk, London.