The EeDaPP outcomes will be presented during an EEMI Webinar on Friday, 25 September, at 10 am CEST.
Email contact for participation: <email@example.com>
The end of August 2020 marks the conclusion of the Horizon 2020 Energy Efficient Data Protocol & Portal (EeDaPP) Project which has delivered – after 30 months of intense work, data collection, market analysis and consultations – very important results for both the Industry and policymakers:
- The EeDaPP Master Template (& accompanying explanatory White Paper) (link to both), a protocol which provides a common Industry benchmark for the collection of data related to building energy performance and which will constitute the basis for the development of disclosure best practices in the Energy Efficient Mortgage Label;
- A comprehensive analysis into the correlation between energy efficiency and credit risk (link). The econometric analysis demonstrates a negative and significant correlation between building energy performance and the probability of mortgage default, potentially paving the way for new policy considerations in relation to energy efficient mortgages (EEM).
The underlying assumption of the Energy Efficient Mortgage Initiative (EEMI), which brings together the EeMAP, EeDaPP and EeMMIP projects, is that energy efficient mortgages represent several advantages for lending institutions, borrowers, and policymakers. Namely, they are believed to reduce the owners’ payment disruption risk, increase property value, and, as a result, reduce credit risk for banks and financial institutions.
The EEMI has a threefold objective. First, to propose a private initiative promoting energy efficiency investments in buildings. Second, to create a standardised EEM to facilitate the acquisition of EE properties and the renovation of those not aligned with EE norms. Third, to evaluate the availability of EE mortgage asset data across EU Member States and gather large scale datasets to investigate the link between buildings’ energy efficiency features, its market value, and the loan’s probability of default (PD) and loss-given-default (LGD).
The econometric evaluation provided in the Report available today focuses on the specific case of Italy. According to the associated portfolio analysis, the percentage of more energy efficient mortgages has been increasing over the last decade, while less efficient properties are predominantly affected by default. Significantly and as indicated above, the econometric evaluations highlight a negative correlation between EE and the owners’ probability of default (PD), thus confirming that EE investments tend to improve owners'/borrowers’ solvency. Additionally, the results indicate that the degree of energy efficiency also matters, i.e., more energy efficient buildings are associated with relatively lower risk of default. Once again, these findings highlight the role of energy efficiency in reducing the default probability of a borrower.
The selection of the portfolio analysed was based on approximately 470,000 real estate valuations. After a data cleaning exercise, the total number of mortgages analysed was 72,980.
Against this background and as you are aware, the EMF-ECBC is leading efforts to establish an EEM Label which will not only facilitate further data collection to substantiate this correlation on an ongoing basis, but which will also secure quality and transparency for market stakeholders in the gathering, processing and disclosure of EEM data, stimulating market development.
Given the relevance of these findings for the mortgage and covered bond industries, as well as key EU policy files including the EU Green Deal, the Renewed EU Action Plan on Sustainable Finance and the implementation of Basel III into EU legislation, the EeDaPP outcomes will be presented during an EEMI Webinar on Friday, 25 September, at 10 am CEST.
Credits to EeDaPP Consortium members (Ca’Foscari University of Venice, CRIF, European DataWarehouse, Hypoport, SAFE Goethe University Frankfurt and TXS) and EEMI Pilot Banks that have been involved in the data collection and market analysis exercise.
Email contact for participation: Luca Bertalot <firstname.lastname@example.org>