Using a CAMA approach to model energy efficiency in housing

Computer Assisted Mass Appraisal (CAMA) utilising hedonic and spatial analysis is well established in the field of property valuation for taxation purposes. In this role these approaches are deployed on large datasets of property attribute data and use prices in a sold sample to estimate value in the general population. With the emergence of the green agenda, much effort has been put into improving the energy efficiency of housing. A key policy has been the introduction of energy ratings which have become mandatory in several jurisdictions, with the aim of informing market choices. Many jurisdictions have also made efforts to improve knowledge of energy efficiency of housing stock, to better target funding and awareness campaigns aimed at encouraging upgrades. Some jurisdictions are now seeking to reward / encourage such activity via tax incentives. This research is based upon a project to bring together several large databases of property based data, held by a tax authority, an energy saving trust and a major social housing provider to establish a basis for statistical analysis. The aim is to estimate the energy efficiency of the entire housing stock of a jurisdiction using the type of attribute data commonly collected for taxation and energy management purposes. The research utilises regression analysis and spatial analysis to understand the pattern of energy inefficiency and to identify hot-spots of poor performance. The aim is to provide a methodology which may be broadly deployed to gain a deeper understanding of energy efficiency in the housing stock and to provide a data test bed to model the performance potential of a range of potential policy options.