Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes

This paper tests to what extent different types of variables (building factors, socio-demographics, attitudes and self-reported behaviours) explain annualized energy consumption in residential buildings, and goes on to show which individual variables have the highest explanatory power. In contrast to many other studies, the problem of multicollinearity between predictors is recognised, and addressed using Lasso regression to perform variable selection. Using data from a sample of 924 English households collected in 2011/12, four individual regression models showed that building variables on their own explained about 39% of the variability in energy consumption, socio-demographic variables 24%, heating behaviour 14% and attitudes & other behaviours only 5%. However, a combined model encompassing all predictors explained only 44% of all variability, indicating a significant extent of multicollinearity between predictors. Once corrected for multicollinearity, building variables predominantly remained as significant predictors of energy consumption, in particular the dwelling’s size and type. Of the sociodemographic predictors, only the household size remained significant, and of the heating behaviours only the length of heating season was significant. Reported beliefs about climate change were also a significant predictor. The findings indicate that whilst people use energy, it is physical building characteristics that largely determine how much is used. This finding, together with the relatively greater time-invariant nature of building characteristics underlines their importance when focusing on seeking to understand residential energy consumption at a stock level. Retrofitting and behaviour change initiatives remain important avenues to reduce consumption, as suggested through the lower energy consumption associated with full double-glazing and shorter heating season. However, the dominance of building size also indicates that living in appropriately sized buildings is of great importance for energy consumption. The results also indicate that more than half of the variability in energy consumption cannot be explained, even when using a wide range of predictors. The paper also discusses the need to collect better occupant-related variables to give a correct representation of the impact of behaviour, such as heating demand temperatures. Furthermore, choices about dwelling characteristics could also be seen as a type of behaviour, even though it cannot be modelled in a cross-sectional analysis as used in this study.