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

• Published in: Applied energy 2015-12, Vol.159, p.589-600
• Main Authors: Huebner, Gesche M., Hamilton, Ian, Chalabi, Zaid, Shipworth, David, Oreszczyn, Tadj
• Format: Article
• Language: English
• Subjects: Behaviour; Buildings; Energy demand; Lasso regression; Multicollinearity; Socio-demographics
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2015.09.028

•Building characteristics explain most variability in domestic energy consumption.•Controlling for building factors, socio-demographics add little explanatory power.•Attitudinal variables contribute very little to explaining energy consumption.•Length of heating season is a significant predictor, even after controlling for region.•Multicollinearity is a crucial issue in analysis of energy consumption. 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 o