Tuesday, June 14, 2011

Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector

Energy consumption from the residential sector is a complex sociotechnical problem that can be explained using a combination of physical, demographic and behavioural characteristics of a dwelling and its occupants. A structural equation model (SEM) is introduced to calculate the magnitude and significance of explanatory variables on residential energy consumption. The benefit of this approach is that it explains the complex relationships that exist between manifest variables and their overall effect through direct, indirect and total effects on energy consumption. Using the English House Condition Survey (EHCS) consisting of 2531 unique cases, the main drivers behind residential energy consumption are found to be the number of household occupants, floor area, household income, dwelling efficiency (SAP), household heating patterns and living room temperature. In the multivariate case, SAP explains very little of the variance of residential energy consumption. However, this procedure fails to account for simultaneity bias between energy consumption and SAP. Using SEM its shown that dwelling energy efficiency (SAP), has reciprocal causality with dwelling energy consumption and the magnitude of these two effects are calculable. When nonrecursivity between SAP and energy consumption is allowed for, SAP is shown to have a moderately negative effect on energy consumption but conversely, homes with a propensity to consume more energy have a higher SAP rating and are therefore more efficient.
For each extra person living in a dwelling, the expected mean floor area ... [increases] by 7.27m2 (β=0.31**), the mean annual household income will increase by £2,463 (β =0.33**), and the mean energy bill will increase by £88/year (β =0.42**). Moreover, by considering the standardised regression weights for total affects it is possible to compare the relative magnitude of effects across different variables. Here, it is shown that Household Occupancy has the largest overall effect on energy expenditure (β = 0.419**) followed by Floor Area (β = 0.258**) and HHLD Income (β = 0.241**).
Using total effects, a £10,000 increase in annual HHLD Income will lead to an expected average increase in Energy Expenditure of £68/year. On the other hand, if we consider only the direct effects of HHLD Income on Energy Expenditure the average increase in Energy Expenditure is only £41/year.
An increase in Energy Pattern, as expected, increases both Temperature Difference and Energy Expenditure. Energy Pattern is an ordered categorical variable ranging between 1 and 5 where 1 represents someone who is never home and rarely uses their heating compared to 5, representing a dwelling where heating is on all the time. The difference in annual Energy Expenditure between these two types of users is, on average £139/year.
The effect of SAP on Energy Expenditure has a moderate but statistically significant effect (β = -0.22**), while Energy Expenditure is also shown to effect SAP (β = 0.23**). That is, for each standardised unit increase in the SAP rating a subsequent decrease in Energy Expenditure of β = -0.22** is expected. Similarly and to put this in context, it is necessary to examine the unstandardised regression weights. Remembering that SAP is on a scale from (0-110), for each unit increase in SAP the average saving in annual Energy Expenditure will be £3.73. For example, if a dwelling with a poor energy efficiency rating with SAP=30, is renovated to, say, SAP=90 the expected annual average saving in energy expenditure will roughly be £222 per annum (£UK1996) Ceteris Paribus.

Perhaps what is more interesting is the finding that dwellings with a propensity to consume more energy due to higher occupancy rates, higher household incomes, larger floor areas, increased energy patterns and warmer internal temperatures are more likely to have higher SAP ratings. This therefore suggests that homes with a propensity to consume more energy would, in fact, consume even larger amounts of energy if it were not for the fact that these homes were already relatively more efficient when compared to the rest of the building stock.
by Scott Kelly
Cambridge University Department of Economics Electric Policy Research Group
EPRG Working Paper 1117, Cambridge Working Paper in Economics 1139; 2011

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