Environmental Engineering Reference
In-Depth Information
sets; 78 % have electric ovens, almost half have dishwashers, although only 14.8 %
have tumble dryers. The average dwelling measures 86.5 m
2
and has
ve rooms.
4 Results
This section presents the results of the residential demand models for electricity and
natural gas. The demand for electricity is estimated via OLS, while the Heckman
model for natural gas is estimated via maximum likelihood. In both cases, robust
standard errors are used. It is important to note that CO
2
emission variable contains
information about the physical characteristics of each dwelling, including its location.
4.1 Demand for Electricity
Table
5
shows the results for two linear regression models analysing residential
demand for electricity. The difference between them lies in the presence of two
interaction terms in panel (b).
The term
natural gas
(
full
)
×
ln (
natural gas price
) estimates the cross elasticity
between electricity and natural gas. The term
electricity
(
full
)
ln (
electricity price
)
serves to estimate the price elasticity of electricity demand in two groups of
households: those that use electricity as their sole fuel (
electricity
(
full
)) and those
that combine electricity with other sources of energy for providing heating and
domestic hot water. In panel (a) the variables
electricity price
and number of rooms
are signi
×
cant at the 10 % level. The variables number of TV sets,
household with
tumble dryer, rated electrical power in household, 2
-
monthly electricity bill
and
CO
2
emissions
are signi
cant at the 1 % level.
Residential electricity consumption increases by 13.9 % per additional house-
hold member, and by 2.9 % per additional room. A household with a tumble dryer
can be expected to consume 17.9 % more electricity than a household without one.
Electricity demand also increases by 10.8 % per additional TV set. A unit increase
in the rate electrical power would increase electricity consumption by 10 %.
Households with 2-monthly electricity billing are found to consume 28 % less
electricity than those that are billed monthly.
In relation to energy ef
ciency related variables, electricity demand price elas-
ticity is found to be
0.722, which means that demand is inelastic. Thus, if the
assumptions of symmetry, exogeneity and constant ef
−
ciency are met the direct
rebound effect should be 0.722. Therefore, according to (
6
) an increase of 10 % in
the energy ef
ciency of electrically powered heating and domestic hot water systems
results in a reduction in electricity consumption of just 2.78 %.
The CO
2
emissions variable is found to have the expected sign
the lower the
dwelling quality rating, the higher are its CO
2
emissions and heating demand. For a
10% reduction inCO
2
emissions, the electricity consumption is reduced by just 0.98%.
—
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