E =
∑
i
A
i
*
∑
j
S
i,j
* I
i,j
,
(A3.5)
where the index i denotes the sectors listed in the first column in Table A3.1. By re-
aggregating the decomposition terms to the national level, interesting comparisons can
be made of developments in energy per unit of gross domestic product (GDP). If both
sides of Equation (A3.5) are divided by GDP, then
E/GDP = ((
∑
i
A
i
*
∑
j
S
i,j
)/GDP) *
∑
j
i,
I
i,j
.
(A3.6)
The product of the activity effect (A) and the structure effect (S) can be defined as the
energy services effect. Thus Equation (A3.6) helps explain how energy per unit of
GDP has changed due to shifts in the ratio of energy services to GDP and due to
changes in end-use energy intensities. The first factor reflects that the structural
evolution of economies and human activities can cause changes in demand for energy
services and, therefore, consumption that enhances or offsets shifts caused by changes
in energy intensities. For example, air travel measured as passenger-km has grown
faster than GDP in many countries, usually more than offsetting declines in air travel
intensity (energy per passenger-km), with an increase in energy use for air travel per
unit of GDP as a result. On the other hand, structural changes away from energy-
intensive manufacturing industries have enhanced the effect of reduced sectoral
intensities in many places and thus accelerated a decline in energy per unit of GDP.
Measuring the impact of these changes in the relationship between energy services
and GDP is therefore crucial to understanding how the ratio of energy use to GDP
changes over time.
4
The developments in energy services per GDP indicator help to show how much of
the change in energy per unit of GDP is due to factors other than changes in energy
intensities. The impact of intensities at the national level is instead captured by the
4
The decomposition presented in this annex can be extended to address changes in CO
2
emissions by
introducing the dimension of fuel mix. This approach can be used to assess how changes in CO
2
emissions per GDP can be decomposed into changes in supply efficiency and fuel mix, final energy
fuel mix, end-use intensity effect, and ratio of energy services to GDP. The approach thus provides
a framework for quantifying the relative impact each of these factors has on CO
2
emission per GDP
trends. Since all of these factors, except the ratio of energy services to GDP, are represented by
some of the ECO indicators presented in this publication, this decomposition approach can help
weighing the impact on overall CO
2
emission trends from the relevant ECO indicators. For more
details on how to decompose CO
2
emissions see: IEA, 2004 Oil Crises and Climate Challenges:
30 Years of Energy Use in IEA Countries. Paris, France: International Energy Agency.
160
energy intensity index at a national level (the I term in Equation A3.6). This is
constructed through weighting the sectoral energy intensity effects (Equation A3.4) at
the base-year value of energy use.
The separation between energy services effects and energy intensity effects is
important from a policy perspective, since restraining energy-service demand is
seldom a policy objective. This decomposition approach allows for observing the
impacts of the policy elements related to energy intensity separately from changes in
the structural and activity components of energy use. This helps both to determine
where policies can be most effective and to monitor progress once they have been
implemented.
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