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Article
Why Electricity Demand Is Highly Income-Elastic in
Spain: A Cross-Country Comparison Based on an
Index-Decomposition Analysis
Julián Pérez-García * and Julián Moral-Carcedo
Facultad Ciencias Económicas, Universidad Autónoma de Madrid, 28049 Madrid, Spain; [email protected]
* Correspondence: [email protected]; Tel.: +34-914-97-2705
Academic Editor: George Tsatsaronis
Received: 1 February 2017; Accepted: 6 March 2017; Published: 11 March 2017
Abstract: Since 1990, Spain has had one of the highest elasticities of electricity demand in the
European Union. We provide an in-depth analysis into the causes of this high elasticity, and we
examine how these same causes influence electricity demand in other European countries. To this
end, we present an index-decomposition analysis of growth in electricity demand which allows us to
identify three key factors in the relationship between gross domestic product (GDP) and electricity
demand: (i) structural change; (ii) GDP growth; and (iii) intensity of electricity use. Our findings show
that the main differences in electricity demand elasticities across countries and time are accounted
for by the fast convergence in residential per capita electricity consumption. This convergence has
almost concluded, and we expect the Spanish energy demand elasticity to converge to European
standards in the near future.
Keywords: electricity demand income elasticity; index decomposition analysis; long-term demand
JEL Classification: Q4; Q43; L; L5; L94
1. Introduction
The pressing issue of global warming has fueled attention for long-run analyses of energy demand.
Competing hypotheses about the causality between economic growth and energy consumption call for
very different degrees of activism for energy conserving policies. As Ozturk [1] pointed out, predicting
the effects that such policies will have on economic growth requires to ex-ante know if use of energy
causes growth or vice versa. If energy demand is caused by economic growth, then the costs in terms
of output losses of energy conserving measures are bearable. On the contrary, if use of energy fuels
economic growth then energy can be a limiting factor to economic growth, and therefore moving
towards less energy-dependent economies will imply a trade-off.
Zhao et al. [2], for instance, summarized these alternatives in four competitive hypothesis: Growth
hypothesis (unidirectional relationship from energy to income growth), Conservation hypothesis
(unidirectional inverse relationship from income growth to energy consumption), Neutrality hypothesis
(there no exists any causal relationship), and Feedback hypothesis (bi-directional causal relationship).
Although these authors provide some empirical references for each hypothesis, the most recent
researches tends to reject the neutral hypothesis [3] and reinforce the feedback hypothesis, as is shown
by Zhao [2] using Chinese provinces data, and Lu [4] by mean of 17 Taiwanese Industries.
According to the survey by Ozturk [1], previous works show conflicting and mixed results
regarding the direction of this causality. The authors of some of these works, such as Chang et al. [5],
Huang et al. [6], Holtedahl and Joutz [7], and Hondroyiannis [8] also pointed out two interesting
features: First, income elasticity, or GDP elasticity of energy demand, is not constant over time nor
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across countries; and, second, there are significant differences in elasticities between the residential
and the productive sector. These differences are linked to the degree of economic development in the
energy-growth nexus, and the “mechanization” of the productive and residential sector.
With respect to the effect of the degree of economic development on the energy-growth nexus,
Huang et al. [6] found no causal relationship between the two variables for low-income countries,
economic growth leading energy consumption positively in middle-income countries, and economic
growth leading energy consumption negatively in high-income countries. Janosi and Grayson [9]
found similar results, confirming that energy consumption tends to respond to economic growth
with higher intensity in less developed countries compared to advanced economies. Yoo and Lee [10]
reported an inverted u-shaped relationship between electricity consumption and per capita income.
However, even though the causality direction will be correctly addressed it is interesting to know
if the nexus energy usage-economic growth is stable or it is changing with the degree of economic
development, and what are the causes this change can be attributed to. From a policy perspective,
a changing relation will require that any conservation measure to be effective has to be adequately
adapted to the “state” of economic development. Moreover, if the link between energy consumption
and economic growth can be broken down by sectors (residential and no-residential) that reacts in a
different way to certain type of policies (for example, measures based on prices), the policy effectiveness
will be conditioned critically by the contribution to energy consumption growth of each sector.
In this way, some recent works have tried to estimate this time-varying elasticity using different
econometric approach for an individual country Chang et al. [5], or panel data with different countries
Chang et al. [11].
In most European countries electricity demand constitutes a significant and growing fraction of
total energy demand. Between 16% and 33% of energy demand in Europe is covered by electricity. Over
the last decade and independently of economic growth, in nearly all European countries, electricity
demand has grown more than energy demand (see Table A1 of Appendix A). Hence, an in-depth
analysis of the income elasticity of electricity demand is a first step towards a better understanding of
the energy-growth nexus.
In addition to cross-country differences we also observe that over time as economies develop and
mechanization increases, the nature of electricity consumption elasticities changes. Both, differences
between countries and changes over time, are usually attributed to differences in the degree of
penetration of electrical appliances in the productive (robotization, etc.) and residential (lighting,
cooling and heating equipment, TV, mobile phones, etc.) sectors. Chang et al. [5], looking at Korean
monthly data find increasing output elasticities of electricity demand for 1985–2012 in the residential,
commercial, and industrial sector. The authors show that income elasticity of electricity demand
increases over time, possibly driven by the proliferation of electronic devices in firms’ production
processes and in household consumption. Variability of elasticities can also be observed by looking
at the highly dispersed estimates for income elasticities of electricity demand in different countries.
For instance, Holtedahl and Joutz [7] considered Taiwanese data for 1955–1996 and find a long-run
income elasticity of residential electricity demand of one, while their short-run estimate is much lower
(0.23). On the other hand, Hondroyiannis [8] who examined the demand for residential electricity
in Greece during 1960–1998, reports a much higher income elasticity of 1565. Other authors, such
as Silk and Joutz [12] using 1949–1993 data on residential electricity consumption in the United
States also find income elasticities smaller than unity. Yamaguchi [13] compared electricity demand
data for 1986–1993 and 1993–2004 in Japan and finds that elasticities increased from 1076 to 1679.
Zachariadis and Pashourtidou [14] used annual data for 1960–2004 to examine electricity consumption
in the residential and service sector in Cyprus. Their results show that long run income elasticities
of electricity consumption are larger than unity. More recently, Hasanov [15], summarized long run
income elasticities of electricity consumption in resource-rich small open developing economies that
ranges from 0.2, in Gulf Cooperation Council between 1975 and 1989, to 5.4 in Bahrain between 1970
and 1997.
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With respect to sectorial differences in income elasticity of electricity consumption,
Bianco et al. [16] found that for Italy the GDP elasticity of non-residential electricity consumption is
fairly high in the short run (1.41) and even larger in the long run (2.20). Their estimated value for
the short-run residential electricity consumption income elasticity, on the contrary, is only 0.29. The
authors also find residential electricity consumption to be characterized by a much more irregular
behavior, linked to population growth and to the increase in electricity intensity due to the diffusion of
air-conditioning appliances. Other studies, such as Holtedahl and Joutz [7] and Hondroyiannis [8],
found income elasticities of electricity consumption in the residential sector of one or larger for very
different countries such as Greece or Taiwan. If all countries exhibited similar differences in long and
short run elasticities by sectors we would expect aggregate elasticities to change over time, depending
on the relative weight of residential and non-residential electricity consumption.
Nevertheless, even when Chang et al. [11], using a panel of 89 countries, highlight the role of
sectoral structure, as well as residential consumption patterns, on the income elasticities of electricity
consumption, they also remarks that “sectoral shifts alone are insufficient to explain the downward
movement in elasticities for a selected number of these countries: France, Germany, Italy, Japan, Korea,
Spain, the UK and the US”.
The current paper provides an in-depth analysis of the relationship between electricity
consumption and economic growth for all 28 countries of the European Union (EU). We focus on the
elasticity of electricity consumption with respect to economic growth in the long run, and we show
how this elasticity varies substantially across countries. Spain had one of the highest elasticities of
electricity demand to GDP among European countries, (almost three times higher than Germany) being
surpassed only by Italy, Portugal, and Malta. This is why we pay special attention to the Spanish case
and its comparison with other European countries where this elasticity has been significantly lower.
A first descriptive analysis of our data does not confirm the intuition that differences in electricity
demand elasticity are simply explained for by a country’s level of development. This is why we try to
provide a better understanding of the driving forces behind a country’s electricity demand elasticity.
To this end, we consider the evolution of electricity demand elasticity in Spain, and we present a simple
framework that allows us to understand how changes in electricity demand elasticity can be related
to deep economic transformations reflected in: (i) structural change; (ii) GDP growth; and (iii) the
intensity of electricity use.
Existing literature highlights all three aspects as main causes for changes in the elasticity of
electricity consumption over time, but there does not exist any structured framework to analyze the
contribution of each. A common feature of previously cited works is that they are all essentially
descriptive studies. Irrespective of the methodological approach used, electricity demand income
elasticity is basically determined from the analysis of the coevolution of electricity consumption and
household income, sectorial gross value added (GVA) or GDP. Most authors provide some insights
into the factors behind the observed variations in elasticities (proliferation of electronic devices,
increasing use of air conditioning, relative price of electricity, etc.), but without providing a clear
framework to analyze these variations. Hence, to the best of our knowledge we are the first to present
a structured framework that can be used to analyze electricity demand elasticities. Based on an
index-decomposition methodology (see Ang [17], and Ang and Zhang [18], among others) we provide
a simple, but very effective, way to analyze the contribution of the three long run drivers of the
changing relationship between electricity and economic growth: structural change, GDP growth, and
intensity of electricity use. Our main findings show that in particular relative intensities of electricity
use play a very important role for explaining observed differences in electricity demand elasticities.
Over the past thirty years, the Spanish economy experienced significant changes to its economic
structure, evolving from a high energy intensive industrial economy with high rates of GDP growth to
a service economy with moderate economic growth and declining electricity consumption after 2012.
In addition to the fact that Spain registered one of the highest electricity demand elasticities during
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this period, its dynamic economic development makes the analysis of the Spanish electricity demand
particularly
interesting.
The remainder
of this paper is organized as follows: the next section describes the main features
The remainder
of this paper
organized
as follows:
next section
features of
of electricity
consumption
in is
Spain
and the
EU. Inthe
Section
3 we describes
present the
ourmain
decomposition
electricity
consumption
in Spain
theresults.
EU. In Given
Sectionthe
3 we
present our
methodology
methodology
together with
ourand
main
importance
of decomposition
intensities of energy
use for
together
with
our
main
results.
Given
the
importance
of
intensities
of
energy
use
for
explaining
the
explaining the observed differences in electricity demand elasticities, in Section 4 we analyze how
observed
differences
electricity
demand
in Section
4 we analyze
these5 intensities
these intensities
havein
evolved
in Spain
and elasticities,
in other European
countries.
Finally,how
Section
concludes.
have evolved in Spain and in other European countries. Finally, Section 5 concludes.
2. Long Term Evolution of Electricity Demand in Spain and the EU
2. Long Term Evolution of Electricity Demand in Spain and the EU
Between 1996 and 2012, electricity consumption in the 28 countries of the European Union [19]
Between
1996 and
2012,rate
electricity
in the 28by
countries
of the
Union
[19]
grew at an average
annual
of 1.1%consumption
while GDP increased
1.7% [20],
i.e.,European
the income
elasticity
grew
at
an
average
annual
rate
of
1.1%
while
GDP
increased
by
1.7%
[20],
i.e.,
the
income
elasticity
of
of electricity demand of the EU-28 combined was less than unity During that period as economic
electricity
demand of the
EU-28 in
combined
was
less than unity
During that
periodintensity—measured
as economic growth
growth outperformed
growth
electricity
consumption,
aggregate
electricity
outperformed
growth
in
electricity
consumption,
aggregate
electricity
intensity—measured
as the ratio
as the ratio of total electricity demand to GDP—was reduced from 0.25 to 0.23 GWh/Million
€.
of
total
electricity
demand
to
GDP—was
reduced
from
0.25
to
0.23
GWh/Million
€.
Irrespective
of the
Irrespective of the causes, in general aggregate electricity intensity decreased in all European
causes,
in between
general aggregate
electricity intensity decreased in all European countries between 1996
countries
1996 and 2012.
and 2012.
However, country heterogeneity is one of the main characteristics of the EU and the degree of
However,
countrydemand
heterogeneity
is one
of the main
characteristics
of the
EU and thewe
degree
of
elasticity
of electricity
is not an
exception.
During
the same period
(1996–2012)
observe
elasticity
of
electricity
demand
is
not
an
exception.
During
the
same
period
(1996–2012)
we
observe
huge differences in average electricity demand income elasticities. For instance Denmark registered
huge
in average
demand income
elasticities.
instance
Denmark
registered
a
a neardifferences
zero elasticity
of 0.15,electricity
whereas Portugal
had a highly
elasticFor
electricity
demand
with
respect to
near
of 0.15,
whereas could
Portugal
had a highly
elastic electricity
demand
with respectwe
to
GDPzero
(1.7).elasticity
While these
differences
be attributed
to differences
in economic
development,
GDP
(1.7).
While
these
differences
could
be
attributed
to
differences
in
economic
development,
we
also observe similar differences for countries such as Bulgaria (0.34) and France (1.14). With the latter
also
observe
similar
differences
for countries
such
as Bulgaria
(0.34)slightly
and France
With the latter
being
the more
developed
country.
Spain with
a per
capita GDP
above(1.14).
the European
mean
being
theelectricity
more developed
with aofper
GDP
slightly
the European
mean
had an
demandcountry.
incomeSpain
elasticity
1.3.capita
During
the
periodabove
of analysis,
only Malta,
had
an electricity
demand
of 1.3.
During
period of
Malta, Portugal,
Portugal,
and Italy
had income
higher elasticity
elasticities,
while
the the
majority
of analysis,
countriesonly
exhibited
average
and
Italy had
elasticities,
while
elasticities
of higher
below one
(see Figure
1).the majority of countries exhibited average elasticities of below
one (see Figure 1).
Figure 1. Elasticity of Electricity Demand to GDP (∆Demand/∆GDP). Source: Own calculations with
Figure 1.data.
Elasticity of Electricity Demand to GDP (ΔDemand/ΔGDP). Source: Own calculations with
Eurostat
Eurostat data.
Figure 2 displays annual elasticities for Spain, the EU-15, Germany, France, UK, and Italy.
While Spain only experienced some transitory periods with elasticities below one, the situation in
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Figure 2 displays annual elasticities for Spain, the EU-15, Germany, France, UK, and Italy. While
Energies 2017, 10, 347
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Spain only experienced some transitory periods with elasticities below one, the situation in these other
countries,
the exception
of Italy
whichofisItaly
morewhich
similar
Spain,
was exactly
thewas
opposite,
these otherwith
countries,
with the
exception
is to
more
similar
to Spain,
exactlywith
the
only
very
few
episodes
when
electricity
demand
elasticities
rose
above
one.
opposite, with only very few episodes when electricity demand elasticities rose above one.
(a) Spain
(b) EU-15
(c) Germany
(d) France
(e) Italy
(f) United Kingdom
Figure 2. Elasticity Demand to GDP in selected countries. Annual data. Source: Own calculations
Figure 2. Elasticity Demand to GDP in selected countries. Annual data. Source: Own calculations with
with Eurostat data.
Eurostat data.
In order to better understand the driving forces behind such pronounced differences in
In
order
to better
understand
theEuropean
driving forces
behindin
such
differences
electricity
electricity
demand
elasticity
across
countries,
thepronounced
following sections
we in
analyze
the
demand
elasticity
across
European
countries,
in
the
following
sections
we
analyze
the
characteristics
characteristics of electricity demand in greater detail. We pay special attention to the case of Spain,
of
electricity
demandbetween
in greater
detail.
We pay
attention to
the case of virtually
Spain, whose
GDP
whose
GDP tripled
1970
and 2012
[21],special
with electricity
consumption
increasing
tripled
between
1970
and
2012
[21],
with
electricity
consumption
virtually
increasing
six-fold
during
six-fold during the same period. However, the Spanish electricity demand elasticity was far from
the
same period.
However,
Spanish
electricity
elasticity
was far
from constant
constant
throughout
this the
period.
Between
1970demand
and 1985
electricity
consumption
in throughout
Spain [22]
this
period.
Between
1970
and
1985
electricity
consumption
in
Spain
[22]
registered
growth
that
registered growth rates that were considerably higher than GDP growth, resulting in anrates
average
were
considerably
higher
than
GDP
growth,
resulting
in
an
average
elasticity
of
2.14.
On
the
other
elasticity of 2.14. On the other hand, from 1985 to 2012 electricity demand elasticity was reduced to
hand,
1985 analysis
to 2012 electricity
demand changes
elasticityrequires
was reduced
to 1.4. Amethodological
thorough analysis
of such
1.4. A from
thorough
of such profound
a structured
framework
profound
changes
requires
a
structured
methodological
framework
that
allows
us
to
better
disentangle
that allows us to better disentangle the driving forces behind electricity demand elasticities. The next
the
driving
forcessuch
behind
electricity demand elasticities. The next section presents such a framework.
section
presents
a framework.
3. Modeling Approach Based on Index Decomposition Methodology
Index decomposition analysis (IDA) is a simple tool that allows us to decompose changes in
electricity consumption in terms of the contribution of different effects. In particular, in this
framework, changes in electricity consumption can be decomposed into the three different effects
Energies 2017, 10, 347
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3. Modeling Approach Based on Index Decomposition Methodology
Index decomposition analysis (IDA) is a simple tool that allows us to decompose changes in
electricity consumption in terms of the contribution of different effects. In particular, in this framework,
changes in electricity consumption can be decomposed into the three different effects mentioned
before: (i) changes in sectorial structure (sectorial share in total GDP); (ii) changes in global economic
activity (aggregate GDP growth); and (iii) sector specific energy intensity (energy used per unit of
GVA). Following the IDA framework, we first decompose total electricity consumption in a given year
t (Ct ), into residential and non-residential consumption (electricity demand by firms and the public
sector). Non-residential electricity consumption, is determined by changes in economic activity, (Yt ),
changes in relative sectorial activity, ( YYitt ), and changes in the intensity of electricity use per unit of
C
i,t i,t ). Change in residential consumption, on the other hand, can be determined as
sectorial output, (I=
Yi,t
a function of population growth and other demographic aspects that determine changes in the number
C
of households (Ht ), and changes in the intensity of electricity consumption by households, (IH,t = HN,tt ).
Combining electricity consumption by the two sectors, we can write the following expression:
N
Ct =
N −1
∑ Ci,t = ∑
i =1
Yt
i =1
Yi,t Ci,t
C
+ Ht N,t =
Yt Yi,t
Ht
N −1
∑
Yt Si,t Ii,t + Ht IH,t
(1)
i =1
where Si,t denotes the share of GVA of each sector over total GDP and Ci,t is the breakdown of electricity
consumption by sector. We specify N sectors and define all N − 1 sectors as non-residential sectors
and the Nth sector as the residential sector.
Denoting the growth rates of all variables with lower case letters, and after some operations, we
arrive at the following expression:
N −1
1 + ct =
∑
wi,t−1 (1 + yt )(1 + si,t )(1 + ii,t ) + wr,t−1 (1 + ht )(1 + i H,t )
(2)
i =1
where wi,t is the weight of sectorial electricity consumption in total electricity consumption.
Alternatively, this weight can be expressed as:
wi,t−1
C
= i,t−1 =
Ct−1
Ci,t−1
Yi,t−1
Ct−1 Yt−1
Yt−1 Yi,t−1
=
Ii,t−1 Yi,t−1
I
= i,t−1 Si,t−1
It−1 Yt−1
It−1
(3)
In a simplified framework where we only consider two sectors, a residential and a non-residential
sector, and where wnr,t denotes the weight of total non-residential electricity consumption, and Inr,t the
average intensity of electricity use across all non-residential sectors, we can rewrite Equation (2) as:
1 + ct = wnr,t−1 (1 + yt )(1 + inr,t ) + wr,t−1 (1 + ht )(1 + i H,t )
(4)
Finally, we can obtain the following expression:
ct = wnr,t−1 yt + wnr,t−1 inr,t + wr,t−1 ht + wr,t−1 i H,t + wr,t−1 i H,t ht + wnr,t−1 inr,t yt
(5)
where the growth rate of total electricity consumption is expressed as the sum of the weighted
contributions of the non-residential activity effect (wnr,t−1 yt ), the non-residential intensity effect
(wnr,t−1 inr,t ), changes in the number of households (wr,t−1 ht ) and the intensity of electricity use in
the residential sector wr,t−1 i H,t , plus a mixed effect either arising from residential or non-residential
consumption (wr,t−1 i H,t ht + wnr,t−1 inr,t yt ).
To analyze in more detail the evolutions of electricity consumption in various EU countries that
were presented in the previous section, we decompose the growth of total electricity consumption
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To analyze in more detail the evolutions of electricity consumption in various EU countries that
were presented in the previous section, we decompose the growth of total electricity consumption
demographic effects
effects (h
(htt), the effects of
following Equation (5). This way we can differentiate between demographic
changes in
in average
averageresidential
residentialelectricity
electricityconsumption
consumption
(iH,t
economic
growth
), and
intensity
changes
(iH,t
), ),economic
growth
(yt(y
), tand
thethe
intensity
of
of non-residential
electricity
consumption
(in,r,t
non-residential
electricity
consumption
(in,r,t
). ).
Figure 3 presents the absolute and relative contributions of each of these effects to the overall
electricity consumption
consumption during the period
period of
of analysis.
analysis. As can be observed, growth in
growth of electricity
activity effect.
effect. In other words, economic
economic growth
electricity demand has been mainly driven by the activity
main factor
factor boosting
boosting electricity
electricity consumption.
consumption. This factor alone can account for nearly
has been the main
observed average growth in
in electricity
electricity consumption
consumption in the
the combined
combined EU-15.
EU-15. Second, the
90% of the observed
evolution of the intensity of electricity consumption by households can explain 22% of the growth in
demand, and finally the demographic component (growth in the number of households) contributed
10%. In the Spanish case, electricity demand has been mainly driven by economic
on average around 10%.
due to
to increases
increases in
in non-residential
non-residential electricity
electricity intensity
growth (44%), while the remaining 56% are due
consumption per
per household
household (21%)
(21%) and
and demographic
demographic changes
changes (9%).
(9%).
(26%), average consumption
(a)
(b)
Figure 3. Break down of the consumption growth: (a) absolute effects (1990–2012); and (b) relative
Figure 3. Break down of the consumption growth: (a) absolute effects (1990–2012); and (b) relative
effects (1990–2012). Source: Own calculations with Eurostat data.
effects (1990–2012). Source: Own calculations with Eurostat data.
A remarkable finding is the negative contribution of the intensity of non-residential electricity
A remarkable
finding
is and
the negative
contribution
the
intensity
of non-residential
electricity
use for
the combined
EU-15
most other
countries. of
For
the
combined
EU-15 this effect
reduces
use
for
the
combined
EU-15
and
most
other
countries.
For
the
combined
EU-15
this
effect
reduces
electricity demand by an average 0.3% (absolute effect) and contributes with a negative 20% to
electricity
bydemand
an average
(absolute
effect)
contributes
with
a negative
20%
to growth
growth in demand
electricity
20%0.3%
(relative
effect).
Thisand
implies
that over
time
economic
activity
has
in
electricity
demand
20%
(relative
effect).
This
implies
that
over
time
economic
activity
has
required
required less electricity per unit of output. It is important to point out that this does not mean
that all
less
electricity
per unit
of become
output. It
is important
to point
out
this does not mean that all economic
economic
activities
have
more
efficient in
the use
ofthat
electricity.
activities
have
become
more
efficient
in
the
use
of
electricity.
In the case of Spain, however, non-residential intensity of electricity use contributes positively
In the case
of Spain, however,
non-residential
intensity
of electricity
use contributes
positively
to
to electricity
consumption.
Regarding
all other reported
effects
we estimate
higher absolute
values
electricity
consumption.
Regardingis all
reported
effects we estimate
values
for
for Spain. Particularly
remarkable
theother
case of
the demographic
effect, forhigher
whichabsolute
Spain ranks
fourth
Spain.
Particularly
remarkable
is
the
case
of
the
demographic
effect,
for
which
Spain
ranks
fourth
(see
(see Figure 4), only surpassed by Malta, Ireland, and Cyprus. The main differences between Spain
Figure
only surpassed
by Malta,
Ireland,
Cyprus.
Theofmain
differences
between
and
and the4),
average
EU-15 hence
are found
in theand
absolute
effects
the industrial
intensity
ofSpain
electricity
the
EU-15
hence are
found in terms
the absolute
effects of
the industrial
of electricity
use
use average
and GDP
growth.
In relative
(percentage
contribution
of intensity
each effect),
the largest
and
GDP
growth.
In
relative
terms
(percentage
contribution
of
each
effect),
the
largest
differences
are
differences are found in the effects of changes in non-residential intensity of electricity use.
foundReturning
in the effects
of changes(5),
in non-residential
electricity
use.
to Equation
we can easily intensity
derive aofsimilar
expression
for the elasticity of
Returning
to
Equation
(5),
we
can
easily
derive
a
similar
expression
for the
elasticity
electricity
electricity demand to GDP, which allows us to also decompose the observed
elasticity
in of
terms
of the
demand
to
GDP,
which
allows
us
to
also
decompose
the
observed
elasticity
in
terms
of
theobtain
same
same three factors used before. By simply dividing Equation (5) by the GDP growth rate we
three
factors used
before. By simply dividing Equation (5) by the GDP growth rate we obtain the
the following
expression:
following expression:
ε c , y ,t c=t
ε c,y,t =
in , r , t
iH , t
i , t ht
ct
h
= wnr ,t −1 + wnr ,t −1in,r,t
+ wr ,t −1ht t + wr , t −1 i H,t
+ wr , t −1 iHH,t
ht+ wnr , t −1inr ,t
=yt wnr,t−1 + wnr,t−1 yt + wr,t−1 yt + wr,t−1 yt + wr,t−1 yt + wnr,t−1 inr,t
(6)
(6)
yt
yt
yt
yt
yt
We can thus break down the income elasticity of electricity demand into the following effects:
We can thus break down the income elasticity of electricity demand into the following effects:
Energies 2017, 10, 347
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Energies 2017, 10, 347
8 of 21
•
••
•
•
•
•
Structure of the demand, i.e., weight of residential and non-residential demand (wn,r,t− 1 ).
Non-residential
intensityi.e.,
(wnr,t
non-residential
intensity relative
− 1nr,t )ofand
Structure of the demand,
weight
residential
and non-residential
demandto(wGDP
n,r,t−1). growth
(w
These effects
changes in the
intensity
of electricity
in
nr,t− 1 inr,t /yt ). intensity
Non-residential
(wnr,t−1nr,tcapture
) and non-residential
intensity
relative
to GDP use
growth
productive
activities.
(wnr,t−1inr,t/yt). These effects capture changes in the intensity of electricity use in productive
Demographic
growth (i.e., number of households) relative to GDP growth.(wr,t− 1 ht /yt ).
activities.
Demographic
growth
number
households)
relative
GDP
ht/yt).
Residential
intensity
of(i.e.,
electricity
useofrelative
to GDP
growthto(w
iH,t yt ), andr,t−1
residential
mixed
r,t− 1 growth.(w
Residential
intensity
electricity
relative
GDP growth
(wr,t−1iH,t
yt), andinresidential
mixed
effect
relative
to GDPofgrowth
(wr,tuse
ht /yt ).toThese
effects reflect
changes
the intensity
of
− 1 iH,t
effect relative
to households.
GDP growth (wr,t−1iH,tht/yt). These effects reflect changes in the intensity of
electricity
use by
electricity use by households.
(a)
(b)
(c)
(d)
Figure 4. Contribution to growth in consumption, by country: (a) residential: demographic effect; (b)
Figure 4. Contribution to growth in consumption, by country: (a) residential: demographic
residential:
average consumption
effect; (c)
non-residential:
economic
growth
effect;effect;
(d)
effect;
(b) residential:
average consumption
effect;
(c) non-residential:
economic
growth
non-residential:
intensity
effect.
Source:
Own
calculations
with
Eurostat
data.
(d) non-residential: intensity effect. Source: Own calculations with Eurostat data.
Figure 5 displays averages of each of these effects for 1990–2012 for all European countries.
None of the effects alone can explain the higher elasticity of electricity demand in Spain; their
combination accounts for the observed differences. All countries seem to share a similar structure
regarding the contribution of the above-mentioned effects to demand elasticity. In particular, the
Energies 2017, 10, 347
9 of 20
Figure 5 displays averages of each of these effects for 1990–2012 for all European countries. None
of the effects alone can explain the higher elasticity of electricity demand in Spain; their combination
accounts for the observed differences. All countries seem to share a similar structure regarding
Energies 2017, 10, 347
9 of 21
the contribution of the above-mentioned effects to demand elasticity. In particular, the structure
Energies 2017, 10, 347
9 of 21
ofstructure
electricity
the share
of residential
and non-residential
consumption,
as well
as the
of demand,
electricityi.e.,
demand,
i.e., the
share of residential
and non-residential
consumption,
as well
intensity
of electricity
use in the
sector sector
seem to
matter
most most
for demand
elasticities.
as
the intensity
of electricity
useresidential
in the
seem
matter
for
demand
elasticities.
structure
of electricity
demand,
i.e.,
theresidential
share of residential
andtonon-residential
consumption,
as well
as the intensity of electricity use in the residential sector seem to matter most for demand elasticities.
Figure 5. Average decomposition of Elasticity Demand to GDP. Source: Own calculations with
Figure 5. Average decomposition of Elasticity Demand to GDP. Source: Own calculations with
Eurostat
Figure 5.data.
Average decomposition of Elasticity Demand to GDP. Source: Own calculations with
Eurostat data.
Eurostat data.
Figure 6 displays the income elasticity of electricity consumption as a function of the intensities
Figure
6 displays
the
income
of
consumption
function
the
intensities
of electricity
in the
residential
and non-residential
The observed
differences
in
electricity
Figure
6use
displays
the
incomeelasticity
elasticity
of electricity
electricitysector.
consumption
asasaafunction
ofof
the
intensities
ofdemand
electricity
use
ininthe
and
sector. The
The
observed
differences
electricity
of
electricity
use
theresidential
residential
andnon-residential
non-residential
sector.
in
electricity
elasticity
seem
to be mainly
driven by differences
inobserved
relative differences
intensities,
inin
both
the
demand
elasticity
seem
to betomainly
driven
by differences
in relative
intensities,
inrole,
bothand
theboth
residential
demand
elasticity
seem
besectors.
mainly
driven
by differences
relative
intensities,
in
the
residential
and non-residential
Demographic
effects
onlyinplay
a marginal
there
are
and
non-residential
sectors.
Demographic
effects
only
play
a
marginal
role,
and
there
are
no
substantial
residential
anddifferences
non-residential
sectors.
Demographic
effects
only play aofmarginal
role, and
there are
no
substantial
between
countries
regarding
the importance
the remaining
factors.
differences
between
countries
regarding
the importance
of the
remaining
factors.
no substantial
differences
between
countries
regarding the
importance
of the
remaining factors.
Figure 6. Income elasticity of electricity consumption versus intensities. Source: Own calculations
Figure
6. Income
elasticity
of electricity
consumption
versus
intensities.
Source:
Own
calculations
with
Eurostat
data.
Figure
6. Income
elasticity
of electricity
consumption
versus
intensities.
Source:
Own
calculations
with
with Eurostat data.
Eurostat data.
4. Long Term Evolution of Electricity Intensities in European Countries
4. Long Term Evolution of Electricity Intensities in European Countries
The previous section showed that most observed differences in aggregate electricity demand
The previous
section showed
that most
observedstructures
differences
in aggregate
electricity
demand
elasticities
can be explained
by differences
in sectorial
(residential
versus
non-residential)
elasticities
can be explained
by differences
in sectorial
structures
(residential
non-residential)
and/or
by differences
in the intensities
of electricity
use;
i.e., the same
sector versus
might use
more or less
and/or by differences in the intensities of electricity use; i.e., the same sector might use more or less
Energies 2017, 10, 347
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4. Long Term Evolution of Electricity Intensities in European Countries
electricity to produce the same amount of output. In this section we will analyze both
The previous section
showed
most observed
aggregate
demand
factors—sectorial
composition
andthat
intensity
of use by differences
sectors—in in
order
to gain electricity
more insight
into
elasticities
can
be
explained
by
differences
in
sectorial
structures
(residential
versus
non-residential)
observed differences in electricity demand elasticities across countries as well as over time.
and/orTaking
by differences
in the
intensities
ofthe
electricity
i.e., the same
use moresector
or less
into account
that
growth in
intensityuse;
of electricity
use sector
by the might
non-residential
electricity
produce the same
of output. In this
section of
we will
both factors—sectorial
can be toapproximated
by amount
a weightedaverage
growth
all analyze
industry-specific
intensities,
compositionCand
intensity of use by sectors—in order to gain more insight into observed differences in
i , t −1
'
=
w
can writeas
the
following
for changes in the intensity
w'i ,t −1 =across
1 , wecountries
i
,
t
−
1
electricity demand, elasticities
well
as overexpression
time.
Cn, r ,t −1 i
Taking into account that growth in the intensity of electricity use by the non-residential sector can
of electricity use by the non-residential sector:
C
be approximated by a weightedaverage growth of all industry-specific intensities, w0i,t−1 = C i,t−1 ,
n,r,t−1
M
changes in the intensity of electricity use by
∑ w0i,t−1 = 1, we can write the followingM expression for
inr ,t ≈ ii ,t w'i ,t −1 + yi ,t w'i ,t −1 − yt
(7)
i
the non-residential sector:
i =1
i =1



M
M
i =1
i =1
≈changes
Equation (7) uses the factinr,t
that
use by the non-residential(7)
i,t−the
1 +intensity
i,t−electricity
1 − yt
∑ ii,t w0in
∑ yi,t w0of
C
Y
S ,t
sector
can be
as changes
in sector
specific
intensities
( I s ,t =
), changes
in the
Equation
(7)expressed
uses the fact
that changes
in the
intensity
of electricity
use by the
non-residential
C
S ,t
sector can be expressed as changes in sector specific intensities (Is,t = YS,t ), changes in the structure of
S,t
structure of electricity consumption, ( w'i ,t −1 ), and changes in sectorial activity,
( Yi ,t ).
electricity consumption, (w0i,t−1 ), and changes
in sectorial activity, (Yi,t ).
order
analyze
structure
electricity
consumption
industrial
sector
and
over
time,
In In
order
to to
analyze
thethe
structure
of of
electricity
consumption
byby
industrial
sector
and
over
time,
we
we
calculate
the
share
of
each
sector’s
electricity
consumption
over
total
consumption
for
all
calculate the share of each sector’s electricity consumption over total consumption for all countries
countries
and years available:
and
years available:
Consumptioni,t,
wi,t ,=
= w′0i,t, wn,r,t
(8)(8)
, ,
∑∑i Consumptioni,t,
Figure
7 depicts
and detailed
detailedindustrial
industrialactivities
activities
Figure
7 depictsthe
theabove
aboveshares
sharesfor
forbasic
basicsectors
sectors (Figure
(Figure 7a)
7a) and
(Figure
7b)
for
Spain
and
the
averages
of
EU-28
and
EU-15.
In
order
to
also
include
information
(Figure 7b) for Spain and the averages of EU-28 and EU-15. In order to also include information onon
other
European
countries,
and third
thirdquartile
quartileofofthe
therespective
respective
other
European
countries,we
wemark
markthe
therange
rangebetween
between the
the second
second and
values
byby
blue
bands.
values
blue
bands.
Sectors
(a) Residential
(b) Agriculture/Forestry
(c) Total Industry
(d) Construction
Figure 7. Cont.
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11 of 21
(e) Services
(f) Transport
Breakdown of industrial activities
(g) Iron and Steel
(h) Non-Ferrous Metals
(i) Mining and Quarrying
(j) Non-Metallic Minerals
(k) Chemical and Petrochemical
(l) Paper, Pulp and Print
(m) Food and Tobacco
(n) Textile and Leather
Figure 7. Cont.
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(o) Transport Equipment
(p) Machinery
(q) Wood and Wood Products
(r) Non-specified (Industry)
Electricity structure
GVA structure
(s) EU-28. Shares on electricity industrial demand versus Shares on Industrial GVA (2000-2012 average)
Electricity structure
GVA structure
(t) Spain. Shares on electricity industrial demand versus. Shares on Industrial GVA (2000–2012 average)
Figure 7. Shares on total final consumption of electricity. Source: Own calculation with Eurostat’s data.
Figure 7. Shares on total final consumption of electricity. Source: Own calculation with Eurostat’s data.
The graphs in Figure 7 show that, in general, the structure of electricity consumption in Spain is
quite similar to the EU-28 and EU-15 averages. However, there are some specific sectors where we
observe clear differences between Spain and the EU averages, both in the level of shares, as well as in
Energies 2017, 10, 347
13 of 20
The graphs in Figure 7 show that, in general, the structure of electricity consumption in Spain
is quite similar to the EU-28 and EU-15 averages. However, there are some specific sectors where
we observe clear differences between Spain and the EU averages, both in the level of shares, as well
as in their trends over time. The main aspect to be highlighted is the fact that in Spain, for more
recent data, we observe a larger share of electricity consumption in the construction, service, and the
residential sectors. Industrial activities, on the other hand, represent a lower fraction in total electricity
consumption compared to other EU countries. Going back to the mid-1990s, the situation in Spain was
exactly the opposite, with consumption shares in residential and service sectors in the lower range and
the share in industrial activities located in the upper range. In addition to these features for Spain, the
data show a remarkable decreasing trend in all EU countries in relative electricity consumption by
industrial activities and by the transportation sector. On the other hand, we observe increasing shares
in the service sector and almost constant shares in agriculture, construction, and the residential sector.
For the residential sector in Spain, we observe an increase in the share of electricity consumption
that is substantially higher compared to other EU countries. While in the early 1990s, values registered
for residential electricity consumption in Spain were found in the second quartile, in recent years
Spanish residential electricity consumption has exceeded the mean and has approached the third
quartile. The rapid increase in per capita income during the period of analysis together with the
specific usages of electricity by Spanish households (cooling and heating equipment) can explain this
increase in electricity intensity in the Spanish residential sector.
Regarding non-residential electricity use, until 2010, the agricultural share in electricity
consumption in Spain was nearly 2% above the EU-15 average. This was due to the larger presence of
the primary sector in Spain’s productive structure. Similarly, the Spanish construction sector, even
though its share in total electricity consumption is relatively low, triples the EU-15 average given the
importance of construction for the Spanish economy during the period of analysis.
Electricity consumption by the Spanish service sector is characterized by a development similar
to that of the residential sector, with recent increases in shares above the EU-15 average. In the case of
the Spanish transportation sector, although we do observe a trend similar to that of most countries,
its absolute share in electricity consumption is substantially lower than the EU-average, especially in
recent periods. These lower levels can be explained by the relatively low share of rail freight transport
compared to road freight transport in Spain. Finally, for all industrial activities, the decreasing trend
shared by all countries is characterized by a steeper slope in Spain. In particular, relative electricity
consumption by Spanish industrial activities decreased from the third quartile in the early nineties
to the second quartile in recent years. The evolution of the productive structure and in particular
the progressive loss of industrial activities experienced by the Spanish economy can explain this
last observation.
Regarding specific industrial activities, the most basic industries such as steel and metallurgy have
a significantly higher share—above the third quartile—in electricity consumption in Spain compared to
other EU countries. This is because Spanish firms use production technologies that are more electricity
intensive compared to firms in other countries. On the other hand, we observe a reduction over time
in relative electricity consumption by machinery and equipment in Spain, while the shares for the EU
averages remain stable or even show a slightly increasing trend. It is most likely that differences in
technologies leading to differences in the intensity of electricity use in these specific industries are
responsible for this trend.
In order to provide a better understanding of how differences in the intensity of electricity use
affect electricity demand elasticities we complement our analysis by looking at sectorial intensities
(I i s,t =
Ci S,t
).
Y i S,t
These intensities are defined as the ratio of sectorial electricity consumption, Cs,t , and
sectorial production, Ys,t , measured in terms of gross value added. We obtain our measure by dividing
electricity consumption by the total value added of each industry, measured in millions of Euros [20].
These intensities indicate how much electricity is needed in order to produce one unit of output.
In the case of the residential sector intensities are calculated as the ratio of electricity consumption to
Energies 2017, 10, 347
14 of 20
population instead of production. We use average per capita consumption instead of consumption per
household
years
Energies 2017, because
10, 347 data on the number of households in each EU country are not available for14
of 21
before 2006.
displays the
the evolution
evolution of
of total
total electricity
electricity intensity
intensity (total
(total electricity
electricity consumption
consumption in
Figure 8 displays
GWh/volume ofofGVA)
with
thethe
average
forfor
thethe
EU-15
andand
EU-28
(lines).
We
GWh/volume
GVA)ininSpain
Spain(bars)
(bars)together
together
with
average
EU-15
EU-28
(lines).
alsoalso
display
thethe
same
data
separately
forforthe
We
display
same
data
separately
theresidential
residentialand
andnon-residential
non-residential sector.
sector. Over
Over time,
converged towards
towards the
the EU
EU average.
average. This convergence is driven
Spanish total electricity intensity has converged
by a reduction in the non-residential intensity of electricity use and by a large increase in residential
per capita
capita electricity
electricity consumption.
consumption.
per
(a) Total. GWh/Million € GVA (2005)
(b) Non Residential. GWh/Million € GVA (2005)
(c) Residential per Capita. GWh/1000 p
Figure 8. Intensity of electricity use (GWh/GVA and GWh per capita), 1990–2012. Source: Own
Figure 8. Intensity of electricity use (GWh/GVA and GWh per capita), 1990–2012. Source: Own
calculation with Eurostat’s data.
calculation with Eurostat’s data.
Looking at the intensities by broad sectors (see Figure 9), we observe a higher relative intensity
Looking
at the
broadinsectors
9),likely
we observe
a higher
relative
intensity
of electricity use
byintensities
the servicebysector
Spain.(see
ThisFigure
is most
because
tourism,
a sector
that is
of
electricity
use
by
the
service
sector
in
Spain.
This
is
most
likely
because
tourism,
a
sector
thathas
is
more intensive in electricity demand (heating and cooling equipment in hotels and restaurants),
more
intensive
in weight
electricity
demand GDP.
(heating
cooling
equipment
hotels andbefore,
restaurants),
has
a relatively
large
in Spanish
In aand
similar
manner
and asinmentioned
the lower
aintensity
relatively
large
weight
in
Spanish
GDP.
In
a
similar
manner
and
as
mentioned
before,
the
lower
of electricity use in the transportation sector is linked to the lower relative share of rail
intensity
of electricity
use inRegarding
the transportation
sector
is linkedactivities,
to the lower
share
of rail freight
freight transport
in Spain.
aggregate
industrial
the relative
intensity
of electricity
use
transport
in
Spain.
Regarding
aggregate
industrial
activities,
the
intensity
of
electricity
use
seems
seems to be converging to EU standards. In Figure 10 we display intensities of electricity use for
to
be converging
to activities
EU standards.
Figure
10 we
display intensities
of electricity
use for between
detailed
detailed
industrial
(TableInA2
of the
Appendix
A shows the
correspondence
industrial
activities
(Table
A2
of
the
Appendix
A
shows
the
correspondence
between
sectors
sectors and statistical classifications of economic activities NACE 2009 codes). Most noteworthyand
are
statistical
classifications
of
economic
activities
NACE
2009
codes).
Most
noteworthy
are
the
differences
the differences in intensities of electricity use between Spain and the EU averages for “Mining and
in
intensities of
electricity
use between
Spainand
and“Paper,
the EU Pulp
averages
“Mining
and Quarrying”,
Quarrying”,
“Wood
and Wood
Products”
andfor
Print”,
but these
last results “Wood
are not
and
Wood
Products”
and
“Paper,
Pulp
and
Print”,
but
these
last
results
are
not
directly
comparable
directly comparable due to discrepancies across countries regarding the sectoral allocation of the
due
to pulps.
discrepancies across countries regarding the sectoral allocation of the paper pulps.
paper
Energies 2017, 10, 347
15 of 20
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15 of 21
15 of 21
(b) Construction
(b) Construction
(a) Industry
(a) Industry
(c) Services
(d) Transport
(c) Services
(d) Transport
Figure 9. Sectorial
intensity. Measured in GWh/million € GVA (2005). Source:
Own calculations with
Figure
9.
Sectorial
intensity.
Measured
in
GWh/million
€
GVA
(2005).
Source: Own calculations with
Eurostat
data. intensity. Measured in GWh/million € GVA (2005). Source:
Figure
9. Sectorial
Own calculations with
Eurostat
data.
Eurostat data.
(a) Iron and Steel & Non-Ferrous Metals
(a) Iron and Steel & Non-Ferrous Metals
(c) Chemical and Petrochemical
(b) Non-Metallic Minerals
(b) Non-Metallic Minerals
(d) Mining and Quarrying
(c) Chemical and Petrochemical
(d) Mining and Quarrying
(e) Food and Tobacco
(f) Textile and Leather
(e) Food and Tobacco
(f) Textile and Leather
Figure 10. Cont.
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16 of 20
16 of 21
(g) Paper, Pulp and Print
(h) Wood and Wood Products
(i) Transport Equipment
(j) Machinery
Figure 10. Industrial activities intensity. Measured in GWh/million € GVA (2005). Source: Own
Figure 10. Industrial activities intensity. Measured in GWh/million € GVA (2005). Source: Own
calculations with Eurostat data.
calculations with Eurostat data.
Table 1 presents the relative intensities of electricity use for different industrial activities for the
Table 1period
presents
the relative
intensities
electricity
use for different
industrial
activities
the
most recent
(2010–2012
averages),
as of
well
as the variation
in intensities
observed
overforthe
most
recent
period
(2010–2012
averages),
as
well
as
the
variation
in
intensities
observed
over
the
entire
entire period (1996–2012). For a quick visual overview, in columns 5–8 we display bars indicating
period
For a reported
quick visual
overview,1–4.
in columns
we columns
display bars
indicating
the size
the
size (1996–2012).
of the intensities
in columns
The last5–8
three
specify
if variations
of
the
intensities
reported
in
columns
1–4.
The
last
three
columns
specify
if
variations
reported
in
reported in columns 9–11 are positive (black bars) or negative (red bars).
columns
9–11
are
positive
(black
bars)
or
negative
(red
bars).
Noteworthy are the high intensity of electricity use in the Spanish basic metals sector, more
Energies
2017, 10, 347 As mentioned before, Spanish firms use production technologies
17 of 21
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17 of 21
than 90% above
the
EU-15
Table
1.
Industry
electricity intensities. Spain and the European Union. 17
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17
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21
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347compared to firms in other countries. The intensity of
17 of
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21
that are more
electricity
electricity
Energies
2017, 10,
10,
347intensive
17 of
of
21
Energies
2017,
347
17
Table
1. Industry
specific
electricity
intensities.
and the
European Union.
Table2017,
1. Industry
specific
electricity
intensities.
Spain
and theSpain
European
Union.
Energies
10, 347
17 of 21
Energies 2017, 10,
347
17 of 21
use in the Spanish
primary
sector
is1.
more
than
double
theand
average
EU-15
intensity.
Table
1. Industry
Industry
specific
electricity
intensities.
Spain
and
the
European
Union.This last
Table 1.
1. Industry
Industry
specific
electricity
intensities.
Spain
and
theSpain
European
Union.
Table
specific
electricity
intensities.
and
European
Union.
Table
specific
electricity
intensities.
Spain
European
Union.
Item
2010–2012
2012/1996
Table
specific
electricity
intensities.
Spain
and
the
European
Union.
Table
1. Industry
Industry
specific
electricity
intensities.
Spain
and the
the
European
Union.
Table 1.
1. Industry
Industry
specific
electricity
intensities.
Spain
and the
theSpain
European
Union.
2010-2012
2012/1996
2010-2012
2012/1996
Table
1.
specific
electricity
intensities.
and
the
European
Union.
observation
is
likely
due
to
Spain’s
relatively
warm
climate
requiring
an
increased
use
of
electricity
Table
1.
Industry
specific
electricity
intensities.
Spain
and
the
European
Table
1.
Industry
specific
electricity
intensities.
Spain
and
the
European
Union.
2010-2012
2012/1996
ΔEU-15
ΔSpain
Δ
Sectors
(GWh
/
Million
€
GVA)
EU-28
EU-15
EA
Spain
EU-28
ΔEU-15
ΔSpain
Δ
Sectors
(GWh
/
Million
€
GVA)
EU-28
EU-15
EA
Spain
EU-28
2010-2012
2012/1996
Sectors (GWh/Million € GVA)
EU-28 EU-15
EA2010-2012
Spain 2010-2012
∆ EU-28 2012/1996
∆ EU-15 Union.
∆2012/1996
Spain
2010-2012
2012/1996
2010-2012
2012/1996
2010-2012
2012/1996
2010-2012
2012/1996
ΔEU-15
ΔSpain
Δ ΔSpain
Sectors
(GWh
Million
GVA)
EU-28
EU-15
EA
Spain
EU-28
TOTAL €
0.222
0.210
0.216
0.233Δ
−3.4
−1.9
ΔEU-15
ΔSpain
Δ EU-28
TOTAL
0.222
0.210
0.216EU-15
0.233in
−3.4
−1.9Δ
−1.7
Sectors
(GWh
Million
GVA)
EU-28
EU-15
EA
Spain
EU-28
TOTAL
0.222 €€€observed
0.210EU-15
0.216
0.233
−
3.4
−
1.9
−
1.7 −1.7
ΔEU-15
ΔSpain
Sectors
/// Million
GVA)
EU-28
EA
Spain
EU-28
ΔEU-15
Δ
Sectors
(GWh
// Million
Million
€€(GWh
GVA)
EU-28
EU-15
EA
Spain
EU-28
for irrigation.
As
mentioned
before,
differences
the
wood
and
furniture
sectors
ΔEU-15
ΔSpain
Sectors
(GWh
/
GVA)
EU-28
EA
Spain
ΔEU-15
ΔSpain
Δ
Sectors
(GWh
Million
GVA)
EU-28
EU-15
EA
Spain
EU-28
2012/1996may be
ΔSpain ΔEU-15
Δ EU-28 ΔEU-15
2010-2012
2012/1996
Sectors (GWh / Million
GVA)/ Million €EU-28
EU-15 EU-28
EA EU-15
Spain 2010-2012
Sectors €(GWh
GVA)
Spain
TOTAL
0.222
0.210
0.216
0.233 −3.4
−3.4
−1.9 ΔSpain
−1.7
NoEA
residential
No0.216
residential
TOTAL
0.222
0.210 0.222
0.216
0.233
−3.4
−1.9Δ EU-28
−1.7 −1.9
TOTAL
0.210
0.216
0.233
−3.4
−1.7
TOTAL
0.222
0.210
0.233
−1.9
−1.7
TOTAL
0.222
0.210
0.216
0.233
−3.4
−1.9
−1.7
TOTAL €(GWh
0.222
0.210
0.216 Spain
0.233Δ EU-28
−3.4
−1.9 ΔSpain
−1.7
ΔEU-15
Δ
Sectors
/
Million
€
GVA)
EU-28
EU-15
EA
EU-28
No
residential
ΔEU-15
ΔSpain
Sectors
(GWh
/
Million
GVA)
EU-28
EU-15
EA
Spain
TOTAL
0.222
0.210
0.216
0.233
−3.4
−1.9
−1.7
TOTAL
0.222
0.210
0.216
0.233
−3.4
−1.9
−1.7
due to discrepancies
countries
regarding
the
sectoral
allocation
some
activities
such as
No0.826
residential
Iron
and Steel
& Non-Ferrous
Metals0.767 0.819
0.767
1.477 −2.0 of −0.8
−2.00.1
−0.8
0.1
Iron and Steel &across
Non-Ferrous
Metals
0.819
1.477
No0.826
residential
No
residential
No
residential
No
residential
No0.216
residential
TOTAL
0.210
0.233 −3.4
−1.7
TOTAL
0.222
0.210 0.222
0.233
−1.9 −3.4
−1.7 −1.9
No0.216
residential
No
residential
Iron
and Steel
Steel
& Non-Ferrous
Non-Ferrous
Metals0.767
0.819
0.767
0.826
1.477
−2.0
−0.8
0.1
Chemical
and
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3
Chemical
and
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3
Iron
and
Steel
&
Non-Ferrous
Metals
0.819
0.826
1.477
−2.0
−0.8
0.1
Iron
and
Steel
&
Non-Ferrous
Metals
0.819
0.767
0.826
1.477
−
2.0
−
0.8
0.1
Iron
and
&
Metals
0.819
0.767
0.826
1.477
−2.0
−0.8
0.1
and
&
Non-Ferrous
Metals
0.819
1.477
−0.8
industries ofIron
paper
pulp
and
celluloses.
Iron
and Steel
Steel
& Non-Ferrous
Non-Ferrous
Metals0.767
0.819
0.767
0.826
1.477 −2.0
−2.00.1
−0.8
0.1
No0.826
residential
Iron
and
&
Metals
0.819
0.767
1.477
−2.0
−0.8
0.1
No0.826
residential
Iron
and Steel
Steel
&Chemical
Non-Ferrous
Metals
0.819
0.767
0.826
1.477
−2.0
−0.8
0.1
and Minerals
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3
Non-Metallic
0.478
0.451
0.464
0.562 −2.5
−2.2
−1.50.3 −0.4
Non-Metallic
0.478
0.451
0.4640.552
0.562 0.849
−2.2
−1.5 −−2.5
−0.4
Chemical
and Minerals
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3 −1.7
ChemicalChemical
and Petrochemical
0.854 0.854
0.816 0.816
0.849
−2.5 −1.7
1.7
Chemical
and
Petrochemical
0.854
0.816
0.552
0.3
and
Petrochemical
0.849
0.552
0.3
Chemical
and
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3
and Steel
& Non-Ferrous
Metals0.767
0.819
0.826
1.477
−2.0
0.1
Iron
and
Steel
&Iron
Non-Ferrous
Metals
0.819
0.826
1.477
−2.0
−0.8
0.1
Chemical
and
Petrochemical
0.854
0.816
0.849 0.767
0.552 to
−2.5
−1.7 such
0.3 −0.8
Chemical
and
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3
Regarding
the
dynamics
of
intensities,
it
is
interesting
note0.562
how−2.2
sectors
basic
metals,
Non-Metallic
Minerals
0.478
0.451
0.464
0.562
−2.2
−1.5
−0.4
Non-Metallic
Minerals
0.478
0.451
0.4640.562
0.562 0.464
−2.2
−1.5
−0.4
Mining and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2 −−2.2
1.9 as
Non-Metallic
Minerals
0.478
0.451
0.464
−
2.2
1.5
−
0.4
Non-Metallic
Minerals
0.478
0.451
−1.5
−0.4
Non-Metallic
Minerals
0.478
0.451
0.464
0.562
−2.2
−1.5
−0.4
Non-Metallic
Minerals
0.478
0.451
0.464
0.562
−1.5
−0.4
Non-Metallic
Minerals
0.478
0.451
0.464
0.562
−2.2
−1.5
−0.4
Chemical
and Minerals
Petrochemical
0.854
0.816
0.849
0.552
−2.5
0.3
Chemical
and Minerals
Petrochemical
0.854
0.816
0.849
0.552
−2.5
−1.7
0.3 −1.7
Non-Metallic
0.478
0.451
0.464
0.562
−2.2
−1.5
−0.4
Non-Metallic
0.478
0.451
0.464
0.562
−2.2
−1.5
−0.4
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Food
and
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5
1.1
Food
and
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5
1.1
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
0.239
0.203
0.306
0.626
2.8
4.2
1.9
and chemicals
display
increasing
intensities
of electricity
while
average
the EU
Mining
and Quarrying
Quarrying
0.239
0.203
0.306in Spain
0.626 −2.2
2.8
4.2 for
1.9
Non-Metallic
Minerals
0.478
0.464
0.562
−0.4
Non-Metallic
Minerals
0.478
0.451
0.464
0.562
−1.5
−0.4
Mining
and Quarrying
Quarrying
0.239
0.203
0.306 0.451
0.626use
2.8
4.2on −2.2
1.9 −1.5
Mining
and
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Food
and
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5
1.1
Textile
and
Leather
0.360
0.347
0.329
0.385
−2.0
−0.7
Textile
and
Leather
0.360
0.347
0.329
0.385
−0.7
Food
and
Tobacco
0.519
0.510
0.5440.426
0.426 0.544
1.0
0.5 0.5
1.1 −2.7
Food
Tobacco
0.519
0.510
0.426
1.0
0.5
Food
and
Tobacco
0.544
0.426
1.0
0.5
1.1
Food
and
Tobacco
0.519 0.519
0.510 0.510
0.544
1.0 −2.7
Food
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5
1.1
Food and
and
Tobacco
0.519
0.510
0.544
0.426 −2.0
1.0
0.51.1 1.1
1.1
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Mining
and
Quarrying
0.239
0.203
0.306
0.626
2.8
4.2
1.9
Food and
and
Tobacco
0.519
0.510 0.360
0.544 0.347
0.426 0.329
1.0
0.5 −2.0
1.1 −2.7
Food
and
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5
1.1
Textile
and
Leather
0.385
−0.7
Paper,
Pulp
and
Print
1.537
1.560
1.393
0.974
−0.6
1.6
2.7
Paper,
Pulp
and
Print
1.537
1.560
1.393
0.974
−0.6
1.6
2.7
Textile
and
Leather
0.360
0.347
0.329
0.385
−2.0
−2.7
−0.7
they showTextile
downward
trends.
On
the
other
hand,
agriculture
in
Spain
has
shown
a
declining
trend
in
Textile
and
Leather
0.360
0.347
0.329
0.385
−2.0
−2.7
−0.7
Textile
and
Leather
0.360
0.347
0.329
0.385
−2.0
−2.7
−0.7
and
Leather
0.360 0.360
0.347 0.347
0.329
0.385
−
2.0 −2.7
2.7
−0.7 −0.7
Textile
and
Leather
0.329
0.385
−0.7
Textile
and
Leather
0.360
0.347
0.329
0.385 −2.0
−2.0
−2.7
−0.7
Food
and
Tobacco
0.426
1.0
0.5
1.1
Textile
and
Leather
0.360
0.347
0.329
0.385
Food
and
Tobacco
0.519
0.510
0.544
0.426
1.0
0.5 −−2.0
1.1 −2.7
Textile
and
Leather
0.360
0.347 0.519
0.329 0.510
0.385 0.544
−2.0
−2.7
−0.7
Paper,
Pulp
and Print
Print
1.537
1.560
1.393
0.974
−0.6
1.62.7 −0.02
2.7
Transport
Equipment
0.265
0.259
0.266
0.204 −0.6
−0.3
Transport
Equipment
0.265
0.259
0.2660.974
0.204 1.393
−0.3
−2.4
−0.02
Paper,
Pulp
and
Print Pulp
1.537
1.560
1.393
0.974
−0.6
1.6 1.6
2.7 −2.4
Paper,
and
1.537
1.560
0.974
−0.6
1.6
2.7
PulpPulp
and
Print
1.537intensity
1.560 1.560
1.393
−0.6over
Paper,
and
Print
1.537
1.393
0.974
1.6
2.7
Paper,
Pulp
and Print
Print
1.537
1.560
1.393 has
0.974 risen
−0.6
1.6
2.7
Textile
and Leather
0.360
0.347
0.329
0.385
−2.0
−0.7
Textile
and
Leather
0.360
0.347
0.329EU
0.385
−2.0
−2.7
−0.7
Paper,
Pulp
and
Print while
1.537
1.560
1.393
0.974
−0.6
1.6 time.
2.7 −2.7
Paper,
Pulp
and
1.537
1.560
1.393
0.974
−0.6
1.6
2.7
intensityPaper,
of electricity
use
the
for
the
average
Transport
Equipment
0.265
0.259
0.266
0.204
−0.3
−2.4
−0.02
MachineryEquipment
0.327
0.318
0.316
0.304 −2.4
−2.4
0.8
−0.9
Machinery
0.327
0.318
0.316
0.304
0.8 −0.3
−0.9 −2.4
Transport Equipment
0.265
0.259 0.265
0.266 0.259
0.204 0.266
−0.3
−2.4
−0.02
Transport
0.204
−0.02
Transport
Equipment
0.265
0.259
0.266
0.204
Transport
Equipment
0.265
0.259
0.2660.204
0.204 1.393
Transport
Equipment
0.265 0.265
0.259 0.259
0.266
Transport
Equipment
0.266
0.204
Transport
Equipment
0.265
0.259
0.204
and Print
1.537
0.974
Paper,
Pulp
and Paper,
Print Pulp
1.537
1.560
1.393
0.974
Transport
Equipment
0.265
0.259
0.266 1.560
0.204 0.266
Transport
0.265
0.259
0.266
0.204
Machinery
0.327
0.318
0.316
0.304
Wood
andEquipment
Wood 0.327
Products 0.327
0.621
0.597
0.630
2.988
Wood
and WoodMachinery
Products
0.621
0.597
0.630
2.988
Machinery
0.327
0.318
0.3160.304
0.304 0.316
0.327
0.318
0.304
Machinery
0.327
0.318
0.316
0.304
Machinery
0.318 0.318
0.316
Machinery
0.316
0.304
Machinery
0.327
0.318
0.316
0.304
Transport
Equipment
0.265
0.259
0.266
0.204
Transport
0.265
0.259
0.266
0.204
MachineryEquipment
0.327
0.318
0.316
0.304
Machinery
0.327
0.318
0.316
0.304
Wood
and Wood
Wood Products
Products 0.621
0.621
0.597
0.630
2.988
Construction
0.027
0.024
0.024
0.032
Construction
0.027
0.024
0.024
0.032
Wood
and Wood
Wood
Products
0.621
0.597
0.630 0.597
2.988 0.630
Wood
and
0.621
2.988
Wood
and
Products
0.630
2.988
Wood and
Wood
Products
0.597 0.597
0.630
Wood
and
Products
0.597
0.630
2.988
Wood
and Wood
Wood 0.621
Products 0.621
0.621
0.597
0.630
2.988
Machinery
0.327
0.318
0.304
Machinery
0.327
0.318
0.316
0.304
Wood
and Wood
Wood
Products
0.621
0.597
0.6302.988
2.988 0.316
Wood
and
Products
0.621
0.597
0.630
2.988
Construction
0.027
0.024
0.024
0.032
Non-specified (Industry) 0.027
0.344
0.338
0.298
0.202
Non-specified
0.344
0.338
0.298
0.202
Construction (Industry)
0.027
0.024 0.027
0.024 0.024
0.032 0.024
Construction
0.032
Construction
0.024
0.032
Construction
0.024
0.024
0.032
Construction
0.027
0.024
0.024
0.032
Construction
0.024 0.024
0.024
0.032
and Wood 0.027
Products 0.027
0.621
0.597
0.630
2.988
Wood
and WoodWood
Products
0.621
0.597
0.630
2.988
Construction
0.027
0.024
0.024
0.032
Construction
0.027
0.024
0.024
0.032
Non-specified
(Industry) 0.344
0.344
0.338
0.298
0.202
Transport
0.129
0.120
0.133
0.108
Transport
0.129
0.120 0.344
0.133 0.338
0.108 0.298
Non-specified
(Industry)
0.338
0.298
0.202
Non-specified
(Industry)
0.202
Non-specified
(Industry)
0.298
0.202
Non-specified
(Industry)
0.344
0.338
0.298
0.202
Non-specified
(Industry)
0.344 0.344
0.338 0.338
0.298
Construction
0.027
0.024
0.032
Non-specified
(Industry)
0.344
0.338
0.298
0.202
Construction
0.027
0.024
0.024
0.032 0.024
Non-specified
(Industry)
0.344
0.338
0.2980.202
0.202
Transport
0.129
0.120
0.133
0.108
Fishing
0.048
0.044
0.054
Fishing
0.048
0.044 0.129
0.054 0.120
Transport
0.129
0.120
0.133
0.108 0.133
Transport
0.108
Transport
0.129
0.120
0.133
0.108
Transport
0.129
0.120
0.133
0.108
Transport
0.129
0.120
0.133
0.108
Non-specified
(Industry)
0.344
0.338
0.298
0.202
Non-specified
(Industry)
0.344
0.338
0.298
0.202
Transport
0.129
0.120 0.048
0.133 0.044
0.108 0.054
Transport
0.129
0.120
0.133
0.108
Fishing
Fishing
0.048
0.044 0.048
0.054 0.044
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777 0.054
Fishing
Fishing
0.048
0.044
0.054
Fishing
0.054
Fishing
0.048
0.044
0.054
Transport
0.129
0.108
Fishing
0.048 0.048
0.044 0.044
0.054
Transport
0.129
0.120
0.133
0.108 0.133
Fishing
0.048
0.044
0.054 0.120
Fishing
0.048
0.044
0.054
Agriculture/Forestry
0.218
0.233
0.208
0.777
Services
0.117
0.108
0.116
0.145
Services
0.117
0.108
0.116
0.145
Agriculture/Forestry
0.218
0.233 0.218
0.208 0.233
0.777 0.208
Agriculture/Forestry
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Fishing
0.048
0.044
0.054
Fishing
0.048
0.044
0.054
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Services
0.117
0.108
0.116
0.145
Residential
Services
0.117
0.108 0.117
0.116 0.108
0.145 Residential
Services
0.116
0.145
Services
0.117
0.108
0.116
0.145
Services
0.117
0.108
0.116
0.145
Services
0.117
0.108
0.116
0.145
Agriculture/Forestry
0.218
0.233
0.777
Agriculture/Forestry
0.218
0.233
0.208
0.777
Services
0.117
0.108
0.1160.145
0.145 0.208
Services
0.117
0.108
0.116
0.145
Services
0.117
0.108
0.116
Residential
(GWh x 1000 Households)
4.06
4.35
Residential (GWh
x 1000 Households)
3.91
4.22 3.91
4.06 4.224.35 Residential
Residential
−0.3
−2.4
−0.3 −2.4
−0.3
−0.6
1.6
−0.3
−2.4
−0.7
−0.3
−2.4
0.8
−2.4
0.8
−2.4 −2.4
−2.4
0.8
−0.3
−2.4
0.8
0.7
2.9
−0.7
−0.3
−0.7
−0.3
−0.7 −0.3
−0.7
−2.4
0.8
−0.7
−0.3
5.8
0.7
2.9
0.7
2.9
0.7
2.9
0.7 −2.9
−0.7
−0.3
0.7
2.9
−1.8
−1.6
5.8
−2.9
5.8
5.8 −2.9
0.7
2.9
5.8
−2.9
32.2
4.8
−1.8
−1.6
−1.8
−
1.8 −1.6
5.8
−2.9
−1.8
−1.6
32.2
4.8
16.4
2.1
32.2
4.8
32.2
4.8
32.2 −1.6
−1.8
32.2
4.8
1.2
0.7
16.4
2.1
16.4
2.1
16.4
2.1
32.2
4.8
16.4
2.1
16.4
1.2
0.7
1.2
0.7
1.2
0.7
16.4
2.1
1.2
0.7
1.2 −1.3
−0.4
Residential
Residential
Residential
Residential
Services
0.116
0.145
Services
0.117
0.108 0.117
0.116 0.108
0.145 Residential
1.2
0.7
Residential
Residential
(GWh xx 1000
1000 Households)
Households)
3.91
4.22
4.06
4.35
1.64
1.834.35
1.74
1.62 −0.4
xxx 1000
Inhabitants)
1.64
1.83
1.74 4.22
1.62 4.06
1.6
0.9
Residential (GWh
Households)
3.91
4.22 Residential
4.06
4.35
−0.4
−1.3
Residential
(GWh
3.91
4.35
(GWh
1000
Residential
3.91
4.22
4.06
−1.3
Residential
(GWh xx 1000
1000 Inhabitants)
Households)
3.91
4.22
4.06
4.35
Residential
Residential (GWh
(GWh
x 1000
1000 Households)
Households)
3.91
4.22 3.91
4.06 4.22
4.35 Residential
−0.4
−1.3
Residential
(GWh
Households)
4.06
4.35
Residential
(GWh xx 1000
1000 Inhabitants)
Inhabitants)
1.641.74
1.831.62
1.74
1.62
Residential (GWh
(GWh
1000 Inhabitants)
Inhabitants)
1.64
1.83 1.64
1.74 1.83
1.62 1.74
1.6
0.9
Residential
(GWh
1.62
Residential
(GWh
xx 1000
1000
Inhabitants)
1.64
1.83
1.6
0.9
Residential
x
1.64
1.83
1.74
1.62
1.6
0.9
Residential
(GWh
x
1000
Inhabitants)
1.64
1.83
1.74
1.62
Households)
3.914.06
4.22
4.06
4.35
Residential
Households)
3.91
4.22
4.35
−0.4
−1.3
x 1000 Inhabitants)
1.64
1.83
1.74
1.62Eurostat
1.6
0.9
Residential (GWh
×1000(GWh
Households)
4.22Own
4.061.64
4.35
−
0.4 data.
Residential
(GWh 3.91
x 1000Source:
Inhabitants)
1.83
1.74 with
1.62Eurostat
Source:
Own
calculations
calculations
with
data.
Residential
(GWh 1.64
x 1000Source:
Inhabitants)
1.83
1.74 with
1.62Eurostat
Residential
(GWh
x 1000 Inhabitants)
1.64
1.83
1.62Eurostat
1.6
0.9
Residential (GWh
×1000
inhabitants)
1.83Own
1.741.641.74
1.62
1.6 data.
Source:
Own
calculations
calculations
with
data.
Source:
Own
calculations
with
Eurostat data.
Source:
Own
calculations
with
Eurostat
data.
Source:
calculations
Eurostat
data.
Own
calculations
Source: Own
Own Source:
calculations
with
Eurostatwith
data.Eurostat
Source:
Ownwith
calculations
with
Eurostat data.
data.
−0.3
−0.02
−−0.6
2.4
−0.02
−0.3
2.7
−0.02
−0.3
−2.4
−0.7
2.0
−0.9
−2.4
−0.9
0.8
−0.9
−2.4
−0.3
−0.02
−0.9
−2.4
−0.7
0.7
3.6
2.0
−0.7
2.0
−−2.4
0.3
2.0
−0.7
−0.9
2.0
−0.7
0.7
5.83.6
0.2
3.6
0.7
0.73.6
2.9
−0.7
2.0
3.6
0.7
5.8
−1.8
−0.9
0.2
5.8
5.8
−2.9
0.70.2
5.8
3.6
0.2
−1.8
32.2
−0.9
−0.9
−1.8
−−1.8
1.6
5.8
0.2
−0.9
−1.8
32.2
16.4
−1.6
32.2
32.2
−1.8
4.8
−0.9
32.2
16.4
1.2
2.4
−1.6
16.4
−1.6
16.4
−1.6
16.4
32.2
−1.6
2.1
16.4
1.2
2.4
1.2
2.4
2.4
1.2
16.4
−1.6
2.4
1.2
0.7
−0.40.8
1.22.4
−0.4
1.60.8
3.9
0.8
−0.4
−0.4
0.8
−0.4
1.6
3.9
1.6
3.9
3.9
1.6
0.8
−−0.4
1.3
1.63.9
1.63.9
0.9
−2.4
−0.02
−0.02−0.02
−2.4
1.6
2.7
−2.4
−0.02
0.8
−0.9
−0.3
2.0
0.8
−0.9
−0.9−0.02
0.8
−0.9
−2.4
0.8
−0.9
−0.3
2.0
2.9
3.6
−0.3
2.0
−0.3
2.0
0.82.0 −0.9
−0.3
2.0
2.9
3.6
−2.9
0.2
2.9
2.93.6 3.6
3.6
−0.3
2.0
2.9
3.6
−2.9
0.2
−1.6
−0.9
−2.9
0.2
−2.9
0.2
2.90.2 3.6
−2.9
0.2
−1.6
−0.9
4.8
−1.6
−1.6
−0.9
−0.9 −0.9
−2.9
0.2
−1.6
−0.9
4.8
2.1
−1.6
4.8
4.8
−1.6
−0.9
4.8
2.1
−1.6
0.7
2.4
2.1
−1.6
2.1
−1.6
2.1
−1.6
4.8
−1.6 −1.6
2.1
0.7
2.4
0.7
2.4
0.72.4 −1.6
2.4
2.1
0.7
2.4
−1.3
0.8
0.7
2.4
−1.3
0.8
0.9
3.9
−1.3
0.8
−1.3
0.8
−1.3
0.8
0.9
3.9
0.9
3.9
0.9
−1.3
0.8
0.90.8 3.9
3.9
0.93.9 3.9
5. ConclusionsSource:
5. Conclusions
Own
calculations
with
Eurostat
data.
Source:
Own
calculations
Eurostat data.
Source:
Own
calculations
with
Eurostatwith
data.
5.
Conclusions
5. Conclusions
Conclusions
5.
Conclusions
5.
5.
Conclusions
5. Conclusions
There
is a between
clear nexus
between
economic
andconsumption.
electricity consumption.
Along this article
There is5.aConclusions
clear
nexus
economic
growth
and growth
electricity
Along this article
5. Conclusions
There
is
aaa between
clear
nexus
between
economic
and
electricity
consumption.
Along
this
There
is5.
aConclusions
clear
nexus
between
economic
growth
and growth
electricity
consumption.
Along
this article
article
There
is
clear
nexus
between
economic
growth
and
electricity
consumption.
Along
this article
article
we
have
referred
to
that
relationship
as
“Income
elasticity
of
electricity
consumption”
defined
as the
we have
referred
to
that
relationship
as
“Income
elasticity
of
electricity
consumption”
defined
as
the
There
is
a
clear
nexus
economic
growth
and
electricity
consumption.
Along
this
There
is
clear
nexus
between
economic
growth
and
electricity
consumption.
Along
this
There is a clear
nexus
economic
growth
and growth
electricity
Along this article
There
is a between
clear nexus
between
economic
andconsumption.
electricity consumption.
Along
this article
article
we
have
referred
to
that
relationship
as
“Income
elasticity
of
electricity
consumption”
defined
as
the
we
have
referred
to
that
relationship
as
“Income
elasticity
of
electricity
consumption”
defined
as
rate
between
in
electricity
consumption
and
GDP,
in parallel
with
the
most
common
rate
between
electricity
consumption
and
in
parallel
with
the
most
common
There
isin
a changes
clear
nexus
between
economic
growth
and
electricity
consumption.
Along
this
article
There
iswe
a changes
clear
nexus
between
economic
growth
andGDP,
electricity
consumption.
Along
this
article
we
have
referred
to that
that
relationship
as
“Income
elasticity
ofconsumption”
electricity
consumption”
defined
as the
the
we
referred
to
relationship
as
“Income
elasticity
of
electricity
defined
as
the
have
referred
to
relationship
as
“Income
of
electricity
consumption”
defined
as
the
we have
have
referred
to that
that
relationship
as
“Income
elasticity
of elasticity
electricity
consumption”
defined
as
the
rate
between
changes
in
electricity
consumption
and
GDP,
in
parallel
with
the
most
common
rate
between
changes
in
electricity
consumption
and
GDP,
in
parallel
with
the
most
common
rate
between
changes
in
electricity
consumption
and
GDP,
in
parallel
with
the
most
common
meaning
of
“price
elasticity”,
which
refers
to
the
unity
changes
induced
in
electricity
consumption
meaning
of
“price
elasticity”,
which
refers
to
the
unity
changes
induced
in
electricity
consumption
we
have
referred
to thatin
relationship
as
“Income
ofconsumption”
electricity
defined
as the
we have
referred
to that
relationship
as
“Income elasticity
of elasticity
electricity
defined
as the
rate
between
changes
in
electricity
consumption
and
GDP,
in parallel
parallel
withcommon
the
most
common
rate
between
changes
in
electricity
consumption
and GDP,
in
parallel
with
theconsumption”
most
rate
between
changes
electricity
consumption
and
GDP,
in
with
the
most
common
of
“price
elasticity”,
which
the
unity
changes
induced
in
electricity
consumption
meaning
of
“price
elasticity”,
which
refers
to
the
unity
changes
induced
in
electricity
consumption
for
each
unity
change
ininprices.
for
each
unity
change
inin
prices.
rate
between
changes
electricity
consumption
and
GDP,in
inelectricity
parallel
with
the most
common
rate
between
changes
electricity
consumption
andto
GDP,
in
parallel
the most
common
meaning
of
“price
elasticity”,
which
refers
to
unity
changes
induced
meaning
of
“price
elasticity”,
which
refers
to
the
changes
induced
in
electricity
consumption
meaning
of meaning
“price
elasticity”,
which
refers
to the
therefers
unity
changes
induced
inwith
electricity
consumption
meaning
of
“price
elasticity”,
which
refers
to
the unity
unity
changes
induced
inconsumption
electricity
consumption
for
each
unity
change
in
prices.
for
each
unity
change
inEU-28,
prices.
for
each
unity
change
in
prices.
In
the
electricity
consumption
grew
at
an
annual
rate
of
1.1%
between
1996
and
2012,
In
the
EU-28,
electricity
consumption
grew
at
an
annual
rate
of
1.1%
between
1996
and
2012,
meaning
of
“price
elasticity”,
which
refers
to
the
unity
changes
induced
in
electricity
consumption
meaning
of
“price
elasticity”,
which
refers
to
the
unity
changes
induced
in
electricity
consumption
for
each
unity
change
in
prices.
for
each
unity
change
in
prices.
for each unity
in prices.
forchange
each unity
change in prices.
InGDP
the
EU-28,
electricity
consumption
grew
at an
an annual
annual
rate
ofintensity
1.1%rate
between
1996
and
2012,
In
the
electricity
consumption
grew
at
an
annual
of
between
and
In
the
EU-28,
electricity
consumption
grew
at
of
1.1%
between
and
while
increased
by
1.7%.
Aggregate
electricity
(GWH/Mill.
€) 2012,
in1996
all European
while
increased
by
1.7%.
Aggregate
electricity
intensity
€) 1.1%
in1996
all
European
for
each
unity
change
in
prices.
for
each
unity
change
inEU-28,
prices.
InGDP
the
EU-28,
electricity
consumption
grew
atrate
an (GWH/Mill.
annual
rate
of
1.1%
between
1996
and 2012,
2012,
In
the
EU-28,
electricity
consumption
grew
at
an
annual
rate
of
1.1%
between
1996
and
2012,
In
the
EU-28,
electricity
consumption
grew
at
an
annual
rate
of
1.1%
between
1996
and
2012,
whileInGDP
GDP
increased
by
1.7%.
Aggregate
electricity
intensity
(GWH/Mill.
€) 1.1%
in1996
all
European
while
GDP
increased
by
Aggregate
electricity
(GWH/Mill.
€)
in
all
while
increased
by
1.7%.
Aggregate
electricity
intensity
€)
in
all
European
countries
the
combined
EU-28
was
reduced
from
0.25
to 0.23
during
that
same
period.
we
countries
theIncombined
EU-28
was1.7%.
reduced
from
0.25
toat
0.23
during
that
same
period.
we
theand
EU-28,
electricity
consumption
grew
an (GWH/Mill.
annual
rate
of
between
andAs
2012,
theand
EU-28,
electricity
consumption
grew
at
an
annual
rate
ofintensity
1.1%
between
and
2012,
while
GDP
increased
by
1.7%.
Aggregate
electricity
intensity
(GWH/Mill.
€)As
in1996
all European
European
while
GDP
increased
by
1.7%.
Aggregate
electricity
intensity
(GWH/Mill.
€)
in
all
European
while
GDP
increased
by
1.7%.
Aggregate
electricity
intensity
(GWH/Mill.
€)
in
all
European
Energies 2017, 10, 347
17 of 20
Noteworthy are the high intensity of electricity use in the Spanish basic metals sector, more
than 90% above the EU-15 average. As mentioned before, Spanish firms use production technologies
that are more electricity intensive compared to firms in other countries. The intensity of electricity
use in the Spanish primary sector is more than double the average EU-15 intensity. This last
observation is likely due to Spain’s relatively warm climate requiring an increased use of electricity for
irrigation. As mentioned before, observed differences in the wood and furniture sectors may be due to
discrepancies across countries regarding the sectoral allocation of some activities such as industries of
paper pulp and celluloses.
Regarding the dynamics of intensities, it is interesting to note how sectors such as basic metals,
and chemicals display increasing intensities of electricity use in Spain while on average for the EU
they show downward trends. On the other hand, agriculture in Spain has shown a declining trend in
intensity of electricity use while the intensity for the EU average has risen over time.
5. Conclusions
There is a clear nexus between economic growth and electricity consumption. Along this article
we have referred to that relationship as “Income elasticity of electricity consumption” defined as the
rate between changes in electricity consumption and GDP, in parallel with the most common meaning
of “price elasticity”, which refers to the unity changes induced in electricity consumption for each
unity change in prices.
In the EU-28, electricity consumption grew at an annual rate of 1.1% between 1996 and 2012,
while GDP increased by 1.7%. Aggregate electricity intensity (GWH/Mill. €) in all European countries
and the combined EU-28 was reduced from 0.25 to 0.23 during that same period. As we have shown
in this paper, across Europe electricity intensity has been reduced mainly due to the progressive
loss of the weight of industrial activities in electricity consumption and GDP and partially due to a
reduction in the intensity of electricity use by industrial activities. These factors have been strong
enough to compensate for the increased weight of services and households in electricity consumption
and their higher intensity of electricity use. The loss of the weight of industrial activities in electricity
consumption is correlated with the de-industrialization of the European economies. Similarly, in
Spain, the progressive reduction of electricity demand income elasticity can be explained for by the
progressive loss of industrial activities.
If we focus on the non-residential consumption, electricity demand can be analyze as a production
input, so that, in absence of technological changes, the production (i.e., Income) elasticity should be 1.
Nevertheless, there are, at least, two opposite trends that can alter this elasticity.
On the one hand, the progressive substitution of capital goods, (production equipment) powered
by electricity instead of other fuels (coal, gas, oil, etc.), or the substitution of labor for capital inputs
(automatization or robotization) can yield elasticities larger than one. This effect can be denoted as
“electrification” process.
Obviously, the substitution process among different energy sources is not just a matter of
technological change, and not infrequently this process is driven by relative prices among different
energy sources, and these differences in relative prices can explain different levels of electricity intensity
among European countries, and along time.
On the other hand, the technological process also generates more efficient equipment, not only in
the non-residential sector, but also in residential one (for instance, low consumption lighting devices).
This increase in efficiency would lead to elasticity levels below one. We can refer to this process as
“Energetic efficiency”.
In a very naïve interpretation we could say that as a country develops its income elasticity should
be larger than one, as the electrification process weights more than energetic efficiency, but once
reached an adequate development level, this elasticity should be going progressively reduced, as the
energetic efficiency becomes the main driver.
Energies 2017, 10, 347
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Results presented in this paper are based on the application of a simple, but very effective,
methodological approach to decompose the growth rates of electricity demand into a number of effects.
In particular, the evolution of electricity demand is influenced by both demographic effects (increases
in population and number of households), as well as economic effects, both structural or long term
(sectoral distribution of production) and cyclical or short term (GDP growth).
Regarding our decomposition analysis of growth of electricity demand in Spain, the following
points should be highlighted:
•
•
•
•
During our period of analysis (1990–2012) energy demand in Spain has been mainly driven by
economic growth (44%), while the remaining 56% is due to increases in the non-residential
electricity intensity (26%), average consumption per household (21%) and demographic
changes (9%).
The contribution of the average consumption per household to growth in electricity demand has
remained fairly constant along the entire period (1990–2012), only turning negative in 2006 and
during the last economic crisis (2008–2012).
Similarly, the intensity of electricity use by the non-residential sector has had a positive impact on
growth in electricity demand during most of the period, being especially significant for earlier
years. This effect has been somewhat reduced, reflecting energy saving motives during the last
economic crisis (2008–2012).
The demographic effect only contributed significantly to electricity demand from the end of the
nineties until the start of the crisis, most likely linked to migratory in-flows.
Our proposed approach allows us to analyze the evolution of the elasticity of electricity demand
with respect to GDP and to identify key factors underlying its evolution. For the Spanish case, we
observe that the most relevant factor for the evolution of the income elasticity of electricity demand has
been the progressive loss of the relative weight of non-residential consumption, together with different
developments in intensities of electricity demand of various productive sectors. Considering the trend
in both magnitudes—electricity demand intensity and elasticity of electricity demand—we expect that
the currently very high elasticity of electricity demand in Spain will continue to decline in the future.
These features have notable implications in terms of policy. On the one hand, long term grid
planning has to take into account the progressively “residential” nature of the demand. This demand
is usually more dispersed/distributed than the industrial demand, more sensitive to temperature
variations, and more price inelastic. Both characteristics increased the stress of the grid capacity
(peak demand/valleys demand), and therefore the risk of local failures, and, more importantly, could
increase the losses in electricity distribution. As total electricity, effectively consumed or lost, is equally
paid by the final consumers, the incentives to invest in loss reduction have to come from the Public
regulator. On the other hand, energy conservation policies have to take into account this long term
demand feature. Due to the increasing weight of residential demand in total electricity demand policies
has to be targeted adequately. An effective impact on household electricity demand requires adopting
not only measures based on prices (taxation and so on) or subsidizing investment in more efficient
technologies, but also psychology based incentives to conserve or even compulsory measures.
Acknowledgments: The authors are grateful to Red Eléctrica de España S.A for providing financial assistance.
We also benefited from comments by Felix Martinez, Mauricio Remacha, and Luis Villafruela from the Department
of Statistics and Information of Red Eléctrica de España S.A. The authors remain solely responsible for any errors
or omissions.
Author Contributions: The study is a result of the full collaboration of all the authors. Julián Pérez-García
conceived the idea of applying the index decomposition analysis to the study of the changing pattern in GDP
elasticity of electricity consumption, and their application to European countries. Julián Moral-Carcedo performed
the analysis of previous works and the motivation and paper’ writing.
Conflicts of Interest: The authors declare no conflict of interest.
Energies 2017, 10, 347
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Appendix A
Table A1. Energy indicators in Europe.
Country
Energy Intensity
(TOE/Mill. €)
(2012)
Electricity
Share (1)
(2012)
Energy
Growth (2)
(2004–2012)
Electricity
Growth (3)
(2004–2012)
European Union (28 countries)
Euro area (18 countries)
Belgium
Bulgaria
Czech Republic
Denmark
Germany
Estonia
Ireland
Greece
Spain
France
Croatia
Italy
Cyprus
Latvia
Lithuania
Luxembourg
Hungary
Malta
The Netherlands
Austria
Poland
Portugal
Romania
Slovenia
Slovakia
Finland
Sweden
United Kingdom
19.44
19.11
19.98
69.54
32.04
11.92
17.82
36.83
12.17
24.11
20.12
19.20
31.27
17.19
22.68
28.59
24.87
14.55
28.41
26.74
15.81
18.87
25.82
24.44
27.44
31.65
30.69
38.85
31.24
15.24
21.8%
22.3%
20.7%
25.9%
20.6%
18.8%
21.3%
20.9%
19.5%
26.1%
24.8%
25.3%
22.3%
20.9%
21.5%
14.6%
15.8%
12.9%
19.0%
32.8%
17.9%
19.7%
16.4%
24.5%
16.0%
22.3%
19.9%
27.6%
33.8%
20.3%
−0.9%
−0.9%
−1.4%
−0.6%
−1.3%
−0.8%
−0.5%
0.2%
−1.4%
−2.2%
−1.6%
−1.1%
−0.6%
−1.0%
−0.5%
0.4%
1.2%
−0.6%
−2.1%
1.6%
−0.4%
0.2%
1.2%
−1.9%
−1.1%
0.1%
−0.8%
−0.5%
−0.6%
−1.6%
0.2%
0.3%
0.1%
1.4%
0.6%
−0.6%
0.1%
2.1%
0.6%
0.6%
0.5%
0.4%
1.4%
0.1%
2.0%
3.0%
1.9%
−0.2%
0.4%
0.9%
0.2%
1.3%
2.0%
0.4%
1.1%
0.0%
0.0%
−0.4%
−0.3%
−0.8%
GDP
Growth
(2004–2012)
1.0%
0.8%
1.2%
2.8%
2.6%
0.4%
1.4%
2.7%
1.1%
−1.5%
0.8%
0.9%
0.5%
−0.3%
1.7%
2.0%
2.8%
1.8%
0.3%
2.2%
1.1%
1.6%
4.2%
−0.1%
2.5%
1.4%
4.3%
1.1%
1.9%
0.8%
Source: Eurostat. GDP measured in 2008 euros. (1) Share of Electrical energy in Total Final Energy Consumption
TOE (tonnes of oil equivalent); (2) Final Energy Consumption. Average growth rate (2004–2012); (3) Electrical energy
consumption. Average growth rate (2004–2012).
Table A2. Sectorial definition and NACE 2009.
NACE rev 2 2009
Sector
1, 2, 3
5
6, 19
35
7, 8, 9
25
24
23
20, 21
26, 27, 28, 33
30
29
10, 11, 12
13, 14, 15
16, 31
17
18, 58
22, 32
41, 42, 43
49, 51, 64, 53
45, 46, 47, 55, 56, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71,
72, 73, 74, 77, 79, 80, 81, 82, 90, 91, 92, 93, 94, 96, 97
36, 37, 38, 39, 84, 85, 86, 87, 88, 99
Agriculture, Hunting, Forestry and Fishing
Mining and Coal
Oil and Natural Gas Extraction
Energy Utilities
Mining
Basic Metals
Non-Ferrous Metallurgy
Building Materials
Chemical Industry
Metal Machinery
Naval Construction and Repair
Transport Manufacturing Industry
Manufacture of Food, Beverage and Tobacco
Textile, Clothing, Leather and Footwear
Wood, Cork and Furniture
Pasta Paper, Paper and Cardboard
Printing and Publishing
Rubber Industries, Plastic and Other
Construction and Public Works
Transportation
Trade & Services
Administration and Public Services
Energies 2017, 10, 347
20 of 20
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