C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 64
that only some 5 has been achieved in practice, implying an energy efficiency gap of some 4.
4. NEMO Ž
This section summarizes the main behavioral equations in NEMO Netherlands .
Energy Demand Model , most of the parameters of which are derived from ICARUS. NEMO models the energy efficiency gap and tries to reconcile bottom-up
and top-down approaches to energy efficiency. The nature of ICARUS has led us to develop a vintage model of the
putty]semi-putty type. In this model, ex-ante substitution possibilities of factors of production are higher than ex-post possibilities. Put differently, it is possible to
retrofit existing vintages after a price increment, but its efficiency gain will be less than the addition of a new, highly efficient vintage while scrapping a less efficient
one.
Ž Fig. 5 shows a nested production structure of the KLEM type see, e.g. Berndt
. Ž
and Wood, 1975 . We assume that it is separable in its inputs. Energy fuel E and
f
. Ž
. electricity E
and capital investments I
and I aimed at energy saving are
e f
e
Ž .
combined to produce capitalrenergy bundles H
and H . These in turn are
f e
Ž .
Ž combined with energy-saving labor L and L , resulting in energy services Z
f e
f
. Ž
. and Z . In the final stage, energy services are combined with materials M , labor
e
Ž .
Ž .
not related to energy-saving L and vintages of capital not related to energy-
Ž .
Ž .
3
saving I to produce physical output Y . NEMO describes only the substitution
Fig. 5. Nested production structure of NEMO.
3
This structure applies to industrial sectors as well as services, where M is replaced by other variables such as office-space.
C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 65
between capital, labor and energy in the production of energy services. Other Ž .
Ž .
models are required to predict output Y , energy services Z
and Z and
f e
Ž .
non-energy inputs M, I , L For a formal derivation of energy use based on cost-minimization with CES
Ž .
production functions we refer to Koopmans et al. 1999 . The main aim of this paper is to show that the parameters of NEMO can be derived from ICARUS. For
this aim, a mere representation of the behavioral equations is sufficient. However, it is worth pointing out one necessary simplification in the derivation due to data
limitations. Starting with cost-minimization in nested CES production function, it is well known that the price elasticities are not constant, but depend on the level of
factors of production. Although ICARUS contains information about the level of energy use, it does not contain information on the present level of capital
Ž .
investments aimed at energy-saving I and I . It gives only additional capital
f e
Ž .
investments necessary to save energy. This required a log linearization of factor demand equations, yielding constant price elasticities that do not depend on levels
of factor demand.
4
The main equations of NEMO are summarized in Box 1. It describes ex-ante w
Ž . Ž .x and ex-post efficiency of vintages Eqs. 1 ] 4 , pointing at differences in energy
Ž . efficiency between new and existing vintages. The final equation 6 represents an
Ž .
index of energy efficiency of total capital stock F at time t in a sector by
t
weighting together all vintages existing at time t, with total investments in the year Ž
. in which the vintage was installed as weights total investments as proxy for Z .
Scrapping of investments is assumed to be linear over a symmetric interval around w
Ž .x
5
Ž . Ž . the average lifetime of a vintage Eq. 5 . We will now describe Eqs. 1 ] 4 in
turn, thereby explaining how each equation implicitly contributes to the energy efficiency gap.
Ž . Eq. 1 defines the ex-ante energy efficiency of a new vintage added in year t
relative to a vintage installed in year t . Two factors affect the ex-ante efficiency. Firstly, performance improvements and lower equipment prices can be translated
into a decreasing price of energy-saving investment per unit of energy saved. A decreasing price of energy-saving techniques leads to substitution of capital for
energy, captured by the time trend a. Secondly, the relative energy price affects efficiency through elasticity b.
Trend parameter a is calibrated such that, at constant 1990 energy prices, simulated energy efficiency improvements in NEMO are equal to energy efficiency
improvements in ICARUS. We have made two important adjustments to account for the remarks in the previous section. Firstly, on the basis of evidence provided in
4
Alternatively, we could have obtained log-linear equations by starting out with Cobb]Douglas production functions. However, we consider the Cobb]Douglas structure as very restrictive. Moreover,
this would have yielded equations for ErZ which would not be log-linear in P rP , if we express P as
E Z
H
a weighted average of P and P .
E I
5
The average lifetime at the sector level is calculated by the weighted average of the lifetime of buildings and appliances or processes, with weights determined by energy consumption aimed at heating
the building and using appliances or processes respectively.
C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 66
Box 1 NEMOs main equations
e a
Ž .
Ex-ante fuel efficiency of the vintage added in year t F s
1 , exclusive of good housekeeping effects
f ,t yb
f
e a
P ,
E rZ
E t
f ,t
f ,t
f
e a ya Ž tyt
f
. Ž .
F s
e 1
f ,t
ž
E rZ
P
f ,t
f ,t
E t
f , 0
Ideal ex-post fuel efficiency in year t of the vintage installed in year t, exclusive of good housekeeping effects
yd
f
i r
P E
rZ
E t f
,t,t f
,t,t
f ,
i r e a yg Ž tyt .
f
Ž . F
s F e
2
f ,t,t
f ,t
ž
E rZ
P
f ,t
f ,t
E t
f ,
Ž .
Ex-post fuel efficiency in vintage t in year t after actual retrofit through partial adjustment , exclusive of good housekeeping effects
a r
E rZ
f ,t,t
f ,t,t
a r e a
F s F
t s t
f ,t,t
f ,t
E rZ
f ,t
f ,t
I
t a r
« i r
a r i r
a r
f
Ž . w
x s F
q C F
y F F
F F
f ,t,ty1
f f
,t,t f
,t,ty1 f
,t,t f
,t,ty1
K
t a r
Ž . s F
other 3
f ,t,ty1
Ex-post fuel efficiency including good housekeeping
yu
f
e p
P rP
E rZ
E t L
,t f
,t,t f
,t,t
f ,
e p i r
Ž . F
s F 4
f ,t,t
f ,t,t
ž
E rZ
P rP
f ,t
f ,t
E t L
,t
f , 0
Ž .
Linear scrapping over interval a , a
min max
c s
t y t - a
ty t min
Ž .
t y t y a
min
s a
F t y t F a
min max
a y a
ma x min
Ž . s
1 t y t a
5
ma x
Fuel efficiency index of total capital stock
t
e p
w x
1 y c Z
F
Ý
ty t f
,t f
,t,t
tstya
ma x
Ž . F s
6
f ,t
t
w x
1 y c Z
Ý
ty t f
,t
tstya
ma x
where similar equations are used for electricity a
, g , h , b , d , u 0 s trends resp. price elasticities
f f
f f
f f
t , t , t s subscripts denoting year t, base year t and vintage t
Z , K s investments in energy saving in year t resp. capital stock in year t
t t
P , P
s real fuel price resp. wage rate in year t.
E L ,t
f ,
C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 67
Ž .
Van Vuuren 1996 , we assume that ICARUS’ energy saving potential is a better approximation for the year 2010 than for 2015. Secondly, we simulate a situation
whereby the whole capital stock of 2010 has the efficiency of the vintage added in 2010, reflecting that ICARUS describes a situation of full penetration of available
and cost-effective energy-saving techniques. The price elasticity b is calculated by fitting a function with constant price elasticity through the constructed points in
Fig. 4.
The parameters a and b are estimated by evaluating ICARUS using a 15 Ž
. discount rate. This is based on Velthuijsen 1995 , who investigated 303 firms and
Ž .
concluded that firms use on average a pay-back time of 5]6 years to evaluate energy saving techniques, which corresponds to a real discount rate of approxi-
Ž .
mately 15. The fact that this is higher than market rates of interest 5]8 can be explained by the non-market failure factors mentioned above. The rest of the
Ž energy efficiency gap the difference between implicit discount rates of 20]25
. and the 15 we use is described in NEMO, as a gradual penetration of new
techniques in the capital stock. Ž . Ž .
Eqs. 2 ] 4 describe ex-post efficiency of vintages, which may differ from the ex-ante efficiency of a vintage for several reasons. Firstly, during the lifetime of a
vintage, retrofit investments may add capital aimed at saving energy in response to w
Ž .x changes in energy prices and technical progress Eq. 2 . Ideal retrofit in year t
Ž .
G t of a vintage installed in year t depends on technological change, reflected by
time trend g, and on the relative energy price through elasticity d. In general, bottom-up information supports that g - a and d - b, showing that ex-post
possibilities of substitution between factors are smaller than ex-ante possibilities, and hence the putty]semi-putty structure of production. The calculation of the
parameters g and d follows similar methods to those for replacement techniques.
In practice not all profitable retrofit investments are undertaken. This con- tributes to the energy efficiency gap. We describe this by a simple partial adjust-
w Ž .x
ment process Eq. 3 . The speed of adjustment depends on the rate of replace- ment of capital stock and other parameters reflecting e.g. competitive pressure. We
calibrate « and c such that half of the profitable retrofit techniques penetrate within 2 years. Empirical information may lead to a review of these parameters.
Ž . Eq. 3 also reflects that it is not possible to adjust to lower energy efficiency
Ž .
higher F by decommissioning retrofit investment during the lifetime of the
w vintage. Nevertheless, total retrofit investments can be reduced by scrapping Eq.
Ž .x 5 retrofitted vintages.
The second reason for the difference between ex-ante and ex-post efficiency is w
Ž .x that good housekeeping in the form of additional labor can save energy Eq. 4 .
This may happen in the year in which the vintage is installed, or afterwards during the lifetime of the vintage. Bottom-up information on good housekeeping ‘invest-
Ž .
ments’ is limited 40 techniques for 19 sectors . We assume that there is no trend Ž .
in Eq. 4 . According to ICARUS ‘good housekeeping’ can be undertaken at little labor costs. We assume that ICARUS neglects costs, contributing to the energy
efficiency gap. Neglected costs are assumed to be so high, that good housekeeping
C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 68
Fig. 6. Explaining the energy gap modeled in NEMO in terms of the implicit discount rate in ICARUS; food and drink sector.
techniques were just not profitable in 1990. Good housekeeping will change only if the energy price changes.
We illustrate NEMO’s partial description of the energy gap in Fig. 6. We have analyzed the fuel efficiency improvement in the food and drinks sector according to
Ž ICARUS with a 15 and 25 discount rate at various prices p s 1990 fuel price;
. fuel intensity in 1990 s 100 . We compare this to NEMOs predictions. The figure
shows that the slopes of the curves are the same. Indeed, this follows from gearing price elasticities to ICARUS results. Secondly, at a 15 discount rate, NEMO
predicts less energy efficiency improvements than ICARUS. This difference shows that NEMO predicts part of the energy efficiency gap. Thirdly, by analyzing
Table 1 NEMOs parameters compared to other studies
Ž .
Long-term efficiency trend per year Long-term price elasticity
Fuel Electricity
Total Fuel
Electricity Total
NEMO Total
y 0.73
y 1.42
y 0.81
y 0.30
y 0.24
y 0.29
Industry y
0.49 y
1.02 y
0.56 y
0.19 y
0.14 y
0.18 Historical studies
a b
c d
Total y
1.3 , y0.93 y
0.30 , y0.62
c d
Industry y
0.20 , y0.27
a
Ž .
Ministry of Economic Affairs 1996 ; 1960]1990.
b
Ž .
Farla and Blok 1997 ; 1985]1994.
c
Ž .
Groot 1988 ; 1965]1985.
d
Ž .
Mittelstadt 1983 ; 1960]1978.
¨
C.C. Koopmans, D.W. te Velde r Energy Economics 23 2001 57]75 69
ICARUS with a 25 discount rate, we may conclude that the part explained by NEMO corresponds to an additional discount rate of up to 10.
We have outlined how we obtained trends and elasticities from the bottom-up information in ICARUS. Table 4 at the end of this paper contains trends and
elasticities for 19 separate sectors, thereby distinguishing between fuel and electric- ity use, and the type of investment. For a detailed discussion of the parameters see
Ž .
Koopmans et al. 1999 . In this paper we will present some general findings and discuss the implicit discount rate in NEMO.
Ž .
Table 1 presents aggregated results over sectors from NEMO. The results show Ž
. a long-term autonomous energy efficiency trend of approximately 0.8 per year
and a long-term price elasticity of energy efficiency of approximately 0.3. The ‘raw’ Ž
ICARUS data suggests an energy efficiency improvement of 1.5]2 per year at a .
15 discount rate , which is caused by the fact that ICARUS describes a hypothet- ical situation of full penetration of available and cost-effective energy saving
techniques in 2015. This hypothetical situation will not occur in reality because actual energy efficiency lags behind technological possibilities.
Ž .
Table 1 also compares NEMOs parameters to results from top-down historical studies. One should however take caution in comparing the studies, for two
reasons. Firstly, the historical studies, using sectoral data on energy use, exclude inter-sectoral effects but include intra-sectoral effects: if energy-intensive sub-sec-
tors grow faster than energy-extensive sub-sectors, it leads to a decline in energy intensity of the sector as a whole. This effect is not accounted for by ICARUS or
NEMO: these focus on efficiency. Secondly, this study investigates energy saving techniques at the energy demand side only, while the study by the Ministry of
Ž .
Economic Affairs 1996 includes energy efficiency improvements at both the supply and demand sides. Table 1 shows that NEMOs elasticities are compatible
with results from other studies. NEMO’s trends, however, are lower. This might be caused by the differences described above. It might also indicate that new tech-
nology for energy efficiency improvements will become available more slowly in the future than it did in the past.
5. Historical simulation
