Linking green stimulus, energy efficiency and technological innovation: The need for complementary policies

mundanemushroomsElectronics - Devices

Nov 21, 2013 (3 years and 27 days ago)

108 views


1







Linking green stimulus, energ
y efficiency and technological
innovation:

T
he need for complementary policies



Edward B Barbier

Department of Economics & Finance

University of Wyoming



February 8, 2011


Final Draft







Paper prepared for the
Europ
ean Commission DG 1 (External Relations)

Project, "
Transatlantic
Opportunities for Meeting Global Challenges in Energy Efficiency and Low Carbon
Technologies
".

Presented at the Transatlantic Energy Efficiency Workshop, UC Berkeley School
of Law, Berkeley,
CA, February 11
-
12, 2011.




2

Summary


The following paper

contains

five
contributions
:



A
n overview and summary

of
global
green stimulus
, especially low carbon and
energy
efficiency (LC/EE) measures, enacted during the 2008
-
9 rec
e
ssion.



An analysis of the e
ffectiveness of such stimulus measures on their own in achieving
long
-
term goals

for improved

energy efficiency,

including implementing necessary
energy R&D.



A review of the key barriers to extending the cost
-
effective energy efficiency elements of
current

green stimulus packages into a long
-
term strategy.



A discussion

of the additional complementary pricing policies and
programs
, such as
carbon pricing, emissions policies, further regulations,
subsidy removal,
etc., which are
required to achieve long
-
term
energy efficiency and R&D goals.



An assessment of the additional challenges facing and assistance required for emerging
market economies, with a focus mainly on development assistance, post
-
Kyoto reform of
the
Clean Development Mechanism (
CDM
)
, and the nee
d for an emerging global carbon
market.

In analyzing the link between green stimulus, energy efficiency and technological
innovation,
this paper advances and explores
an important hypothesis
:
as the stimulus packages
enacted during 2008
-
9 are wound down, t
he energy efficiency elements


which typically have
the highest net benefits


should be continued. This paper finds that this hypothesis is plausible,
provided that energy efficiency policies are appropriately designed and executed, and more
importantly
, that they are supported by a range of

complementary pricing policies. These
include economy
-
wide pricing and regulatory policies, such as

carbon pricing, emissions pol
icies
and additional regulatory incentives
; removal of fossil fuel subsidies; prescrip
tive and targeted
incentive programs; behavioral nudging; and combined or improved design of energy efficiency
programs
.


Developing

economies may also need additional support, especially in the form of
technological and capital assistance, reform of the C
DM and the development of a global carbon
market.


O
verview of green stimulus during the 2008
-
9 recession

A unique feature of the global policy re
sponse to the 2008
-
9 recession wa
s that, as part of
their efforts to boost aggregate demand and growth, some g
overnments adopted expansionary
policies that also incorporated a sizable "green fiscal" component. Such measures were wide
ranging, including

support for renewable energy, carbon capture and sequestration, energy
efficiency, public transport and rail, and

improving electrical grid transmission
, as well as other
public investments and incentives aimed at environmental protection (
Barbier 2010a
,
b;
Robins et
al. 2009 and 2010). Several studies have shown that such "green stimulus" policies could foster
a mor
e sustainable, low
-
carbon economic development in the medium term while creating
growth and employment in "clean energy" sectors (Barbier 2010a
,
b; Houser et al. 2009; Pew
Charitable Trusts 2009; Pollin et al. 2008; Renner et al. 2008).

Green stimulus measu
res can be separated into three broad categories

of support
:


3



Energy efficiency

-

S
upport for energy conservation in buildings; fuel efficient vehicles;
public transport and rail; and improving electrical grid transmission.



Low carbon power

-

S
upport for re
newable energy
(geothermal, hydro, wind and solar),
nuclear power,
and carbon capture and sequestration.



Water, waste and pollution control



Support for water, waste and pollution management
and control, including water conservation, treatment and supply.

It is common to refer to two of these areas, low carbon power (LC) and energy efficiency
(EE), as comprising collectively the
clean energy

sector of an economy (Barbier 2010a
,b
; Pew
Charitable Trusts 2009).

Green stimulus in
the above

three areas is measu
red in terms of the additional fiscal
commitments made by
national
governments during the 2008
-
9 recession in the form of
spending plans or tax breaks.
Additional investments resulting from regulatory mandates, such
as renewable energy obligations, vehicl
e fuel use standards, or energy efficiency requirements,
are usually not included.

Table 1 summarizes the global green stimulus enacted by governments from September
2008 through December 2009.

Annex 1 provides a further breakdown of the major green
stimu
lus packages enacted during the recession, by region and country.

Of the $3.3 trillion allocated worldwide to fiscal stimulus over 2008
-
9, $522 billion was
devoted to green exp
enditures or tax breaks. Almost
the
entire global
green stimulus was by the
G20
, which comprise the world's
twenty
largest and richest countries.
1

Globally, green spending
amounted to just under 16% of total fiscal stimulus and 0.7% of world GDP.

Support for energy efficiency was a prominent component of most green stimulus
packages
(see Table 1 and Annex 1), amounting to $335 billion over 2008
-
9
, or nearly two thirds
of all green spending globally
. Although the amounts vary from country to country, just under
two thirds of the green stimulus
globally
went to energy efficiency. This

allocation appears to
reflect a general consensus that support for energy efficiency measures were a relatively
effective and fast way of creating jobs while curbing energy use during the recession (Barbier
2010a
,
b; Houser et al. 2009; Pew Charitable Trus
ts 2009; Pollin et al.

2008; Renner et al. 2008).
$87.1 billion of energy efficiency spending globally was for energy conservation in buildings,
$21.4 billion for developing fuel
-
efficient vehic
les, $135.2 for
rail and public transport, and
$97.1 billion

for
improvements in electrical grid transmission

(see Annex 1)
.

However, the
amount spent on these different energy efficiency investments varied considerably from country
to country. For example, almost all of China's support for energy efficiency was
for grid and rail
improvements. In contrast, the European Union and the United States spent more on building
conservation than any other energy efficiency category.





1

The members of the G20 include 19 countries (Argentina, Australia, Brazil, Canada, China, France, Germany,
Indi
a, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, the United
Kingdom and the United States) plus the European Union.


4

Assessment of green stimulus and energy efficiency measures


At the 2008
Group of Eight (
G8
)

summit in Hokkaido, Japan, leaders committed to
implementing the 25 energy efficiency recommendations of the International Energy Agency
(IEA 2008).
2

The recommendations were aimed at seven priority areas: cross
-
sectoral activity,
buildings, appliance
s, lighting, transport, industry and power utilities.
The IEA estimated that
full implementation globally of the proposed actions could save annually around 9.2 exajoules
(EJ) of final energy consumption, or 8.2 gigatonnes (Gt) of carbon
-
dioxide (CO
2
) equ
ivalent
greenhouse gas
(GHG)
emissions, by 2030. This
amounts

to around one fifth of projected
energy
-
related emissions in 2030, or about twice the European Union's current yearly emissions.


The 2008
-
9 recession provided further rationale for government
-
led efforts to boost
energy efficiency investments. As argued by the IEA (2009
a
, p. 2), "i
mprovements in energy
efficiency can deliver some of the largest and cheapest CO
2

reductions.

Importantly in a time of
financial crisis, they can also often be imple
mented quickly and bring more

benefits for
e
mployment than any other category of energy technology.
"



As noted previously, t
he
fact that

energy efficiency measures
featured prominently in
many
fiscal stimulus packages
adopted during the 2008
-
9 recession s
uggests support for this
view expressed by the IEA.
However, as we have also seen, not all countries adopted green
stimulus measures, and even those that did, varied in how much was spent on energy efficiency.

The purpose of the following section is to
assess in more detail, first, the e
xtent to which
green stimulus and energy efficiency measures were adopted as part of global economic recovery
efforts, and second, whether energy efficiency measures d
o have an advantage over other green
stimulus measures

in terms of speed of disbursement, employment creation, and large and cheap
greenhouse gas reductions. In addition, the section concludes by examining whether energy
efficiency spending and tax breaks alone are sufficient to achieve long
-
term savings in
energy
consumption and CO
2

emissions.


Green stimulus



As Figure 1 indicates, the United States and China accounted for over two thirds of the
global expenditure on green fiscal stimulus during 2008
-
9. The world's largest economy, the
European Union, cont
ributed substantially less to the global total. Total green spending by
all of
Europe totaled only $57

billion
; in contrast, the Asia Pacific region spent
$342 billion

(see
Annex 1). The governments of key European economies, such France, Germany, and the

United
Kingdom, spent much less on clean energy and other environmental investments than the major
Asi
a
-
Pacific economies,
Japan and South Korea. Several G20 governments did not commit any
,
or very little,

funds to green stimulus, including the large eme
rging market economies of Brazil,
India and Russia (see Table 1).

As shown in Figure 2, green stimulus measures and investments amounted globally to
around 16% of all fiscal stimulus spending during the recession. However, only a handful of
economies devo
ted a substantial amount of their total fiscal spending to green investments. The



2

The eight countries comprising the G8 are Canada, France, Germany, Italy, Japan, Russia, the U
nited Kingdom
and the United States. The European Union is represented in the G8 but cannot host or chair.

The 25 energy
efficiency recommendations were prepared under the mandate of the G8 Gleneagles Plan of Action in July 2005.


5

most notable is South Korea, which allocated nearly 80% of its total expenditure to green
investments. China apportioned around a third of its total fiscal spending to gree
n measures.
Around 60% of the European Union's fiscal stimulus was for green investments, but as indicated
in Figure 1, the overall size of this investment was relatively small. In comparison, whereas the
United States
total expenditure on

green stimulus

was large
,
it

comprised only 12% of total fiscal
spending. Overall, most G20 governments were cautious as to how much of their stimulus
spending was allocated to low
-
carbon and other environmental investments during the 2008
-
9
recession.

Perhaps most rev
ealing, however, was the share of green stimulus measures in gross
domesti
c product (GDP)
, as illustrated in Figure 3.

Very few
governments spent 1
%
or more
of
GDP on
green
investments during the recession.
With the exception of Sweden, all these
countrie
s were from the Asia Pacific region. L
arge
-
scale green

stimulus programs
, such as the
5
% of GDP planned by South Korea and
the 3% of
China
,

were

the exce
ption rather than the
norm.

The United States spent 0.9% of GDP on green stimulus, more than the globa
l average,
but the European Union spent only
0.2% of GDP (see Table 1).


Energy efficiency


Figure 4 indicates
the total energy efficiency spending by country in response to the
2008
-
9 recession. China spent by far the most on these measures ($182 billion
), well over half
the global total ($328 billion).
The US also spent a considerable amount on energy efficiency
($58 billion), whereas the European Union allocated less than $10 billion to such measures. The
major Asia Pacific economies, Japan and South
Korea, spent more on energy efficiency than the
major European economies, Germany, France, the United Kingdom and Sweden.

Figure 5

confirms that energy efficiency measures had a prominent role in the total fiscal
stimulus packages of some countries. China
, the European Union and South Korea spent at least
20% each on energy efficiency. Other European countries, such as Norway, France, the United
Kingdom and Germany also devoted around 13 to 17% of their total fiscal stimulus to energy
efficiency. In contr
ast, despite its large expenditure on green stimulus, the United States
allocated only 6% of its total fiscal spending to energy efficiency measures (Table 1).


The perceived effectiveness of energy efficiency measures as a cost
-
effective and quick
means t
o creating jobs while reducing energy use and GHG em
issions is reflected in Figure 6
.

Many countries that adopted green stimulus packages during the 2008
-
9 recession tended to
focus almost exclusively on energy efficiency measures. Although 42% of the Eu
ro
pean Union's
green stimulus was

devoted to energy efficiency,
individual European countries allocated much
more. For example, the entire green stimulus packages of Austria, Belgium, Germany, Italy and
Sweden consisted of investments aimed at improving e
nergy efficiency.
The United Kingdom
allocated 84% of its green stimulus to energy efficiency, France 83% and Norway 56%.
Although energy efficiency investments amounted to
84% of China's green stimulus, they were
only half of green spending in the Unite
d States.


Figure 7 shows the ten economies with the largest green stimulus depicte
d in Figure 1,
and compares this spending

to their energy efficiency investments.
Even among these ten
e
conomies
, those

with smaller green stimulus packages tended to focus
mainl
y on energy
efficiency measures.

The only exception was Saudi Arabia, which spent its green stimulus

6

entirely on water supply and management.
In contrast,
the

five economies with
the
large
s

green
stimulus packages
, such as China, the United States,
Japan and European Union,

also included

sizable investments in
low carbon power
investments
and waste, water and pollution control.


Global p
erformance of energy efficiency stimulus


An analysis by HSBC Global Research

estimates

the disbursement of energy

efficiency
and
other components of global green stimulus packages (Robins et al. 2010). The
comparison
is indicated in Figure 8.
Green stimulus spending is likely to

continue through 2012, but with the
bulk of the spending occurring in 2010. Energy eff
iciency investment follows this trend.
A
round

$56 billion of spending on energy efficiency occurred in 2009, which nearly triple
d

to
$165 billion throughout 2010 before
expecting to
tail off to $
92 billion in 2011. By 2012, only
$11 billion will
remain f
or spending on
energy efficiency from the
2008
-
9 global
green stimulus
packages.


However, the speed of disbursement of energy efficiency measures appears to be only
slightly faster than other green stimulus. As indicated in Figure 6, around 64% of all gl
obal
green stimulus packages were devoted to energy efficiency.
But energy efficiency comprised
just 68% of green funding in 2009, and its
final share is likely

to be 67% in 2010, 63% in 2011
and 41% in 2012

(see Figure 8)
.
Thus,
the rate of disbursement

of energy efficiency spending
has been fairly constant, and in the early years, consistent with its share of overall stimulus
packages enacted over 2008
-
9. Thus,

estimated
green stimulus spending
over 2009
-
2012 does
not appear to be
frontloaded with ener
gy efficiency measures.


Individual countries have also varied considerably in how quickly they have spent their
green stimulus (Robins et al.
2009 and
2010). China accelerated its green spending in the first
half of 2009, and then slowed down in the seco
nd half. It spent an estimated $67 billion of its
green stimulus over 2009. In contrast, Australia, Canada, France and the United States started
slowly but ended 2009 with a faster rate of disbursement.
South Korea spent $2.3 billion of its
green stimul
us steadily throughout 2009. The European Union has been one of the slowest
economies to deliver on its green stimulus spending.

Administrative delays and political
considerations appear to have been the major reason for the slow disbursement of funds,
e
specially in the European Union, Germany and the United Kingdom. However, poorly
developed programs have also been a factor. For example, in Australia, the Home Insulation
Program helped to insulate over 915,000 homes in 2009, but had to be suspended in
early 2010,
along with the solar hot water rebate program, because of safety concerns (Robins et al. 2010).


Some indication of the success as well as the difficulties of implementing energy
efficiency measures as part of stimulus spending can be gained by

a specific country example.
One of the few green stimulus programs that has been analyzed
in detail is the American
Recovery and Reinvestment Act.


American Recovery and Reinvestment Act



T
he
February 2009
$787 billion
American Recovery and Reinvestment

Act
(ARRA)
in
the United States
devoted

around $
78.5

billion to retrofit buildings, expand mass transit and
freight rail, construct a “smart” electrical grid transmission system and expand renewable energy
supply.
Additional investments in water infrastr
ucture resulted in a $94.1 billion green stimulus

7

package

(see Annex 1)
.
Total green spending under the ARRA
amount
s

to

0.7% of US GDP
, and
aim
s

to
create

or save

around 2 million jobs

(Barbier 2010
a
)
.


Houser et al. (2009) analyzed a green recovery progra
m for the United States that
contained many of the same stimulus measures as enacted in the ARRA.
The
y found
that the
decreased cost and consumption of energy from the entire program have the potential to save the
US economy an average of US$450 million p
er year for every US$1 billion invested. In addition,
every $1 billion in government spending would lead to approximately 30,000 job
-
years and
reduce annual US greenhouse gas (GHG) emissions

by 592,600 tons between 20
12 and 2020.
3

The employment gains represent a 20 percent increase in jobs creation over more traditional
infrastructure spending.


Table 2
illustrates the relative impacts per billion dollars spent of the energy efficiency,
low carbon power and convention
al stimulus investments analyzed by Houser et al. (2009).
These impacts are depicted in terms of speed of implementation, employment creation, and
reductions in US energy costs, oil imports and GHG emissions. As the table shows,
the
energy
efficiency pro
grams
were
anticipated

to
be implemented relatively quickly,
and have moderate to
high employment impacts.
Although energy efficiency measures have more varied impacts on
energy cost, import and GHG reductions
, these impacts for some programs are also sig
nificant.



The ARRA incorporated some versions of the clean energy measures indicated in Table
2. For example, the Act appropriates $5 billion for the Weatherization Assistance Program to
pay up to $6,500 per dwelling to assess and reduce a household's e
nergy bills (CEA 2010
a
). An
additional $3.2 billion is allocated to the Energy Efficiency and Conservation Block Program to
subsidize energy conservation programs of US states.
Similar measures under the Act bring the
total support for energy conservation

to nearly $20 billion.
The ARRA also provides $10.5
billion to modernize
the electricity grid, $6.1 billion to promote advanced vehicles and fuels
technologies, and $18.1 billion for mass transit and high
-
speed rail (See Table 3).


The US Council

of Econo
mic Advisors (CEA) releases quarterly reports assessing the
impacts
of the ARRA in terms of actual spending and job creation
. However, only the
second
quarterly

report breakdowns these impacts

by

various clean energy programs

(CEA 2010a)
. The
results are

depicted in Table 3.
Only 5.7% of the clean energy funds were actually dispersed by
the end of 2009. Although the rate of disbursement for ene
rgy efficiency programs (6.4%) wa
s
slightly
better, it was

still surprisingly low given expectations that these

programs could be
implemented relatively quickly (see Table 2).

For example, the Weatherization Assistance
Program actually spent only $500 million over 2009, and the Energy Efficiency and
Conservation Block Grant just $85 million.

Nevertheless, energy
efficiency funding accounted
for around 68% of the clean energy outlays in 2009.


Due to updated cost estimates, CEA (2010b) revised the total amount apportioned from
the ARRA to clean energy to $94.8 billion compared to the $90.2 billion indicated in Tabl
e 3.
Nevertheless, the rate of disbursement continues to be slow. For example, through the end of the
3
rd

Quarter of 2010 (Sept 30, 2010), only $57.7 of clean energy spending had been obligated, and
$25.9 billion (27.3% of the total) had been spent (CEA
2010c).

Unfortunately, the recent
quarterly reports do not indicate the disbursement by type of clean energy investments, such as
energy efficiency.




3

In Houser et al. (2009)
, employment effects
are measured in job
-
years, or the number of full
-
time equivalent jobs
lasting one year.


8

The clean energy programs implemented under the ARRA saved or created nearly 52,000
jobs in 2009, and induc
ed perhaps an additional 11,000 jobs (see Table 3).

Energy efficiency
contributed a large proportion to this employment creation (70%).


By 2012, clean energy
stimulus under the Act could create or save 720,000
job
-
years of employment, with energy
effici
ency accounting for 455,000 job
-
years.

By the end of the 3
rd

Quarter of 2010, clean energy
investments were estimated to have saved or created 224,800 jobs (CEA 2010c). This suggests
that the total job
-
year estimates for 2012 are in reach, despite the sl
ow disbursement of clean
energy investments, including energy efficiency.

One important spin
-
off of the ARRA was the US "Cash for Clunkers" program, the
Consumer Assistance to Recycle and Save (CARS), which is discussed in Box 1.
CARS was not
initially par
t of the ARRA, but was enacted separately in June 2009.
Official assessment
indicates

that
CARS
was

a
highly
successful en
ergy efficiency stimulus
, as suggested by
proponents (see Houser et al. 2009 and Table 2).
CARS

was implemented quickly, within

a
mo
nth

of enactment
, and it generated significant reduction in fuel consumption, GHG emissions
and air pollution, while at the same time stimulating economic growth and creating employment.

But as outlined in Box 1, there is considerable disagreement about t
he amount of overall
economic and environmental benefits generated by CARS, with the range of net benefits ranging
from a loss of $1,600 per vehicle to a gain of $400 per vehicle. In addition, as the program was
funded by

taking $2 billion initially alloc
ated under the ARRA for long
-
term renewable energy
loans. Thus, any resulting reduction in low carbon power generation must be included as an
additional cost of CARS.


Summary and conclusion

of green stimulus

assessment

There is an emerging consensus that

the green stimulus spending by G20 governments
during the 2008
-
9 recession did not amount to a concerted global green recovery effort

(Barbier
2010a, b and d;
Bowen and Stern 2010;
Strand and Toman 2010)
.


The main problem is too
much reliance on short
-
ter
m green stimulus measures and not sufficient adoption of
complementary pricing and regulatory measures to provide incentives for long
-
term in
vestments
in clean energy, including the adoption of energy efficiency, and for spurring the necessary
technologica
l innovations.

A good example of the problem is illustrated by the ARRA, which
included

around $
78.5

billion to retrofit buildings, expand mass transit and freight rail, construct a “smart” electrical
grid transmission system and expand renewable energy
supply

throughout the United States
.

As
we have seen, the ARRA promises to
generate

massive savings in energy, oil imports and GHG
emissions by 2030, as well as create 720,000 job
-
years of employment by 2012.

But the original
plans that were the "bluepri
nt" for the ARRA called for
a comprehensive cap
-
and
-
trade system to
limit CO
2

emissions
and the removal of fossil fuel subsidies

to finance and improve the
effectiveness of the proposed clean energy investments (Podesta et al. 2007; Pollin et al. 2008)
.
S
o far, these additional policies have failed to materialize, and without them, the current stimulus
to private investment and job creation in green sectors may be largely temporary.
As Houser et
al. (2009)
warn

in their assessment of many low carbon and e
nergy efficient stimulus measures
contained in the ARRA:

"A green stimulus is no replacement for comprehensive climate and
energy policy. Even the most aggressive short
-
term spending will have only a modest impact on
US greenhouse gas emissions and depend
ence on foreign sources of energy."


9

Unfortunately, this outcome could be the norm across countries. Without additional
policy measures, some of the
2008
-
9
green spending by the
G20 will be wasted;

its impact on
long
-
term investment and job creation in gre
en sectors will be restricted by ongoing fossil fuel
subsidies and other market distortions, as well as the lack of effective environmental pricing
policies and regulations

(Barbier 2010a, b and d; Bowen and Stern 2010; Strand and Toman
2010).
For example,

many clean energy investments are still too costly compared to conventional
energy sources. Fossil fuel subsidies further distort this cost competitiveness. The lack of
policies and regulations to include the costs of carbon emissions and pollution also

artificially
lowers the market price of using conventional energy. Evidence from the United States suggests
that

such "direct emission" policies are critical for spurring private investment and induced
technological change in clean energy sectors

(Goulde
r 2004)
.

Strand and Toman (2010) also maintain that there may also be a trade
-
off between short
-
run and long
-
run growth, environmental and employment impacts of green stimulus programs.
Given such trade
-
offs, the promotion of green projects on short
-
term
stimulus grounds may
prove to be a second
-
best alternative from an environmental perspective, in particular if it helps
to reduce “locking in” more fossil fuel energy
-
intensive and less clean capital stock in the longer
run.

Included in Strand and Toman's

analysis is an assessment of the possible short versus long
-
term gains of
some

energy efficiency measures contained in current green stimulus packages.
Their evaluation of these measures is summarized in Table 4. Although energy efficiency
measures on t
he whole fare better than other green stimulus,
even among energy efficiency
measures, there are "few obvious candidates for triple
-
win policies, with simultaneously strong
benefits for short
-
term economic recovery, longer
-
term growth, and long
-
term enviro
nmental
benefits" (Strand and Toman 2010, p. 23).
However, the authors also emphasize that pricing
reforms, including taxation and removing energy
-
related price distortions, can not only provide
increased incentives for long
-
term private investment
in cle
an energy and technological
innovation but also help finance ongoing investment in energy efficiency and other green
measures with less of a public debt burden. Similar arguments in favor of complementary
policies for long
-
term green investments are put f
orward by Barbier (2010a,d).

To summarize the key findings of this section, e
nergy efficiency played

a prominent role
in current green stimulus enacted during the 2008
-
9 recession. Although
the new energy
efficiency investments are

likely to continue unt
il 2012, eventually spending will be completely
disbursed. Some studies have questioned the effectiveness of green stimulus, including energy
efficiency. They are unlikely to be a substitute for the use of complementary pricing policies to
encourage ener
gy
conservation
.

As the stimulus
spending enacted during 2008
-
9 winds

down,
the energy efficiency elements should be continued, provided that they are appropriately
designed and executed. In addition,
they should be

supported by a range of complementary

pricing policies, from carbon pricing, emissions policies and additional regulatory incentives to
ensure the effectiveness of long
-
term energy efficiency policies.


Towards a long run strategy


If the energy efficiency elements of current green stimulus p
ackages are to be continued,
and possibly even expanded, into a long
-
term strategy, then key institutional, political and
market failures need to be addressed. Recent assessments of long
-
term energy efficiency
strategies point to some of these problems.

They fall generally into three categories:


10



barriers to implementing cost
-
effective energy efficiency policies



barriers faced by consumers and firms in adopting cost
-
effective energy efficiency
measures, and



barriers to financing cost
-
effective energy effic
iency measures, especially in developing
economies.


For example, the International Energy Agency (IEA) has evaluated the progress of both
IEA member countries and the G8 in implementing the 25 energy efficiency recommendations
from the 2005 Gleneagles Pla
n of Action (IEA 2008, 2009b and 20
09c
; Jollands et al. 2010).

The overall consensus, as summarized in IEA (20
09b
), is that, although considerable progress
has been made in adopting energy efficiency policies and innovative financial instruments, no
count
ry has fully or substantially implemented more than 57% of the relevant IEA
recommendations, and two countries

(Poland and Spain)

report less than 10% implementation.
The
IEA (20
09b
, p.12) concludes that the principle

reason why
the full range of cost
-
eff
ective
energy efficiency policies has not been adopted is that "energy efficiency continues to face
pervasive barriers including lack of access to capital for energy efficiency investments,
insufficient information, principal
-
agent problems and externality

costs that are not reflected in
energy prices." The full range of information, market and technological barriers are summarized
in Table 5.


Table 5 indicates that
one of the key barriers to widespread adoption of energy efficiency
measures over the long

term is
energy
-
related price distortions, which
artificially lowers the cost
of inefficient energy use and technologies. Energy efficient measures that would otherwise

be
cost
-
effective still face

a competitive market disadvantage.
As discussed in the pr
evious section,
such
pervasive
price distortions
were considered a major obstacle to the effective implementation
of energy efficiency and other green stimulus measures. The perverse incentives arising from
such distortions will continue to be an obstacle

to any long run strategy for energy efficiency.


Ano
ther important
hindrance is
the
energy efficiency paradox
,
which

is defined as the
inclination of households and firms to require very high internal rates of return in order to make
energy efficiency inv
estments
(
Ansar and Sparks 20
09
;
Tietenberg 2009; Gil
linghan et al. 2006;
Popp 2010). The factors often cited for this paradox are the various information and behavioral
barriers listed in Table 5.

The disincentives

caused by such barriers can be extreme
ly high. A
survey of studies in the US shows that the average implicit discount rates by households and
firms making energy saving investments range from 0.26 to 3.00 with a median of 0.67, which is
well above the range for plausible risk
-
adjusted discoun
t rates in standard net present value
analysis (Ansar and Sparks 2009).

In the United States, attempts to address the energy efficiency paradox have focused on
providing better information through certification by the federal government, such as the Energ
y
Star program, or by private organizations, such as the Leadership in Energy and Environmental
Design (LEED) program for buildings (
Dixon et al. 2010;
Gillingham et al. 2006;
Tietenberg
2009). The Energy Star program is a certified labeling scheme for mo
re energy efficient
appliances, heat pumps, furnaces, thermostats and similar products purchased by consumers and
businesses.
LEED establishes standards for the design, construction and operation of energy
-
saving green buildings. Although they provide ad
ditional information, these labeling programs
leave the level of energy efficiency to the purchaser of the product or building. To eliminate

11

inefficient choices from the feasible set of purchas
ing options, the US has also

adopted minimum
or average energy

efficiency standards for buildings and products.

In developing economies, many energy
efficiency
investment projects with favorable
internal rates of return remain unfunded because of the lack of effective financing programs and
delivery mechanisms. What

is needed is usually
a combination of additional
technical
and
financial
support for
investments
that can either realize
the potential efficiency gains

or achieve
operating cost savings.
Inadequate

f
inancing
is a persistent problem not only in low income

countries but also emerging market economies in Asia, including China and India
(Bat
tacharya
and Cropper 2010; Carmody and Ritchie 2007;
Chandler and Gwin

2008;
Taylor et al. 2008
;
Zho
u et al. 2009). The factors often cited for t
he

lack of financing
an
d delivery mechanisms for
energy efficiency in developing economies
are the market organization and technological
barriers listed in Table 5.




The role of complementary policies

Complementary policies are critical to overcoming the key barriers to long
-
t
erm and
widespread energy efficiency adoption in all economies. Such policies are also important for
ensuring the success of continuing the cost
-
effective energy efficiency elements of current green
stimulus packages into a long
-
term strategy.

Such comple
mentary policies include:



Economy
-
wide pricing and regulatory policies



e.g.,
carbon pricing
, direct emissions
policies

and energy efficiency resource standard
s




Removal of fossil fuel subsidies

-

eliminates perverse incentiv
es in energy markets and
provides an immediate source of financing for long
-
term energy efficiency strategies.



Prescriptive and
targeted
incentive programs



e.g., targeted subsidies

and rebates
,
energy
efficiency
portfolio
standards
,
tradable white cert
ificates
.



B
ehavioral nudging



Non
-
priced based behavioral interventions, such as home energy
-
use reports, information on energy
-
efficient products, energy efficiency promotions
, etc.




C
ombined/improved design of
energy efficiency
programs

-

e
.g., combin
ing energy
efficiency with other clean energy or government investment programs
.


Economy
-
wide pricing and regulatory policies


Economy
-
wide pricing and regulatory policies have an important role to place in
promoting long
-
run technological innovation that

are necessary for low
-
carbon investments and
improved energy efficiency in an economy.
Carefully targeted public investment, especially in
support of R&D and other complementary infrastructure, not only boost shortfalls in private
investment during a cre
dit
-
constrained recession but also have the capability of inducing
technological innovation necessary for widespread adoption of low
-
carbon power and energy
efficiency in the economy (see Box 2). But "technology
-
push policies", such as research and
develop
ment (
R&D
) subsidies, public investments and other initiatives, mainly deal with one
type of market failure affecting induced innovation in low carbon technologies and energy

12

efficiency,

the inability of private investors’ to appropriate all the knowledge
gains generated by
R&D
. A

second market failure stems from the climate change externalit
ies

associated with the
combustion of fossil fuels

and other economic activities that generate greenhouse gas (GHG)
emissions. Public investments and expenditures in

support of private R&D cannot address this
second market failure. Instead, technology
-
push policies and investments must be supplemented
by "
direct emissions
"

policies
, such as carbon pricing,

to ensure that

GHG
-
generating activities

take into account cl
imate change externalities. As discussed in Box 2,
both types of policies


direct emissions and technology
-
push
measures



are necessary to promote induced
technological change
and energy saving
by the private secto
r in the long run
.

Studies for reduci
ng greenhouse gas emissions in the United States
, Europe and other
OECD economies

show that combining the two policies substantially lower the costs of meeting
targets compared to relying just on a technology
-
push approach, such
as
a R&D subsidy for low
-
ca
rbon energy options

and energy efficiency
(
Blesl et al. 2010;
Pew Charitable Trusts 2009; IEA
2009b and 2009c; Goulder 2004; Fischer and Newell 2008; Popp 2010).
Although the optimal
portfolio of policies invariably includes
some form of emissions price
and subsidies for
technology R&D and learning, carbon pricing and direct emissions policies are generally the
most efficient policy option if only a single economy
-
wide policy can be adopted. For example,
Fischer and Newell 2008, p. 160) conclude from the
ir analysis of the US electricity sector: “We
find that for anything beyond very small emissions reduction targets, the emissions price is the
most efficient single policy for reducing emissions, since it simultaneously gives incentives for
fossil energy p
roducers to reduce emissions intensity, for consumers to conserve, and for
renewable energy producers to expand production and to invest in knowledge to reduce their
costs.”


Removal of fossil fuel subsidies

Globally, fossil fuel consumption subsidies amou
nted to $557 billion in 2008
(IEA/OPEC/OECD/World Bank 2010). Production subsidies accounted for an additional $100
billion. Together, these subsidies account for roughly 1% of world GDP.


Such fossil fuel consumpt
ion and production subsidies are an add
itional market failure
prevent
ing improved energy efficiency
in economies. By artificially lowering the cost of using
fossil fuels, such subsidies deter consumers and firms from adopting energy efficiency measures
that would otherwise be
cost
-
effective in

the absence of any subsidies.

Removal of
such
perverse incentives w
ould therefore boost energy savings substantially. For example, phasing
out all fossil fuel consumption and production
subsidies by 2020 could result in a 5.8% reduction
in global primar
y energy demand and a 6.9% fall in greenhouse gas emissions

(IEA/OPEC/OECD/World Bank 2010)
.

The financial savings could
also
be redirected to
funding the continuation of many of the
energy efficiency programs initiated during by governments during the 200
8
-
9 recession.
As
noted above (see Table 1 and Annex 1), the
energy efficiency component of green stimulus
packages amounted to $335 billion over 2008
-
9, which is only about half of the estimated annual
cost of global fossil fuel consumption and productio
n subsidies.



13

Prescriptive and targeted incentive programs

New energy efficient products and technologies usually are more expensive

than
conventional alternatives
. As a result, a variety of prescriptive and targeted incentive programs
have been develop
ed to entice consumers to purchase the new products and firm
s

to invest in the
new technologies by
either
lowering their relative costs

or stipulating an energy efficiency
requirement
. Such incentive programs include
targeted subsidies and rebates, energy

efficiency
portfolio standards
, ratepayer
-
funded energy efficiency programs

and tradable white certificates
(
Cappers and Goldman 2010;
Gillingham et al. 2006;
del Río 2010;
Ti
e
tenberg 2009;

Transue
and Felder 2010).

Targets for energy efficiency in the Un
ited States and Europe are increasingly being set
through energy efficiency portfolio standards (EEPS). These standards stipulate that some
portion of energy demand must be met through improved energy efficiency or how much energy
efficiency potential mus
t be installed. Minimum or average energy efficiency standards for
buildings and products, which were discussed above, are one example of EEPS.
Requiring
utilities to meet explicit energy savings goals through l
egislative or regulatory mandates is

a
nother

example.
Over half of US states have some form of EEPS, and they are increasingly
being used in a number of European countries for setting energy efficiency targets (Cappers and
Goldman 2010; del Río 2010;
Dixon et al. 2010;
T
i
e
tenberg 2009; Transue and
Felder 2010).

New incentive programs are increasingly being used to improve the cost
-
effectiveness of
meeting the energy efficiency targets mandated by EEPS. For example, in the United States,
ratepayer
-
funded energy efficiency programs are becoming a pop
ular method of meeting such
targets

for fossil
-
fuel based electricity generation
. However, because of the time it takes for the
energy savings to be reflected in utility bills, the way in which such programs account for a
recover costs from ratepayers can

have an important influence on incentives (Cappers and
Goldman 2010). Most utilities prefer charging annually for energy efficiency program costs in
order to minimize their perceived regulatory risk for the potential disallowance or under
-
recovery of pro
gram costs in future years. But this cost recovery strategy means that it takes
some time before the cost savings from improved energy efficiency are realized and average
customer bills begin to fall. However, if energy efficiency costs are amortized ove
r a multi
-
year
period, then the ratepayers
will realize bill savings much more quickly, and will be more likely to
support and participate in the program.

Tradable white certificates are another incentive mechanism increasingly used in Europe
and the Unite
d States to energy efficiency targets in electricity generation. Energy suppliers or
distributers are required to meet a certain energy
-
saving target among end
-
users. The energy
savings are measured, verified and certified through the issuing of a white
certificate. The value
of the tradable white certificate (TWC) in terms of kilowatt hours (kWh) of energy savings is
calculated against a baseline
. Certificates can either be earned through actual energy saving
activities and investments
,
of by acquiring
TWC
s from others who have saved more energy than
necessary to achieve compliance
.

TWCs are considered more cost effective in the long run than current subsidy or rebate
programs, which generally target the most reduction in energy efficiency per dollar or
euro
expended (Tietenberg 2009
; Transue and Felder 2010
).

Rather than government or regulatory
agencies determining which technologies to support with pre
-
set rebates or subsidies, a TWC
program allows the market to establish the most cost
-
effective way f
or end users to achieve

14

energy savings. In addition, b
y allowing end users to choose currently whether to invest in
saving energy or purchase certificates from others,
a TWC scheme

allows them time consider
making investments that minimize the present val
ue of the costs of energy savings. However,
a
rebate or subsidy requires less upfront cost to implement, setting up a TWC scheme inevitably
require higher program cost outlays.

Another advantage of r
ebates

is that they can be used to encourage consumers
to buy
energy efficient products.

Rebate payments are either employed as once
-
off payments at the
time of sale or as a post
-
sale mail
-
in coupon. According to Transue and Felder (2010, p. 103),

rebates are popular incentives
because they require relativ
ely straightforward implementation,
rely on simple economic principles, and when structured properly transform target markets to
eliminate future rebate needs….In the EEPS case, rebate payments cover incremental cost
differences between efficient and ineff
iciency measures, removing incentives to purchase
traditional technologies and stimulating demand for efficient ones.”






Behavioral nudging

Non
-
priced
-
base behavioral interventions also have a role to play in encouraging
households to overcome many
of the barriers that prevent them from adopting existing energy
-
saving technologies, such as better insulation, fuel
-
efficient vehicles and efficient appliances and
lighting
(Allcott and Mullainathan 2010; Dietz et al.

2009). Evidence suggests

that
such
b
ehavioral nudging may be even more cost
-
effective if initiative through a package of energy
efficiency incentive programs and policies.
As summarized by Dietz et al. (2009), t
he most
effective interventions typically (
i
) combine several

policy tools (e.g.
, information, persuasive
appeals, and incentives)

to address multiple barriers to behavior change; (
ii
) use

strong social
marketing, often featuring a combination of mass

media appeals and participatory, community
-
based approaches

that rely on social netw
orks and can alter community social

norms; and (
iii
)
address multiple targets (e.g., individuals, communities,

and businesses).

Such programs can
be
cost
-
effectively scaled
up
to million
s
of

households and can

reduce electricity
use
in the average
househol
d by 2% (Allco
tt and Mullainathan 2010)
.


Combined/improved design of energy efficiency programs


A number of pilot programs and experiments have been co
nducted to try and improve
the
cost
-
effectiveness of the energy efficiency programs introduced during t
he 2008
-
9 recession.
Some of the innovations that have shown the greatest potential involve merging energy
efficiency with other clean energy or government investment programs, such as c
ombining
energy efficiency house weatherization and other programs wi
th low
-
cost mortgage provision for

poor households (Nevin 2010);
combining energy efficiency and smart grid programs (Jackson
2010); combining energy efficiency and renewa
ble energy electricity programs

(Cappers and
Goldman 2010
;
del Río 2010).


For exampl
e, Nevin (2010)
proposes an energy
-
efficient housing stimulus strategy
for the
US
that could (
i
) create jobs quickly; (
ii
) reduce home energy bills by 30 to 50%; (
iii
) stabilize
home values and reduce foreclosures; (
iv
) reduce lead poisoning among children
; and (
v
)
imp
lement regulatory reforms that provide incentives for cost
-
effective energy saving
investments in homes.

The suggested program involves combining the “lead
-
safe” window

15

replacement from the ARRA, the Making Home Affordable plan to reduce home

foreclosures,
and the home weatherization program of the Department of Energy and Housing and Urban
Development (HUD).
Nevin maintains that such a combined program could help to halt the
decline in home prices, given recent evidence that home value incre
ases by around $20 for every
dollar reduction in annual utility bills. In addition, providing federal funding for window
replacement and other home weatherization in any home purchased from the inventory of
foreclosed homes would target such equity
-
enhanc
ing investment to neighborhoods hardest hit
by foreclosures.



Jackson (2010) finds that combining basic appliance and energy efficiency building
standards with smart grid improvements are much more effective than relying on the latter
improvements alone.

In particular, targeting the most energy
-
efficient 25%
households while
encouraging a 20% participation rate in a smart grid program reduces peak hour electricity use
by 33% more than relying on a 50% smart grid participation program on its own. As the l
atter is
a much more expensive program, combining both energy efficiency and smart grid programs are
therefore likely to be more cost effective.


Combining renewable energy promotion and energy efficiency initiatives is also likely to
lead to greater syner
gies between energy and cost savings.
Cappers and Goldman (2010) find
that regulations that require
US
electricity generating utilities to adopt
energy efficiency and
renewable energy portfolio standards simultaneously are likely to be the least
-
cost meth
od of
reducing fossil fuel energy use.
del Río (2010) also finds considerable energy and cost savings
occur in Europe when energy efficiency measures are added to support schemes to encourage
more electricity produced with renewable energy sources.
The i
nteractions are particularly
strong when tradable green certificates


certificates that are issued for every Megawatt hour
(MWh) of electricity generated from renewable energy


are employed using relative quotas.
If
the quota is set in terms of percent
age of overall energy distribution and use, then the energy
efficiency scheme has the potential to reduce electricity demand and production, thus affecting a
utility’s renewable energy requirement. The result is an increase in the uptake of energy
efficie
ncy measures, reduced electricity demand and more rapid attainment of energy saving
targets. The combined policy also provides an incentive for technical innovation and cost
reductions in energy saving technologies.




Assistance to developing economies


In order to implement widespread and effective energy efficiency interventions, many
developing economies will require substantial assistance in o
vercoming the skills, technological
and capital gap

that they face.

This gap is the principal cause of the ma
rket organization and
technological barriers identified in Table 5 that lead to underinvestment in energy efficiency
projects that have favorable rates of return. Targeting development assistance in these areas
should therefore be a pri
ority for the Unite
d States,
European Union

and other major

aid
donors
to improve the adoption of energy efficiency in low income and emerging market economies.


For example, many developing economies face a serious “capital gap” in private and
public financial investments t
hat will constrain them from implementing a long
-
term energy
efficiency strategy.

Access to financing is a major constraint if developing economies are
expected to invest in
such a strategy
.
Even before the current economic crisis, official
development as
sistance contributed US$5.4 billion annually to all energy projects worldwide,

16

which is below the estimated US$8.3 billion in annual low carbon energy investments needed
just for the Asia
-
Pacific region and the $30 billion required for all dev
eloping regions (UN
ESCAP 2008; Wheeler

2008).
In some large emerging market
economies, notably in Asia,
s
ufficient capital is available from the private sector, both in terms of private investments within
developing countries and financing from global an
d regional capital markets, but only if there is
a stable regulatory framework for investment in the developing economy, favorable market
conditions and incentives, and reduced uncertainty regarding the long
-
term price signal for
carbon

(Carmody and Ritchi
e 2007; Taylor et al. 2008
; UN ESCAP 2008
)
.


In addition to the “capital gap” there is also a substantial “skills and technological gap”
for low and middle income economies in adopting
energy efficiency

and low
-
carbon
technologies. Many developing econom
ies spend little on research and development (R&D) on
these technologies and have a chronic shortage of workers with the complementary skills need to
develop and apply low
-
carbon technologies. Instead, most low and middle income countries,
with possibly t
he exception of China
, India and perhaps a few other large emerging market
economies

with some domestic capacity in some clean technologies, are highly dependent on the
importation and transfer of techn
ologies and skills developed elsewhere. It is recognized that the
transfer of new technologies and skills facilitates the development of an indigenous technological
capacity and workforce that enables future innovations and long
-
term adoption of low
-
carbo
n
technologies. But most developing economies lack even the minimum R&D capacity and skilled
workforce capable of attracting the transfer of many
energy efficiency

and low
-
carbon
innovations

(Ockwell et al. 2008)
.


The Clean Developmen
t Mechanism (CDM)

is increasingly viewed as an important
mechanism for solving some of the constraints to reducing the carbon dependency

of developing
economies (
Barbier 2010a
). Certainly
, the CDM has achieved success in securing the financing
and transfer of
energy efficiency
and
other
low
-
carbon technologies in developing countries, and
above all, in effectively creating a global trading market.
There are concerns
, however,

about the
ab
ility of

the current system

to establish a long
-
term global price signal for carbon
.

First, its projects tend to be concentrated in a handful of large emerging market
economies
, such as China
, India,
Brazil and Mexico. Low
-
income economies and particularly
Sub
-
Saharan African countries host very few CDM projects.

Second, most of the expected certified emission reduction (CER) credits earned by 2012
are from mainly large
-
scale projects, such as inciner
ation of greenhouse gases, grid
-
connected
renewable electricity generation, fuel switching, reducing transmission losses, and capturing
fugitive methane emissions. Important sectors, such as transportation, building and construction,
afforestation and ref
orestation, small
-
scale rural energy projects and energy efficiency, are
poorly represented in the current CDM project portfolio.

Third, although the pipeline of projects coming through the CDM has
improved
, the scale
of the mechanism needs to be increased
, so that it can deliver significantly greater finance and
emission reductions globally. In addition, scaling up may require a much simpler and more
transparent mechanism, such as sectoral benchmarks that enable entities to receive CER credits
for achievi
ng a targeted emissions intensity per unit output or technological benchmarks, which
would allow the inclusion of
both energy efficiency improvements as well as
new techniques,
such as carbon capture and storage, second
-
generation biofuels or simple home p
hotovoltaic
solar systems.


17

A variety of proposals have been suggested for scaling up and reforming the CDM,
increasing its coverage of countries to more low
-
income and Sub
-
Saharan economies and
including more sectors and technologies in the mechanism
, incl
uding energy efficiency (Collier
et al. 2008; Hepburn and Stern 2008; Lloyd and Subbarao 2009;
Olsen and Fenhann 2008;
Schneider et al. 2008; Wheeler 2008)
. Such ideas should help the international community agree
on the best way to extend the CDM and glo
bal carbon market beyond 2012
,
preferably as part of
a global climate change agreement, and to include reforms of the mechanism to increase the
coverage of developing economies, the sectors and technologies and the overall financing of
energy efficiency pr
ojects
.


Conclusion

Many G20 governments included substantial energy efficiency measures as part of their
fiscal stimulus packages
that were implemented

in response to the 2008
-
9 recession.

Such
measures included s
upport for energy conservation in buildin
gs; fuel efficient vehicles; public
transport and rail; and improving electrical grid transmission
. As this review has indicated,
many of the energy efficiency measures in these packages have some of the highest net benefits,
and thus should be continued
after the initial stim
ulus programs have
been fully disbursed by
20
12.

However,
such a
long
-
run energy efficiency strategy will have reduc
ed effectiveness
unless it is

supported by a range of complementary pricing policies. These include economy
-
wide pric
ing and regulatory policies, such as carbon pricing, emissions policies and additional
regulatory incentives; removal of fossil fuel subsidies; prescriptive and targeted incentive
programs; behavioral nudging; and combined or improved design of energy effi
ciency programs.

Employing the right portfolio of policies and incentives have been shown to increase both cost
and energy savings considerably,
as well as promote induced
innovation

in low carbon
technologies and energy efficiency.

Both low
-
income and em
erging market economies face substantial technical and financial
barriers that lead to the underfunding of many energy efficiency investment projects with
favorable internal rates of return. There are two ways in which
the international community can
help

alleviate this bottleneck. First, major aid donors should target their assistance to developing
economies
to overcome
the skills, technological and capital gap that they face in implementing
energy efficiency measures over the long term.

Second, r
eform
of the CDM is necessary to
establish a long
-
term global price signal for carbon, and
to increase the coverage of developing
economies, the sectors and technologies and the overall financing of energy efficiency projects.

18

References

Abrams, Burton A. and Ge
orge R. Parsons. 2009. "Is CARS a Clunker?"
The Economists' Voice

Vol. 6. Iss. 8,
Article 4. Available at
http://www.bepress.com/ev/vol6/iss8/art4

Allcott, Hunt and Sendhill Mullainathan. 2010. "Be
havior and Energy Policy."
Science

327:1204
-
1205.

Ansar, Jasmin and Roger Sparks. 2009. "The experience curve, option value, and the energy paradox."
Energy
Policy

37:1012
-
1020.

Barbier, Edward B. 2010a.
A Global Green New Deal: Rethinking the Economic Rec
overy
. Cambridge University
Press, Cambridge, UK.

Barbier,

Edward
B. 2010b. "Global Governance: the G20 and a Global Green New Deal."
Economics: The Open
-
Access, Open
-
Assessment E
-
Journal
, Vol. 4, 2010
-
2.
http://www.economics
-
ejournal.org/economics/journalarticles/2010
-
2

Barbier, Edward
B. 2010c. "Green Stimulus, Green Recovery and Global Imbalances."
World Economics

11(2):1
-
27.

Barbier, E
dward
B. 2010d. "How is the global gr
een new deal going?"
Nature

464:832
-
833.

Battacharya, Soma and Maureen L. Cropper. 2010. "Options for Energy Efficiency in India and Barriers to Their
Adoption: A Scoping Study.


RfF Discussion Paper 10
-
20. April, 2010. Resources for the Future, Washington

DC.

Blesl, Markus, Tom Kober, David Bruchof and Ralf Kuder. 2010. “Effects of climate and energy policy related
measures and targets on the future structure o the European energy system in 2020 and beyond.”
Energy Policy
,
in press.

Bowen, Alex and Nichola
s Stern. 2010. "Environmental policy and the economic downturn. January 2010. Centre
for Climate Change Economics and Policy Working Paper No. 18 and Grantham Research Institute on Climate
Change and the Environment Working Paper No. 16. London, UK.

Capper
s, Peter and Charles Goldman. 2010. “Financial impact of energy efficiency under a federal combined
efficiency and renewable electricity standard: Case study of a Kansas ‘super
-
utility’”.
Energy Policy

38:3998
-
4010.

Carmody, J. and D. Ritchie. 2007.
Invest
ing in Clean Energy and Low Carbon Alternatives in Asia
.

Asian
Development Bank, Manila, The Philippines.

Chandler, William and Holly Gwin. 2008.
Financing Energy Efficiency in China.

Carnegie Endowment for
International Peace, Washington, DC.

Ching, Anna, Mika Clark, Tania Dutta and Yan Zhu. 2010. "Comment on Abrams and Parsons: CARS is Hardly a
Clunker"
The Economists' Voice

(February 2010) Available at
http://www.bepress.com/ev/vol6/i
ss8/art4

Collier, Paul, Gordon Conway and Tony Venables. 2008. “Climate change and Africa.”
Oxford Review of Economic
Policy

24(2):337
-
353.

Council of Economic Advisors

(CEA)
. 2010
a
.
American Recovery and Reinvestment Act of 2009:Second Quarterly
Report
.
January 13, 2010. Executive Office of the President of the United States, Washington, DC.

Council of Economic Advisors (CEA). 2010b.
American Recovery and Reinvestment Act of 2009:Fourth Quarterly
Report
. July 14, 2010. Executive Office of the President of

the United States, Washington, DC.

Council of Economic Advisors (CEA). 2010
c
.
American Recovery and Reinvestment Act of 2009:Fifth Quarterly
Report
. November 18, 2010. Executive Office of the President of the United States, Washington, DC.

Del

o, Pablo.

2010. “A
nalysing the interactions between renewable energy promotion and energy efficiency
support schemes: The impact of different instruments and design elements.”
Energy Policy

38:4978
-
4989.

Dietz, Thomas, Gerald T. Gard
ner, Jonathan Gillingham, Paul C
. Stern and Michael R. Vandenbergh.
2009.
"Household actions can provide a beharioral wedge to
rapidly reduce U.S. carbon emissions."

Proceedings of
the National Academy of Sciences

106(44):18542
-
18546.

Dixon, Robert K., Elizabeth McGowan, Ganna Onysko and

Richard M. Scheer. 2010. “US energy conservation and
efficiency policies: Challenges and opportunities.”
Energy Policy

38(11):6398
-
6408.

Fischer, Carolyn and Richard G. Newell. 2008. "Environmental and technology policies for climate mitigation."
Journal
of Environmental Economics and Management

55:142
-
162.

Gillingham, Kenneth, Richard Newell and Karen Palmer. 2006. "Energy Efficiency Policies: A Retrospective
Examination."
Annual Review of Environment and Resources

31:161
-
182.

Goulder, Lawrence. 2004. “I
nduced Technological Change and Climate Policy.” Pew Center on Global Climate

Change, Arlington,VA.

Hepburn, Cameron and Nicholas Stern. 2008. “An new global deal on climate change.”
Oxford Review of Economic
Policy

24(
2):259
-
279.


19

Houser, Trevor
, S
hahshank Mohan and Robert

Heilmayr. 2009.
A Green Global Recovery? Assessing US Economic
Stimulus and the Prospects for International Coordination.

Policy Brief Number PB09
-
3. Peterson Institute for
International Economics

and World Resources Institute
, Washington, DC, February
.

International Energy Agency (IEA). 2008.
Towards a Sustainable Energy Future: IEA Programme of Work on
Climate Cha
nge, Clean Energy and Sustainable Development.

IEA, Paris.

International Energy Agency (IEA). 2009
a
.
Ensuring Green Growth in a Time of Economic Crisis: The Role of
Energy Technology.

IEA, Paris.

International Energy Agency (IEA). 2009b.
Implementing Energ
y Efficiency Policies: are IEA countries on track?

IEA, Paris.

International Energy Agency (IEA).

2009c
.
Progress with Implementing Energy Efficiency Policies in the G8.

IEA,
Paris.

IEA/OPEC/OECD/World Bank. 2010.
Analysis of the Scope of Energy Subsidies

and the Suggestions for the G
-
20
Initiative.

Joint Report Prepared for Submission to the G
-
20 summit Meeting Toronto (Canada), 26
-
72 June
2010.

Jackson, Jerry. 2010. "Improving energy efficiency and smart grid program analysis with agent
-
based end
-
use
for
ecasting models."
Energy Policy

38(7):3771
-
3780.

Jollands, Nigel, Paul Waide, Mark Ellis, Takao Onoda, Jens Laustsen, Kanako Tanaka, Philippine de T'Serclaes,
Ingrid Barnsley, Rick Bradley and Alan Meier. 2010. "The 25 energy efficiency policy recommendati
ons to the
G8 Gleneagles Plan of Action."
Energy Policy

38(11):6409
-
6418
.

Lloyd, Bob and Srikanth Subbarao. 2009. “Development challenges under the Clean Development Mechanism
(CDM)
)
-
Can renewable energy intitiativ
es be put in place before peak oil?”
Energy Policy

37:237
-
245.

National Highway Traffic Safety Administration (NHTSA). 2009.
Consumer Assistance to Recycle and Save Act of
2009.

Report to Congress. December 2009. NHTSA, Washington, DC.

Nevin, Rick. 2010.
"Energy
-
efficient housing stimulus that pays for itself."
Energy Policy

38:4
-
11.

Ockwell, David G., Jim Watson, Gordon MacKerron, Prosanto Pal and Farhana Yamin. 2008. “Key policy
considerations for facilitating low carbon technology transfer to developing

countries.”
Energy Policy

36:4104
-
4115.

Olsen, Karen

H.

and Jørgen Fenhann, eds.
A Reformed CDM


including new Mechanisms for Sustainable
Development.

Capacity Development for CDM (CD4CDM) Project, UNEP Rise Centre, Denmark, pp. 59
-
72.

Pew Charitable Tru
sts. 2009.
The Clean Energy Economy: Repowering Jobs, Businesses and Investments Across
America.

Pew Charitable Trusts, Washington, DC.

Podesta, John, Todd Stern, and Kit Batten. 2007.
Capturing the Energy Opportunity: Creating a Low
-
Carbon
Economy
. Center

for American Progress
, Washington, D.C.

Pollin, R., Heidi Garrett
-
Peltier, James Heintz, and Helen Scharber.
2008.
Green Recovery: A Program to Create
Good Jobs and Start Building a Low
-
Carbon Economy.

Center for Ameri
can Progress
, Washington DC.

Popp, David. 2010. "Innovation and Climate Policy." NBER Working Paper 15673. National Bureau of Economic
Research, Cambridge, MA.

Renner, Michael, Sean Sweeney and Jill Kubit.2008.
Green J
obs: Towards a Decent Work in a Sustainable, Low
-
Carbon World.
UNEP/ILO/IOE/ITUC, Geneva.

Robins, Nick, Robert Clover and Charanjit Singh. 2009.

Taking stock of the green stimulus
. 23 November 2009.
HSBC Global Research, New York
.

Robins, Nick, Robert Clov
er and D Saravanan. 2010.

Delivering the green stimulus
, 9 March 2010. HSBC Global
Research, New York
.

Schneider, Malte, Andreas Holzer and Volker H. Hoffmann.
2008. “Understanding the CDM’s contribution to
technology transfer.”
Energy Policy

36:2930
-
2938

Tietenberg, Tom. 2009. "Reflections


Energy Efficiency Policy: Pipe Dream or Pipeline to the Future?"
Review of
Environmental Economics and Policy

3(2):304
-
320.

Taylor, Robert P., Chandresekar Govindarajalu, Jeremy Levin, Anke S. Meyer and William A. Ward
. 2008.
Financing Energy Efficiency: Lessons from Brazil, China, India and Beyond.

The World Bank, Washington
DC.

Transue, Morghan and Frank A. Felder.
2010.
"Comparison of energy efficiency incentive programs: Rebates and
white certificates."
Utilities Po
licy

18:103
-
111.

United Nations Economic and Social Commission for Asia

and the Pacific (ESCAP)
.

2008.

Energy Security and
Sustainable Development in Asia and the Pacific.

ESCAP, Bangkok, Thailand
.


20

Wheeler, David. 2008. “Globa
l Warming: An Opportunity for Greatness.” Ch. 2 in Nancy S. Birdsall, ed.
The White
House and the World. A Global Development Agenda for the Next US President.
Center for Global
Development, Washington DC.


Zhou, Nan, Mark D. Levine and Lynn Price. 2010. "
Overview of current energy
-
efficiency policies in China."
Energy Policy

38(11):6439
-
6452
.


21

Table 1
.
Global
Green
Stimulus
, from September 2008 through December 2009




Green Stimulus (US$ bn)




Total
fiscal

stimulus

(US$ bn)


Low
carbon

power
a



Energy

efficiency
b


Waste,

water and
pollution
c




Total



GDP

(US bn)
d


GS

as %
of TS


GS

as %

of GDP

Argentina

13.2





526.4

0.0%

0.0%

Australia

43.8

3.5

6.5

9.9

9.3

773.0

22.7
%

1.3
%

Brazil

3.6





1,849.0

0.0%

0.0%

Canada

31.8

1.1

1.4

0.3

2.8

1,271.0

8.7
%

0.2%

China

64
9.1

1.6

182.4

34.0

218.8

7,099.0

33.
6
%

3.1
%

France

33.7

0.9

5.1

0.2

6.2

2,075.0

18
.2%

0.3%

Germany

104.8


13.8


13.8

2,807.0

13.2%

0.5%

India

13.7


1.0


1.0

2,966.0

7.3
%

0.0%

Indonesia

5.9

0.1

0.0


0.1

843.7

1.7%

0.0%

Italy

103.5


1.3


1.3

1,800.0

1.3%

0.1%

Japan

711
.9

14
.0

29.1

0.2

43.3

4,272.0

6.1
%

1.0
%

Mexico

7.7


0.8


0.8

1,353.0

9.7%

0.1%

Russia

20.0





2,097.0

0.0%

0.0%

Saudi Arabia

126.8



9.5

9.5

546.0

7.5%

1.7%

South Africa

7.5


0.7

0.1

0.8

467.8

10.7%

0.2%

South Korea

7
6
.1

30.9

15.2

13.8

59.9

1,206.0

78.7
%

5
.0%

Turkey






853.9


0.0%

United Kingdom

35.5

0.9

4.9

0.1

5.8

2,130.0

16.3
%

0.3
%

United States

976.9

39.3

58.3

20.0

117.7

13,780.0

12.0%

0.9
%

European Union
e

38.8

13.1

9.6


22.8

14,430.0

58.7%

0.2%

Total G20

3,
004.3

105.3

330.1

78.1

513.5

63,145.8

17.1
%

0.8
%

Total Other
f

314.1

2.3

5.3

1.0

8.6

6,902.9

2.7%

0.1%

Global Total

3,
318.4

107.6

335.4

79.1

522.1

70,048.7

15.7
%

0.7%


Sources: Barbier (2010a); Robins et al. (2009) and (2010).

Notes:

a

Support for renew
able energy (geothermal, hydro, wind and solar, nuclear power, and carbon capture and
sequestration.


b

Support for energy conservation in buildings; fuel efficient vehicles; public transport and rail; and
improving electrical grid transmission.


c

Support

for water, waste and pollution control, including water conservation, treatment and supply.


d

Based on 2007 estimated Gross Domestic Product (GDP) in terms of purchasing power parity, from the
US Central Intelligence Agency The World Factbook, available
at
https://www.cia.gov/library/publications/the
-
world
-
factbook/rankorder/2001rank.html


e

Only the direct contribution by the European Union

(EU)
is inclu
ded.

f
Includes t
he national
stimulus packages of
non
-
G20 EU countries: Austria,
Belgium,
Greece,
Hungary,
the Netherlands, Poland, Portugal
,
Spain

and Sweden
. The non
-
EU countries in this group are Chile, Israel,
Malaysia, New Zealand, Norway, the Phili
ppines, Switzerland, Thailand and Vietnam.


22

Table 2.
Relative
Impacts of a US Green Recovery Program (per $ billion spent)







Program objective

Speed of
Implementation


Employment

Energy

savings

Energy
security

Climate
change


How quickly the
money g
ets spent


Job
-
years
created

Long
-
term
energy cost
reductions

Reductions
in US oil
imports

Direct
emission
reductions

Energy efficiency






Household
weatherization

Weatherize 377,000 homes

High

Moderate

Low

Moderate

Moderate

Federal building
retrofits

Reduce Federal energy
consumption by 8 trillion BTU

High

Moderate

Moderate

Very low

Moderate

Green school
construction

Improve efficiency of all new
schools by 33%

Moderate

Moderate

High

Very low

High

Hybrid tax credit

Additional purchases of
190,000 hy
brids

Moderate

Low

Very low

Very low

Very low

Cash for c
lunkers

500,000 vehicles traded in

Moderate

Very high

Moderate

Moderate

High

Mass transit

Decrease vehicle
-
miles
traveled by 18 million/year

High

High

Very low

Moderate

Very low

Smart
metering

Inst
all smart meters on 4.4
million homes

Moderate

High

Very high

Low

Low

Low carbon power






Production tax credit
extension

1,500 megawatts of additional
wind generation capacity

Low

High

High

Low

High

Investment tax credit
increase

300 megawatts of add
itional
solar power

Low

High

Low

Very low

Low

Carbon capture and
storage demo projects

Fund the CCS component of a
500 MW demo project

Very low

Moderate

Low

Very low

Moderate

Battery research and
development

Develop next generation
battery technology

Ver
y low

Moderate

Very high

Very high

Very high

Conventional stimulus programs






Tax cuts

Increase consumer spending by
$333 million

Very high

Very low

--

--

--

Road investment

Increase vehicle
-
miles traveled
by 11 million/year

High

Moderate

Negative

Ne
gative

Negative


Source: Adapted from Houser et al. (2009).

23

Table 3
.

A
merican
R
ecovery and
R
einvestment
A
ct

Clean Energy Spending and Job
Creation





Funds

($ mn)



Outlays
a

($ mn)

Direct and
indirect
jobs
created
a



Total jobs
created
a,b

Total

job
-
yea
rs
through
2012
c

Energy efficiency

19,935

1,162

12,100

14,500

179,000

Grid modernization

10,453

72

800

1,000

80,600

Advanced vehicles and fuels

6,142

450

4,700

5,800

37,000

Transit and high
-
speed rail

18,113

1,805

18,900

22,900

158,200

Total energy ef
ficiency

54,643

3,489

36,500

44,200

454,800

Renewable generation

26,598

1,479

13,200

16,900

192,00

Carbon capture and sequest.

3,400

4

--

100

26,500

Green innovation and training

3,549

123

1,500

1,700

32,200

Clean energy equipment manuf.

1,624

14

200

2
00

9,500

Other

408

12

200

200

3,700

Total clean energy

(energy efficiency share, %)

90,222

(60.6%)

5,121

(68.1%)

51,700

(70.6%)

63,200

(69.9%)

719,600

(63.2%)


Source: CEA (2010).

Notes:

a
Through December 31, 2009.


b
Includes estimate of additional in
duced jobs created.


c

Estimated. A job
-
year is one person employed for one year.


24


Table 4. Short and Long
-
Term Effects of Various Energy Efficiency Stimulus Measures




Type of effect


Program

Short
-
term
stimulus

Long
-
term
growth

Greenhouse
gas reductio
ns

Environmental
improvement

Energy efficiency retrofits

High

Medium

Medium

Medium

Energy efficiency
improvements in new capital


Low/Medium


Low/Medium


High


Medium/High

Green transport infrastructure

Low/Medium

Low

Medium/High

Medium/High

Cash for c
lunkers

Medium

Low

Low

Low/Medium

Power grid expansion

Low

Medium/High

Low/Medium

Variable


Source: Strand and Toman (2010, Table 5.1).


25

Table 5. Barriers to Implementing Cost
-
Effective Energy Efficiency Policies


Category

Barrier

Key problem associated

with barrier

Necessary condition

Information and
behavioral
barriers

Price distortion

Costs associated with energy and incumbent
technologies may not be included in their
prices; energy and incumbent technologies may
be subsidized

Remove price distortion
s
and subsidies; apply
appropriate market
-
based
instruments.


Information

Information on availability and nature of an
energy efficient product is not easily available
or accessible at time of investment

Improve accessibility and
availability of informati
on
on energy efficient
products.


Transaction costs

Perceived costs involved in making a decision
to purchase and use equipment outweigh
perceived benefits.

Reduce transaction costs
,


Bounded
rationality

Constraints on time, attention, and the ability t
o
process information lead consumers to make
less efficient and sub
-
optimal decisions

Reduce the constraints on
consumers' decisions.

Market
organization
barriers

Finance

The initial cost of a project may be higher than
the finance threshold; poor or con
strained
access to funds.

Enhanced access to finance.


Inefficient market
organization

Principal agent problems; established
companies may have market power to guard
their positions.

Enhanced access to finance;
better market organization;
better designed
policies


Poor regulation at
national or
international level

Regulations and codes not keeping pace with
development or leading to inefficient
outcomes.

Improved regulatory
framework, standards and
implementation

Technological
barriers

Capital stock
turn
over rates

Sunk costs; tax rules or regulations that
encourage long depreciation; inertia

Improve incentives to invest
in energy efficient new
capital


Uncompetitive
market pricing and
practices

Failure to benefit from scale economies,
learning by doing,

technological diffusion

Regulation and reform of
uncompetitive pricing
practices; improve scale
economies, learning by
doing and technological
diffusion.


Technology and
skill
-
specific
barriers

Lack of familiarity with energy efficient
technology or insu
fficient human skills for that
technology

Enhance skills and technical
know
-
how.


Source: Adapted and modified from Jollands et al. (2010).

26

Figure 1.

Total Green Stimulus by Country ($ billion)



Total Green Stimulus Spending by Country ($bn)
514.3
218.0
117.7
59.9
43.3
22.8
13.8
9.9
9.5
6.2
5.8
0
100
200
300
400
500
600
Gl obal total
Chi na
Uni ted States
South Korea
Japan
European Uni on
Germany
Austral i a
Saudi Arabi a
France
Uni ted Ki ngdom


Source: Based on Table 1.



27

Figure 2. Green Stimulus as

a Share of Total Fiscal Stimulus


Green Stimulus as a Share of Total Fiscal Stimulus
15.8%
78.7%
58.7%
33.6%
31.0%
22.7%
18.2%
16.3%
13.2%
12.0%
10.7%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Gl obal share
South Korea
European Uni on
Chi na
Norway
Austral i a
France
Uni ted Ki ngdom
Germany
Uni ted States
South Afri ca

Source: Based on Table 1.



28

Figure 3. Green Stimulus as a Share of Gross Domestic Product (GDP)



Green Stimulus as a Share of Gross Domestic Product (GDP)
0.7%
5.0%
3.1%
1.7%
1.3%
1.3%
1.0%
0.9%
0.5%
0.4%
0.3%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
Gl obal share
South Korea
Chi na
Saudi Arabi a
Austral i a
Sweden
Japan
Uni ted States
Germany
Norway
France



Source: Based on Table 1.


29

Figure 4. Total Energy Efficiency Spending by Country ($ billion)



Total Energy Efficiency Spending by Country ($ bn)
327.9
182.4
58.3
29.1
15.2
13.8
9.6
6.5
5.1
4.9
4.2
0
50
100
150
200
250
300
350
Gl obal Total
Chi na
Uni ted States
Japan
South Korea
Germany
European Uni on
Austral i a
France
Uni ted Ki ngdom
Sweden



Source: Based on
Table 1.

30

Figure 5
. Energy Efficiency as a Share of Total Fiscal Stimulus



Energy Efficiency as a Share of Total Fiscal Stimulus
10.1%
28.1%
24.8%
20.0%
17.2%
15.1%
14.7%
13.7%
13.2%
9.7%
9.3%
0%
5%
10%
15%
20%
25%
30%
Gl obal Total
Chi na
European Uni on
South Korea
Norway
France
Austral i a
Uni ted Ki ngdom
Germany
Mexi co
South Afri ca



Source: Based on Table 1.



31

Figure 6. Energy Efficiency as a Share of Green Stimulus



Energy Efficiency as a Share of Green Stimulus
83%
64%
56%
50%
42%
30%
25%
0%
0%
0%
51%
84%
84%
88%
100%
100%
100%
100%
100%
100%
100%
100%
65%
67%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Austria
Belgium
Germany
India
Israel
Italy
Mexico
Sweden
South Africa
United Kingdom
China
France
Japan
Australia
Global share
Norway
Canada
United States
European Union
Indonesia
South Korea
Poland
Saudi Arabia
Spain



Source: Based on Table 1.



32

Figure 7. Comparison of Green Stimulus and Energy Effici
ency Spending ($ billion)



59.9
43.3
22.8
13.8
9.9
9.5
6.2
5.8
218.0
117.7
58.3
182.4
15.2
29.1
9.6
0
50
100
150
200
250
China
United States
South Korea
Japan
European Union
Germany
Australia
Saudi Arabia
France
United Kingdom
Green Sti mul us ($ bn)
Energy Effi ci ency ($ bn)


Source: Based on Table 1.


33

Figure 8. Disbursement of Global Green Stimulus Spending

($billion)
, 2009
-
2012







Source: Robins et al. (2010).

Notes: e = E
stimated.



34

Box 1. Was CARS a Clunker?


As part of the fiscal stimulu
s efforts implemented during t
he 2008
-
9 recession
, the
Consumer Assistance to Recycle and Save (CARS) Act was signed into law on June 24, 2009.
Popularly known as "Cash for Clunkers", the program provided a subsidy payment to owners
who traded in their ve
hicles to purchase or lease a new, more fuel
-
efficient vehicle. The credit
amount was either $3,500 or $4,500, depending upon the amount of improved fuel efficiency.
CARS appropriated an initial $1 billion, which was then increased by $2 billion in Augus
t 2009.

CARS ran from July 1 through November 1, and paid out a total of $2.
85 billion in
vouchers. The National Highway and Traffic Safety Administration (NHSTSA) estimates that
nearly 680,000 older vehicles were replaced by more fuel
-
efficient vehicles
(NHSTA 2009).
The
average payment per
owner was $4,209,

and the average improvement in fuel efficiency per
vehicle was 9.2 miles.
The NHSTA (2009) estimates that 49% of the new vehicles were
manufactured domestically, and that CARS resulted in a $3.8 bil
lion to $6.8 billion increase in
GDP, with over 60,000 jobs created or saved. The gains in vehicle fuel efficiency are estimated
to
lower

fuel consumption over the next 25 years by 824 million gallons, leading to a decline in
greenhouse gas (GHG) emission
s of 9 million metric tons. The reduction in GHG emissions is
estimated to generate a social benefit of
approximately
$278 million over 25 years (in 2008 $).

In addition, the

decline

in air pollutants, including carbon monoxide (CO), volatile organic
car
bons (VOC),
nitrogen oxides (NO
x
), fine particulate matter (PM2.5) and sulfur dioxide (SO
2
)
is expected to yield additional benefits of $345 billion over the next 25 years (in 2008 $).

However, CARS has also been criticized as being economically inefficien
t. For example,
Abrams and Parsons (2009)
argue that, although taxpayers are paying the full subsidy of $4,209
per vehicle, the net consumer surplus of the payment is only $1,600 for each owner ($2,600
average value of the subsidy less the $1,000 average
value of a clunker). The

average national
cost per vehicle then is $2,600. In comparison, they estimate the environmental benefits of
CARS from the improvements in fuel efficiency to be only $596 per vehicle for reductions in
GHG emissions and air polluti
on. As a result, there is a net social cost of around $2,000 per
vehicle, and with around 700,000 vehicles sold, a total welfare loss of around $1.4 billion.

Ching et al. (2009) counter that Abrams and Parsons have neglected to include in their
estimates
the $2,000 per year benefits in gasoline savings per owner and the $300 in scrap value
per clunker. Added to the $596 environmental benefits, there is now a benefit per vehicle trade
of $3,000, or a net social gain of $400 per vehicle. In addition, Ching
et al (20
10
) argue that the
boosts to GDP and employment should not be ignored, which the NHSTA (2009) suggest are
significant. There may be additional benefits of CARS from encouraging improvements in
technology for future fuel efficient vehicles.

One un
intended impact of CARS was how it was funded. Robins et al. (2009) point out
that $2 billion was siphoned from the American Recovery and Reinvestment Act (ARRA)
allocation to for long
-
term loans for renewable energy. Thus, one of the additional costs of

CARS must be any resulting reduction in low carbon power generation from this reallocation
of
green stimulus
.




35

Box 2.
Economy
-
W
ide Policies and Induced
Innovation in Low Carbon and Energy
Efficiency Technologies


Goulder

(2004)
highlights the role of
tw
o types of economy
-
wide policies in

promoting
induced technological change to reduce carbon dependency

through improved energy efficiency
and adopting low
-
carbon power
.


Such

induced technological innovation

can be efficiently
promoted

in the long run

thro
ugh
combining “direct emission pol
icies”, such as a cap
-
and
-
trade
system

and other emission pricing policies
, with
"technology
-
push policies", such as research
and development (
R&D
)

subsidies

and other policies

for encouraging private sector
innovation
dir
ectly (see table below)
.
T
he boost to private sector R&D and
the gains from learning
-
by
-
doing as the firms become more familiar

with new low
-
carbon
and energy efficient
technologies,
products and processes

lead to long
-
run cost reductions and

induce addit
ional technolog
ical
change
.


For example, d
irect emissions policies
, such as carbon taxes and cap
-
and
-
trade,
would
raise
the
prices of fossil fuels and of energy sources

derived from them, such as electricity. Firms
that utilize these fuels might find it w
orthwhile to invest

more R&D aimed at developing
alternative production processes that reduce fossil fuel consumption,

since discovery of such
processes could now yield significant cost savings. Technology
-
push policies such as subsidy
programs can also in
duce technological change by

stimulating additional R&D.
Goulder finds
evidence that such R&D
has led to large cost reductions in many important energy
-
related areas.

For example, he cites a N
ational Research Council (NRC)
study of

39 R&D programs

in energ
y
efficiency and clean
energy that
found that
these programs taken together

yielded an annual rate
of return of over 100 percent
. Increased utilization of new products, processes and technologies
in turn stimulates learning
-
by
-
doing. The result is furthe
r cost reductions in adopting low
-
carbon
innovations.
A typical estimate is that, for relatively new technologies,

costs fall by 20 percent
for every doubling of cumulative experience.


Based on these findings, Goulder argues that there is strong rationale

for employing both
direct emissions and technology
-
push policies simultaneously, even when the associated cost
reductions from induced technological change are uncertain. The rationale stems from two
market failures in private adoption of low
-
carbon tech
nologies

and energy efficiency innovation
.
First, private investment in R&D tends to be sub
-
optimal as a result of the inability of private
investors to appropriate all the returns to R&D.
Some of the knowledge stemming from R&D
spills over and benefits
firms

other than the investing firm. As a result, in the absence of public
intervention, investments in R&D tend

to fall short of the amount which would maximize social
net benefits. This provides a rationale for technology
-
push policies, including subsidi
es to R&D.

Second, current economic
reliance on
fossil
fuels generally exceeds socially efficient levels
because market prices of these fuels fail to capture

climate
-
related externalities.

Hence
the
market
price
s are well

below the full social cost, the

s
um of private and external cost. This
promotes dependence on fossil fuels that is excessive in terms of

economic efficiency

and

provides a compelling rationale for direct emissions policies

such as carbon taxes

or cap
-
and
-
trade

that can

bring the prices of

fossil fuels more in line with their social cost.


Goulder concludes that both types of policies


direct emissions and technology
-
push
policies


are necessary to promote induced technological change to reduce carbon dependency.
Studies for reducing gre
enhouse gas emissions in the United States show that combining the two
policies substantially lower the costs of meeting targets compared to relying just on a
technology
-
push approach, such a R&D subsidy for low
-
carbon energy options

and energy
efficiency
.


36



Public policies for
inducing innovation in energy efficiency and low
-
carbon power

Direct emissions policies

Technology
-
push policies

Carbon taxes

Subsidies to R&D in
clean energy

technologies

Carbon quotas

Public
-
sector R&D in clean energy

technologi
es

Cap
-
and
-
trade for greenhouse gas (GHG)
emissions

Government
-
financed technology competitions
(with awards)

Subsidies to GHG emission abatement

Strengthened patent rules


Source:

Adapted from Goulder

(

2004
,
Box 1
)
.


37

Annex 1. Major Green and Economic Stimulus Plans by Country and Region, from
September 2008 through December 2009




Country




Package




Date




Period

Total
Fiscal
Stimulus

(US$ bn)


Green
Stimulus

(US$ bn)


Low carbon
power



Energy efficiency


Was
te,
water and
pollution

Renewable

CCS

Building

Vehicle

Rail

Grid

Australia

Nation Building and Jobs Plan

3
-
Feb
-
09

2009
-
12

26.7

3.1

0.32


2.06


0.76




Budget 2009
-
2020

12
-
May
-
09

2009
-
13

17.1

6.8

1.40

1.77

0.17


3.46



China

NDRC Stimulus Package

9
-
Nov
-
08

2009
-
10

586.1

200.8



7.31

1.50

98.65

70.0

23.38


Budget 2009

6
-
Mar
-
09

2009

63.0

17.2

1.58




4.95


10.63

Indonesia

Stimulus Plan

28
-
Jan
-
09

2009

5.9

0.1

0.07




0.03



Japan

Pckg to Safeguard People's Daily Lives

19
-
Dec
-
08

2009 on

485.9

12.4



12.43






Countermeasures to Economic C
risis

10
-
Apr
-
09

2009 on

154.0

23.6

1.07

12.93

5.90

3.70





Second Supplementary Budget

8
-
Dec
-
09

2010

72.0

7.2



4.09

2.95



0.2

South Korea

Green New Deal

6
-
Jan
-
09

2009
-
12

76.1

59.9

1.80

29.05

6.41

1.80

7.01


13
.89

Saudi Arabia

Budget 2009

23
-
Dec
-
08

2009

126.8

9.5







9.45

Asia Pacific
a




1,6350.5

342.0

6.2

43.7

38.4

9.9

116.0

70.0

57.8

European Union

Economic Recovery Plan

26
-
Nov
-
08

2009
-
10

38.8

24.7

0.65

12.49

2.85

3.88


4.85


Germany

Stimulus Plan

5
-
Nov
-
08

2009
-
10

104.8

13.8



10.39

0.69

2.75



France

Revival Plan

10
-
Dec
-
08

2009
-
10

33.7

6.1

0.87


0.57


0.39

4.13

0.19

Italy

Emergency Package

28
-
Nov
-
08

2009 on

103.5

1.3





1.32



Spain

Stimulus Package

27
-
Nov
-
08

2
009

14.2

0.8







0.83

United Kingdom

Budget 2009

22
-
Apr
-
09

2009
-
11

34.9

5.2

0.10

0.64

0.79

1.72

1.93


0.05


Prebudget Report 2009

9
-
Dec
-
09

2010
-
11

0.6

0.6

0.07

0.06

0.39

0.04




Other EU states

Stimulus packages

Jan
-
09

2009
-
10

207.1

3.2

1.9


0.8

0.3

0.0


0.1

European Union



537.0

55.8

3.
6

13.2

15.7

6.7

6.4

9.0

1.2


Norway

Fiscal Stimulus

26
-
Jan
-
09

2009

2.9

0.9

0.2

0.0

0.2

0.0

0.3


0.2

Europe




539.9

56.6

3.8

13.2

15.9

6.7

6.7

9.0

1.4

Canada

Economic Action Plan

27
-
Jan
-
09

2009
-
13

31.8

2.8

0.16

0.92

0.24


0.39

0.79

0.27

Mexico

Aggr for

Home Economics & Emp

7
-
Jan
-
09

2009

7.7

0.8



0.75





United States

Emergency Economic Stabilization Act

3
-
Oct
-
08

10 years

185.0

18.7

10.25

2.60

3.34

0.76

0.33

0.92

0.52


American Recov and Reinvest
Act

1
7
-
Feb
-
09

10 years

787.0

94.1

22.53

3.95

27.40

4.0
0

9.59

11.00

15.58


Budget 2010

Mar
-
09

2010

4.9

4.9





1.00


3.90

Americas
b




1,024.1

121.2

32.9

7.5

31.7

4.8

11.3

12.7

20.3

South Africa

Budget 2009
-
2010

11
-
Feb
-
09

2009
-
11

7.5

0.8



0.10


0.61


0.10

Global




3,318.4

522.1

43.2

64.4

87.1

21.4

135.2

91.7

79.1

Sources: Robins et al. (2010) and Table 1.

Notes:
a

Includes India and Thailand stimulus.
b

Includes Argentina and Chile stimulu
s
.