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FOIA Number: 2017-1095-F
FOIA
MARKER
This is not a textual record. This is used as an
administrative marker by the William J. Clinton
Presidential Library Staff.
Collection/Record Group:
Clinton Presidential Records
Subgroup/Office of Origin:
Council of Economic Advisers
Series/Staff Member:
Michele Jolin
Subseries:
OA/ID Number:
23919
FolderID:
Folder Title:
Partial Staff Only Review Docs - [Climate Change] [3]
Stack:
Row:
Section:
Shelf:
Position:
S
21
1
11
2
Review of DOE Labs Study
Unspecified Policies:
No Program Descriptions: The authors do not estimate the costs or even describe the
programs necessary to stimulate the adoption of the new energy-efficient technology they
find could reduce emissions of approximately 200 million metric tons of carbon
equivalent (MMTCE) by 2010. These reductions correspond to about ½ of the reductions
needed to attain 1990 levels by 2010. In the absence of cost estimates this information is
of little use in the evaluation of alternative policy options.
Costs of Programs: Given reasonable assumptions, government programs may cost many
tens of billions of dollars per year above the costs of existing programs to reduce 200+
million tons of carbon. The marginal cost of emissions reductions, including the cost of
the government program, is likely to greatly exceed the permit price. As a result these
programs may be less cost-effective than a cap-and-trade emissions control program.
Luck: The transportation sector requires "luck" in terms of technological innovation to
achieve the projected emissions reductions. Without a permit price, this luck appears
likely only through stringent standards, such as increasing CAFE.
Overestimates Reductions/Underestimates Costs:
Behavioral Changes Ignored: The analysis appears to ignore the behavioral changes that
offset the energy efficiencies promised by the new technologies. For example, more
efficient windows lead to houses with more glass, and more efficient cars lead to more
vehicle miles traveled. Thus these innovations offer real value to consumers, but smaller
energy savings than engineers forecast.
Cost Effectiveness Calculated Using Average, Not Marginal Prices: Many of the
innovations in electrical use appear to be assumed to be cost effective based on an
assumption of average, not marginal electricity prices. The marginal prices may be half
as much as the average prices.
Price Declines Resulting from Reductions in Energy Demand Are Not Taken into
Account: The study assumes a 12% decrease in energy use, but does not account for this
effect on price when calculating cost effectiveness for energy efficient technologies.
Study Double Counts Emissions Reductions Occurring Under Business-As-Usual: The
labs study double counts 22 MMTCE in reductions in the efficiency case that will occur
under the business-as-usual case.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis: The double
counting of dispatching and retooling coal plants to natural gas results in about 9
MMTCE of overestimated reductions.
Industry Sector Analysis Ignores the Costs of Accelerating Retirement.
The Five Lab Study
Five National Labs Assess Potential of Energy Technologies to
Reduce Carbon Emissions
- LABS: Lawrence Berkeley, Oak Ridge, Argonne, Renewable Energy, Pacific Northwest
- Externally Peer Reviewed: U.Tenn, Monsanto, EPRI, GRI, Harvard, NAS,
Stanford (Huntington), UNC (Link), and UCSB (DeCanio)
Assumes
- Expanded Technology Strategy (R&D and Diffusion)
- Carbon Dioxide has a price and is traded
Lab Study Results
US Carbon Emissions in MMTCE
1800
1800
1700
1700
EIA Carbon Estimate
Business
as Usual
1600
- 1600
1500
- 1500
*
$ 25/T
2010 Impact of High Efficiency +
1400
Low Carbon Technologies for
1400
Two Permit Trading Prices
*
$50/T
1300
1300
1200
1200
1990
1997
2010
Low-Carbon Technologies
Technology
Cost to
Incremental
Carbon Reduction
Generate
Cost
Potential
*cents/kWh
$/ton Carbon
(MMT)
Utilities
- Carbon Dispatch
--
$30
55
- Gas Repowering
2.5 - 3.2
$30
40
(24-83+)
- Biomass co-firing
2.7 - 3.2
$38
17
(16-24+)
- Wind
2.5 - 3.5
$42
7
(6-20+)
- Other
--
$25
9
(7-12)
Industry
- Advanced Turbine
2.5 - 3.5
$40
17
(15-26)
- Industry Specific
--
$40
14
(13-16)
Buildings
- Fuel Cell
5.0 - 6.0
$30
3
Transportation
- Non-corn Ethanol
--
--
16
Total (rounded)
180 (160-250)
*Average costs as of 2005
Energy Efficient Technologies
Technology
Carbon Reduction Potential
(MMT)
Utilities
- Generation Efficiency
8 (7-13)
Industry
- R&D and Diffusion
51
Buildings
- Standards and Diffusion
59
Transportation
- Passenger Cars
28
- Light Trucks
28
- Heavy Trucks
14
- Aircraft
14
Total (rounded)
200
Business and Consumer Annual
Costs and Cost Savings in 2010
40
35
Costs
30
Cost Savings
$ billions
25
20
15
10
5
0
Utilities
Industry
Buildings
Transportation
08/12/97 TUE 12:33 FAX 202 6222633
001
Office of Economic Policv
Department of the Treasurv Washington. D. C.
am
FAX
mors
5 labs
Date: August 12, 1997
Number of pages including cover sheet:
Luku
Eromo
Name
FAX Number
Phone Number
To:
Jeff Frankel
395-6947
Jay Shogren
395-
From:
David Wilcox
202-622-2633
2-2200
REMARKS:
Urgent
For your review
Reply ASAP
Please comment
Attached are partial comments. Having an advance
look may be useful.
08/12/97 TUE 12:33 FAA 202
P.002/011
AUG-11-1997 14:11
CEA
Wilcox
MEMORANDUM
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
DATE:
August 11, 1997
RE:
Review of DOE Labs Study, June 10 Draft
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypothetical climate policy scenarios. The
study finds that, with unspecified "very aggressive policies" and a $50/ton permit price, carbon
emissions can be stabilized at 1990 levels by 2010. In should reviewing be the hisklighted we believe it is
beneficial to highlight several limitations of the study would First, the authors do not provide describe
descriptions of the government programs that stimulate the necessary technology
adoption to reduce emissions of 180 million metric tons of carbon equivalent (MMTCE). Based
Itind
on the actual history of CCAP. we estimate the costs of government programs to achieve these
this
reductions could total $45 billion (1995$), depending on the form of the marginal cost curve.
alarmingly Small
We annuitized this figure and found that government programs could cost $1.1 billion annually
into perpetuity. These are costs in addition to existing program costs to improve energy
yes
efficiency technology development and adoption. Second, the analyses across sectors are not
integrated. Therefore, the penetration rate of energy efficient technologies may be overestimated
because the separate sectoral analyses do not account for declines in fuel prices. Third, the
industry sector analysis ignores the costs of accelerating capital retirement, resulting in either an
overestimate of reductions or 20 underestimate of costs. Fourth, the transportation sector
requires "luck" in terms of technological innovation to achieve the projected emissions
reductions. Fifth, the utilities sector analysis resulted in double counting of emissions reductions.
examples of the qualifications can provide additional insight into the projections of
emissions reductions and costs. Upon receiving the final version of the report and
documentation of the analyses, we will update this review.
Doesn't the analysis
also ignora
Overview of Report
implementation costs?
The Labs Study estimated the carbon emissions reduction opportunities available through
technology development and adoption and fuel switching. The Study employs the Energy
Information Administration's 1997 baseline (AEO97) for the buildings and industry sectors. For
the transportation sector, the authors changed the AEO97 assumption of increasing fuel
efficiency in automobiles to constant fuel efficiency. For the utility sector, the baseline was
modified to reflect a fully competitive bulk-power market in the year 2010. Discharge,
1
08/12/97 TUE 12:34 FAX 202 6222633
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AUG-11-1997 14:11
CEA
P.003/011
shutdown, repowering, and new construction decisions were optimized to select the amount of
capacity that minimized the cost of the power-supply system plus the cost of unserved energy. ?
Compared to AEO97, the final baseline has slightly lower energy prices, larger electricity sales,
and a greater share of gas generation. The study provides emissions reductions from this baseline
for two scenarios: 1) "efficiency and 2)"high efficiency/low carbon" over the period 1998-
2010. The study describes neither the policies necessary to achieve emissions reductions nor the
costs of federal programs for these scenarios, only their outcomes: increased adoption rates and
better technologies.
more electricity and more gasgeneration we
Efficiency Scenario
and with more gasoline consuming consumption, a lot more amen't energy
in
This case assumes that all technologies adopted are at zero or negative net cost to the user given
the baselve
more aggressive federal policies to stimulate development and diffusion of energy efficient
Does This
technologies. The Study estimates that 120 MMTCE will be reduced at negative net cost in this
make sense
wiR
scenario. None of these reductions occur in the utility sector as a function of fuel switching or
lower
what is
technology adoption to increase combustion efficiency.
HigH saying! Efficiency/Low Carbon Scenario
prices?
this
sensence
This case assumes a "greater commitment" to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
?
AEE is not specified), increased domestic and international R&D in low-carbon technologies.
and a "change in psychology". The Study estimates reductions of 180 MMTCE from the
baseline through energy efficient technology adoption at negative net cost (see high efficiency
without low carbon technology in chart below). The carbon permits will yield an additional 150-
200 MMTCE of reductions through low-carbon technology adoption. Given that these occur at a
permit price of $50/ton, the Study estimates the upper limits of these costs to be $10 billion per
year in 2010.
Carbon Emissions (MMTCE): 1990 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 1390
Review
The Lab Study employs several important assumptions in the analyses. Learning about these
qualifications can enhance one $ understanding of the estimates regarding cost-effectiveness and-
2
08/12/97 TUE 12:35 FAX 202 6222633
004
P.004/011
AUG-11-1997 14:12
CEA
discuss
emissions reductions in this study. We present several of the most significant assumptions end-
discussions of their impact below.
The Study Does Not Specify Policies to Achieve Carbon Reductions
"Cost effectiveness is improved because R&D, in combination with increased
deployment efforts. result in declining capital costs. We do not specify the
policies, economic conditions, or exogenous events that could precipitate such
changes" (p. 1.4).
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study makes vague references to policies and only provides details morely
Tea what these unidentified policies would result in: 1) "better technology" (p. 1.5); 2) "higher
penetration rates" (p. 1.6); 3) "changing the capital recovery factor [in industry sector] from 33%
to 15%" (p. 4.8); and 4) "technological breakthroughs" (p. 5.3). These policy effects would
result in reductions of 180 MMTCE for "free": firms and individuals receive energy cost-savings
in excess of technology adoption and implementation costs.
I thought these were ignored?
The report specifically states that the efficiency case reduces, but does not eliminate, market
barriers (p. x), and that implementation costs are ignored (p. xvi). First, we will discuss the
implications of reducing market barriers, and then WE will address the cost issue. Market barriers" can
occur even in well-functioning but occasionally complex, private markets. Information is fully
This is
transmitted among all those in the market, although some information may seem incomplete to
too text-
non-participants (read: policy or market analysts) A person addresses all real costs, but these
Even in The
costs can go undetected by analysts, hence the term "hidden costs". For market barriers, private
lookish.
costs match social costs, and barners resource allocation is efficient. Policy intervention to eliminate a
*
market barrier cannot make society better off and usually makes society worse off, regardless of
could
inserture the implementation mechanism.¹
ial
here from next pacf.
may help
mater
The economics literature has identified several barriers that explain the slow rate of technology
adoption:- 1) qualitative attributes differ across technologies; 2) private attributes of information;
3) private discount rate diverges from social rate) and 4) crogeneous usage levels.
Qualitative artributes of technologies can affect adoption Consumers of technology prefer
Energy Heiency is not one only thing that ma Mcrs to consumers.
Indent
technologies because of a set of characteristics, not just energy efficiency. For example, some
technology consumers may purchase a product with a lower efficiency than another product
because the former is more reliable than the efficiency-superior product.
I
In contrast, policy intervention to eliminate a market failure (such as carbon emissions)
may make society better off, depending on the costs of the intervention.
3
08/12/97 TUE 12:35 FAX 202 6222633
005
AUG-11-1997 14:12
CEA
P.000/011
New technologies may be costly to integrate with existing dues. until
Private attributes of information include the tasks of learning how a new technology works with all compt
one's existing suite of technologies and identifying technology suppliers. Transaction costs exist complex ofa
would expect arbitrage to occur where middlemen consultants would assess the needs of syskmare
with these tasks. If opportunities for economic gains in supplying this information exist, one
potential adopters and match them with the appropriate suppliers. it may make sense fully depreciated replace an
energy-inetticient component with another likenge-
The social discount rates to evaluate new technologies may not fully capture the uncertainty and inefficient
N°
risks faced by individuals and firms. These private actors may use a much higher discount rate component
reflecting the uncertainty of future energy prices, the reliability of the technology, the
irreversibility of a technology investment, and the constraints on their ability to borrow capital.
If innest ment is irreversible, secial = private, doesn't it?
Heterogeneous use of energy intensive technology can affect who benefits from does efficiency not mean that it
is
investments and who does not. Just If a technology is cost-effective on average may cost-
effective for individuals, who do not use much energy. Those who may use the device less
1 intensurely may find it optimal to purchase a less efficient model.
These four types of market barriers illustrate the economic behavior that explains the apparent
under adoption of energy efficiency technology (the "efficiency gap") These barriers clearly
demonstrate the difference between the technological maximum adoption (which only assumes
technology costs) and the economic maximum adoption (which assumes total costs). set of
limate change policies to stimulate technology adoption could increase efficiency, but only
because they also decrease the effect of a market failure (carbon emissions). Social welfare is
improved because the net benefits of indirectly fixing the market failure exceed the costs of
could move
removing the barriers If carbon emissions are appropriately priced (assuming in this case that
$50/ton is the correct carbon price), a policy to remove a barrier (e.g., lower the capital recovery
of this
factor from 33% to 15%), will generate negative net benefits. High adoption rates will be
realized once prices rise enough for some technologies to elear the barriers.
pase. to
From the literature on market barriers, we know that the costs of reducing barriers are greater
than their benefits. In this the authers of the Labs Study da not provide an estimate of the
costs to government of to lewer market barriers to achieve these substantial duations
only provide benefits in terms of projected emissions reductions). We calculated estimates of the
costs of emissions reduction programs based on the government's experience with the Climate
Change Action Plan (CCAP). CCAP promotes carbon reductions through a broad array of
voluntary programs that stimulate "cost-effective"wechnolog financially adoption by in private firms.
Participation hva finn in a CCAP program implies that carbon IS reduced and the firm gains
reducing financially. emig CCAP received appropriations totaling $494 million (1995$) during the FY95
FY97 period. During this period, the Department of Energy and the Environmental Protection
Agency can account for reductions of 14 MMTCE (see attached table). Each ton of carbon
reduced in CCAP cost the federal government. on average, $35.29 (1995$) over this three year
period. Assuming a flat marginal cost curve (MC = AC of CCAP) to reduce 180 MMTCE
beyond the baseline, the government costs of the unidentified policies in the Labs Study would
Need footnote
Note that CCAP efforts are incorporated In the AE097 baseline.
I think
4
questroning why
any goit action is
required to attain truly cost
Heating reductions
08/12/97 TUE 12:37 FAX 202 6222633
P.006/011
AUG-11-1997 14:13
CEA
attaining the reduction 180 MMTCE PER year
A exceed $6.3 billion. To account for the opportunity COST of capital through time, we annuhized
this value and found that overnment costs would about the S150 million annuallysisto
perpetality However, the marginal IS costs of technology adoption in the efficiency and high
efficiency/low carbon scenarios are definitely higher than the 1075 average could cost of be 14 million much metric
tons reduced in the baseline scenario, especially agaregate as more and more efforts to reduce emissions are
higher.
undertaken. Assuming that costs increase 10% for every 10 million metric tons of carbon
reduced. then the government cost would total $16.1 billion (annuffy of $375 million). This is a
slowly increasing marginal cost curve given baseline assumptions of gains in energy efficiency.
Assuming that costs increase 20% for every 10 million metric tons of carbon reduced, then the
cost to government would exceed $45.2 billion (annuity of of ST.T bilien) (see attached chart).
The Sectoral Analyses Are Not Integrated
"The model runs for each of the three end-use sectors were not integrated and
therefore may overstate the effects of technology penetration. In an integrated
modeling effort, fuel prices might fall as consumption declines, resulting in less
penetration of energy-conserving technologies" (p. 1.1).
The analyses of the various sectors assume that the reduction of 180 MMTCE occurs through
energy efficient technology adoption without any price effect. This implies that, with
government programs, private agents will adopt technologies because the benefits (energy cost-
savings) exceed the costs of adoption. The authors claim that these reductions occur at zero or
negative net costs. By failing to account for the effect of decreased energy demand due to energy
efficiency technology adoption, some of those adoption decisions that occur on the margin would
no longer generate positive net benefits for private consumers. The Labs Study indicates that
energy consumption will decline from the baseline by 11.6% under the high efficiency/low
carbon case (p. xi). This decrease in demand should result in a decrease in the price of energy,
and cause some energy efficient technologies to become unattractive to private agents.
In addition. the absence of an integrated analysis precludes an assessment of the economy-wide
effects of a tradeable permit system. As previous studies have indicated, the nature of the permit
allocation (e.g., grandfathering, auction, or a hybrid) and the characteristics of the revenue
recycling (e.g., various adjustments to existing taxes) can affect economy-wide investment.
Understanding the effects on investment is instrumental in assessing the likelihood of success of
these scenarios, given that they rely on substantial R&D and technology adoption.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means
that, at the margin, all investments are not likely to be cost effective at our
assumed 15% CRF [capital recovery factor]. Since we do not have a model to
3 We employed a 7% discount rate to calculate the annuities in this paper.
5
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account for this potential early retirement and the economic losses, we must
caveat our estimates of investment and net costs. the investment cost may be
understated by the amount of loss due to any early retirement that may occur" (p.
4.15).
This assumption implies that one of three results should be accounted for in the analysis. First,
the projected emissions reduction should be revised downward, because the assessment of the
industry sector overestimates technology adoption by ignoring these costs. Second, the cost of
reducing emissions. if the reduced carbon from this sector remains constant, should increase,
with some technology adoption decisions occurring at positive net costs. Third, if the authors
maintain the same costs and emissions estimates, then the costs of government programs to
somehow force down the CRF from 33% to 15% would increase.
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
"[B]ecause the [transportation sector] outcomes postulated in the high
efficiency/low carbon scenario require technological breakthroughs, they require a
certain degree of luck to be achieved by 2010. There are no credible methods to
accurately gauge the probability of such breakthroughs - we believe they stand a
decent chance of occurring with an intensification of research efforts, but we stop
short of claiming they are a likely outcome of such an intensification" (p. 5.3).
Note that this statement includes two qualifications: luck on top of intensified research efforts.
To achieve just the efficiency level of emissions reductions for this sector (73 MMTCE), these
intensified research efforts may require two to ten times existing funding on transportation (p.
5.3). To gain a sense of the magnitude of what such an increase in funding might be, consider
that the Partnership for a New Generation of Vehicles (PNGV) alone is funded at the federal
level at $263 million. Private sector costs of participating in the PNGV are in addition to this
large sum. Further, the estimates of costless (on net) carbon reductions relies on a series of
tenuous assumptions: commercial development of the fuel cell for passenger cars, commercial
availability of cellulosic ethanol (and the elimination of the ethanol excise tax exemption), and
an apparently arbitrary 30% reduction in costs for "certain key technologies" (p. 5.24). These
technologies are not identified, and the report does not provide documentation for the NEMS
model runs conducted for the transportation sector.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options. including:
converting coal-based power plants to natural gas; cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution systems;
extending the life of existing nuclear plants; increasing generation and capacity of
existing hydropower plants; and constructing new powerplants using advanced
coal technologies. Each of these options is assessed independently. Thus.
6
08/12/97 TUE 12:38 FAX 202 6222633
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CEA
LIA/700'-
interactions between the options are not taken into account, and the possibility of
double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First, utilities
undertake fuel switching at the $50/ton permit price through carbon-ordered dispatching.
Second, utilities modify their capital stock through several technology options such as those
listed in the above quotation. As electricity production moves away from coal in the first
analysis, fewer and fewer plants (and therefore potential emissions reductions) will be available
for conversion to natural gas or cofiring with biomass. The second set of analyses were "static"
and did not optimize unit/plant production cost, dispatch, or system load. Conversations with
one of the co-authors (Stanley Hadley of Oak Ridge National Laboratory) indicate that 10 GW of
coal-to-gas conversions (approximately 9 million tons of carbon reductions) were double-
counted.
Furthermore, the analysis of specific options did not examine the effect of increasing fuel prices
(from gas demand due to coal-to-gas repowering). Given the range of assumptions considered in
the study, the authors actually estimated that repowering coal plants for natural gas could result
in carbon reductions between 5 million and 269 million tons (p. 7.2), depending on the gas/coal
price differential, the cost of carbon. and the costs of sulfur dioxide and nitrous oxide emissions.
This is quite a substantial range. The Labs Study estimates that natural gas consumption will
increase 14% to 191% above 2010 baseline consumption. However, the DRI 1.25 run in the IAT
report indicates a 16% decline in natural gas consumption, while the SGM run resulted in only a
negligible decline and Markal-Macro generated a 6% increase in natural gas consumption. These
three models indicate that a non-integrated analysis that does not account for the price change in
natural gas may overestimate natural gas substitution for coal and emissions reductions from fuel
switching.
4
Hadley noted that a subsequent draft of the report should address at least some of the
double counting. but he did not provide details.
7
08/12/97 TUE 12:39 FAX 202 6222633
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Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
-
New
Rebuild America
2.0
1.6
--
1 and 2
Expanded Green Lights and Energy
3.6
3.3
1
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
:
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
I
7
Residential Appliance Standards
6.8
0.2
I
S and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
-
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
:
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
:
New
Expand Markets for Next-Generation
0.2
Lighting Products
New
Fuel Cells Initiative
0.0
I
Industrial Sector Actions
19.0
4.8
I
12
Motor Challenge
8.8
1.8
--
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization
4.2
2.1
--
17
Improve Efficiency of Fertilizer
2.7
0.8
--
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
-
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
-
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
:
Energy Supply Actions
10.8
1.3
--
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
08/12/97 TUE 12:39 FAX 202 6222633
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P.010/011
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
-
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
-
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
--
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
-
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
:
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
-
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
-
32
Expand Natural Gas STAR
3.0
3.4
--
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
-
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.3
1.0
:
Program
Actions to Address Other Greenbouse Gases
16.3
25.4
-
17
Improved Fertilizer Management
4.5
5.3
-
40
Significant New Alternatives Program
5.0
6.4
--
41
HFC-23 Partnerships
5.0
5.0
-
42
Voluntary Aluminum Partnership
1.8
2.2
--
New
Environmental Stewardship Initiative
Not included
6.5
-
Foundation Actions
11.3
-
Climate Wise
Not estimated
1.8
:
Climate Challenge
Not estimated
7.6
--
State and Local Outreach Programs
Not estimated
1.9
-
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
Costs of Reductions ($/ton)
AUG-11-1997 14:15
,000
TC = $45.2 billion; Annuity = $1.1billion
800
TC = $16.1 billion; Annuity = $375 million
08/12/97 TUE 12:40 FAX 202 6222633
CEA
600
TC = $6.4 billion; Annuity = $148 million
400
200
0
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
140-150
150-160
160-170
170-180
Carbon Reductions (MMTC)
MC = AC of CCAP
MC Increases 10% Every 10 MMTC
P.011/01
MC Increases 20% Every 10 MMTC
TTOM
DOELABS3.MEM
Page 1
MEMORANDUM
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
DATE:
August 11, 1997
RE:
Review of DOE Labs Study, June 10 Draft
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypothetical climate policy scenarios. The
study finds that, with unspecified "very aggressive policies" and a $50/ton permit price, carbon
emissions can be stabilized at 1990 levels by 2010. We believe several limitations of the study
should be highlighted; some of these are serious.
First, the authors do not estimate the costs or even describe the programs necessary to
stimulate the adoption of technology necessary to reduce emissions of 180 million metric
tons of carbon equivalent (MMTCE) by 2010. These reductions correspond to about 1/3
of the reductions needed to attain 1990 levels by 2010. In the absence of cost estimates it
is impossible to evaluate the merit of the technology options.
--Based on the actual history of CCAP, we estimate the costs of government
programs to achieve these reductions could total $45 billion (1995$), depending
on the form of the marginal cost curve. We annuitized this figure and found that
government programs could cost $1.1 billion annually into perpetuity. These are
costs in addition to existing program costs to improve energy efficiency
technology development and adoption.
Second, the penetration rate of energy efficient technologies may be overestimated
because the separate sectoral analyses do not account for declines in fuel prices that
would result from adoption.
Third, the industry sector analysis ignores the costs of accelerating capital retirement.
Fourth, the transportation sector requires "luck" in terms of technological innovation to
achieve the projected emissions reductions.
Fifth, the utilities sector analysis resulted in double counting of emissions reductions.
Upon receiving the final version of the report and documentation of the analyses, we will update
this review.
DOELABS3.MEM
Page 2
Overview of Report
The study provides emissions reductions for two scenarios: 1) "efficiency" and 2)"high
efficiency/low carbon", over the period 1998-2010. The study describes neither the policies
necessary to achieve emissions reductions nor the costs of federal programs for these scenarios,
only their outcomes: increased adoption rates and better technologies through technology
development and adoption and fuel switching.
The Study employs the Energy Information Administration's 1997 baseline (AEO97) for the
buildings and industry sectors. For the transportation sector, the authors changed the AEO97
assumption of increasing fuel efficiency in automobiles to constant fuel efficiency. For the
utility sector, the baseline was modified to reflect a fully competitive bulk-power market in the
year 2010. Discharge, shutdown, repowering, and new construction decisions were optimized to
select the amount of capacity that minimized the cost of the power-supply system plus the cost of
unserved energy. Compared to AEO97, the final baseline has slightly lower energy prices, larger
electricity sales, and a greater share of gas generation.
Efficiency Scenario
This case assumes that all technologies adopted are at zero or negative net cost to the user given
more aggressive federal policies to stimulate development and diffusion of energy efficient
technologies. The Study estimates that 120 MMTCE will be reduced at negative net cost in this
scenario. No fuel switching by utilities or industry occurs in this scenario.
High Efficiency/Low Carbon Scenario
This case assumes a "greater commitment" to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
autonomous energy efficiency index is not specified), increased domestic and international R&D
in low-carbon technologies, and a "change in psychology". The Study estimates reductions of
180 MMTCE from the baseline through energy efficient technology adoption at negative net cost
(see high efficiency without low carbon technology in chart below). The carbon permits will
yield an additional 150-200 MMTCE of reductions through low-carbon technology adoption.
Given that these occur at a permit price of $50/ton, the Study estimates the upper limits of these
costs to be $10 billion per year in 2010.
Carbon Emissions (MMTCE): 1990 - 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 - 1390
DOELABS3.MEM
Page 3
Review
The Lab Study employs several important assumptions in the analyses. We discuss several of the
most significant assumptions and discussions of their impact below.
The Study Does Not Specify Policies to Achieve Carbon Reductions
"Cost effectiveness is improved because R&D, in combination with increased
deployment efforts, result in declining capital costs. We do not specify the policies,
economic conditions, or exogenous events that could precipitate such changes" (p. 1.4).
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study merely asserts that these unidentified policies would result
in: 1) "better technology" (p. 1.5); 2) "higher penetration rates" (p. 1.6); 3) "changing the capital
recovery factor [in industry sector] from 33% to 15%" (p. 4.8); and 4) "technological
breakthroughs" (p. 5.3). These policy effects would result in reductions of 180 MMTCE for
"free": firms and individuals receive energy cost-savings in excess of technology costs.
The report specifically states that the efficiency case reduces, but does not eliminate, market
barriers (p. x). Market barriers can occur in well-functioning private markets. Even in the
presence of such barriers, resource allocation is efficient. Policy intervention to eliminate a
market barrier cannot make society better off and usually makes society worse off, regardless of
the implementation mechanism. 1 A set of climate change policies to stimulate technology
adoption could increase efficiency, but only because they also decrease the effect of a market
failure (carbon emissions). Social welfare is improved because the net benefits of indirectly
fixing the market failure exceed the costs of removing the barriers. If carbon emissions are
appropriately priced (assuming in this case that $50/ton is the correct carbon price), a policy to
remove a barrier (e.g., lower the capital recovery factor from 33% to 15%), will generate
negative net benefits. High adoption rates will be realized once prices rise enough for some
technologies to clear the barriers.
The economics literature has identified several barriers that may help explain the slow rate of
technology adoption.
Energy efficiency is not the only thing that matters to consumers. Other qualities of
products appeal to consumers' preferences. For example, some technology consumers
may purchase a product with a lower efficiency than another product because the former
is more reliable than the efficiency-superior product.
New technologies may be costly to integrate with existing technologies. Consumers of
new technologies need to expend effort to understand how to match the two sets of
DOELABS3.MEM
Page 4
technologies. Until all components of a complex system are fully depreciated, it may
make sense to replace an energy-inefficient component with another, likewise inefficient
component.
The social discount rates to evaluate new technologies may not fully capture the
uncertainty and risks faced by individuals and firms. These private actors may use a
much higher discount rate reflecting the uncertainty of future energy prices, the reliability
of the technology, the irreversibility of a technology investment, and the constraints on
their ability to borrow capital.
Just because a technology is cost-effective on average, it does not mean that it is
cost-effective for all individuals. Those who use the device less intensively may find it
optimal to purchase a less efficient model.
These barriers clearly demonstrate the difference between the technological maximum adoption
(which only assumes technology costs) and the economic maximum adoption (which assumes
total costs).
The Labs Study does not provide an estimate of the cost to government of lowering market
barriers. We estimated the costs of emissions reduction based on the government's experience
with the Climate Change Action Plan (CCAP). CCAP promotes carbon reductions through a
broad array of voluntary programs that stimulate "cost-effective" technology adoption by private
firms.2 Firms participating in a CCAP program benefit financially in return for reducing
emissions. CCAP received appropriations totaling $494 million (1995$) during the FY95 -
FY97 period. During this period, the Department of Energy and the Environmental Protection
Agency can account for reductions of 14 MMTCE (see attached table).3 Each ton of carbon
reduced in CCAP cost the federal government, on average, $35.29 (1995$) over this three year
period.
Assuming a flat marginal cost curve (MC = AC of CCAP) to reduce 180 MMTCE beyond the
baseline, the government costs of the unidentified policies in the Labs Study would exceed $6.3
billion. To account for the opportunity cost of capital through time, we annuitized this value and
found that government costs would run about $150 million annually into perpetuity.4 However,
the marginal costs of technology adoption in the efficiency and high efficiency/low carbon
scenarios are definitely higher than the average cost of 14 million metric tons reduced in the
baseline scenario, especially as more and more efforts to reduce emissions are undertaken.
Assuming that costs increase 10% for every 10 million metric tons of carbon reduced, then the
government cost would total $16.1 billion (annuity of $375 million). This is a slowly increasing
marginal cost curve given baseline assumptions of gains in energy efficiency. Assuming that
costs increase 20% for every 10 million metric tons of carbon reduced, then the cost to
government would exceed $45.2 billion (annuity of $1.1 billion) (see attached chart).
Price Declines Resulting from Reductions in Energy Demand Are Not Taken into Account
"The model runs for each of the three end-use sectors were not integrated and therefore
DOELABS3.MEM
Page 5
may overstate the effects of technology penetration. In an integrated modeling effort, fuel
prices might fall as consumption declines, resulting in less penetration of
energy-conserving technologies" (p. 1.1).
The analyses of the various sectors assume that the reduction of 180 MMTCE occurs through
energy efficient technology adoption without any energy price effect. This implies that, with
government programs, private agents will adopt technologies because the benefits (energy
cost-savings) exceed the costs of adoption. The authors claim that these reductions occur at zero
or negative net costs. However, if the energy prices fall due to the decline in energy demand,
some of those adoptions would no longer generate positive net benefits for private consumers.
The Study indicates that energy consumption will decline from the baseline by 11.6% under the
high efficiency/low carbon case (p. xi). This decrease in demand should result in a decrease in
the price of energy, and cause some energy efficient technologies to become unattractive to
private agents.
The efficiency scenario should be modified to reflect the downward effect on prices resulting
from decreased energy consumption. The high efficiency scenario should reflect two
counteracting effects on prices: the decline, in energy consumption and the $50/ton permit fee.
The Study ignores the former effect and insufficiently incorporates the latter effect. For example,
in the buildings chapter, the penetration rate is assumed to be 65% instead of 60% of the
maximum cost-effective technical potential in this scenario because of the $50/ton permit price.5
However, the energy-cost savings calculations for buildings technologies assume the same
energy price as in the business as usual scenario. Since the study assumes that exogenous,
undefined policy influences drive the penetration rates, the penetration rate should be set at 60%
and the energy cost-savings should be recalculated with the appropriate energy price. In the
industry chapter, the high efficiency penetration rate is assumed to be double the rate used in the
efficiency scenario, which is the undefined "normal" rate. It is impossible to determine how
much of this doubling of penetration results from undefined, aggressive policy efforts and how
much results from the permit price.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means that, at
the margin, all investments are not likely to be cost effective at our assumed 15% CRF
[capital recovery factor]. Since we do not have a model to account for this potential early
retirement and the economic losses, we must caveat our estimates of investment and net
costs. the investment cost may be understated by the amount of loss due to any early
retirement that may occur" (p. 4.15).
The omission of costs related to the early retirement of capital implies that either
the projected emissions reduction should be revised downward, because less technology
will be adopted; or
the cost of reducing emissions should be revised upward; or
DOELABS3.MEM
Page 6
the cost of government programs to somehow force down the CRF from 33% to 15%
would increase.
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
"[B]ecause the [transportation sector] outcomes postulated in the high efficiency/low
carbon scenario require technological breakthroughs, they require a certain degree of luck
to be achieved by 2010. There are no credible methods to accurately gauge the
probability of such breakthroughs -- we believe they stand a decent chance of occurring
with an intensification of research efforts, but we stop short of claiming they are a likely
outcome of such an intensification" (p. 5.3).
Note that this statement includes two qualifications: luck on top of intensified research efforts.
These intensified research efforts may require two to ten times existing funding on transportation
(p. 5.3). For perspective on what this might mean, it is worth keeping in mind that the
Partnership for a New Generation of Vehicles (PNGV) alone is funded at the federal level at
$263 million, and there are substantial additional private sector costs.
The "luck" apparently pertains to a number of tenuous technological assumptions: commercial
development of the fuel cell for passenger cars, commercial availability of cellulosic ethanol (and
the elimination of the ethanol excise tax exemption), and an apparently arbitrary 30% reduction
in costs for "certain key technologies" (p. 5.24). These technologies are not identified, and the
report does not provide documentation for the NEMS model runs conducted for the
transportation sector.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options, including: converting
coal-based power plants to natural gas; cofiring coal with biomass; efficiency
improvements in generation and transmission and distribution systems; extending the life
of existing nuclear plants; increasing generation and capacity of existing hydropower
plants; and constructing new powerplants using advanced coal technologies. Each of
these options is assessed independently. Thus, interactions between the options are not
taken into account, and the possibility of double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First,
utilities undertake fuel switching at the $50/ton permit price through
carbon-ordered dispatching. Utilities would change their fuel mix by
dispatching more electricity from their lower carbon-emitting facilities (e.g.,
nuclear, hydropower, and natural gas) and less from coal plants. Second,
utilities modify their capital stock through several technology options such as
those listed in the above quotation. As electricity production moves away from
coal through modified dispatching, fewer and fewer plants (and therefore
potential emissions reductions) will be available for conversion to natural gas or
cofiring with biomass. The second set of analyses were "static" and did not
optimize unit/plant production cost, dispatch, or system load. Conversations
DOELABS3.MEM
Page 7
with one of the co-authors (Stanton Hadley of Oak Ridge National Laboratory)
indicate that 10 GW of coal-to-gas conversions (approximately 9 million tons of
carbon reductions, or 7% of reductions for dispatching and conversions) were
double-counted.5
AUG-11-1997 14:11
CEH
P.002/011
Wilcox
MEMORANDUM
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
DATE:
August 11, 1997
RE:
Review of DOE Labs Study, June 10 Draft
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypothetical climate policy scenarios. The
study finds that, with unspecified "very aggressive policies" and a $50/ton permit price, carbon
beneficial to highlight several limitations of the study would should First, the authors do not provide describe
emissions can be stabilized at 1990 levels by 2010. In reviewing LE the Wishted we believe it is
descriptions of the government programs necessary that to stimulate the necessary technology
180 ton
adoption to reduce emissions of 180 million metric tons of carbon equivalent (MMTCE). Based
Itind
on the actual history of CCAP, we estimate the costs of government programs to achieve these
reductions could total $45 billion (1995$), depending on the form of the marginal cost curve.
1/3
14 of
We annuitized this figure and found that government programs could cost $1.1 billion annually
small
into perpetuity. These are costs in addition to existing program costs to improve energy
the way
efficiency technology development and adoption. Second, the analyses across sectors are not
integrated. Therefore, the penetration rate of energy efficient technologies may be overestimated
because the separate sectoral analyses do not account for declines in fuel prices. Third, the
steeply
industry sector analysis ignores the costs of accelerating capital retirement, resulting in either an
mereasi
overestimate of reductions or an underestimate of costs. Fourth, the transportation sector
requires "luck" in terms of technological innovation to achieve the projected emissions
marging
reductions. Fifth, the utilities sector analysis resulted in double counting of emissions reductions.
cost
These examples of the qualifications can provide additional insight into the projections of
emissions reductions and costs. Upon receiving the final version of the report and
documentation of the analyses, we will update this review.
Doesn't the analysis
also ignora
Overview of Report
implementation costs?
The Labs Study estimated the carbon emissions reduction opportunities available through
technology development and adoption and fuel switching. The Study employs the Energy
Information Administration's 1997 baseline (AEO97) for the buildings and industry sectors. For
the transportation sector, the authors changed the AEO97 assumption of increasing fuel
efficiency in automobiles to constant fuel efficiency. For the utility sector, the baseline was
modified to reflect a fully competitive bulk-power market in the year 2010. Discharge,
1
AUG-11-1997
LCH
shutdown, repowering, and new construction decisions were optimized to select the amount of
capacity that minimized the cost of the power-supply system plus the cost of unserved energy ?
Compared to AEO97, the final baseline has slightly lower energy prices, larger electricity sales,
and a greater share of gas generation. The study provides emissions reductions from this baseline
for two scenarios: 1) "efficiency" and 2) 'high efficiency/low carbon" over the period 1998-
2010. The study describes neither the policies necessary to achieve emissions reductions nor the
costs of federal programs for these scenarios, only their outcomes: increased adoption rates and
better technologies.
with more electricity and more 995 generate
Efficiency Scenario
and more gasoline conjumption, aren't we
consuming a lot more energy in
This case assumes that all technologies adopted are at zero or negative net cost to the user given
the baselli
more aggressive federal policies to stimulate development and diffusion of energy efficient
Does This
technologies. The Study estimates that 120 MMTCE will be reduced at negative net cost in this
make sens
scenario.
None of these reductions occur in the utility sector as a function of fuel switching or
wir
what is
technology adoption to increase combustion efficiency.
lower
this
High saying! Efficiency/Low Carbon Scenario
prices?
sentence
This case assumes a "greater commitment" to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
AEE is-not specified), increased domestic and international R&D in low-carbon technologies,
and a "change in psychology". The Study estimates reductions of 180 MMTCE from the
baseline through energy efficient technology adoption at negative net cost (see high efficiency
without low carbon technology in chart below). The carbon permits will yield an additional 150-
200 MMTCE of reductions through low-carbon technology adoption. Given that these occur at a
permit price of $50/ton, the Study estimates the upper limits of these costs to be $10 billion per
year in 2010.
Carbon Emissions (MMTCE): 1990 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 1390
Review
The Lab Study employs several important assumptions in the analyses. Loarning about these
qualifications can enhance one understanding of the estimates regarding cost effectivenes and
2
discuss
emissions reductions in this study. We present several of the most significant assumptions and-
discussions of their impact below.
The Study Does Not Specify Policies 10 Achieve Carbon Reductions
"Cost effectiveness is improved because R&D, in combination with increased
deployment efforts, result in declining capital costs. We do not specify the
policies, economic conditions, or exogenous events that could precipitate such
changes" (p. 1.4).
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study makes vague references to policies and only provides details. morely
assertsthate on what these unidentified policies would result in: 1) "better technology" (p. 1.5); 2) "higher
penetration rates" (p. 1.6); 3) "changing the capital recovery factor [in industry sector] from 33%
to 15%" (p. 4.8); and 4) "technological breakthroughs" (p. 5.3). These policy effects would
result in reductions of 180 MMTCE for "free": firms and individuals receive energy cost-savings
in excess of technology adoption and implementation costs.
I thought these were ignored?
The report specifically states that the efficiency case reduces, but does not eliminate, market
barriers (p. x), and that implementation costs are ignored (p. xvi). First, we will discuss the
implications of reducing market barriers, and then we will address the cost issue. Market barriers" can
occur even in well-functioning, but occasionally complex, private markets. Information is fully
This is
transmitted among all those in the market, although some information may seem incomplete to
so text-
non-participants (read: policy or market analysts) A person addresses all real costs, but these EVEN in The
costs can go undetected by analysts, hence the term "hidden costs". For market barriers, private
Lookish.
costs match social costs, and resource allocation is efficient. Policy intervention to eliminate a
of berners
market barrier cannot make society better off and usually makes society worse off, regardless of
could # ial
the implementation mechanism.¹
here from next pace.
may help
mater
The economics literature has identified several barriers that explain the slow rate of technology
adoption:- 1) qualitative attributes differ across technologies; 2) private attributes of information;
3) private discount rate diverges from social rate) and 4) erogeneous usage levels.
Energy efficiency is not the only thing that ma Hers to consumers.
Indent
Qualitative attributes of technologies can affect adoption Consumers of technology prefer
technologies because of a set of characteristics, not just energy efficiency. For example, some
technology consumers may purchase a product with a lower efficiency than another product
because the former is more reliable than the efficiency-superior product.
1
In contrast, policy intervention to eliminate a market failure (such as carbon emissions)
may make society better off, depending on the costs of the intervention.
3
New technologies may be costly to imtegrate with existing ones. until
Private attributes of information include the tasks of learning how a new technology works with all compan
one's existing suite of technologies and identifying technology suppliers. Transaction costs exist ofa
with these tasks. If opportunities for economic gains in supplying this information exist, one
comptex
would expect arbitrage to occur where middlemen consultants would assess the needs of systemare
potential adopters and match them with the appropriate suppliers. it may make sense fully depreciate replace a
encrgy-inetticient component with another likenise.
The social discount rates to evaluate new technologies may not fully capture the uncertainty and inetticer
N°
risks faced by individuals and firms. These private actors may use a much higher discount rate companer
reflecting the uncertainty of future energy prices, the reliability of the technology, the
irreversibility of a technology investment, and the constraints on their ability to borrow capital.
If innest ment is inreversible, secial = private, doesn't it?
Heterogeneous use of energy Just intensive because technology can affect who benefits from &does efficiency not mean
that
if
is
investments and who does not. If a technology is cost-effective on average HE may not be cost-
effective for individuals' who do not use much energy. These who may use the device less
utensmily may find it optimal to purchase a less efficient model.
These four types of market barriers illustrate the economic behavior that explains the apparent
under adoption of energy efficiency technology (the "efficiency gap"). These barriers clearly
demonstrate the difference between the technological maximum adoption (which only assumes
technology costs) and the economic maximum adoption (which assumes total costs). A set of
climate change policies to stimulate technology adoption could increase efficiency, but only
because they also decrease the effect of a market failure (caibon emissions). Social welfare is
improved because the net benefits of indirectly fixing the market failure exceed the costs of
(or
removing the barriers If carbon emissions are appropriately priced (assuming in this case that
$50/ton is the correct carbon price), a policy to remove a barrier (e.g., lower the capital recovery
of 0 this
factor from 33% to 15%), will generate negative net benefits. High adoption rates will be
page. to prevous
realized once prices rise enough for some technologies to elear the barriers.
From the literature on market barriers, we know that the costs of reducing barriers are greater
than their benefits. In this case the authors of the Labs Study do not provide an estimate of the
of lowerng
costs to government to lower market barriers to achieve these substantial reductions (and they
only provide benefits in terms of projected emissions reductions). We calculated estimates of the
costs of emissions reductions programs based on the government's experience with the Climate
Change Action Plan (CCAP). CCAP promotes carbon reductions through a broad array of
voluntary programs that stimulate in "cost-effective" technology adoption by private firms.
benefit financially in
reducing
Participation emissions, by a firm in a CCAP program implies that carbon IS reduced and the firm gains
financially. CCAP received appropriations totaling $494 million (1995$) during the FY95
FY97 period. During this period, the Department of Energy and the Environmental Protection
Agency can account for reductions of 14 MMTCE (see attached table). Each ton of carbon
reduced in CCAP cost the federal government, on average, $35.29 (1995$) over this three year
period. Assuming a flat marginal cost curve (MC = AC of CCAP) to reduce 180 MMTCE
beyond the baseline, the government costs of the unidentified policies in the 1 abs Study would
2
Need footnote
I think
Note that CCAP efforts are incorporated in the AE09 baseline.
stockflows anced
4
questroning why
any govt action is
required to attain truly cost
attaining the reduction 180 MMTCE BY year
^ exceed $6.3 billion. To account for the opportunity COSE of capital through time, we annuftized
this value and found that government costs would sume run about the $150 million annually
perpetuity: However, the marginal as 11 costs almos of technology adoption in the efficiency and high
efficiency/low carbon scenarios are definitely higher than the average could cost of to 14 million much metric
tons reduced in the baseline scenario, especially aggregast as more and 1075 more efforts to reduce emissions are
higher.
undertaken. Assuming that costs increase 10% for every 10 million metric tons of carbon
reduced, then the government cost would total $16.1 billion per (annuffy of $375 million). This is a
slowly increasing marginal cost curve given baseline assumptions of gains in energy efficiency.
Assuming that costs increase 20% for every 10 million metric tons of carbon reduced, then the
cost to government would exceed $45.2 billion (annuity of $1.1 officen) (see attached chart).
Price declines resul Hing from reductions in energy demant
The Are price increases
The Sectoral Analys Not Integrated are not taken into recount.
"The model runs for each of the three end-use sectors were not integrated and
induced
the permits tavien modeling effort, fuel prices might fall as consumption declines, resulting in less
by
therefore may overstate the effects of technology penetration. In an integrated
schime into account? penetration of energy-conserving technologies" (p. IS 1.1). this right? why the with
the $50/ton
The analyses of the various sectors assume that the reduction of 180 MMTCE occurs through
fee?
energy efficient technology adoption without any price effect This implies that, with
Add FN
government programs, private agents will adopt technologies because the benefits (energy cost-
savings) exceed the costs of adoption. The authors the enery claim that these fall reductions due Qccur to the at zero decliner or
negative net costs. By failing However, to account If for the effectof prices decreased energy demand due to energy
efficiency technology adoption, some of those adoption decisions that occur on the margin would
no longer generate positive net benefits for private consumers. The Labs Study indicates that
energy consumption will decline from the baseline by 11.6% under the high efficiency/low
carbon case (p. xi). This decrease in demand should result in a decrease in the price of energy,
and cause some energy efficient technologies to become unattractive to private agents.
In addition. the absence of an integrated analysis precludes an assessment of the economy-wide
effects of a tradeable permit system. As previous studies have indicated, the nature of the permit
allocation (e.g., grandfathering, auction, or a hybrid) and the characteristics of the revenue
recycling (e.g., various adjustments to existing taxes) can affecteconomy-wide investment.
Understanding the effects on investment is instrumental in assessing the likelihood of success of
these scenarios, given that/they rely on substantial R&D and technology adoption.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means
that, at the margin, all investments are not likely to be cost effective at our
assumed 15% CRF [capital recovery factor]. Since we do not have a model to
3 We employed a 7% discount rate to calculate the annuities in this paper.
I'd like to see this neallys hammer 2 points:
(1) Firms will do what is profitable negardless of you if programs;
(2) Assumed hurdle rate for industry is exagenously reduced from
account for this potential early retirement and the economic losses, we must
caveat our estimates of investment and net costs. the investment cost may be
understated by the amount of loss due to any early retirement that may occur" (p.
4.15).
?
The mission of costs repled to early reternement of capital implies that
This assumption implies thatcone of three results should be accounted for in the analysis First. will either be
the projected emissions reduction should be revised downward, because the less assessment technology of the
adepted
industry sector overestimates technology adoption by ignoring these costs. Second, the cost of
because with some technology adoption adopted decisions occurring at positive net costs' Third, if the authors
reducing emissions will the reduced be carbon from this sector remains constant, should increase, benevised up
maintain the same costs and emissions estimates, then the costs of government programs to
? This
somehow force down the CRF from 33% to 15% would increase.
locsn't
flow
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
logically
"[B]ecause the [transportation sector] outcomes postulated in the high
efficiency/low carbon scenario require technological breakthroughs, they require a
certain degree of luck to be achieved by 2010. There are no credible methods to
accurately gauge the probability of such breakthroughs - we believe they stand a
decent chance of occurring with an intensification of research efforts, but we stop
short of claiming they are a likely outcome of such an intensification" (p. 5.3).
Note that this statement includes two qualifications: luck on top of intensified research efforts.
To achieve just the efficiency level of emission reductions for this sector (73 MMTCE), these
intensified research efforts may require two to ten times existing funding on transportation (p.
For
5,3). To gain a sense of the magnitude of what such an increase in funding might be, epnsider
perspes what this might worth keep
that the Partnership for and a New There Generation are of substatial Vehicles (PNGV) alone is funded at the federal
level at $263 million, Private sector costs, of participating in the PNGV are in addition to this
It
The
"luck"
large our Further, the estimates of costless (on net) carbon reductions relies on a series of
tenuous assumptions: commercial development of the fuel cell for passenger cars, commercial
apparently
availability of cellulosic ethanol (and the elimination of the ethanol excise tax exemption), and
pertains
an apparently arbitrary 30% reduction in costs for "certain key technologies" (p. 5.24). These
to a
technologies are not identified, and the report does not provide documentation for the NEMS
jumber
model runs conducted for the transportation sector.
of
tenvous
technologicals
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options, including:
converting coal-based power plants to natural gas; cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution systems;
extending the life of existing nuclear plants; increasing generation and capacity of
existing hydropower plants; and constructing new powerplants using advanced
coal technologies. Each of these options is assessed independently. Thus,
6
interactions between the options are not taken into account, and the possibility of
double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First, utilities
undertake fuel switching at the $50/ton permit price through dispatching
Second, utilities modify their capital stock through several technology options such as those
listed in the above quotation. As electricity production moves away from coal in the first
analysis, fewer and fewer plants (and therefore potential emissions reductions) will be available
what
for conversion to natural gas or cofiring with biomass. The second set of analyses were "static"
ufirst"
and did not optimize unit/plant production cost, dispatch, or system load. Conversations with
analysis?
one of the co-authors (Stanley Hadley of Oak Ridge National Laboratory) indicate that 10 GW of
coal-to-gas conversions (approximately 9 million tons of carbon reductions) were double-
counted.⁴
express as a % ofsomething
Furthermore, the analysis of specific options did not examine the effect of increasing fuel prices
(from gas demand due to coal-to-gas repowering). Given the range of assumptions considered in
the study, the authors actually estimated that repowering coal plants for natural gas could result
in carbon reductions between 5 million and 269 million tons (p. 7.2), depending on the gas/coal
price differential, the cost of carbon, and the costs of sulfur dioxide and nitrous oxide emissions.
This is quite a substantial range. The Labs Study estimates that natural gas consumption will
increase 14% to 191% above 2010 baseline consumption. However, the DRI 1.25 run in the IAT
report indicates a 16% decline in natural gas consumption, while the SGM run resulted in-eady a
negligible decline and Markal-Macro generated a 6% increase in natural gas consumption. These
three models indicate that a non-integrated analysis that does not account for the price change in
natural gas may overestimate natural gas substitution for coal and emissions reductions from fuel
switching.
message is a bit murky.
what point?
4
Hadley noted that a subsequent draft of the report should address at least some of the
double counting, but he did not provide details.
7
Auu-11-1yy 14.14
LCH
P.009/011
Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
-
New
Rebuild America
2.0
1.6
-
I and 2
Expanded Green Lights and Energy
3.6
3.3
-
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
--
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
-
7
Residential Appliance Standards
6.8
0.2
-
s and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
-
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
-
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
--
New
Expand Markets for Next-Generation
0.2
-
Lighting Products
New
Fuel Cells Initiative
0.0
:
Industrial Sector Actions
19.0
4.8
-
12
Motor Challenge
8.8
1.8
-
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization.
42
2.1
-
17
Improve Efficiency of Fertilizer
2.7
0.8
--
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
-
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
--
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
--
Energy Supply Actions
10.8
1.3
-
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
HOG-11-1997 14:15
LEH
P.010/011
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
-
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
-
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
--
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
I
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
:
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
-
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
-
32
Expand Natural Gas STAR
3.0
3.4
--
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
-
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.8
1.0
--
Program
Actions to Address Other Greenhouse Gases
16.3
25.4
-
17
Improved Fertilizer Management
4.5
53
--
40
Significant New Alternatives Program
5.0
6.4
-
41
HFC-23 Partnerships
5.0
5.0
-
42
Voluntary Aluminum Partnership
1.8
22
--
New
Environmental Stewardship Initiative
Not included
6.5
--
Foundation Actions
11.3
-
Climate Wise
Not estimated
1.8
--
Climate Challenge
Not estimated
7.6
--
State and Local Outreach Programs
Not estimated
1.9
-
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
Costs of Reductions ($/ton)
HOG-11-1997 14:15
TC = $45.2 billion; Annuity = $1.1billion
1,000
800
TC = $16.1 billion; Annuity = $375 million
CEA
600
TC = $6.4 billion; Annuity = $148 million
400
200
0
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
140-150
150-160
160-170
170-180
Carbon Reductions (MMTC)
MC = AC of CCAP
MC Increases 10% Every 10 MMTC
IIA/IIA'H
MC Increases 20% Every 10 MMTC
MEMORANDUM
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
DATE:
August 7, 1997
RE:
Review of DOE Labs Study, June 10 Draft
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypothetical climate policy scenarios. The
study finds that, with "very aggressive policies" and a $50/ton permit price, carbon emissions can
be stabilized at 1990 levels by 2010. In reviewing the report we believe it is beneficial to
highlight several of the caveats the authors explicitly state. First the authors do not provide
enfitront
descriptions of the government programs necessary to stimulate the necessary technology
adoption to reduce 180 million metric tons of carbon emissions. We devised an estimate of the costs of
3
government programs to achieve these reductions based on the nation's experience with CCAP,
and found that program costs could total $45 billion (1995$). Second, the analyses across sectors
are not integrated. Therefore, the penetration rate of energy efficient technologies may be
overestimated because the separate sectoral analyses do not account for cross-sector interactions
(e.g., in energy prices). Third, the industry sector analysis ignores the costs of accelerating
capital retirement, resulting in either an overestimate of reductions or an underestimate of costs.
Fourth, the transportation sector requires "luck" in terms of technological innovation to achieve
the projected emissions reductions. Fifth, the utilities sector analysis resulted in double counting
of emissions reductions. These examples of the qualifications can provide additional insight into
the projections of emissions reductions and costs. Upon receiving the final version of the report
and documentation of the analyses, we will conduct a more thorough review.
Overview of Report
The Labs Study estimated the carbon emissions reduction opportunities available through
technology development and adoption and fuel switching. The Study employs the Energy
Information Administration's 1997 baseline (AEO97) for the buildings and industry sectors. For
the transportation sector, the authors changed the AEO97 assumption of increasing fuel
efficiency in automobiles to constant fuel efficiency. For the utility sector, the baseline was
modified to reflect a fully competitive bulk-power market in the year 2010. Discharge,
shutdown, repowering, and new construction decisions were optimized to select the amount of
capacity that minimized the cost of the power-supply system plus the cost of unserved energy.
Compared to AEO97, the final baseline has slightly lower energy prices, larger electricity sales,
1
neither
and a greater share of gas generation. The study provides emissions reductions from this baseline
for two scenarios: 1) "efficiency" and 2)"high efficiency/low carbon". The study does not
describe the policies necessary to achieve emissions reductions nor the costs of federal programs
for these scenarios, only their outcomes: increased adoption rates and better technologies.
Efficiency
This case assumes that all technologies adopted are cost-effective given more aggressive federal
policies to stimulate development and diffusion of energy efficient technologies. Since these
technologies are cost-effective, they all have a net cost less than or equal to zero. The Study
estimates that 120 will be reduced at negative net cost in this scenario. None of these
reductions occur in the utility sector as a function of fuel switching or technology adoption to
increase combustion efficiency.
High Efficiency/Low Carbon
reductions of
of
This case assumes a "greater commitment" to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
AEEI is not specified), increased domestic and international R&D in low-carbon technologies,
and a "change in psychology". The Study estimates/ 180 hithics of carbon emissions reductions
from the baseline through energy efficient technology adoption at negative net cost (see high
efficiency without low carbon technology in chart below). The carbon permits will yield an
additional 150-200 MATGE of reductions through low-carbon technology adoption. Given that
these occur at a permit price of $50/ton, the Study estimates the upper limits of these costs to be
$10 billion per year in 2010.
Carbon Emissions (hintse): MMD 1990 - 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 - 1390
(20
180
Review
The authors of the Lab Study are forthright about many of the assumptions underlying the
analysis. Learning about these qualifications can enhance one's understanding of the estimates
regarding cost-effectiveness and emissions reductions in this study. We present several of the
most significant assumptions and discussions of their impact below.
The Study Does Not Specify Policies to Achieve Carbon Reductions
2
"Cost effectiveness is improved because R&D, in combination with increased
deployment efforts, result in declining capital costs. We do not specify the
policies, economic conditions, or exogenous events that could precipitate such
changes" (p. 1.4).
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study makes vague references to policies and only provides details
on what these unidentified policies would result in: 1) "better technology" (p. 1.5); 2) "higher
penetration rates" (p. 1.6); 3) "changing the capital recovery factor [in industry sector] from 33%
to 15%" (p. 4.8); and 4) "technological breakthroughs" (p. 5.3).
The authors assume that policies are implemented that significantly lower the barriers to
technology adoption without any discussion of their costs. In effect, this assumes the magical
wand of government intervention is waved to lower technology marginal costs enough to get 180
million tons of carbon reductions for "free": firms and individuals receive energy cost-savings in
excess of the technology adoption and implementation costs.
CEA AlternotiveCostErmates
Since the authors do not provide an estimate of the costs to government to lower market barriers
to achieve these substantial reductions, we calculated estimates of the costs of emissions
reductions programs based on the government's experience with the Climate Change Action Plan
(CCAP). CCAP promotes carbon reductions through a broad array of voluntary programs that
stimulate "cost-effective" technology adoption by private firms. Participation by a firm in a
CCAP program implies that carbon is reduced and the firm gains financially.¹ CCAP received
appropriations totaling $494 million (1995$) during the FY95 - FY97 period. During this period,
the Department of Energy and the Environmental Protection Agency can account for 14 million
of
metric tons of reduced earbon (see attached table). Each ton of carbon reduced in CCAP cost the 14 MMICE
federal MUTTE government $35.29 (1995$). Assuming a flat marginal cost curve (MC=AC) to reduce
can he
180 million metric tons of earbon beyond the baseline, the government costs of the unidentified
expected
policies in the I abs Study would exceed $6.3 billion. However, the marginal costs of technology
prequied to EMISSAS requestions
adoption are definitely higher than the average cost of the first 14 million metric tons, especially
to be
as more and more efforts to reduce emissions are undertaken. Assuming that costs increase 10%
at
for every 10 million metric tons of carbon reduced, then the government cost would come to
least as
$16.1 billion. This is slowly increasing marginal cost curve given baseline assumptions of gains
as
in energy efficiency. Assuming that costs increase 20% for every 10 million metric tons of
high
carbon reduced, then the cost to government would exceed $45.2 billion.
The Sectoral Analyses Are Not Integrated
1 Note that CCAP efforts are incorporated in AEO97.
3
"The model runs for each of the three end-use sectors were not integrated and
therefore may overstate the effects of technology penetration. In an integrated
modeling effort, fuel prices might fall as consumption declines, resulting in less
penetration of energy-conserving technologies" (p. 1.1).
The analyses of the various sectors assume that 180 million tons of carbon reduction occurs
through energy efficient technology adoption without the price effect of a $50/ton permit. This
implies that, with government programs, private agents will adopt technologies because the
benefits (energy cost-savings) exceed the costs of adoption. The authors claim that these
reductions occur at negative net costs. By failing to account for the effect of decreased energy
demand due to energy efficiency technology adoption, some of those adoption decisions that
occur on the margin would no longer generate positive net benefits for private consumers. The
Labs Study indicates that energy consumption will decline from the baseline by 11.6% under the
high efficiency/low carbon case (p. xi). This decrease in demand should result in a decrease in
the price of energy, and cause some energy-intensive technologies to become unattractive to
private agents.
In addition, the absence of an integrated analysis precludes an assessment of the economy-wide
effects of a tradeable permit system. As previous studies have indicated, the nature of the permit
allocation (e.g., grandfathering, auction, or a hybrid) and the characteristics of the revenue
recycling (e.g., various adjustments to existing taxes) can affect economy-wide investment.
Understanding the effects on investment is instrumental in assessing the likelihood of success of
these scenarios, given that they rely on substantial R&D and technology adoption.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means
that, at the margin, all investments are not likely to be cost effective at our
assumed 15% CRF [capital recovery factor]. Since we do not have a model to
account for this potential early retirement and the economic losses, we must
caveat our estimates of investment and net costs. the investment cost may be
understated by the amount of loss due to any early retirement that may occur" (p.
4.15).
This assumption implies that one of three results should be accounted for in the analysis. First,
the projected emissions reduction should be revised downward, because the assessment of the
industry sector overestimates technology adoption by ignoring these costs. Second, the cost of
reducing emissions, if the reduced carbon from this sector remains constant, should increase,
with some technology adoption decisions occurring at positive net costs. Third, if the authors
maintain the same costs and emissions estimates, then the costs of government programs to
somehow force down the CRF from 33% to 15% would increase.
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
4
"[B]ecause the [transportation sector] outcomes postulated in the high
efficiency/low carbon scenario require technological breakthroughs, they require a
certain degree of luck to be achieved by 2010. There are no credible methods to
accurately gauge the probability of such breakthroughs -- we believe they stand a
decent chance of occurring with an intensification of research efforts, but we stop
short of claiming they are a likely outcome of such an intensification" (p. 5.3).
Note that this statement includes two qualifications: luck on top of intensified research efforts.
To achieve just the efficiency level of emissions reductions for this sector (73 million MMTCO tons), these
intensified research efforts may require two to ten times existing funding on transportation (p.
5.3). To gain a sense of the magnitude of what such an increase in funding might be, consider
that the Partnership for a New Generation of Vehicles alone is funded at the federal level at $263
million. Further, the estimates of costless (on net) carbon reductions relies on a series of tenuous
assumptions: commercial development of the fuel cell for passenger cars, commercial availability
of cellulosic ethanol (and the elimination of the ethanol excise tax exemption), and an apparently
arbitrary 30% reduction in costs for "certain key technologies" (p. 5.24). These technologies are
not identified, and the report does not provide documentation for the NEMS model runs
conducted for the transportation sector.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options, including:
converting coal-based power plants to natural gas; cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution systems;
extending the life of existing nuclear plants; increasing generation and capacity of
existing hydropower plants; and constructing new powerplants using advanced
coal technologies. Each of these options is assessed independently. Thus,
interactions between the options are not taken into account, and the possibility of
double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First, utilities
undertake fuel switching at the $50/ton permit price through carbon-ordered dispatching.
Second, utilities modify their capital stock through several technology options such as those
listed in the above quotation. As electricity production moves away from coal in the first
analysis, fewer and fewer plants (and therefore potential emissions reductions) will be available
for conversion to natural gas or cofiring with biomass. The second set of analyses were "static"
and did not optimize unit/plant production cost, dispatch, or system load. Conversations with
one of the co-authors (Stanley Hadley of Oak Ridge National Laboratory) indicates that 10 GW
of coal-to-gas conversions (approximately 9 million tons of carbon reductions) were double-
counted.²
2 Hadley noted that a subsequent draft of the report should address at least some of the
double counting, but he did not provide details.
5
Furthermore, the analysis of specific options did not examine the effect of increasing fuel prices
(from gas demand due to coal-to-gas repowering). Given the range of assumptions considered in
the study, the authors actually estimated that repowering coal plants for natural gas could result
in carbon reductions between 5 million and 269 million tons (p. 7.2), depending on the gas/coal
price differential, the cost of carbon, and the costs of sulfur dioxide and nitrous oxide emissions.
This is quite a substantial range. The Labs Study estimates that natural gas consumption will
increase 14% to 191% above 2010 baseline consumption. However, the DRI 1.25 run in the IAT
report indicates a 16% decline in natural gas consumption, while the SGM run resulted in only a
negligible decline and Markal-Macro generated a 6% increase in natural gas consumption. These
three models indicate that a non-integrated analysis that does not account for the price change in
natural gas may overestimate natural gas substitution for coal.
6
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
--
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
-
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
--
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
--
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
--
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
--
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
-
32
Expand Natural Gas STAR
3.0
3.4
--
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
--
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.8
1.0
--
Program
Actions to Address Other Greenhouse Gases
16.3
25.4
-
17
Improved Fertilizer Management
4.5
5.3
--
40
Significant New Alternatives Program
5.0
6.4
--
41
HFC-23 Partnerships
5.0
5.0
--
42
Voluntary Aluminum Partnership
1.8
2.2
--
New
Environmental Stewardship Initiative
Not included
6.5
--
Foundation Actions
11.3
--
Climate Wise
Not estimated
1.8
--
Climate Challenge
Not estimated
7.6
--
State and Local Outreach Programs
Not estimated
1.9
--
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
-
New
Rebuild America
2.0
1.6
:
1 and 2
Expanded Green Lights and Energy
3.6
3.3
--
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
--
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
--
7
Residential Appliance Standards
6.8
0.2
--
8 and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
--
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
-
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
--
New
Expand Markets for Next-Generation
0.2
--
Lighting Products
New
Fuel Cells Initiative
0.0
--
Industrial Sector Actions
19.0
4.8
-
12
Motor Challenge
8.8
1.8
--
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization
4.2
2.1
--
17
Improve Efficiency of Fertilizer
2.7
0.8
--
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
-
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
--
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
--
Energy Supply Actions
10.8
1.3
-
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
for mont in effizing cests
list ignored /madmawledged costs
policies
implementation
MEMORANDUM
mht acceptance
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
3 07
DATE:
August 7, 1997
RE:
Review of DOE Labs Study, June 10 Draft
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypothetical climate policy scenarios. The
be
more
study finds that, with "very aggressive policies" and a $50/ton permit price, carbon emissions can
explait
be stabilized at 1990 levels by 2010. In reviewing the report, we believe it is beneficial to
e what
highlight several of the caveats the authors explicitly state. First, the authors do not provide
they us?
say in
descriptions of the government programs necessary to stimulate the necessary technology
BALST,
release
adoption to reduce 180 million tons of carbon emissions. We devised an estimate of the costs of
government programs to achieve these reductions based on the nation's experience with CCAP,
and found that program costs could total $45 billion (1995$). Second, the analyses across sectors
are not integrated. Therefore, the penetration rate of energy efficient technologies may be
overestimated because the separate sectoral analyses do not account for cross-sector interactions
(e.g., in energy prices). Third, the industry sector analysis ignores the costs of accelerating
capital retirement, resulting in either an overestimate of reductions or an underestimate of costs.
Fourth, the transportation sector requires "luck" in terms of technological innovation to achieve
the projected emissions reductions. Fifth, the utilities sector analysis resulted in double counting
of emissions reductions. These examples of the qualifications can provide additional insight into
the projections of emissions reductions and costs. Upon receiving the final version of the report
and documentation of the analyses, we will conduct a more thorough review.
Overview of Report
The Labs Study estimated the carbon emissions reduction opportunities available through
technology development and adoption and fuel switching. The Study employs the Energy
Information Administration's 1997 baseline (AEO97) for the buildings and industry sectors. For
the transportation sector, the authors changed the AEO97 assumption of increasing fuel
efficiency in automobiles to constant fuel efficiency. For the utility sector, the baseline was
modified to reflect a fully competitive bulk-power market in the year 2010. Discharge,
shutdown, repowering, and new construction decisions were optimized to select the amount of
capacity that minimized the cost of the power-supply system plus the cost of unserved energy.
Compared to AEO97, the final baseline has slightly lower energy prices, larger electricity sales,
1
and a greater share of gas generation. The study provides emissions reductions from this baseline
for two scenarios: 1) "efficiency" and 2) "high efficiency/low carbon". The study does not
describe the policies necessary to achieve emissions reductions nor the costs of federal programs
for these scenarios, only their outcomes: increased adoption rates and better technologies.
Efficiency
This case assumes that all technologies adopted are cost-effective given more aggressive federal
policies to stimulate development and diffusion of energy efficient technologies. Since these
technologies are cost-effective, they all have a net cost less than or equal to zero. The Study
estimates that 120 mmtce will be reduced at negative net cost in this scenario. None of these
reductions occur in the utility sector as a function of fuel switching or technology adoption to
increase combustion efficiency.
High Efficiency/Low Carbon
This case assumes a "greater commitment" to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
AEEI is not specified), increased domestic and international R&D in low-carbon technologies,
and a "change in psychology". The Study estimates 180 mmtce of carbon emissions reductions
from the baseline through energy efficient technology adoption at negative net cost (see high
efficiency without low carbon technology in chart below). The carbon permits will yield an
additional 150-200 mmtce of reductions through low-carbon technology adoption. Given that
these occur at a permit price of $50/ton, the Study estimates the upper limits of these costs to be
$10 billion per year in 2010.
Carbon Emissions (mmtce): 1990 - 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 - 1390
Review
The authors of the Lab Study are forthright about many of the assumptions underlying the
analysis. Learning about these qualifications can enhance one's understanding of the estimates
regarding cost-effectiveness and emissions reductions in this study. We present several of the
most significant assumptions and discussions of their impact below.
The Study Does Not Specify Policies to Achieve Carbon Reductions
2
"Cost effectiveness is improved because R&D, in combination with increased
deployment efforts, result in declining capital costs. We do not specify the
policies, economic conditions, or exogenous events that could precipitate such
changes" (p. 1.4).
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study makes vague references to policies and only provides details
on what these unidentified policies would result in: 1) "better technology" (p. 1.5); 2) "higher
penetration rates" (p. 1.6); 3) "changing the capital recovery factor [in industry sector] from 33%
to 15%" (p. 4.8); and 4) "technological breakthroughs" (p. 5.3).
The authors assume that policies are implemented that significantly lower the barriers to
technology adoption without any discussion of their costs. In effect, this assumes the magical
wand of government intervention is waved to lower technology marginal costs enough to get 180
million tons of carbon reductions for "free": firms and individuals receive energy cost-savings in
excess of the technology adoption and implementation costs.
Since the authors do not provide an estimate of the costs to government to lower market barriers
to achieve these substantial reductions, we calculated estimates of the costs of emissions
reductions programs based on the government's experience with the Climate Change Action Plan
(CCAP). CCAP promotes carbon reductions through a broad array of voluntary programs that
stimulate "cost-effective" technology adoption by private firms. Participation by a firm in a
CCAP program implies that carbon is reduced and the firm gains financially.¹ CCAP received
appropriations totaling $494 million (1995$) during the FY95 - FY97 period. During this period,
the Department of Energy and the Environmental Protection Agency can account for 14 million
metric tons of reduced carbon (see attached table). Each ton of carbon reduced in CCAP cost the
federal government $35.29 (1995$). Assuming a flat marginal cost curve (MC=AC) to reduce
180 million metric tons of carbon beyond the baseline, the government costs of the unidentified
policies in the Labs Study would exceed $6.3 billion. However, the marginal costs of technology
adoption are definitely higher than the average cost of the first 14 million metric tons, especially
as more and more efforts to reduce emissions are undertaken. Assuming that costs increase 10%
for every 10 million metric tons of carbon reduced, then the government cost would come to
$16.1 billion. This is slowly increasing marginal cost curve given baseline assumptions of gains
in energy efficiency. Assuming that costs increase 20% for every 10 million metric tons of
carbon reduced, then the cost to government would exceed $45.2 billion.
The Sectoral Analyses Are Not Integrated
1
Note that CCAP efforts are incorporated in AEO97.
3
"The model runs for each of the three end-use sectors were not integrated and
therefore may overstate the effects of technology penetration. In an integrated
modeling effort, fuel prices might fall as consumption declines, resulting in less
penetration of energy-conserving technologies" (p. 1.1).
The analyses of the various sectors assume that 180 million tons of carbon reduction occurs
through energy efficient technology adoption without the price effect of a $50/ton permit. This
implies that, with government programs, private agents will adopt technologies because the
benefits (energy cost-savings) exceed the costs of adoption. The authors claim that these
reductions occur at negative net costs. By failing to account for the effect of decreased energy
demand due to energy efficiency technology adoption, some of those adoption decisions that
occur on the margin would no longer generate positive net benefits for private consumers. The
Labs Study indicates that energy consumption will decline from the baseline by 11.6% under the
high efficiency/low carbon case (p. xi). This decrease in demand should result in a decrease in
the price of energy, and cause some energy-intensive technologies to become unattractive to
private agents.
In addition, the absence of an integrated analysis precludes an assessment of the economy-wide
effects of a tradeable permit system. As previous studies have indicated, the nature of the permit
allocation (e.g., grandfathering, auction, or a hybrid) and the characteristics of the revenue
recycling (e.g., various adjustments to existing taxes) can affect economy-wide investment.
Understanding the effects on investment is instrumental in assessing the likelihood of success of
these scenarios, given that they rely on substantial R&D and technology adoption.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means
that, at the margin, all investments are not likely to be cost effective at our
assumed 15% CRF [capital recovery factor]. Since we do not have a model to
account for this potential early retirement and the economic losses, we must
caveat our estimates of investment and net costs. the investment cost may be
understated by the amount of loss due to any early retirement that may occur" (p.
4.15).
This assumption implies that one of three results should be accounted for in the analysis. First,
the projected emissions reduction should be revised downward, because the assessment of the
industry sector overestimates technology adoption by ignoring these costs. Second, the cost of
reducing emissions, if the reduced carbon from this sector remains constant, should increase,
with some technology adoption decisions occurring at positive net costs. Third, if the authors
maintain the same costs and emissions estimates, then the costs of government programs to
somehow force down the CRF from 33% to 15% would increase.
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
4
"[B]ecause the [transportation sector] outcomes postulated in the high
efficiency/low carbon scenario require technological breakthroughs, they require a
certain degree of luck to be achieved by 2010. There are no credible methods to
accurately gauge the probability of such breakthroughs -- we believe they stand a
decent chance of occurring with an intensification of research efforts, but we stop
short of claiming they are a likely outcome of such an intensification" (p. 5.3).
Note that this statement includes two qualifications: luck on top of intensified research efforts.
To achieve just the efficiency level of emissions reductions for this sector (73 million tons), these
intensified research efforts may require two to ten times existing funding on transportation (p.
5.3). To gain a sense of the magnitude of what such an increase in funding might be, consider
that the Partnership for a New Generation of Vehicles alone is funded at the federal level at $263
million. Further, the estimates of costless (on net) carbon reductions relies on a series of tenuous
assumptions: commercial development of the fuel cell for passenger cars, commercial availability
of cellulosic ethanol (and the elimination of the ethanol excise tax exemption), and an apparently
arbitrary 30% reduction in costs for "certain key technologies" (p. 5.24). These technologies are
not identified, and the report does not provide documentation for the NEMS model runs
conducted for the transportation sector.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options, including:
converting coal-based power plants to natural gas; cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution systems;
extending the life of existing nuclear plants; increasing generation and capacity of
existing hydropower plants; and constructing new powerplants using advanced
coal technologies. Each of these options is assessed independently. Thus,
interactions between the options are not taken into account, and the possibility of
double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First, utilities
undertake fuel switching at the $50/ton permit price through carbon-ordered dispatching.
Second, utilities modify their capital stock through several technology options such as those
listed in the above quotation. As electricity production moves away from coal in the first
analysis, fewer and fewer plants (and therefore potential emissions reductions) will be available
for conversion to natural gas or cofiring with biomass. The second set of analyses were "static"
and did not optimize unit/plant production cost, dispatch, or system load. Conversations with
one of the co-authors (Stanley Hadley of Oak Ridge National Laboratory) indicates that 10 GW
of coal-to-gas conversions (approximately 9 million tons of carbon reductions) were double-
counted.²
2
Hadley noted that a subsequent draft of the report should address at least some of the
double counting, but he did not provide details.
5
Furthermore, the analysis of specific options did not examine the effect of increasing fuel prices
(from gas demand due to coal-to-gas repowering). Given the range of assumptions considered in
the study, the authors actually estimated that repowering coal plants for natural gas could result
in carbon reductions between 5 million and 269 million tons (p. 7.2), depending on the gas/coal
price differential, the cost of carbon, and the costs of sulfur dioxide and nitrous oxide emissions.
This is quite a substantial range. The Labs Study estimates that natural gas consumption will
increase 14% to 191% above 2010 baseline consumption. However, the DRI 1.25 run in the IAT
report indicates a 16% decline in natural gas consumption, while the SGM run resulted in only a
negligible decline and Markal-Macro generated a 6% increase in natural gas consumption. These
three models indicate that a non-integrated analysis that does not account for the price change in
natural gas may overestimate natural gas substitution for coal.
6
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
--
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
I
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
--
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
--
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
:
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
--
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
-
32
Expand Natural Gas STAR
3.0
3.4
:
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
--
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.8
1.0
--
Program
Actions to Address Other Greenhouse Gases
16.3
25.4
-
17
Improved Fertilizer Management
4.5
5.3
:
40
Significant New Alternatives Program
5.0
6.4
--
41
HFC-23 Partnerships
5.0
5.0
I
42
Voluntary Aluminum Partnership
1.8
2.2
--
New
Environmental Stewardship Initiative
Not included
6.5
I
Foundation Actions
11.3
-
Climate Wise
Not estimated
1.8
:
Climate Challenge
Not estimated
7.6
--
State and Local Outreach Programs
Not estimated
1.9
:
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
--
New
Rebuild America
2.0
1.6
--
1 and 2
Expanded Green Lights and Energy
3.6
3.3
--
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
--
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
--
7
Residential Appliance Standards
6.8
0.2
:
8 and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
--
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
--
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
:
New
Expand Markets for Next-Generation
0.2
--
Lighting Products
New
Fuel Cells Initiative
0.0
:
Industrial Sector Actions
19.0
4.8
-
12
Motor Challenge
8.8
1.8
--
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization
4.2
2.1
--
17
Improve Efficiency of Fertilizer
2.7
0.8
--
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
-
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
--
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
--
Energy Supply Actions
10.8
1.3
--
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
BAsed an the
actual history of
MEMORANDUM
CCAP, we estimate
TO:
Jay Shogren
FROM:
Joe Aldy and Quindi Franco
RANDI'S
DATE:
August 7, 1997
RE:
Review of DOE Labs Study, June 10 Draft
evil
United
eye
We provide an assessment of U.S. Carbon Reductions by 2010 and Beyond: The Potential
Impact of Energy-Efficient and Low-Carbon Technologies (DOE Labs Study, June 10 draft).
The report identifies carbon reductions and their associated costs in the buildings, industry,
transportation, and electric power sectors under two hypotherical climate policy scenarios. The
study finds that, with "very aggressive policies" and a $50/ton permit price, carbon emissions can
be stabilized at 1990 levels by 2010. In reviewing the report, we believe it is beneficial to
highlight several of the caveats the authors explicitly state. First the authors do not provide
descriptions of the government programs necessary to stimulate the necessary technology
should.
adoption to reduce 180 million tons of carbon emissions, We devised an estimate of the costs of
government programs to achieve these reductions based on the nation's experience with CCAP,
The
be.
Add
and found that program costs could total $45 billion (1995$). Second, the analyses across sectors
we
d to are not integrated. Therefore, the penetration rate of energy efficient technologies may be
fiel pice
$ton
Tech,
overestimated because the separate sectoral analyses do not account for cross sector interactions
(e.g., in energy prices). Third, the industry sector analysis ignores the costs of accelerating
maigins
costs
capital retirement, resulting in either an overestimate of reductions or an underestimate of costs.
ravg.
Fourth, the transportation sector requires "luck" in terms of technological innovation to achieve
the projected emissions reductions. Fifth, the utilities sector analysis resulted in double counting
of emissions reductions. These examples of the qualifications can provide additional insight into
source
the projections of emissions reductions and costs. Upon receiving the final version of the report
and documentation of the analyses, we will conduct a more thorough review.
update
Overview of Report
The Labs Study estimated the carbon emissions reduction opportunities available through
technology development and adoption and fuel switching. The Study employs the Energy
Information Administration's 1997 baseline (AEO97) for the buildings and industry sectors. For
the transportation sector, the authors changed the AEO97 assumption of increasing fuel
efficiency in automobiles to constant fuel efficiency. For the utility sector, the baseline was
modified to reflect a fully competitive bulk-power market in the year 2010. Discharge,
shutdown, repowering, and new construction decisions were optimized to select the amount of
capacity that minimized the cost of the power-supply system plus the cost of unserved energy.
Compared to AEO97, the final baseline has slightly lower energy prices, larger electricity sales,
With changing flot mig
30%
Town bigger sport recently vehicley bee
and a greater share of gas generation. The study provides emissions reductions from this baseline
for two scenarios: 1) "efficiency" and 2) 'high efficiency/low carbon". The study does not
describe the policies necessary to achieve emissions reductions nor the costs of federal programs
for these scenarios, only their outcomes: increased adoption rates and better technologies.
Efficiency
Seanario
#25 ? zero net cest to the user
This case assumes that all technologies adopted are cost given more aggressive federal
policies to stimulate development and diffusion of energy efficient technologies. Since these
technologies are cost effective, they all have a net cost less than or equal to zero. The Study
estimates that 120 mmtce will be reduced at negative net cost in this scenario. None of these
reductions occur in the utility sector as a function of fuel switching or technology adoption to
increase combustion efficiency.
&
High Efficiency/Low Carbon
@ $50/t
This case assumes a "greater commitment to reduce emissions through federal policies, in
concert with state and private activities and a $50/ton permit price that stimulates low carbon
technologies (read: primarily fuel switching). The policy is announced in 2000 and the policy's
restrictions are phased-in through 2010. There is an assumed announcement effect (although an
AEEI is not specified), increased domestic and international at R&D in low-carbon technologies,
and a "change in psychology The Study estimates 180 mmtce of carbon emissions reductions
from the baseline through energy efficient technology adoption at negative net cost (see high
efficiency without low carbon technology in chart below). The carbon permits will yield an
additional 150-200 mmtce of reductions through low-carbon technology adoption. Given that
these occur at a permit price of $50/ton, the Study estimates the upper limits of these costs to be
$10 billion per year in 2010.
Carbon Emissions (mmtce): 1990 - 2010
1990
2010
2010
2010 High Efficiency
2010 High
Baseline
Efficiency
(w/o Low Carbon Tech)
Efficiency/Low Carbon
1340
1720
1600
1540
1340 - 1390
Review
The authors of the Lab Study are forthright about many of the assumptions underlying the
analysis. Learning about these qualifications can enhance one's understanding of the estimates
regarding cost-effectiveness and emissions reductions in this study. We present several of the
most significant assumptions and discussions of their impact below.
2
1)
Dear
In
The Study Does Not Specify Policies to Achieve Carbon Reductions
"Cost effectiveness is improved because R&D, in combination withhncreased
deployment efforts, result in declining capital costs. We do not specify the
policies, economic conditions, or exogenous events that could precipitate such
changes" (p. 1.4).
calculation?
The entire study is premised on two sets of undefined policies: an "aggressive" or "invigorated"
public sector effort to stimulate energy efficient technology adoption (efficiency case) and a
"very aggressive" public sector effort to stimulate technology development and adoption (high
efficiency/low carbon case). The only specific policy instrument mentioned in the report is a
$50/ton tradeable permit. The study makes vague references to policies and only provides details
on what these unidentified policies would result in: 1) "better technology" (p. 1.5); 2) "higher
penetration rates" (p. 1.6); 3) "changing the capital recovery factor [in industry sector] from 33%
to 15%" (p. 4.8); and 4) "technological breakthroughs" (p. 5.3).
The authors assume that policies are implemented that significantly lower the barriers to
technology adoption without any discussion of their costs. In effect, this assumes the magical
wand of government intervention is waved to lower technology marginal costs enough to get 180
million tons of carbon reductions for "free": firms and individuals receive energy cost-savings in
excess of the technology adoption and implementation costs.
Since the authors do not provide an estimate of the costs to government to lower market barriers
to achieve these substantial reductions, we calculated estimates of the costs of emissions
reductions programs based on the government's experience with the Climate Change Action Plan
(CCAP). CCAP promotes carbon reductions through a broad array of voluntary programs that
stimulate "cost-effective" technology adoption by private firms. Participation by a firm in a
CCAP program implies that carbon is reduced and the firm gains financially.¹ CCAP received
appropriations totaling $494 million (1995$) during the FY95 - FY97 period. During this period,
the Department of Energy and the Environmental Protection Agency can account for 14 million
metric tons of reduced carbon (see attached table). Each ton of carbon reduced in CCAP cost the
federal government $35.29 (1995$) Assuming a flat marginal cost curve (MC=AC) to reduce
180 million metric tons of carbon beyond the baseline, the government costs of the unidentified
policies in the Labs Study would exceed $6.3 billion. However, the marginal costs of technology
adoption are definitely higher than the average cost of the first 14 million metric tons, especially
as more and more efforts to reduce emissions are undertaken. Assuming that costs increase 10%
for every 10 million metric tons of carbon reduced, then the government cost would come to
$16.1 billion. This is slowly increasing marginal cost curve given baseline assumptions of gains
good to
in energy efficiency. Assuming that costs increase 20% for every 10 million metric tons of
have
carbon reduced, then the cost to government would exceed $45.2 billion.
other
3/
evidence
1 Note that CCAP efforts are incorporated in AEO97.
on how
fast MC
V
3
redise
risue
The Sectoral Analyses Are Not Integrated
"The model runs for each of the three end-use sectors were not integrated and
therefore may overstate the effects of technology penetration. In an integrated
modeling effort, fuel prices might fall as consumption declines, resulting in less
penetration of Frew energy conserving technologies" (p. 1.1).
or
The analyses of the various sectors assume that 180 million tons of carbon reduction occurs
through energy efficient technology adoption without the price effect of a $50/ton permit. This
implies that, with government programs, private agents will adopt technologies because the
benefits (energy cost-savings) exceed the costs of adoption. The authors claim that these
reductions occur at negative net costs. By failing to account for the effect of decreased energy
demand due to energy efficiency technology adoption, some of those adoption decisions that
occur on the margin would no longer generate positive net benefits for private consumers. The
Labs Study indicates that energy consumption will decline from the baseline by 11.6% under the
/high efficiency/low carbon case (p. xi). This decrease in demand should result in a decrease in
the price of energy, and cause some energy-intensive technologies to become unattractive to
private agents.
Powehang ante
off
how
yruch
they
In addition, the absence of an integrated analysis precludes an assessment of the economy-wide
effects of a tradeable permit system. As previous studies have indicated, the nature of the permit
allocation (e.g., grandfathering, auction, or a hybrid) and the characteristics of the revenue
wer- predict
recycling (e.g., various adjustments to existing taxes) can affect economy-wide investment.
, J
Understanding the effects on investment is instrumental in assessing the likelihood of success of
these scenarios, given that they rely on substantial R&D and technology adoption.
The Industry Sector Analysis Ignores the Costs of Accelerated Retirement
"When the economic losses of accelerated retirement are accounted for this means
that, at the margin, all investments are not likely to be cost effective at our
assumed 15% CRF [capital recovery factor]. Since we do not have a model to
account for this potential early retirement and the economic losses, we must
caveat our estimates of investment and net costs. the investment cost may be
understated by the amount of loss due to any early retirement that may occur" (p.
4.15).
This assumption implies that one of three results should be accounted for in the analysis. First,
the projected emissions reduction should be revised downward, because the assessment of the
industry sector overestimates technology adoption by ignoring these costs. Second, the cost of
reducing emissions, if the reduced carbon from this sector remains constant, should increase,
with some technology adoption decisions occurring at positive net costs. Third, if the authors
maintain the same costs and emissions estimates, then the costs of government programs to
somehow force down the CRF from 33% to 15% would increase.
4
The Transportation Sector Requires "Luck" to Achieve Carbon Reductions
are there
"[B]ecause the [transportation sector] outcomes postulated in the high
with
efficiency/low carbon scenario require technological breakthroughs, they require a
included
certain degree of luck to be achieved by 2010. There are no credible methods to
accurately gauge the probability of such breakthroughs -- we believe they stand a
an your
decent chance of occurring with an intensification of research efforts, but we stop
short of claiming they are a likely outcome of such an intensification" (p. 5.3).
45 B ?
Note that this statement includes two qualifications: luck on top of intensified research efforts.
To achieve just the efficiency level of emissions reductions for this sector (73 million tons), these
intensified research efforts may require two to ten times existing funding on transportation (p.
5.3). To gain a sense of the magnitude of what such an increase in funding might be, consider
that the Partnership for a New Generation of Vehicles alone is funded at the federal level at $263
million. Further, the estimates of costless (on net) carbon reductions relies on a series of tenuous
assumptions: commercial development of the fuel cell for passenger cars, commercial availability
of cellulosic ethanol (and the elimination of the ethanol excise tax exemption), and an apparently
privacy
arbitrary 30% reduction in costs for "certain key technologies" (p. 5.24). These technologies are
not identified, and the report does not provide documentation for the NEMS model runs
conducted for the transportation sector.
are in redation
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis
"Chapter 7 considers other electricity supply technology options, including:
converting coal-based power plants to natural gas; cofiring coal with biomass;
efficiency improvements in generation and transmission and distribution systems;
extending the life of existing nuclear plants; increasing generation and capacity of
existing hydropower plants; and constructing new powerplants using advanced
coal technologies. Each of these options is assessed independently. Thus,
interactions between the options are not taken into account, and the possibility of
double counting is therefore likely" (p. 7.1).
The emissions reductions in the electricity sector come from two sources. First, utilities
undertake fuel switching at the $50/ton permit price through carbon-ordered dispatching.
Second, utilities modify their capital stock through several technology options such as those
listed in the above quotation. As electricity production moves away from coal in the first
analysis, fewer and fewer plants (and therefore potential emissions reductions) will be available
for conversion to natural gas or cofiring with biomass. The second set of analyses were "static"
and did not optimize unit/plant production cost, dispatch, or system load. Conversations with
one of the co-authors (Stanley Hadley of Oak Ridge National Laboratory) indicates that 10 GW
5
of coal-to-gas conversions (approximately 9 million tons of carbon reductions) were double-
counted.²
Furthermore, the analysis of specific options did not examine the effect of increasing fuel prices
(from gas demand due to coal-to-gas. repowering). Given the range of assumptions considered in
the study, the authors actually estimated that repowering coal plants for natural gas could result
in carbon reductions between 5 million and 269 million tons (p. 7.2), depending on the gas/coal
price differential, the cost of carbon, and the costs of sulfur dioxide and nitrous oxide emissions.
This is quite a substantial range. The Labs Study estimates that natural gas consumption will
increase 14% to 191% above 2010 baseline consumption. However, the DRI 1.25 run in the IAT
report indicates a 16% decline in natural gas consumption, while the SGM run resulted in only a
negligible decline and Markal-Macro generated a 6% increase in natural gas consumption. These
three models indicate that a non-integrated analysis that does not account for the price change in
natural gas may overestimate natural gas substitution for coal.
2
Hadley noted that a subsequent draft of the report should address at least some of the
double counting, but he did not provide details.
6
Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
--
New
Rebuild America
2.0
1.6
--
1 and 2
Expanded Green Lights and Energy
3.6
3.3
--
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
--
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
--
7
Residential Appliance Standards
6.8
0.2
--
8 and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
-
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
--
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
--
New
Expand Markets for Next-Generation
0.2
Lighting Products
New
Fuel Cells Initiative
0.0
--
Industrial Sector Actions
19.0
4.8
-
12
Motor Challenge
8.8
1.8
--
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization
4.2
2.1
--
17
Improve Efficiency of Fertilizer
2.7
0.8
--
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
--
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
--
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
--
Energy Supply Actions
10.8
1.3
--
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
--
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
I
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
:
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
--
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
--
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
:
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
-
32
Expand Natural Gas STAR
3.0
3.4
--
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
--
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.8
1.0
--
Program
Actions to Address Other Greenhouse Gases
16.3
25.4
-
17
Improved Fertilizer Management
4.5
5.3
:
40
Significant New Alternatives Program
5.0
6.4
--
41
HFC-23 Partnerships
5.0
5.0
--
42
Voluntary Aluminum Partnership
1.8
2.2
:
New
Environmental Stewardship Initiative
Not included
6.5
--
Foundation Actions
11.3
-
Climate Wise
Not estimated
1.8
--
Climate Challenge
Not estimated
7.6
:
State and Local Outreach Programs
Not estimated
1.9
--
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
12/30/97 TUE 10:34 FAX 202 6222633
001
Office of Economic Policy
Department of the Treasury
Washington, D.C. 20220
FAX
Date:
Number of pages including cover sheet: 5
Dec.30, 1997
Name
Fax Number
Phone Number
To: Jff Franked
395-6958
395-5046
From: Jon Gruber
202-622-2633
REMARKS:
Urgent
For your review
Reply ASAP
Please comment
Hold Close
12/30/97 TUE 10:35 FAX 202 6222633
4.
002
Jeff-
-
Larry Summers suggested that I talk, on deep background, to a couple of outside experts to see
what they would view as reasonable for our economic analysis. I attach (for your eyes only,
obviously) some discussion of their views. I also attach a revised set of runs that I think Joe
should do, reflecting these views. I haven't passed these on to Joe yet.
My only question is: have I been too conservative on the possibilities for JI/LDC participation?
Maybe we should do some runs where JI/LDCs give us more benefits than the 20% that I
assume? I don't know enough about the structure of the model to assess this.
Give me a call when you get in and lets discuss.
Jon
12/30/97 TUE 10:35 FAX 202 6222633
003
Expert Opinion on Economic Analysis
Contacts: Rob Stavins, Mike Toman, Dick Schmalansee
Starting Point: Roughly $100/ton from SGM model (this is with domestic only, and 1% AEEI)
All experts seem comfortable with this model and have great respect for Edmunds and Batelle.
They seem to think that this is a sensible starting point. Stavins did note that this assumes that
we equate marginal costs and pursue only least cost efficient paths to reduction. He points out
that in reality this is unlikely. Schmalansee highlighted that timing is key - but the runs that
CEA is using are calibrated for reductions to start in 2005, when our permit system kicks in.
Annex I Trading: Pure Annex I trading can roughly halve costs to $50; the umbrella might get the
price down to $30
There was general comfort with the numbers, but all highlighted that this was conditional on
perfect trading being in place, and there was also general skepticism that this could emerge.
Stavins once again highlighted that this assumes we find global least cost reductions, which
seems even more suspect since it requires other countries to be efficient as well. On the other
hand, all recognize the huge value of the Russian tons. There was some skepticism that the EU
would, at the end of the day, let themselves get shut out of the Russian tons.
Technology: The IAT used an AEEI of 1.25, and it was mildly criticized as a bit optomistic - but
this was before the $6 billion in the budget, and without any price signal. 5 Labs implies an
AEEI of 1.71. An AEEI of 1.25 would bring price down to roughly $80.
I think that there would be support for 1.25 AEEI, but not for much more - certainly nothing
approaching 5 labs. Schmalansce pointed out that, even without an explicit price signal, Kyoto
highlights that "the train is moving" and should promote the growth of the energy efficient
technologies.
Joint Implementation and LDCs: Models tell us effect of Annex I trading, and worldwide
trading. Question is: how much of the gap between these two is closed by JI?
Would be little support for claiming anything close to the majority of this gap. But there would,
I think, be support for claiming a small share, say 10-20% of the gap. Schamalansee said <10%,
Toman said up to 20%. There was no real view on the prospects of additional LDC participation,
but pretty strong skepticism that it would amount to much.
ini,
Electriticity Restructuring: We can claim economic benefits from restructuring. Can we claim
some enviro benefits as well?
Gruenspecht says that we can get electricity savings of 10% from restructuring. This is $20
billion now and ??? in 2010. Joskow says 8-10%, but will defer to Howard as well. By 2010,
stranded costs are all paid, so that we get full benefits of lower prices.
12/30/97 TUE 10:35 FAX 202 6222633
4.
004
There was generally strong skepticism among this group about claims of environmental benefits.
Toman even pointed out that Howard Gruenspecht had actually changed his position on this over
the past year. I think that the best we can do here is claim environmental neutrality, and maybe
sqres
some qualitative statements about potential gains. putting numbers on this is going to get us in
trouble.
Other Benefits: There may be gains from reducing costs of meeting NAAQS. or health benefits
(but not both).
There was support for some benefits here. Toman thought that most of the action would be
health benefits, since he didn't think that NAAQS would be effective by 2010. Ray notes that
administration policy is that NAAQS will be effective by then, so that the benefits will bc in
dollars, not health.
Bottom Line: There seems to be professional support for claiming some technology gains, some
small JI/LDC benefit, full Annex I trading gains, and perhaps for some gains from umbrella. But
we have to recognize that this analysis will be criticized by some folks on the grounds that it is
too idealistic on trading, and by others on the grounds that it implies that we buy our way out of
the majority of our reductions. Both these criticisms will rise in proportion to the gains that we
claim from umbrella.
It seems like an analysis with 1.25 AEEI, Annex I trading including EU (no umbrella), and
JI/LDC that gets 20% of WW trading benefits would be pretty well received. Moving to the
umbrella would bring some criticism, but not an avalanche, Going beyond that on trading or
technology would be steeply criticized. I remain unclear on how much we can justify on JI/LDC
12/30/97 TUE 10:36 FAX 202 6222633
4
005
Given these comments, here is a revised set of runs that I think we should do:
Model Permutations to Consider:
1) Full Annex I trading
2) Umbrella - trading block that excludes EU and Eastern Europe
3) AEEI of 1.25
4) JI/LDC participation that gets us 20% of the gains of worldwide trading (beyond Annex I
trading).
Question: Are interactions linear? Worth trying some combined and separate cstimates to get a
feel for this, although we don't want to get out of control. I would suggest the following set of
runs:
1-3) Do the first three factors individually
4) Annex I trading with JI/LDC
5) Annex I trading, with umbrella, and JI/LDC
6) Higher AEEI, with Annex I trading
7) Higher AEEI, with Annex I trading and umbrella
8) Higher AEEI, with Annex I trading and JI/LDC
9) Higher AEEI, with Annex I trading, umbrella, and JI/LDC
For each of these cases, we should show what happens to permit price, and what share of our
reductions are purchased abroad.
12/30/97 TUE 10:34 FAI 202 6222633
J.
001
Office of Economic Policy
Department of the Treasury
Washington, D.C. 20220
FAX
Date:
Dec. Dec. 30, 1997 1997
Number of pages including cover sheet: 5
Name
Fax Number
Phone Number
To: Jeff Frankee
395-6958
395-5046
From: Jon Gruber
202-622-2633
REMARKS:
Urgent
For your review
Reply ASAP
Please comment
Hold Close
12/30/97 TUE 10:35 FAI 202 6222633
002
Jeff
Larry Summers suggested that I talk, on deep background, to a couple of outside experts to see
what they would view as reasonable for our economic analysis. I attach (for your eyes only,
obviously) some discussion of their views. I also attach a revised set of runs that I think Joe
should do, reflecting these views. I haven't passed these on to Joe yet.
My only question is: have I been too conservative on the possibilities for JI/LDC participation?
Maybe we should do some runs where JI/LDCs give us more benefits than the 20% that I
assume? I don't know enough about the structure of the model to assess this.
Give me a call when you get in and lets discuss.
Jon
12/30/97 TUE 10:35 FAI 202 6222633
003
Expert Opinion on Economic Analysis
Contacts: Rob Stavins, Mike Toman, Dick Schmalansee
Starting Point: Roughly $100/ton from SGM model (this is with domestic only, and 1% AEEI)
All experts seem comfortable with this model and have great respect for Edmunds and Batelle.
They seem to think that this is a sensible starting point. Stavins did note that this assumes that
we equate marginal costs and pursue only least cost efficient paths to reduction. He points out
that in reality this is unlikely. Schmalansee highlighted that timing is key - but the runs that
CEA is using are calibrated for reductions to start in 2005, when our permit system kicks in.
Annex I Trading: Pure Annex I trading can roughly halve costs to $50; the umbrella might get the
price down to $30
There was general comfort with the numbers, but all highlighted that this was conditional on
perfect trading being in place, and there was also general skepticism that this could emerge.
Stavins once again highlighted that this assumes we find global least cost reductions, which
seems even more suspect since it requires other countries to be efficient as well. On the other
hand, all recognize the huge value of the Russian tons. There was some skepticism that the EU
would, at the end of the day, let themselves get shut out of the Russian tons.
Technology: The IAT used an AEEI of 1.25, and it was mildly criticized as a bit optomistic - but
this was before the $6 billion in the budget, and without any price signal. 5 Labs implies an
AEEI of 1.71. An AEEI of 1.25 would bring price down to roughly $80.
I think that there would be support for 1.25 AEEI, but not for much more - certainly nothing
approaching 5 labs. Schmalansce pointed out that, even without an explicit price signal, Kyoto
highlights that "the train is moving" and should promote the growth of the energy efficient
technologies.
Joint Implementation and LDCs: Models tell us effect of Annex I trading, and worldwide
trading. Question is: how much of the gap between these two is closed by JI?
Would be little support for claiming anything close to the majority of this gap. But there would,
I think, be support for claiming a small share, say 10-20% of the gap. Schamalansee said <10%,
Toman said up to 20%. There was no real view on the prospects of additional LDC participation,
but pretty strong skepticism that it would amount to much.
Electriticity Restructuring: We can claim economic benefits from restructuring. Can we claim
some enviro benefits as well?
Gruenspecht says that we can get electricity savings of 10% from restructuring. This is $20
billion now and ??? in 2010. Joskow says 8-10%, but will defer to Howard as well. By 2010,
stranded costs are all paid, so that we get full benefits of lower prices.
12/30/97 TUE 10:35 FAI 202 6222633
001
There was generally strong skepticism among this group about claims of environmental benefits.
Toman even pointed out that Howard Gruenspecht had actually changed his position on this over
the past year. I think that the best we can do here is claim environmental neutrality, and maybe
:
some qualitative statements about potential gains . putting numbers on this is going to get us in
trouble.
Other Benefits: There may be gains from reducing costs of meeting NAAQS, or health benefits
(but not both).
There was support for some benefits here. Toman thought that most of the action would be
health benefits, since he didn't think that NAAQS would be effective by 2010. Ray notes that
administration policy is that NAAQS will be effective by then, so that the benefits will bc in
dollars, not health.
Bottom Line: There seems to be professional support for claiming some technology gains, some
small JI/LDC benefit, full Annex I trading gains, and perhaps for some gains from umbrella. But
we have to recognize that this analysis will be criticized by some folks on the grounds that it is
too idealistic on trading, and by others on the grounds that it implies that we buy our way out of
the majority of our reductions. Both these criticisms will rise in proportion to the gains that WC
claim from umbrella.
It seems like an analysis with 1.25 AEEI, Annex I trading including EU (no umbrella), and
JI/LDC that gets 20% of WW trading benefits would be pretty well received. Moving to the
umbrella would bring some criticism, but not an avalanche, Going beyond that on trading or
technology would be steeply criticized. I remain unclear on how much we can justify 00 JI/LDC
12/30/97 TUE 10:36 FAI 202 6222633
005
Given these comments, here is a revised set of runs that I think we should do:
Model Permutations to Consider:
1) Full Annex I trading
2) Umbrella - trading block that excludes EU and Eastern Europe
3) AEEI of 1.25
4) JI/LDC participation that gets us 20% of the gains of worldwide trading (beyond Annex I
trading).
Question: Are interactions linear? Worth trying some combined and separate estimates to get a
feel for this, although we don't want to get out of control. I would suggest the following set of
runs:
1-3) Do the first three factors individually
4) Annex 1 trading with JI/LDC
5) Annex I trading, with umbrella, and JI/LDC
6) Higher AEEI, with Annex I trading
7) Higher AEEI, with Annex I trading and umbrella
8) Higher AEEI, with Annex I trading and JI/LDC
9) Higher AEEI, with Annex I trading, umbrella, and JI/LDC
For each of these cases, we should show what happens to permit price, and what share of our
reductions are purchased abroad.
phonecon.m13
Page 1
Talking Points for Calls to Potential Economist Validators
Wanted to talk to you about global climate change and the Kyoto agreement.
Know you have been following issue, and wanted to provide our perspective on the
economics involved:
As the letter from 2,500 economists [which you signed] on this issue indicates,
"The most efficient approach to slowing climate change is through market based
policies. In order for the world to achieve its climate objectives at minimum cost,
a cooperative approach among nations is required -- such as an international
emissions trading program."
The treaty we agreed to in Kyoto, and the Administration's overall approach to
climate change, emphasize this market-based approach. The Kyoto agreement
includes provisions for international trading, for a Clean Development
Mechanism, and for other sources of flexibility. We prevailed on these and other
key points against very broad opposition.
At same time, the treaty did not bring developing countries on board and that is
the next great hurdle. Without it, treaty will never get ratified and the global
problem won't get solved.
I think it is extremely important that economists start pointing out that if the provisions of
the Kyoto agreement are fully implemented, the costs are likely to be quite modest. In
particular, international trading and other aspects of the treaty (e.g., six gases, sinks)
dramatically reduce the costs involved, and many outside studies are neglecting to reflect
the institutional details of what was actually agreed.
The opposition, as you may have seen, is already on the field. [WEFA]
What I would like to do is start to engage thoughtful leaders like yourself on this issue. I
would like to get your best thoughts on how we should be proceeding in analyzing the
issue and making our case with the public. And I would hope to enlist your moral
support for our efforts to deal with this issue in a sound and sober manner.
We will also need your help in thinking through many of the important questions
as we move forward. For example, if we ratify the Kyoto agreement, designing an
effective cap-and-trade system for carbon emissions will be one of our most
important public policy challenges over the next decade, and we will need the
help of people like you to make sure we get it right.
We are trying to organize a dinner with the Vice President, Deputy Secretary Summers,
and Chair Yellen in the near future to focus on the economic aspects of climate change,
and I hope you'll be available to join us.
JF 10/16/97
DRAFT TALKING POINTS, TO DEFEND AN AGGRESSIVE GCC PROGRAM
We will protect the environment, and at the same time protect the economy.
Vigorous economic growth and environmental protection must go hand in hand.
The President has spent five years growing the economy, and laying the foundations
to sustain that growth into the future. He is not going to endanger that record now.
"I have worked far too hard to revitalize the American economy to jeopardize our
progress now." [Oct. 1, 1997, WH meeting with weather forecasters.]
The U.S. will not go along with an agreement that threatens sustained economic
growth.
While the President is deeply committed to reducing carbon emisssion, no one could
reasonably expect that he -- or future adminstrations or Congresses -- would allow
the costs of this effort to become extreme. That's why we have built in regular
economic reviews, to monitor our progress and re-assess how the economy is
responding.
Economic models are always subject to a great deal of uncertainty, and forecasts are
all the more so. In this case we are talking about unexplored territory.
Fifteen years ago, we never thought we souls see an unemployment rate under 5
percent, a core inflation rate of under 2.5 percent, and a Federal budget deficit well
under $50 billion. But that's what has happened. So a degree of modesty with
regard to our forecasting abilities is appropriate.
The economics of technological progress, for example, is a big unknown. The
processes of invention, innovation, diffusion, and learning, fall under the sway of
other Muses at least as much as under the dictates of the goddess of Economics.
The President has faith in the American people, in their ingenuity and determination
to overcome obstacles.
In 194_ President Roosevelt called the leaders of industry to the White House, and
asked how much, with an all-out effort, they could increase their production of war-
related materials and equipment. He then announced to the American people goals
that were more ambitious by an order of %. In the end, those goals were
attained. The key was national mobilization in the fact of a shared global threat.
Climate change is a shared global threat. We might not be able to replicate the
achievement of 1941. The American people are not all familiar with the new threat.
But the President believes that we will never know what we can accomplish unless
we try.
"If we would change our habits tomorrow, just some of our habits, we could with no
extra charge, no cost at all on society, get rid of 20 percent of the GHG with
presently available technology' [8/4/97 press conference]. It is impossible to know
to what extent American will heed the call. We consumers are fond of our
incandescent light bulbs, our high-flow showers and our sport utility vehicles.
Industry is fond of its old ways of doing things as well. But the adoption of carbon-
saving technology has to be a large part of the solution, and there is no knowing how
far it can take us.
Even more unknown than future technological progress is the extent to which the
cost of addressing climate change can be substantially reduced by so-called "where
flexibility." There are many other countries that could reduce emissions relative to
their "business-as-usual" paths at lower costs than can industrialized countries such
as the U.S.. We are insisting at Kyoto on a number of treaty provisions that would
take advantage of this to reduce the costs to the American economy. These
provisions include international trading, joint implementation, and -- most
significantly - participation by developing countries. Many countries disagree with
one or more of these proposals. Furthermore, even if we somehow were able to win
agreement with all our flexibility proposals, it is difficult to know whether they
could be implemented efficiently and enforced fully. But if these uncertainties were
resolved in a positive manner, there would be scope for bringing down the costs very
substantially.
DRART
≈:
DO YOU BELIEVE THAT IT IS POSSIBLE TO MEET THE BINDING TARGET
OF 1990 EMISSIONS LEVELS BY 2010 WITHOUT INFLICTING HEAVY
COSTS ON THE ECONOMY?
A:
I believe that the President's package of R&D initiatives, tax cuts for energy efficiency,
Federal government energy initiatives, and the market-based permit trading system will
be a solid first step in addressing the critical problem of global climate change. While the
President is deeply committed to reducing carbon emissions, no one could reasonably
expect that he - or future administrations or Congresses would allow the costs of this
effort to become extreme. That's why we have built in regular economic reviews, to
monitor our progress and re-assess how the economy is responding. [SAFETY VALVE
ALSO.]
After all, making predictions 10 or 15 years into the future is very difficult. We can not
know with any precision how factors such as technological breakthroughs or successful
international trading could lower the costs of addressing climate change.
ä
BUT DON'T MODELS SHOW THAT REACHING 1990 LEVELS BY 2010 WILL
REQUIRE $100 OR $200 PER TON INCREASES IN CARBON PRICES?
A:
There is no definitive answer as to how much it will cost to reach 1990 levels by 2010.
Different economic models come up with different numbers based on different
assumptions. Many published estimates are in the range that you mention. But as just
one example of the uncertainties involved, full worldwide permit trading -- which
admittedly may be difficult to implement -- has the potential to reduce costs
substantially, to perhaps $10 or $20 per ton. If such a worldwide system of trading
were to develop, the costs will thus be substantially lower.
In sum, there is substantial uncertainty surrounding how the economy will behave in 10
or 15 years. I must admit that 15 years ago, I never thought I would see an
unemployment rate under 5 percent, a core inflation rate of under 2.5 percent, and a
Federal budget deficit well under $50 billion. But that's what's happened. So I would
urge a similar degree of modesty here. The important point is that the President's plan
is a solid first step in reducing carbon emissions without inflicting excessive costs on
the economy.
Q:
BUT DOESN'T YOUR OWN ANALYSIS SHOW THAT REACHING 1990 BY
2010 WOULD INVOLVE SUBSTANTIAL COSTS?
A:
It seems inappropriate for me to reveal the analysis and views that I have shared with
the President. I can say that I have informed him of the results from conventional
economic models available in the public domain, and discussed both the benefits and
limitations of such models. Given the importance I attach to frank internal discussions,
I would prefer not to elaborate beyond that.
Q:
HOW DO YOU DEFINE "EXCESSIVE" COSTS? IS $50 PER TON
EXCESSIVE?
A:
[ANSWER DEPENDS ON SAFETY VALVE DECISION.]
≈:
BUT WON'T THIS EFFORT CAUSE JOB LOSSES OF OVER 1.5 MILLION
JOBS?
A:
President Clinton's top priority, since his first days in office, has been revitalizing the
economy, creating jobs and investing in people and technology to enhance long-term
growth. And we have made tremendous progress: growth is strong, unemployment is
down to 4.9 percent, and over 13 million jobs have been created since January 1993. He
is not going to jeopardize that progress.
As for the specific impact of reducing carbon emissions to 1990 levels by 2010, I
would emphasize once again that different economic models come up with different
numbers based on different assumptions, and that there is substantial uncertainty
involved in the estimates. Furthermore, no one could reasonably expect that this
President -- or future administrations or Congresses - would allow the costs of the effort
to become extreme. That's why we have built in regular economic reviews, to monitor
our progress and re-assess how the economy is responding. [SAFETY VALVE ALSO.]
≈:
IF YOU DON'T KNOW HOW MUCH IT WILL COST TO REACH 1990
LEVELS BY 2010, HOW CAN YOU JUSTIFY GOING FORWARD WITH SUCH
A POLICY?
As I have said, it is difficult to determine the exact cost of policies designed to reach 1990
emissions levels by 2010. Global climate change involves economic and physical
processes that operate globally and over decades, if not centuries.
But the science is clear and compelling: we humans are changing the global climate.
Over time, climate changes will disrupt agriculture, cause droughts and floods and the
spred of infectious diseases. We must take steps now to reduce greenhouse gas
emissions, and after carefully weighing the advantages and disadvantages of different
approaches, the President has decided that reducing emissions to 1990 levels by 2010 is
the best way forward.
The President's approach -- which starts with increased R&D spending, tax incentives
for energy efficiency, and an aggressive effort on the Federal government's own
energy efficiency -- recognizes the uncertainties involved in reducing carbon emissions.
No one could reasonably expect that this President -- or future administrations or
Congresses -- would allow the costs of the effort to become extreme. That's why we
have built in regular economic reviews, to monitor our progress and re-assess how the
economy is responding. [SAFETY VALVE ALSO.]
DRAFT
Q:
DO YOU BELIEVE THAT IT IS POSSIBLE TO MEET THE BINDING TARGET
OF 1990 EMISSIONS LEVELS BY 2010 WITHOUT INFLICTING HEAVY
COSTS ON THE ECONOMY?
A:
I believe that the President's package of R&D initiatives, tax cuts for energy efficiency,
Federal government energy initiatives, and the market-based permit trading system will
be a solid first step in addressing the critical problem of global climate change. While the
President is deeply committed to reducing carbon emissions, no one could reasonably
expect that he -- or future administrations or Congresses -- would allow the costs of this
effort to become extreme. That's why we have built in regular economic reviews, to
monitor our progress and re-assess how the economy is responding. [SAFETY VALVE
ALSO.]
After all, making predictions 10 or 15 years into the future is very difficult. We can not
know with any precision how factors such as technological breakthroughs or successful
international trading could lower the costs of addressing climate change.
a:
BUT DON'T MODELS SHOW THAT REACHING 1990 LEVELS BY 2010 WILL
REQUIRE $100 OR $200 PER TON INCREASES IN CARBON PRICES?
A:
There is no definitive answer as to how much it will cost to reach 1990 levels by 2010.
Different economic models come up with different numbers based on different
assumptions. Many published estimates are in the range that you mention. But as just
one example of the uncertainties involved, full worldwide permit trading -- which
admittedly may be difficult to implement -- has the potential to reduce costs
substantially, to perhaps $10 or $20 per ton. If such a worldwide system of trading
were to develop, the costs will thus be substantially lower.
In sum, there is substantial uncertainty surrounding how the economy will behave in 10
or 15 years. I must admit that 15 years ago, I never thought I would see an
unemployment rate under 5 percent, a core inflation rate of under 2.5 percent, and a
Federal budget deficit well under $50 billion. But that's what's happened. So I would.
urge a similar degree of modesty here. The important point is that the President's plan
is a solid first step in reducing carbon emissions without inflicting excessive costs on
the economy.
Q:
BUT DOESN'T YOUR OWN ANALYSIS SHOW THAT REACHING 1990 BY
2010 WOULD INVOLVE SUBSTANTIAL COSTS?
A:
It seems inappropriate for me to reveal the analysis and views that I have shared with
the President. I can say that I have informed him of the results from conventional
economic models available in the public domain, and discussed both the benefits and
limitations of such models. Given the importance I attach to frank internal discussions,
I would prefer not to elaborate beyond that.
≈:
HOW DO YOU DEFINE "EXCESSIVE" COSTS? IS $50 PER TON
EXCESSIVE?
A:
[ANSWER DEPENDS ON SAFETY VALVE DECISION.]
Q:
BUT WON'T THIS EFFORT CAUSE JOB LOSSES OF OVER 1.5 MILLION
JOBS?
A:
President Clinton's top priority, since his first days in office, has been revitalizing the
economy, creating jobs and investing in people and technology to enhance long-term
growth. And we have made tremendous progress: growth is strong, unemployment is
down to 4.9 percent, and over 13 million jobs have been created since January 1993. He
is not going to jeopardize that progress.
As for the specific impact of reducing carbon emissions to 1990 levels by 2010, I
would emphasize once again that different economic models come up with different
numbers based on different assumptions, and that there is substantial uncertainty
involved in the estimates. Furthermore, no one could reasonably expect that this
President -- or future administrations or Congresses -- would allow the costs of the effort
to become extreme. That's why we have built in regular economic reviews, to monitor
our progress and re-assess how the economy is responding. [SAFETY VALVE ALSO.]
Q:
IF YOU DON'T KNOW HOW MUCH IT WILL COST TO REACH 1990
LEVELS BY 2010, HOW CAN YOU JUSTIFY GOING FORWARD WITH SUCH
A POLICY?
As I have said, it is difficult to determine the exact cost of policies designed to reach 1990
emissions levels by 2010. Global climate change involves economic and physical
processes that operate globally and over decades, if not centuries.
But the science is clear and compelling: we humans are changing the global climate.
Over time, climate changes will disrupt agriculture, cause droughts and floods and the
spred of infectious diseases. We must take steps now to reduce greenhouse gas
emissions, and after carefully weighing the advantages and disadvantages of different
approaches, the President has decided that reducing emissions to 1990 levels by 2010 is
the best way forward.
The President's approach -- which starts with increased R&D spending, tax incentives
for energy efficiency, and an aggressive effort on the Federal government's own
energy efficiency -- recognizes the uncertainties involved in reducing carbon emissions.
No one could reasonably expect that this President -- or future administrations or
Congresses -- would allow the costs of the effort to become extreme. That's why we
have built in regular economic reviews, to monitor our progress and re-assess how the
economy is responding. [SAFETY VALVE ALSO.]
Some analysts have proposed using revenues from the sale of emissions permits (designed
to slow global warming) to plug the projected entitlements financing gap. This memo argues that
earmarking is a bad idea, because there is no inherent connection between the magnitude of the
two streams, and because the size of both streams (particularly the emission permit revenues) is
extremely uncertain.
Comparison of Anticipated Magnitudes
The first three columns of the attached table show the Social Security Actuary's low,
intermediate, and high estimates of the annual financing shortfall in the Social Security system as a
fraction of GDP (excluding interest payments or receipts on trust fund balances).¹ In the
intermediate projections, the shortfall is monotonically increasing over time, although about 80
percent of the ultimate deterioration has occurred by 2030, when the shortfall is projected to be
about 1.7 percent of GDP.
The next three columns show projected emissions permit revenues as a fraction of GDP
under the "Peak in 2015" plan (the least aggressive option considered), under three assumptions
about the nature of the market for emissions permits: no international trading, trading among
Annex I countries, and global trading.2 Revenue estimates in 2030 vary by about a factor of ten
depending on the assumption about trading. In the "no trading" regime, revenues in 2030 are
roughly the same size as the Social Security shortfall, but under the other two options revenues fall
far short. By 2050, revenues under "no trading" are more than twice the Social Security shortfall,
but under the Annex I trading regime revenues are about 3/4 of the shortfall. The remaining
columns of the table show projections of revenues under Annex I trading for the main alternatives
to the "Peak in 2015" plan. Revenues for either the "-10% in 2010" or the "1995 in 2010" plans
roughly match the intermediate projection of the Social Security financing gap by 2050, but in the
early decades revenues substantially exceed the financing gap. Revenues from the "1990 in 2010"
plan exceed the financing gap early on but are about 2/3 of the financing gap by 2050.
Of course, the emission-permit revenue scenarios that best match the intermediate
projections of the Social Security shortfall do not even remotely match the low or high projections
of the Social Security shortfall. Furthermore, the degree of uncertainty about the emission permit
revenues is enormous. As an example, the current market price of sodium dioxide emissions
permits in the US is about 1/10 of the price that economists had anticipated before the opening of
the market.
Public Finance Considerations
Standard public finance theory indicates that earmarked taxes are generally a bad idea,
because an optimizing social planner should be free to choose the overall tax schedule to minimize
¹This memo ignores Medicare because the cost estimates for Medicare are so extremely
uncertain at this point.
²The permit price streams, emissions paths, and GDP for the climate policy simulations are
outputs of SGM. Permit revenues assume an annual auction of all permits allocated to the U.S.
goyernment.
efficiency losses, and free to allocate incoming revenues to the places where the social marginal
utility of expenditure is highest. From this perspective, the circumstances in which earmarking is
least damaging are those in which the tax revenues bear some relationship to expenditure needs.
The best example is the dedication of gasoline tax revenues to a trust fund for highway
construction and maintenance. On this test, earmarking emissions permit revenues to financing
Social Security is a terrible idea. Many of the kinds of shocks that would affect emission permit
revenues (especially improvement of emissions technologies) are completely unrelated to shocks
to the need for Social Security revenues, while shocks to Social Security needs are probably
negatively correlated with emission permit revenues. For example, if fertility increases, Social
Security financing needs will decline (at least over the projection period), but the extra population
will produce more pollution and therefore more emission permit revenues.
The most persuasive arguments for earmarked taxes are generally public choice or political
economy arguments, which begin either from the premise that the policymaker's objective
function differs from that of society, or that the politics of the specific earmarked tax and
expenditure have some important interaction that justifies the inefficiencies of earmarking. The
best argument that can be made along such lines in this context is that the emission permit is
"good" in a sense not likely to be appreciated by the political system at large (presumably because
of global externalities), and that therefore it is important to tie the selfish interests of some
powerful constituency to the fate of the emissions permits revenues. Specifically, the argument is
that if emission permits are perceived as funding Social Security, they may survive political battles
because the AARP would defend them (I use the AARP here as a stand-in for all self-proclaimed
guardians of Social Security). This argument is not persuasive. The enormous uncertainty about
the magnitude of emission permit revenues makes it seem very unlikely that the AARP would be
keen to tie the fate of Social Security to an emissions-permit horse in the first place. Even if the
Social Security and emissions permits could be linked initially, it seems likely that any shocks to
emissions permit revenues would only make the AARP more eager to switch to a more reliable
source of revenues. By contrast, the payroll tax is very well-suited as a source of Social Security
revenues, because benefits are a function of wages and wage growth, so long-term productivity
shocks affect both revenues and expenditures in similar ways.
Conclusion
A less explicit link between entitlements needs and emission permit revenues is more
palatable than earmarking. In essentially any forseeable future, the retirement of the baby boom
generation will expand the Federal spending beyond any automatic increase in revenues, putting
pressure on the Federal deficit. Extra general revenues from emissions permits would likely be
used to some extent to plug that deficit hole, although it also seems likely that part of the revenues
would be absorbed by extra spending. One could then use standard public finance arguments to
say that, if emission permits are desirable from a social welfare perspective, they should be phased
in gradually over time, with a time path chosen to deliver revenues just when the budget deficit is
under the greatest pressure.
Emissions Trading Revenues
Social Security Financing Gap
(Annual, Percent of GDP)
(Annual, Percent of GDP)
Peak in 2015
1990 in 2010
-10% in 2010
1995 in 2010
Year
Low
Intermediate
High
US Only
Annex I
Global
Annex I
Annex I
Annex I
2000
0.6
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2005
0.7
0.3
-0.2
0.0
0.0
2010
0.7
0.1
-0.5
0.0
0.0
0.0
0.6
1.2
1.2
2015
0.3
-0.3
-1.0
0.0
0.0
0.0
0.8
1.4
1.4
0.1
0.4
0.1
0.9
1.5
1.5
2020
-0.2
-0.9
-1.6
2025
-0.5
-1.4
-2.3
1.2
0.7
0.2
1.0
1.5
1.6
2030
-0.7
-1.7
-2.7
1.7
0.9
0.2
1.0
1.5
1.6
-1.8
-3.0
2.3
1.1
0.2
1.1
1.6
1.6
2035
-0.7
2040
-0.5
-1.7
-3.2
3.0
1.2
0.3
1.2
1.6
1.7
2045
-0.4
-1.7
-3.4
3.7
1.3
0.3
1.2
1.7
1.8
2050
-0.3
-1.7
-3.6
4.7
1.3
0.3
1.3
1.8
1.9
Social Security & Carb Tax Revenues
Some analysts have proposed using revenues from the sale of emissions permits (designed
to slow global warming) to plug the projected entitlements financing gap. This memo argues that
earmarking is a bad idea, because there is no inherent connection between the magnitude of the
two streams, and because the size of both streams (particularly the emission permit revenues) is
extremely uncertain.
Comparison of Anticipated Magnitudes
The first three columns of the attached table show the Social Security Actuary's low,
intermediate, and high estimates of the annual financing shortfall in the Social Security system as a
fraction of GDP (excluding interest payments or receipts on trust fund balances). In the
intermediate projections, the shortfall is monotonically increasing over time, although about 80
percent of the ultimate deterioration has occurred by 2030, when the shortfall is projected to be
about 1.7 percent of GDP.
The next three columns show projected emissions permit revenues as a fraction of GDP
under the "Peak in 2015" plan (the least aggressive option considered), under three assumptions
about the nature of the market for emissions permits: no international trading, trading among
Annex I countries, and global trading.² Revenue estimates in 2030 vary by about a factor of ten
depending on the assumption about trading. In the "no trading" regime, revenues in 2030 are
roughly the same size as the Social Security shortfall, but under the other two options revenues fall
far short. By 2050, revenues under "no trading" are more than twice the Social Security shortfall,
but under the Annex I trading regime revenues are about 3/4 of the shortfall. The remaining
columns of the table show projections of revenues under Annex I trading for the main alternatives
to the "Peak in 2015" plan. Revenues for either the "-10% in 2010" or the "1995 in 2010" plans
roughly match the intermediate projection of the Social Security financing gap by 2050, but in the
early decades revenues substantially exceed the financing gap. Revenues from the "1990 in 2010"
plan exceed the financing gap early on but are about 2/3 of the financing gap by 2050.
Of course, the emission-permit revenue scenarios that best match the intermediate
projections of the Social Security shortfall do not even remotely match the low or high projections
of the Social Security shortfall. Furthermore, the degree of uncertainty about the emission permit
revenues is enormous. As an example, the current market price of sodium dioxide emissions
permits in the US is about 1/10 of the price that economists had anticipated before the opening of
the market.
Public Finance Considerations
Standard public finance theory indicates that earmarked taxes are generally a bad idea,
because an optimizing social planner should be free to choose the overall tax schedule to minimize
¹This memo ignores Medicare because the cost estimates for Medicare are so extremely
uncertain at this point.
²The permit price streams, emissions paths, and GDP for the climate policy simulations are
outputs of SGM. Permit revenues assume an annual auction of all permits allocated to the U.S.
government.
efficiency losses, and free to allocate incoming revenues to the places where the social marginal
utility of expenditure is highest. From this perspective, the circumstances in which earmarking is
least damaging are those in which the tax revenues bear some relationship to expenditure needs.
The best example is the dedication of gasoline tax revenues to a trust fund for highway
construction and maintenance. On this test, earmarking emissions permit revenues to financing
Social Security is a terrible idea. Many of the kinds of shocks that would affect emission permit
revenues (especially improvement of emissions technologies) are completely unrelated to shocks
to the need for Social Security revenues, while shocks to Social Security needs are probably
negatively correlated with emission permit revenues. For example, if fertility increases, Social
Security financing needs will decline (at least over the projection period), but the extra population
will produce more pollution and therefore more emission permit revenues.
The most persuasive arguments for earmarked taxes are generally public choice or political
economy arguments, which begin either from the premise that the policymaker's objective
function differs from that of society, or that the politics of the specific earmarked tax and
expenditure have some important interaction that justifies the inefficiencies of earmarking. The
best argument that can be made along such lines in this context is that the emission permit is
"good" in a sense not likely to be appreciated by the political system at large (presumably because
of global externalities), and that therefore it is important to tie the selfish interests of some
powerful constituency to the fate of the emissions permits revenues. Specifically, the argument is
that if emission permits are perceived as funding Social Security, they may survive political battles
because the AARP would defend them (I use the AARP here as a stand-in for all self-proclaimed
guardians of Social Security). This argument is not persuasive. The enormous uncertainty about
the magnitude of emission permit revenues makes it seem very unlikely that the AARP would be
keen to tie the fate of Social Security to an emissions-permit horse in the first place. Even if the
Social Security and emissions permits could be linked initially, it seems likely that any shocks to
emissions permit revenues would only make the AARP more eager to switch to a more reliable
source of revenues. By contrast, the payroll tax is very well-suited as a source of Social Security
revenues, because benefits are a function of wages and wage growth, so long-term productivity
shocks affect both revenues and expenditures in similar ways.
Conclusion
A less explicit link between entitlements needs and emission permit revenues is more
palatable than earmarking. In essentially any forseeable future, the retirement of the baby boom
generation will expand the Federal spending beyond any automatic increase in revenues, putting
pressure on the Federal deficit. Extra general revenues from emissions permits would likely be
used to some extent to plug that deficit hole, although it also seems likely that part of the revenues
would be absorbed by extra spending. One could then use standard public finance arguments to
say that, if emission permits are desirable from a social welfare perspective, they should be phased
in gradually over time, with a time path chosen to deliver revenues just when the budget deficit is
under the greatest pressure.
Emissions Trading Revenues
Social Security Financing Gap
(Annual, Percent of GDP)
(Annual, Percent of GDP)
Peak in 2015
1990 in 2010
-10% in 2010
1995 in 2010
Year
Low
Intermediate
High
US Only
Annex I
Global
Annex I
Annex I
Annex I
2000
0.6
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.0
2005
0.7
0.3
-0.2
0.0
0.0
0.0
0.0
0.0
0.0
2010
0.7
0.1
-0.5
0.0
0.0
0.0
0.6
1.2
1.2
2015
0.3
-0.3
-1.0
0.0
0.0
0.0
0.8
1.4
1.4
2020
-0.2
-0.9
-1.6
0.1
0.4
0.1
0.9
1.5
1.5
2025
-0.5
-1.4
-2.3
1.2
0.7
0.2
1.0
1.5
1.6
2030
-0.7
-1.7
-2.7
1.7
0.9
0.2
1.0
1.5
1.6
2035
-0.7
-1.8
-3.0
2.3
1.1
0.2
1.1
1.6
1.6
2040
-0.5
-1.7
-3.2
3.0
1.2
0.3
1.2
1.6
1.7
2045
-0.4
-1.7
-3.4
3.7
1.3
0.3
1.2
1.7
1.8
2050
-0.3
-1.7
-3.6
4.7
1.3
0.3
1.3
1.8
1.9
09/11/97 THU 16:31 FAX 202 6222633
001
Office of Economic Policy
Department of the Treasury
Washington, D.C. 20220
FAX
Date: 9/11/97
Number of pages including cover sheet: 11
Name
Fax Number
Phone Number
To: Joe Aldy
395-6853
395-1455
From: Lara Thuldoon 202-622-2633
622-6773
REMARKS:
Urgent
For your review
Reply ASAP
Please comment
002
ranges
Effect on Fuel Prices
4P if
AP if
AP if
AP if
APif
AP if
APif
permit
permit
permit
permit
permit
permit
permit
price =
price =
price =
price =
price =
price =
price =
AP if permit
4P if permit
$100
$50
$80
$90
$140
$30
$200
price = $5
price = $25
Natural gas
$1.6000
$0.8000
$1.2800
$1.4400
$2.2400
$0.4800
$3.2000
$0.0800
0.4
$/thousand Cubic Feet
Fuel Oil
$0.3000
$0.1500
$0.2400
$0.2700
$0.4200
$0.0900
$0.6000
$0.0150
0.075
$/gallon
Electricity
$0.0150
$0.0075
$0.0120
$0.0135
$0.0210
$0.0045
$0.0300
$0.0008
0.00375
$/kWh
LPG
$0.3000
$0.1500
$0.2400
$0.2700
$0.4200
$0.0900
$0.6000
$0.0150
0.075
$/gallon
Gasoline
$0.2600
$0.1300
$0.2080
$0.2340
$0.3640
$0.0780
$0.5200
$0.0130
0.065
$/gallon
Coal
$70.00
$35.00
$56.00
$63.00
$98.00
$21.00
$140.00
$3.50
17.5
$/ton
Oil
$14.00
$7.00
$11.20
$12.60
$19.60
$4.20
$28.00
$0.70
3.5
$/barrel
09/11/97 THU 16:31 FAX 202 6222633
Par 1
003
Joe's Runs
1
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $5
Number
% HH
Q/hh of
QAP Scaled
of HH
using
each US
down by
A Expenditure -
(millions)
Units/HH
this fuel
HH
P
AP
QAP
12%
AQ/Q
& = -0.4
Natural
Gas
58.7
87.50
60.77%
53.17
$6.20
0.08
$4.25
$3.74
-0.01
$2.53
Units -
thousand
cubic feet
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.02
$1.15
$1.01
-0.01
$0.68
Units -
Gallons
$/gal
Electricit
y
96.6
9,965.00
100.00%
9,965.00
$0.08
0.00
$7.47
$6.58
0.00
$4.46
Units - kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.02
$0.65
$0.57
-0.01
$0.38
Units -
Gallons
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.01
$12.19
$10.73
0.00
$7.26
Units -
Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$25.71
$22.63
$15.31
Total Indirect Costs per Household (1992 dollars)
$28.45
$25.04
$16.94
09/11/97 THU 16:32 FAX 202 6222633
Total Costs per Household (1992 dollars)
$54.16
$47.66
$32.25
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
0.08%
0.07%
0.05%
increased total expenditure as a percentage of median income
0.18%
0.16%
0.11%
Par- 1
4 004
Joe's Runs
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $25
>
Number
% HH
Q/hh of
QAP Scaled
of HH
using
each US
down by
A Expenditure -
(millions)
Units/HH
this fuel
HH
P
AP
QAP
12%
AQ/Q
E = -0.4
Natural
Gas
58.7
87.50
60.77%
53.17
$6.20
0.40
$21.27
18.72
-0.03
$12.21
Units -
thousand
cubic feet
S/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.08
$5.74
5.05
-0.03
$3.25
Units -
Gallons
$/gal
Electricit
y
96.6
9,965.00
100.00%
9,965.00
$0.08
0.00
$37.37
32.88
-0.02
$21.74
Units - kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.08
$3.23
2.84
-0.03
$1.83
Units -
Gallons
Sigal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.07
$60.95
53.64
-0.02
$35.21
Units -
Gallons
Sigal
$/gal
Total Direct Costs per Household (1992 dollars)
$128.55
$113.13
$74.24
Total Indirect Costs per Household (1992 dollars)
$142.25
$125.18
$82.15
09/11/97 THU 16:32 FAX 202 6222633
Total Costs per Household (1992 dollars)
$270.80
$238.31
$156.38
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
0.42%
0.37%
0.24%
increased total expenditure as a percentage of median income
0.89%
0.78%
0.51%
Par ?
005
Joe's Runs
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $30
Number
% HH
Q/hh of
QAP Scaled
of HH
using
each US
down by
A Expenditure -
(millions)
Units/HH
this fuel
HH
P
AP
QAP
12%
AQ/Q
E = -0.4
Natural
Gas
58.7
87.50
60.77%
53.17
$6.20
$0.4800
$25.52
$22.46
-0.03
$14.52
Units -
thousand
cublc feet
$/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
$0.0900
$6.88
$6.06
-0.04
$3.85
Units -
Gallons
$/gal
$/gal
Electricit
y
96.6
9,965.00
100.00%
9,965.00
$0.08
$0.0045
$44.84
$39.46
-0.02
$25.92
Units - kWh
$/kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
$0.0900
$3.87
$3.41
-0.04
$2.17
Units -
Gallons
$/gal
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
$0.0780
$73.15
$64.37
-0.03
$41.92
Units -
Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$154.26
$135.75
$88.39
Total Indirect Costs per Household (1992 dollars)
$170.70
$150.22
09/11/97 THU 16:33 FAX 202 6222633
$97.81
Total Costs per Household (1992 dollars)
$324.97
$285.97
$186.20
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
0.51%
0.44%
0.29%
increased total expenditure as a percentage of median income
1.06%
0.94%
0.61%
Par
006
1.
ranges
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $50
Number
% HH
Q/hh of
of HH
using
each US
A Expenditur
QAP scaled
(millions)
Units/HH
this fuel
HH
P
AP
AQ/Q
e - E = -0.4
QAP
down by 12%
Natural Gas
58.7
87.50
60.77%
53.17
$6.20
0.80
-0.05
$23.33
$42.54
$37.43
Units - thousand
cubic feet
$/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.15
-0.07
$6.12
$11.47
$10.09
Units - Gallons
$/gal
$/gal
Electricity
96.6
9,965.00
100.00%
9,965.00
$0.08
0.01
-0.04
$42.11
$74.74
$65.77
Units - kWh
$/kVh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.15
-0.07
$3.45
$6.45
$5.68
Units - Gallons
$/gal
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.13
-0.04
$67.68
$121.91
$107.28
Units - Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$142.68
$257.11
$226.25
Total Indirect Costs per Household (1992 dollars)
$157.89
$284.50
$250.36
Total Costs per Household (1992 dollars)
$300.57
$541.61
$476.62
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
0.47%
0.84%
0.74%
09/11/97 THU 16:33 FAX 202 6222633
increased total expenditure as a percentage of median income
0.98%
1.77%
1.56%
Par ,
007
1.
ranges
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $80
Number
% HH
Q/hh of
of HH
using
each US
A Expenditur
QAP scaled
(millions)
Units/HH
this fuel
HH
P
AP
AQ/Q
e - S = -0.4
QAP
down by 12%
Natural Gas
58.7
87.50
60.77%
53.17
$6.20
1.28
-0.08
$35.21
$68.06
$59.89
Units - thousand
cubic feet
$/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.24
-0.11
$9.05
$18.35
$16.15
Units - Gallons
$/gal
$/gal
Electricity
96.6
9,965.00
100.00%
9,965.00
$0.08
0.01
-0.06
$64.75
$119.58
$105.23
Units - kWh
$/kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.24
-0.10
$5.12
$10.32
$9.08
Units - Gallons
$/gal
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.21
-0.07
$103.04
$195.06
$171.65
Units - Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$217.18
$411.37
$362.01
Total Indirect Costs per Household (1992 dollars)
$240.32
$455.21
$400.58
Total Costs per Household (1992 dollars)
$457.50
$866.58
$762.59
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
09/11/97 THU 16:33 FAX 202 6222633
increased direct expenditure as a percentage of median income
0.71%
1.35%
1.19%
increased total expenditure as a percentage of median income
1.50%
2.84%
2.50%
Par
008
ranges
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $90
Number
% HH
Q/hh of
of HH
using
each US
A Expenditur
QAP scaled
(millions)
Units/HH
this fuel
HH
P
AP
AQ/Q
e- 8 = -0.4
QAP
down by 12%
Natural Gas
58.7
87.50
60.77%
53.17
$6.20
1.44
-0.09
$38.83
$76.57
$67.38
Units - thousand
cubic feet
$/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.27
-0.12
$9.91
$20.65
$18.17
Units - Gallons
$/gal
$/gal
Electricity
96.6
9,965.00
100.00%
9,965.00
$0.08
0.01
-0.07
$71.86
$134.53
$118.38
Units - kWh
$/kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.27
-0.12
$5.61
$11.61
$10.22
Units - Gallons
$/gal
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.23
-0.08
$113.96
$219.44
$193.10
Units - Gallons
S/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$240.16
$462.79
$407.26
Total Indirect Costs per Household (1992 dollars)
$265.75
$512.11
$450.65
Total Costs per Household (1992 dollars)
$505.90
$974.90
$857.91
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
09/11/97 THU 16:34 FAX 202 6222633
increased direct expenditure as a percentage of median income
0.79%
1.52%
1.33%
increased total expenditure as a percentage of median income
1.66%
3.19%
2.81%
Pa- 1
009
Incidence
4.
Incidence of an Energy tax by Percent Share of Current Income
For a $100/ton Permit
x
Q/hh of
Number of HH
% HH using
each US
A Expenditure -
QAP
(millions)
Units/HH
this fuel
HH
P
ДР
AQ/Q
E = -0.4
unadjusted
12% reduc
Natural Gas
58.7
87.50
60.77%
53.17
6.20
1.60
-0.10
$42.26
$85.07
74.86377
Units - thousand cubic feet
S/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
0.90
0.30
-0.13
$10.71
$22.94
20.18862
Units - Gallons
S/gal
$/gal
Electricity
96.6
9,965.00
100.00%
9,965.00
0.08
0.02
-0.07
$78.75
$149.48
131.538
Units - kWh
$/kWh
$/gal
LPG
8.1
513.00
8.39%
43.02
0.92
0.30
-0.13
$6.06
$12.90
11.3561
Units -- Gallons
S/gal
S/gal
Gasoline
84.9
1,067.00
87.89%
937.77
1.16
0.26
-0.09
$124.43
$243.82
214.5611
Units - Gallons
$/gal
S/gal
Total Direct Costs per Household (1992 dollars)
$262.21
$514.21
452.5076
Total Indirect Costs per Household (1992 dollars)
$290.15
$569.01
500.7256
Total Costs per Household (1992 dollars)
$552.35
$1,083.22
953.2332
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
0.86%
1.68%
increased total expenditure as a percentage of median income
1.81%
3.55%
Sources: Number of HH - Energy Information Administration/Household Energy Consumtion and Expenditures Survey 1993, adjusted to 1994 dollars
Units/HH - EIA, RECS 1993 Average Consumption per HH (adjusted to 1994 dollars)
09/11/97 THU 16:34 FAX 202 6222633
% HH using this Fuel - (Number of hh)/(units/HH)
Q/hh of each US HH - (Units/HH)*(%HH using the Fuel)
Price - EIA
AP - Buisness Daily, August 7, 1997, p.1
AQ/Q - based on price elaticity of demand for energy of -0.4 from Energy Economics and Policy, 1980, p. 232.
A Expenditure - E = -0.4 -> new price*new quantity - old price*old quantity
QAP - unadjusted
Pa- 1
010
ranges
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $140
Number
% HH
Q/hh of
of HH
using
each US
1 Expenditur
QAP scaled
(millions)
Units/HH
this fuel
HH
P
ДР
AQ/Q
e - E = -0.4
QAP
down by 12%
Natural Gas
58.7
87.50
60.77%
53.17
$6.20
2.24
-0.14
$54.25
$119.10
$104.81
Units - thousand
cubic feet
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
0.42
-0.19
$13.28
$32.12
$28.26
Units - Gallons
$/gal
Electricity
96.6
9,965.00
100.00%
9,965.00
$0.08
0.02
-0.10
$104.12
$209.27
$184.15
Units - kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
0.42
-0.18
$7.54
$18.07
$15.90
Units - Gallons
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
0.36
-0.13
$161.96
$341.35
$300.39
Units - Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$341.15
$719.90
$633.51
Total Indirect Costs per Household (1992 dollars)
$377.50
$796.61
$701.02
Total Costs per Household (1992 dollars)
$718.65
$1,516.51
$1,334.53
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
09/11/97 THU 16:35 FAX 202 6222633
increased direct expenditure as a percentage of median income
1.12%
2.36%
2.07%
increased total expenditure as a percentage of median income
2.35%
4.97%
4.37%
Par
011
Joe's Runs
Incidence of an Energy tax by Percent Share of Current Income
Permit price = $200
Number
% HH
Q/hh of
QAP Scaled
of HH
using
each US
down by
A Expenditure -
(millions)
Units/HH
this fuel
HH
P
ДР
QAP
12%
AQ/Q
6 = -0.4
Natural
Gas
58.7
87.50
60.77%
53.17
$6.20
$3.2000
$170.14
$149.73
-0.21
$66.96
Units -
thousand
cubic feet
$/gal
$/gal
Fuel Oil
10.8
684.00
11.18%
76.47
$0.90
$0.6000
$45.88
$40.38
-0.27
$15.29
Units -
Gallons
$/gal
$/gal
Electricit
y
96.6
9,965.00
100.00%
9,965.00
$0.08
$0.0300
$298.95
$263.08
-0.15
$135.62
Units - kWh
$/kWh
$/kWh
LPG
8.1
513.00
8.39%
43.02
$0.92
$0.6000
$25.81
$22.71
-0.26
$8.75
Units -
Gallons
$/gal
$/gal
Gasoline
84.9
1,067.00
87.89%
937.77
$1.16
$0.5200
$487.64
$429.12
-0.18
$205.14
Units -
Gallons
$/gal
$/gal
Total Direct Costs per Household (1992 dollars)
$1,028.43
$905.02
$431.77
Total Indirect Costs per Household (1992 dollars)
$1,138.01
$1,001.45
$477.78
09/11/97 THU 16:35 FAX 202 6222633
Total Costs per Household (1992 dollars)
$2,166.44
$1,906.47
$909.56
Median HH Income (1992 dollars)
$30,543.18
$30,543.18
$30,543.18
increased direct expenditure as a percentage of median income
3.37%
2.96%
1.41%
increased total expenditure as a percentage of median income
7.09%
6.24%
2.98%
Par- ,
pre-Kyoto
Comments on $500 million/year Technology Proposal
DOE's response does not appear to have answered the request of the Principals for a detailed
description of the "technology option" in terms of specific policies (dollars spent on R&D, dollars
spent on diffusion, imposition of standards, price measures, and moral suasion) and their best-guess
estimated effects. At first DOE seems to say that the predicted effects are pure R&D, and then it
turns out that there are hidden assumptions about public awareness changing or standards being
changed. We continue to believe that much, if not all, of the R&D is probably worth doing,
particularly along the lines of the PCAST report. But we also continue to believe in a pessimistic
bottom line for the odds of incremental payoffs in terms of carbon reductions by 2010. As John
Holdren said in his 9/28 presentation, the time lag for the payoff, even to applied R&D, is simply
too long to expect that by 2010 we would get more than "diddly" from new spending.
DOE stated that this proposal is based on the efficiency case in the 5 Labs Study. In a review of the
proposal presented on 9/29, it appears that there are numerous divergences from the 5 Labs Study
efficiency case. In light of the inconsistencies apparent in the proposal, and the substantial
methodological flaws in the 5 Labs Study, it seems imprudent to base significant policy decisions
on information received thus far. The point was raised at the 8/19/97 meeting on the 5 Labs Study
that this study should not go to or be used by principals. To date, there appears to be insufficient
justification to modify this view.
General Comments
The 5 Labs Study indicates that government programs, utility programs, and state programs
cost 15% of technology costs (p. 1.13). Since DOE apportions all carbon savings in their
proposal to the federal programs listed in the summary chart, we assume that all costs accrue
to the federal government. In the "optimistic" assessment of the costs and benefits, DOE
claims that government programs will likely only cost about 7% of technology costs, because
half of emissions reductions occur through standards (see below). Assuming that this is true,
and that the technology costs of the efficiency case range between $26 - $49 billion/year in
the optimistic assessment (p. 1.14), then government programs should cost between $1.82 -
$3.49 billion/year. However, using a 13.5% government cost stipulation (based on a 15%
government program cost, minus 10% [instead of 50%] of these costs because of standards),
the costs of government programs would range between $3.51 - $6.62 billion/year. The
proposal presented on 9/29 costs 3 to 13 times less than projected by the 5 Labs Study, and
yet generates greater carbon savings.
The proposal employs standards to a much lesser extent than the 5 Labs Study. In the Study,
"at least half of the efficiency occurs as a result of federal policies (e.g., standards and carbon
permit charges)" (p. 1.13). Since the efficiency case does not include a carbon permit
system, we assume that half of the carbon savings in the efficiency case result from
standards. However, in this proposal, only about 10% of the emissions reductions occur due
to standards (on the high ends of the ranges, 20 MMTCE out of 206 MMTCE).
The projected carbon savings for 2010, while indicated as approximately 155 MMTCE, has
a range of 127-206 MMTCE. Note that this large range does not overlap with the 5 Labs
Study projection of 126 MMTCE (p. 1.12).
The efficiency case is portrayed in the 5 Labs Study as carbon savings that occur because of
already available and cost-effective technologies. In effect, government policies are only
necessary to overcome market barriers. However, this proposal appears to be more reliant
on R&D than on deployment and diffusion of existing technologies. Using the upper bounds
of the ranges of carbon savings, we find that more than half of emissions reductions (104 of
206 MMTCE) result from R&D programs.
Specific Comments
Buildings Sector
Two programs claim to achieve 17-29 MMTCE. Note that under the 5 Labs efficiency case, 25
MMTCE of potential reductions were identified (p. 1.12), with a different penetration assumption
than the one provided in the summary chart. The Study employed a 35% penetration rate assumption
(p. 3.3), while this summary chart claims to be based on a 15-25% assumption for equipment
efficiency and a 25% assumption for 21st Century Housing. With the lower penetration rate
assumed in this proposal, we would assume that the carbon savings would be less than those found
in the 5 Labs Study -- instead, they are greater. Based on these assumptions and the information
provided by the 5 Labs Study, we would expect carbon savings to range between 11-18 MMTCE.
Equipment Efficiency: The 5 Labs Study indicates that a total of 25 MMTCE can be reduced in
residential and commercial buildings under the efficiency case. The 9/26 memo describes this set
of programs to include fuel cells, even though fuel cells are not in the 5 Labs efficiency case (they
only come into play in high efficiency case, although the text is very unclear about whether fuel cells
actually generate any benefits prior to 2020).
21st Century Housing: There is insufficient detail provided in the 9/26 memo to identify the
appropriate carbon savings in the 5 Labs Study.
Transportation Sector
The 5 Labs Study projects 73 MMTCE reductions in emissions under the efficiency case (p. 1.12),
while this proposal estimates carbon savings ranging between 65 - 87 MMTCE. Note that this upper
bound is almost equivalent to the high efficiency case with a $25/ton permit fee in the Study (88
MMTCE).
Two PNGV Categories: The 5 Labs Study indicates that annual PNGV funding is approximately
$250 million/year (p. 5.2). The two categories of increased PNGV programs would sum to $140
million/year in FY99 and $260 million/year in FY03. This increase is much less than believed
necessary to achieve the goals of the PNGV program. The authors of the 5 Labs Study note that for
PNGV to be successful, "substantial additional funding for R&D will be required, perhaps two to
ten times what is presently being spent" (p. 5.7). The proposal increases funding to just the lower
end of this required spending level.
Industry Sector
The 5 Labs Study projects 28 MMTCE of carbon emissions reductions under its efficiency case (p.
1.12). This proposal estimates carbon savings under three categories of programs ranging between
30 - 65 MMTCE. Note that the upper end of this range is 11 MMTCE more than the high efficiency
case with a $25/ton permit fee in the 5 Labs Study.
Industries of the Future: In the 5 Labs Study, the list of heavy manufacturing industries in table 4.6
(p. 4.10) corresponds to the list of the Industries of the Future on the DOE webpage
(http://www.oit.doe.gov/iof/industry.html) In this table, these industries account for only 9
MMTCE in the efficiency case and 21 MMTCE in the high efficiency case ($50/ton permit system).
However, the proposal notes that Industries of the Future programs can achieve carbon reductions
ranging between 10 - 20 MMTCE.
Utilities Sector
Three categories of programs claim to generate carbon savings of 15-25 MMTCE. However, the
efficiency case in the 5 Labs Study does not project any reductions in carbon emissions in this sector
(p. 1.12). Further, the carbon sequestration R&D category of programs is not described in the 9/26
memo.
For additional review of the methodological flaws in the sectoral analyses, refer to earlier memos
that provide comments on the 5 Labs Study.
EXECUTIVE OFFICE OF THE PRESIDENT
COUNCIL OF ECONOMIC ADVISERS
WASHINGTON, D.C. 20500
SENIOR ECONOMIST
MEMORANDUM
TO:
Joe Romm
Acting Assistant Secretary for Energy Efficiency and Renewable Energy
U.S. Department of the Energy
FROM:
Jason Shogren IS and Joe Aldy
DATE:
August 22, 1997
RE:
Review of 5-Labs Report: Scenarios of U.S. Carbon Reductions
Enclosed you will find our comments on the report Scenarios of U.S. Carbon Reductions. We
appreciate the opportunity to review the report and we trust you will incorporate our comments.
4
Comments on "Scenarios of U.S. Carbon Reductions" (5 Labs Study)
General comment
The report, Scenarios of U.S. Carbon Reductions, presents a useful cataloging of the
technological options that could play a key role in reducing greenhouse gas emissions. The
report does not present the specific policies or the behavioral responses that will trigger the
adoption or diffusion of these technologies. As such, the report cannot serve as the basis of
decision-making by top policy-makers (as opposed to background detail that others may find
useful). The report as written, however, leaves the impression that these technologies are policy,
which they are not. The U.S. government does not have directly under its control the decisions
of private firms and consumers whether to adopt these technologies. The report must be either
redone to reflect how likely these technologies will be used given the behavioral responses to
likely policies, or reframed to reflect what it is--a catalog of technologies that might be used to
address global climate change. The latter path is more straightforward and could readily be
accomplished. Among other changes, it is essential that DOE remove references to "net
savings" from the report because this does not reflect the actual costs of implementing these
policies.
Our specific comments follow.
Executive Summary
1) paragraph 3: The point regarding the opportunity to reduce emissions through "a vigorous
national commitment" should be explicit that this commitment is implemented through federal
policies. To state that 120 MMTCE can be reduced by "energy efficiency alone" seems to imply
that these reductions are free. These reductions through energy efficiency are induced by
aggressive policies, and the statement should reflect that. The subsequent discussion of
reductions with carbon permits should also reflect that the level of reductions can occur only
through a carbon pricing policy in addition to any non-price policies (e.g., standards).
2) Paragraph 4: Estimates of energy cost savings should not be provided unless and until an
adequate estimation approach is used to calculate cost savings.
3) Paragraph 5: This paragraph should really concentrate on the point that this study identifies a
vast array of technologies that may reduce carbon emissions through climate policy. This is the
true strength of the study, and it should be emphasized more.
1
Chapter 1
4) The entire study is premised on two sets of undefined policies: an "aggressive" or
"invigorated" public sector effort to stimulate energy efficient technology adoption (efficiency
case) and a "very aggressive" public sector effort to stimulate technology development and
adoption (high efficiency/low carbon case). The only specific policy instrument mentioned in
the report is a tradeable permit at prices of $25/ton and $50/ton. The study merely asserts that
these unidentified policies would result in: 1) "better technology" (p. 2.5); 2) "higher penetration
rates" (p. 2.5); 3) "changing the capital recovery factor [in industry sector] from 33% to 15%" (p.
4.6); and 4) "technological breakthroughs" (p. 5.3). These policy effects would result in
reductions of about 200 MMTCE for "free": firms and individuals receive energy cost-savings
greater than or equal to technology adoption costs.
The report specifically states that the efficiency case reduces, but does not eliminate, market
barriers and that implementation costs are ignored. Policy intervention to eliminate a market
barrier cannot make society better off and generally makes society worse off to the extent that it
imposes costs. In particular, a set of climate change policies to stimulate technology adoption
could increase efficiency, but only because they also decrease the effect of a market failure
(carbon emissions). Social welfare is improved because the net benefits of indirectly fixing the
market failure exceed the costs of removing the barriers. If carbon emissions are appropriately
priced (assuming in this case that $50/ton is the correct carbon price), a policy to remove a
barrier will generate negative net benefits. High adoption rates will be realized once prices rise
enough for some technologies to clear the barriers.¹
The economics literature has identified several barriers that help explain the slow rate of
technology adoption.²
Qualitative attributes of technologies can affect adoption. Consumers of technology
prefer technologies because of a set of characteristics, not just energy efficiency. For
example, some consumers may purchase a product with a lower efficiency because the
former is more reliable than the efficiency-superior product.
1
In contrast, policy intervention to address a market failure (such as unpriced carbon emissions) may well
make society better off, depending on the stringency of the intervention.
2
For a review of these issues, see Gilbert Metcalf and Kevin Hassett, "Measuring the Energy Savings
from Home Improvement Investments: Evidence from Monthly Billing Data," National Bureau of Economic
Research Working Paper 6074, June 1997; Jeffrey A. Dubin and Daniel L. McFadden, "An Econometric Analysis
of Residential Electric Appliance Holdings and Consumption," Econometrica, vol. 52, no. 2, 1984; Adam B. Jaffe
and Robert N. Stavins, "Energy-Efficiency Investments and Public Policy", Energy Journal, vol. 15, no. 2, 1994;
Albert L. Nichols, "Demand-Side Management: Overcoming Market Barriers or Obscuring Real Costs?" Energy
Policy, vol. 22, no. 10, 1994; Jerry Hausman, "Individual Discount Rates and the Purchase and Utilization of
Energy-Using Durables," Bell Journal of Economics, vol. 10, 1979.
2
New technologies may be costly to integrate with existing ones. Until all components of
a complex system are fully depreciated it may make sense to replace energy inefficient
components with another like-wise inefficient component.
Uncertainty of future energy prices, or constraints on the ability to borrow capital may
make households act as if they have implausibly high implicit discount rates.
Just because a technology is cost-effective on average does not mean that it is cost-
effective for all individuals. Those who may use the device less intensively may find it
optimal to purchase a less efficient model.
These barriers clearly demonstrate that investments to minimize energy costs are different from
investments to minimize the total costs of production.
The study provides a crude estimate of the costs to government of lowering market barriers to
achieve the estimated emissions reductions. A sense of the likely costs can be derived by
evaluating the experience of the Climate Change Action Plan (CCAP). CCAP promotes carbon
reductions through a broad array of voluntary programs that stimulate "cost-effective"
technology adoption by private firms. Participation by a firm in a CCAP program is supposed to
reduce carbon emissions and to offer financial returns.³ We do not address an important
threshold question of why cost-minimizing firms would ever need any need help from
government programs to take actions that would lower their costs.
CCAP received appropriations totaling $494 million (1995$) during the FY95 - FY97 period.
We assume that these costs are distributed uniformly over the three years. During this period, the
Department of Energy and the Environmental Protection Agency can account for reductions of
14 MMTCE (see attached table). Evaluating the cost effectiveness of these programs requires an
assumption about emissions reductions in the outyears. Since the programs are persuading firms
to adopt innovations that offer financial returns, we believe that the firms would soon have
adopted them in the absence of the programs. Thus the emissions reductions might last for
several years. To develop illustrative cost estimates we assume between 2 and 7 years of
emissions reductions. We describe our estimates given the assumption of 2 years; the method for
the assumption of 7 years is identical.4 Assuming constant effectiveness of program
expenditures, the emissions reductions attributable to past expenditures would grow from 2.8
million tons in the first year to 5.6 million in the second year and third years, and then decline to
2.8 million tons in the 4th year, before falling to 0 in the 5th and subsequent years. The ratio of
3
Note that CCAP efforts are incorporated in the AEO97 baseline.
4
This analysis was conducted based on the June 10 draft that stated 180 MMTCE of reductions associated
with government programs could be expected under a "very aggressive" set of policies. Since the August 1 draft
notes that more non-price policy induced reductions would be expected, the cost estimates provided in this
discussion underestimate the program costs associated with this greater number of reductions.
3
the present value of these costs and of these tons is $33/ton using a 7 percent discount rate. Thus
taking into account the lag between program expenditures and emissions reductions, the average
cost effectiveness is $33/ton (with a 7 year assumption the cost effectiveness is $13/ton).
Assuming constant program effectiveness would imply Federal costs of $5.9 billion per year
(with the 7 year assumption the total cost estimate would be half as much.)
We believe that there are several good reasons to think that the cost of reducing emissions will
rise, however, as these or similar programs are expanded. For example, if the potential adopters
differed in terms of their cost savings (or willingness to adopt innovations) then the government
program would encounter diminishing returns as it tried to reach the less receptive users of
technology. Suppose that the (marginal) program cost effectiveness deteriorated by 10 percent
every time the annual reductions in emissions grew by as much as the annual reductions implied
by the current program. In this instance the marginal cost of achieving 180 million tons of
emissions reductions would be about 21 times greater than the marginal cost of the existing
program, and far in excess of reasonable values for a ton of carbon emissions averted. In this
case the total cost of the program would be $45 billion per year. Similar assumptions for the 7
year case would lead to total costs of nearly $7 billion per year, and marginal costs of $80/ton.
Thus we believe that the cost of a government program to ensure energy reductions of 180
million metric tons of carbon could easily run into many tens of billions of dollars per year. In
addition, the marginal cost-effectiveness of these programs could substantially exceed reasonable
estimates of the value of carbon emissions reductions.
Of course the government might choose to achieve these reductions using command and control
type regulations, such as national building codes, or increasingly stringent CAFE standards.
These would substitute private sector costs for government administrative costs.
5) 1.1, paragraph 1: Sentence 3 should note that "the improved performance and increased
penetration of efficient and low-carbon technologies" are program- and price-induced.
6) 1.1, section 1.1, purpose 1: The statement about a "vigorous national commitment" should be
explicit that this means a commitment through government programs.
7) 1.4, Table 1.1: The study notes that it employs EIA's Annual Energy Outlook 1997
projections for the business-as-usual case in 2010 with a modification to the transportation
sector. However, the numbers in this chart do not match up with the numbers in the AEO97
reference case. In fact, they are much closer to the AEO97 low economic growth case (for
industry and buildings). We assume that the labs study is using the reference case from AEO97
since it uses the reference case carbon emissions for 2010. If this is the case, then the following
should be the sectoral breakdown of energy consumption (AEO97, pp. 97-99, and pp. 125-127):
4
Buildings:
36.81 quads
Residential:
20.83 quads
Commercial:
15.98 quads
Industrial:
39.69 quads
Transportation:
31.39+ quads⁵
Total:
107.89+ quads
If the labs study employs the low economic growth case, then it should state so explicitly in the
report and explain why this case, as opposed to the reference or other cases, was selected.
Otherwise, the AEO97 numbers should be used.
8) 1.6, Table 1.2: The 2010 BAU carbon emissions for buildings and industry seem not to match
the AEO97 reference case emissions for these sectors. AEO97 projects carbon emissions to be
576.1 MMTCE for buildings (residential: 321.4; commercial: 254.7) and industry to be 548.5
MMTCE in 2010. This implies that, with the adjusted transportation emissions, BAU should
total 1740 MMTCE, not 1720.
9) 1.8, Table 1.3: The study states that it employs the Annual Energy Outlook business-as-usual
(BAU) forecast for the buildings and industry sectors, with modifications that are "not greatly
different from the EIA case" (p. 1.2) for the transportation sector.⁶ The one modification stated
in the study affects the fuel efficiency of the light duty vehicle fleet. While AEO97 assumes that
fuel efficiency will increase in the future, the labs study assumes that fuel efficiency will remain
constant. This change should result in a slower rate of energy efficiency improvement in the
economy under business as usual conditions.
The AEO97 BAU forecast assumes an improvement of energy efficiency of 0.9% per year
through 2015 (annual E/GDP = -0.9%) (AEO97, p. 4). The study assumes energy efficiency
improvement under BAU occurs at a rate of 0.77%. This difference appears to be somewhat
significant. Inferring from the transportation chapter (table 5.1), this report states that energy use
would increase 0.9 quads over the AEO97 reference case. CEA contacted Art Andersen at the
Energy Information Administration to determine how much of an effect holding fuel efficiency
constant would have on the E/GDP ratio.⁷ According to Andersen, constant fuel efficiency
would "disappear in the rounding" in the E/GDP ratio. He stated that this assumption would
5
The 1997 AEO projects transportation energy consumption to be 31.39 quads in 2010. With the labs
study assumption regarding constant fuel efficiency, the projected energy consumed in this sector should increase.
Although the text never explicitly states the extent of this increase, we inferred that it is 0.9 quads. However, since
Andersen informed us that the increase would be 0.6 quads, we assessed both in a subsequent comment.
6
The labs study also modified the electricity sector forecast, but that modification is not relevant to our
discussion of the energy efficiency of the economy.
7
Art Andersen is the Director of the Energy Demand and Integration Division, EIA.
5
result in energy use increasing by 0.6 quads in 2010 over the reference case. CEA recalculated
the E/GDP ratio used in the AEO97 BAU to account for this extra energy use (assuming GDP
remains the same across these cases), and found that annual E/GDP would decrease 0.86% under
the constant fuel efficiency assumption (0.6 quads case). With the inference from the
transportation chapter, the annual E/GDP rate would be -0.85% (0.9 quads case). The labs study
BAU assumes fewer energy efficiency improvements than should be expected under these
adjusted BAU scenarios.
Two related implications arise from this. First, since the study employs a modified version of the
AEO97 energy use forecast, it should modify the AEO97 carbon emissions forecast. With a
slower improvement in energy efficiency under the lab study assumptions, the 2010 BAU carbon
emissions should be greater than the 1722.4 MMTCE in AEO97 (AEO97, p. 120). As we note in
the previous comment, by incorporating the AEO97 reference case carbon emissions for
buildings and industry, the BAU should be about 1740 MMTCE. This obviously implies that
more reductions will be necessary to stabilize emissions at the 1990 level in 2010.
Second, the carbon reductions calculated for the various scenarios in this study are based on this
-0.77% E/GDP BAU. This implies that some of the carbon reductions claimed under the
efficiency and high efficiency cases actually occur in the -0.86% BAU. This double-counting
could be significant. The CEA-generated BAU (0.6 quads case) accounts for 17% of the E/GDP
gains assumed in the efficiency case (see attached chart).⁸ The alternative CEA-generated BAU
(0.9 quads case) accounts for 15% of the E/GDP gains assumed in the efficiency case. Assuming
that E/GDP and carbon reductions are perfectly correlated (given that the efficiency case
involves no fuel switching, this is reasonable), then the efficiency case overestimates emissions
reductions by 18 to 20 MMTCE.
The text should explain why the lab study E/GDP ratio differs from the AEO97 ratio since it
does not seem to result exclusively from keeping fuel efficiency constant. Further, the 2010
BAU emissions reductions should reflect the E/GDP ratio (whether it is -0.77%, -0.85%, -0.86%,
or some other rate) used in the study.
10) 1.11, Table 1.4: It would be valuable to understand the effect of non-price policies and
permit prices on the carbon reductions. Could you break down the high efficiency cases into two
categories: non-price policy induced and permit induced technology adoption?
11) 1.12, paragraph 1: The discussion on government programs costing 15% of investment costs
should include references to the literature that have estimated this percentage. Does the literature
describe the marginal costs for government programs, or does it just provide this average cost
value? Consistent with the literature on technology adoption, the marginal costs should not be
8 The AEO97 BAU would capture 25% of the efficiency gains in the efficiency scenario.
6
assumed to be the same for all units of adoption. In fact, it is likely that the marginal costs
increase for higher rates of adoption.
12) 1.12, paragraph 1: The text in this paragraph notes that government costs in the best estimate
case are 15% of total investment costs, while figure A-1.1 on p. A-1.2 indicates that the costs are
7% of investment costs for the end-use sectors and 1% for the electricity sector. Which costs are
correct?
13) 1.12, paragraph 1: The text notes that "one could argue that a social discount rate" of 3% or
7% should be used. Alternatively, one could argue that since these analyses assess private
decisions on technology adoption, that private marginal rates of time preference should be used
that reflect "current market behavior". This analysis is not attempting to conduct a social
benefit-cost analysis. Rather, it is attempting to model the private individual or firm's benefits
and costs associated with a technology adoption decision. Since this report projects technology
adoption assuming a set of aggressive policies, the rates of time preference actually used by
individuals and firms should be used in assessing the extent of adoption.
Further, the report should not rely on government fiat to lower discount rates. It is very difficult
to lower people's time preferences through policy. Government programs do not increase
adoption rates by lowering time preferences, but by lowering the costs of adoption or increasing
the benefits of adoption. For example, government programs cost-share the adoption of
environmentally-benign agricultural production techniques through the Environmental Quality
Incentives Program. Farmers still employ the same discount rate, but their stream of costs are
lower because of the government subsidy, and so adoption increases. The report should not
assume that government policies can lower private time preference rates, but rather that
government policies can affect the stream of costs and benefits of an adoption decision.
14) 1.12, paragraph 5: Again, until the complete costs of investment and accurate cost-savings
can be estimated, the text on net benefits should be deleted.
15) 1.13, Table 1.5: The estimates of carbon reductions under the alternative view do not appear
to match with the carbon reductions in table A-1.2 on p. A-1.5. It seems implausible that
discount rates could double and have no effects on any technology adoption decision in this
report. Are the numbers in the appendix the right set? Is it true that every single energy efficient
technology adoption decision is cost-effective under the "best estimate" discount rate and the
"alternative view" discount rate? If these technologies are such big winners, then why aren't
people and firms already adopting them?
16) 1.14: Unless and until the costs and cost-savings issues are adequately addressed, estimates
of net savings should be omitted.
17) 1.15, paragraph 3: As stated in the executive summary comments, the text should not state
"energy efficiency alone can take the nation 30 to 50% of the way to 1990 levels." If energy
7
efficiency could achieve these reductions "alone", there would be no need for an invigorated
federal policy effort. It should be explicitly stated that policy instruments to achieve this goal are
omitted from the analysis.
Chapter 2
18) 2.6, transportation sector bullet: The text states that the transportation sector analysis uses a 5
year time horizon. However, the description of the best estimate and alternative view cost
effectiveness calculations on p. A-1.10 indicate that a time horizon of 14 years was used.
Further, the transportation chapter indicates that the cost effectiveness analyses were conducted
using a 6% discount rate in combination with a decline in usage and depreciation to calculate fuel
savings (p. 5.45). The footnote to table 5.9 implies that the analyses used a 14 year time horizon
as well. The report should clarify these inconsistencies.
Chapters 3-7
19) There does not appear to be any discussion of the $25/ton permit scenario in these chapters.
Further, the appendices do not explicitly detail this case. The results from this scenario need to
be documented in the text and in the appendices. For example, it is impossible to identify the
penetration rate for this scenario in the buildings chapter (see p. 3.3). The industry chapter
discusses three scenarios: BAU, efficiency, and high efficiency (p. 4.2). The descriptions of the
high efficiency case in transportation on p. 5.3 and p. 5.31 do not even mention a permit price.
The electricity sector appears to only consider a $50/ton permit (p. 6.9).
20) The results from the alternative view cost analysis should be incorporated in these chapters.
Chapter 3
21) 3.3: In the context of fully incorporating the effects of climate policy on energy prices, the
analyses on buildings technologies should be modified. Under the efficiency case, energy
consumption declines. This scenario should be changed to reflect the downward effect on prices
resulting from this decreased energy consumption. The result would be to reduce the net
improvement in energy use resulting from technological advances. The high efficiency scenario
should reflect two counteracting effects on prices: the decline in energy consumption and the
$50/ton permit fee. The study ignores the former effect and insufficiently incorporates the latter
effect. For example, in the buildings chapter, the penetration rate is assumed to be 65% instead
of 60% of the maximum cost-effective technical potential in this scenario because of the $50/ton
permit price. However, the energy-cost savings calculations for buildings technologies assume
the same energy price as in the business as usual scenario. Since the study assumes that
exogenous, undefined policy influences drive the penetration rates, the penetration rate should be
set at 60% and the energy cost-savings should be recalculated with the appropriate energy price.
In addition, the assumed energy use for these technologies should be based on consumers'
responses to the lower operating costs. For example, if running an air conditioner becomes less
8
expensive with a new energy efficient technology, people will run the air conditioner more. This
latter effect decreases the carbon reductions associated with each adoption decision.
22) 3.9 and Appendix C-1: The study uses the average cost of electricity to calculate the energy
cost savings of these technologies. Many of the electricity-dependent technologies are only cost
effective based on the assumption of average, not marginal electricity prices. Since marginal
prices may be much lower than average prices, especially in cases where households use less
electricity, this may overestimate the extent of cost effective technologies. The analysis should
be modified using marginal electricity prices.
23) 3.23, box: The text in the box is not clear on the inclusion of fuel cell technology in the high
efficiency scenarios. The first paragraph states that fuel cells were not included in the main
building sector scenarios. However, emissions reductions of 3 MMTCE from fuel cells are listed
under buildings in Table 1.4 on p. 1.11. Further, the discussion on fuel cells in the text outside of
this box implies that fuel cell technology will not be available until 2020 (since it falls in the
section "Potential for Advanced Technologies in 2020"). If the study relies on ADL's analysis of
fuel cell adoption, then the assumptions of ADL's assessment should be provided in an appendix.
Two issues should be addressed here. First, if fuel cells are projected to be adopted under the
high efficiency scenarios, then this discussion should be placed in the appropriate section of this
chapter (not the 2020 section), and the inconsistencies in the text should be remedied. Second, if
fuel cells are adopted, then a discussion of the carbon emissions accounting should be provided
to ensure that the study does not double count emissions reductions from energy efficient
technology adoption and from switching energy sources to fuel cells.
24) 3.29, summary bullet two: This states that the high efficiency scenario yields 91 MMTCE of
carbon reductions from the BAU emissions level. However, Table 1.4 indicates that only 44
MMTCE of reductions occur under the $25/ton permit price and only 62 MMTCE of reductions
occur under the $50/ton permit price. Which carbon reduction estimate is correct?
Chapter 4
25) 4.6, paragraph 4: The analysis assumes that the capital recovery factor falls by more than
half. This appears to be an arbitrary reduction. Did industry behave as if it operated under a
lower CRF during the 1970s oil shocks? There is no discussion of the economic behavior
necessary to result in this outcome.
26) 4.6, paragraph 4: The high efficiency penetration rate is assumed to be double the rate used in
the efficiency scenario, which is the undefined "normal" rate. It is impossible to determine how
much of this doubling of penetration results from undefined, aggressive policy efforts and how
much results from the permit price. It would be valuable to understand the relative impacts of
both.
9
27) 4.13, paragraph 4: The text states that the high efficiency case causes an acceleration of
capital retirement, but does not estimate these costs. Could you estimate the costs of early
retirement? If not, can you provide some information on the extent of early retirement (e.g.,
percentage of capital retired early under this scenario)?
Chapter 5
28) Does this sectoral analysis consider the impact of a permit price? Neither the $25/ton permit
nor the $50/ton permit are mentioned in the entire chapter. Do all improvements in fuel
efficiency and cellulosic ethanol result from non-price policy responses? As the report states, a
degree of "luck" is required to achieve the necessary technological breakthroughs to result in the
projected carbon reductions. However, without a price incentive, the probability of the nation
becoming "lucky" appears more unlikely. If this analysis does not incorporate the permit prices,
then this should be made explicit in the discussion of the high efficiency case.
29) The methodology for this sector is insufficiently transparent to grasp easily the impact of
technology development and adoption on carbon reductions. Further, the appendices for
transportation do not provide the details to remedy the shortcomings in the chapter. It is difficult
to compute carbon reductions from increases in fuel efficiency. The text should take the reader
through the process of piecing together all of these energy efficient technologies, illustrating the
final effect on fuel economy, and then translating this into carbon reductions.
30) 5.4, Table 5.1: Why do the energy consumption numbers for this sector in 1997 vary across
scenarios? We understand that the start year for the scenario analyses is 1998 (e.g., refer to Table
4.8 on p. 4.12 that implies 1998 as the start year for assessing cumulative incremental
investment).
31) 5.21, paragraph 2: Does the assumption about reducing technology costs reflect any
empirical analysis on transportation technologies? For example, the 1970s oil shocks and fuel
efficient imports spurred domestic fuel efficiency R&D. Does this analysis incorporate
information about accelerating technology development and lowering technology costs that may
be available from this earlier period?
32) 5.23, paragraph 3: As we have noted before, it is difficult to modify consumers' preferences.
Assuming that the demand for horsepower will decrease because consumers will become "more
green" over the next decade appears tenuous. This statement is repeated on p. 5.32. Is there any
evidence that concern about global warming has affected consumers' purchase decisions to date?
33) 5.25, paragraph 1: If the turbocompound diesel engine and the advanced LE-55 heat engine
are not available in the reference case (which implies that the earliest these are available is 2016),
then how are they made available by 2003? Is there any precedent for accelerating transportation
technology from a time horizon of at least 18 years to a horizon of only 5 years? How do these
10
engines conform to present emissions standards for particulates and NOₓ and how will future
standards under the new ozone and particulate matter rules affect them?
34) 5.25, paragraph 1: The efficiency case assumes that advanced drag reduction in heavy trucks
has become available this year, but this is excluded from the reference case. First, has this
actually occurred? Second, if it has already occurred, then why is it excluded from BAU?
35) 5.25, paragraph 4: Again, the assumption of reducing a technology price appears arbitrary.
What is the basis for assuming that the trigger price for heavy truck technologies will fall?
36) 5.25, paragraph 5: The efficiency analysis assumes penetration rates of 100% for several of
the heavy truck technologies over a 20 year period. This seems incongruous with the
assumptions in the other sector analyses that imply much lower penetration rates. 100%
penetration of a technology within 20 years, that is not expected to be available 18 years from
now in the BAU, appears to be an extreme and unsubstantiated assumption.
37) 5.32, paragraph 1: The analysis assumes that fuel cells, because their costs are unknown, will
be cost effective. This is an entirely arbitrary assumption, especially for a technology that is not
even projected to become available in the BAU scenario. There is absolutely no economic basis
for this assumption. This assumption is all the more extraordinary given that this analysis does
not (apparently) incorporate the impacts of a carbon permit on fuel prices.
38) 5.36, Table 5.7: If the scenarios overestimate fuel economy, as stated in the footnote, then the
numbers should be revised to remedy this error.
39) 5.38, paragraph 2: The modification of assumed improvement of fuel efficiency by
multiplying the expected improvement by 0.7 to reflect offsetting performance effects, appears
arbitrary. Why wouldn't the fraction be much smaller? The introduction to this chapter indicates
that almost all improvements in fuel efficiency are offset by performance effects. Why would
only 30% of fuel efficiency improvements in the future be offset?
40) 5.45: The chapter is not explicit about its accounting of fuel efficiency improvements in light
duty vehicles and the change in the fuel mix reflecting an increase in cellulosic ethanol and the
use of fuel cell technology. We cannot determine if carbon reductions are double counted. The
study does not discuss how cellulosic ethanol and fuel cells are accounted for in the energy cost
savings description on pp. 5.43-5.45. If the reductions from fuel efficiency and the reductions
from cellulosic ethanol and fuel cells do not overlap, then this should be stated explicitly. Again,
a more transparent presentation of the methodology would address the readers' uncertainty about
this issue.
41) 5.45, Table 5.9: The cost effectiveness estimates assume a constant price of $1.20 per gallon
through the life of the vehicles. The gasoline price should be adjusted down to reflect the impact
of decreased gasoline consumption due to fuel efficiency. Further, vehicle miles traveled should
11
increase through time as cars become more fuel efficient, consistent with the trend to date,
instead of held constant.
Chapter 7
42) 7.1, paragraph 2: If the report has eliminated the double counting in this sector evident in the
June 10 draft, then the sentence that states that double counting is "a likely possibility" should be
deleted. A reference to appendix G-2 should be inserted.
43) 7.2, paragraph 3: Again, if the double counting has been remedied by integrating the
dispatching and repowering analyses, then the following sentence should be modified: "The
analytical approach was static in that the cost of repowering was computed for each candidate
power plant but the analysis did not optimize unit/plant production cost, dispatch, or system
load."
44) 7.6, paragraph 5: The reference to appendix G-2 appears to be wrong. This reference implies
that appendix G-2 provides a methodology for SO₂ and NOₓ benefits. Nothing in the text of
chapter 7 reads as if the double counting issue from the June 10 draft has been resolved.
Appendices
45) A-1.9: The alternative view cost-effective estimates for buildings assumes an 18 year time
horizon. However, the methodology discussion on p. 2.5 states that a "technology is defined as
'cost-effective' if it delivers a good or service at equal or lower life-cycle costs relative to the
current practice". If cost-effectiveness is measured in terms of a technology's life cycle, then
shouldn't the time horizon for calculating the stream of benefits be constrained by the life of the
product? It is not possible for a technology to generate cost savings beyond its lifetime. In the
buildings case, the end uses with the largest potential carbon reductions in the high efficiency
case are other uses (10 MMTCE commercial, 6 MMTCE residential) and lighting (7 MMTCE
commercial, 6 MMTCE residential). These account for 29 of the 62 MMTCE of reductions for
this sector. However, the lifetimes for these end uses are much shorter than 18 years. For other
uses, the lifetime ranges from 7 (commercial) to 10 years (residential). For lighting, the lifetime
ranges from 1 (residential) to 12 years (commercial). The cost effectiveness estimates should be
recalculated using specific end use lifetimes.
12
Summary of Greenhouse Gas Emissions-Reduction Actions
Million Metric Tons of Carbon Equivalent
Source: U.S. Climate Action Report-1997
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
Residential & Commercial Sector Actions
26.9
10.3
I
New
Rebuild America
2.0
1.6
--
1 and 2
Expanded Green Lights and Energy
3.6
3.3
--
Star Buildings
3
State Revolving Fund for Public
1.1
Terminated
Buildings
4
Cost-Shared Demonstrations of
Emerging Technologies
5
Operation and Maintenance Training
3.8
0.0
--
for Commercial Building Facility
Managers and Operators
6
Energy Star Products
5.0
4.3
:
7
Residential Appliance Standards
6.8
0.2
:
8 and 11
Energy Partnerships for Affordable
Housing
9
Cool Communities
4.4
0.4
--
10
Update State Building Codes
New
Construction of Energy-Efficient
0.1
:
Commercial and Industrial Buildings
New
Superwindow Collaborative
0.0
--
New
Expand Markets for Next-Generation
0.2
:
Lighting Products
New
Fuel Cells Initiative
0.0
--
Industrial Sector Actions
19.0
4.8
--
12
Motor Challenge
8.8
1.8
:
13
Industrial Golden Carrot Programs
2.9
Merged into Action 12
14
Accelerate the Adoption of Energy-
Terminated
Efficient Process Technologies
15
Industrial Assessment Centers
0.5
CCAP Component Terminated
16
Waste Minimization
4.2
2.1
:
17
Improve Efficiency of Fertilizer
2.7
0.8
:
Nitrogen Use
18
Reduce the Use of Pesticides
Terminated
Transportation Sector Actions
8.1
5.3
:
19
Cash Value of Parking
20
Innovative Transportation Strategies
6.6
4.6
:
21
Telecommuting Program
22
Fuel Economy Labels for Tires
1.5
0.7
--
Energy Supply Actions
10.8
1.3
-
23
Increase Natural Gas Share of Energy
Use Though Federal Regulatory
2.2
Terminated
Reform
Action
Action Title
1993 Action
1997 U.S. CAR
Actual
Number
Plan Estimate
Revised Estimate
Reductions
for 2000
for 2000
to Date
24
Promote Seasonal Gas Use for Control
2.8
0.5
:
of Nitrogen Oxides
25
High-Efficiency Gas Technologies
0.6
Terminated
26
Renewable-Energy Commercialization
0.8
0.3
--
27
Expand Utility Integrated Resource
1.4
Terminated
Planning
28
Profitable Hydroelectric Efficiency
2.0
0.0
--
Upgrades
29
Energy-Efficient Distribution
Transformer Standards
0.8
0.5
--
30
Energy Star Distribution Transformers
31
Transmission Pricing Reform
0.8
Terminated
New
Green Power Network
Not included
0.0
--
Land-Use Change & Forestry Actions
10.0
2.4
-
43
Private Depletion of Nonindustrial
4.0
Terminated
Private Forests
44
Accelerate Tree Planting in
0.5
0.4
--
Nonindustrial Private Forests
16
Waste Minimization
4.2
2.0
--
9
Expand Cool Communities
0.5
To be determined
Methane Actions
16.3
15.5
--
32
Expand Natural Gas STAR
3.0
3.4
--
33
Increase Stringency of Landfill Rule
4.2
6.3
--
34
Landfill Methane Outreach Program
1.1
1.9
--
35
Coalbed Methane Outreach Program
2.2
2.6
--
36
RD&D for Coal Mine Methane
1.5
Terminated
37
RD&D for Landfill Methane
1.0
Terminated
38
AgSTAR Program
1.5
0.3
--
39
Ruminant Livestock Efficiency
1.8
1.0
--
Program
Actions to Address Other Greenhouse Gases
16.3
25.4
I
17
Improved Fertilizer Management
4.5
5.3
--
40
Significant New Alternatives Program
5.0
6.4
--
41
HFC-23 Partnerships
5.0
5.0
--
42
Voluntary Aluminum Partnership
1.8
2.2
:
New
Environmental Stewardship Initiative
Not included
6.5
--
Foundation Actions
11.3
-
Climate Wise
Not estimated
1.8
--
Climate Challenge
Not estimated
7.6
--
State and Local Outreach Programs
Not estimated
1.9
--
Total GHG Emission Reductions From CCAP
108.6
76.0
14.0
Data is not readily available for cumulative emissions reductions for many CCAP programs. Emissions
reductions of about 5 MMTCE can be attributed to DOE's CCAP programs. EPA's Office of Air and
Radiation is responsible for emissions reductions of about 9 MMTCE through their CCAP programs.
1.05
Improvements in Efficiency, 1997-2010 Under Alternative
No Efficiency
Annual E/GDP Rates
BAU-CEA (0.6)
1
*
BAU-CEA (0.9)
0.95
BAU-DOE5
Efficiency Case
0.9
18-20 MMTCE
120 MMTCE
0.85
All efficiency values
are shown relative
to a 1997 E/GDP
ratio indexed to 1.
0.8
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
08/20/97 WED 11:41 FAX 202 6222633
4.
001
Office of Economic Policy
Department of the Treasury Washington, D.C. 20220
FAX
Date: August 20, 1997 at 11:38 AM
Number of pages including cover sheet: 8
Name
FAX Number
Phone Number
To:
JAY SHOGREN
395-6809
JOE ALDY
From:
Robert Gillingham
202-622-2633
202-622-2220
REMARKS:
Urgent
X
For your review
Reply ASAP
Please comment
See what you think.
08/20/97 WED 11:42 FAX 202 6222633
002
COMMENTS ON SCENARIOS OF U.S. CARBON REDUCTIONS
Scenarios of U.S. Carbon Reductions, commonly known as the "5-labs study,"
examines the "potential for energy-efficient and low-carbon technologies to reduce
carbon emissions in the United States." This study does a very nice job of
cataloging the current state and likely future path of technological developments.
What it does not do, however, is shed much light on what role technology is likely to
play in mitigating the growth of carbon emissions, or on what government can or
should do to enhance this role.
As a tool for developing and implementing a technology policy, the report is
hampered by the fact that it does not address any of the processes that determine
the rate at which technology is developed and implemented. Rather, it catalogs
technologies that currently exist, are likely to exist or could possibly exist by 2010,
determines whether they are "cost-effective," and then makes somewhat arbitrary
assumptions about the rate at which they are implemented. Although the analysis
is couched in terms of the adoption of cost-effective technologies, cost-effectiveness
is not rigorously defined; no evidence is presented on whether decision-makers are
or are not acting in their best interest. It is important to recognize that the paper
does not demonstrate an irrational unwillingness to invest in energy efficiency. The
paper suggests that the adoption of standards and codes is necessary to ensure
appropriate consumer behavior; again, no such demonstration is made. In other
words, the study does not and cannot present evidence on the costs to either society
or individual consumers and businesses of alternative technology paths.
The study reaches three overarching conclusions:
A vigorous national commitment to develop and deploy cost-effective energy-
efficient and low-carbon technologies has the potential to substantially reduce
energy consumption and carbon emissions.
We would not argue with this conclusion. Rather we question (1) the level
of government involvement-government R&D, tax incentives, efficiency
standards, etc.-that would be necessary in the absence of energy-price
increases and (2) whether the substantial increases in relative energy prices
that would likely accompany constraints on carbon emissions would not be
the most important component of any national commitment to reduce
emissions.
Carbon emissions can be reduced in ways that reduce energy costs more than
they increase other societal costs.
We question this assertion. The study makes only rudimentary cost-benefit
calculations that ignore important considerations that reasonably effect
decisions to invest in energy efficiency. It also substantially understates the
costs of government policies to promote technology.
The next generation of energy-efficient and low-carbon technologies promises to
08/20/97 WED 11:43 FAX 202 6222633
003
enable the continuation of an aggressive pace of cost-effective carbon reductions
over the next quarter century.
Again, absent a careful cost-benefit analysis, this conclusion is overly
speculative. For instance, with respect to the transportation sector, the
report concedes that future technological breakthroughs will be necessary to
develop and implement the high-efficiency, low-carbon technologies. It is a
stretch to assume that these breakthroughs will be forthcoming and that
they will pass rigorous cost-benefit tests, especially in the absence of strong
price signals.
The methodology used in the report is to analyze sequentially the three major
end-users of energy-the residential and commercial building, industry and
transportation sectors-and separately analyze the electric utility sector. For each
sector, the study develops three scenarios-business-as-usual, efficiency, and high-
efficiency/low carbon. They are conceptually defined as follows:
Business-as-usual (BAU). Best estimate of future energy use given current
trends in service demand, stock turnover and natural progress in the efficiency
of new equipment. Assumes no change in federal policies.¹
Efficiency (EFF). Likely market penetration of "cost-effective," energy-efficient
technologies given "an invigorated effort to promote energy efficiency through
enhanced public and private-sector R&D and market transformation activities."
High-efficiency/low-carbon (HE/LC). Optimistic but feasible market
penetration for energy efficient and low-carbon technologies given a "greater
commitment to reduce carbon emissions resulting from actions that might
include the creation of a market value for carbon of $25 and $50 per tonne."
With the exception of the range of carbon emission charges, which seems out of
place and is largely ignored in the study, these conceptual definitions are very
vague. The operational definitions vary by sector and will be discussed in turn
below.
BUILDINGS
For buildings, the business-as-usual scenario is the Annual Energy Outlook
(AEO) reference case. The efficiency scenario assumes that 35 percent of the "cost-
effective energy savings potential" relative to the BAU is achieved. The high-
efficiency/low-carbon scenario assumes that 65 percent of these savings are
achieved. We have a number of problems with this analysis.
The cost-effective energy saving potential is badly defined. The study makes two
critical assumptions in defining cost effectiveness. First, the analysis takes as given
1
The report provides relatively little analysis of past trends and their determinants. The past has
certainly informed our view of the future, and a more detailed analysis of the price and quantity paths, both
past and in the BAU scenario, would be very useful.
2
08/20/97 WED 11:43 FAX 202 6222633
004
that engineering estimates of energy use for alternative technologies are known
with certainty and independent of the age of the capital good in which the
technology is embodied. There is evidence that adopting these estimates is likely to
overestimate savings (e.g., attic insulation may not be perfectly installed; consumers
may increase usage rates for energy-efficient appliances or consumers may add
more windows when their energy costs are reduced). Second, the analysis ignores
the trends and uncertainty around these trends in the future prices of both capital
goods and energy as well as the potential irreversibility of investment decisions
(proper treatment of these issues goes a long way toward explaining high measured
internal rates of return, which are often confused with high discount rates). As a
result of these two assumptions, the study almost certainly exaggerates the "cost-
effectiveness" of investments in energy efficiency.
The assumed take-up rates of 35 percent and 65 percent are arbitrary. The study
makes no attempt to model behavior; rather it makes arbitrary assumptions about
the rate at which energy-saving investments are made. With no idea what
determines the rate at which new technologies are adopted, we have no basis for
informed policy-making. The HE/LC case includes substantial price increases in
energy, yet the study simply raises the take-up rate for technologies deemed cost-
effective under a different-and much lower-scenario of energy prices. The
assumed take-up rate under the EFF case is bad enough, but the failure to explain
how a carbon price would change the decision-making calculus in the HE/LC case is
even worse.
A number of the examples are based on 1997 technologies. For instance, the
refrigerator example assumes adoption of an energy-efficient 1995 model. This
ignores the fact that refrigerator efficiency has been improving at a rapid rate for
over 20 years (6.2 percent per year from 1972 to 1991). What does the AEO assume
for the 1995 to 2010 period? Is it reasonable to assume that the type of saving
assumed in the EFF case should be incorporated in the BAU case? Or is the BAU
unnecessarily pessimistic?
The bulk of the savings in buildings are largely unexplained, coming from
"miscellaneous electricity uses." The study admits that because of the importance of
these uses, "it is crucial that more research be carried out, both to characterize how
energy in used in the miscellaneous category and to identify technologies for
improving the efficiency of sub-categories." With no clear understanding of these
fundamental aspects of electricity use, how can we be confident to assume that this
2 See, e.g., Gilbert Metcalf and Kevin Hassett, "Measuring the Energy Savings from Home Improvement
Investments: Evidence from Monthly Billing Data," National Bureau of Economic Research Working Paper
6074, June 1997.
3 See Robert Pindyck, "Irreversibility, Uncertainty, and Investment," Journal of Economic Literature 29,
1991, for a review of some of these issues. Also, see Gilbert Metcalf and Donald Rosenthal, "The 'New' View of
Investment Decisions and Public Policy Analysis: An Application to Green Lights and Refrigerators," Journal of
Policy Analysis and Management, Vol. 14, No. 4, 1995, for an application.
3
08/20/97 WED 11:44 FAX 202 6222633
005
category accounts for most of the presumed savings?
INDUSTRY
For the industrial sector, the study relies on the Long-Term Industrial Energy
Forecasting (LIEF) model, an econometric forecasting model, to explain investment
in conservation technology; it uses the industrial module of the National Energy
Modeling System (NEMS), which does not model investment, to assess the effect of
that investment on energy use. The business-as-usual scenario is the Annual
Energy Outlook (AEO) reference case. The efficiency scenario assumes that the
"capital recovery factor" (CRF) for energy-efficient investment in the LIEF is
reduced from 33 percent to 15 percent.4 The high-efficiency/low-carbon scenario
assumes, in addition, that the penetration rates for energy-efficient technology are
doubled relative to the BAU scenario. This analysis suffers from problems similar
to those in the analysis of the buildings sector.
The study models investment in the EFF and HE/LC scenarios by arbitrarily
assuming that the return criterion for energy-efficient investment is reduced by more
than 50 percent. No rationale is provided for this approach, nor are any policies
posited that would lead to this result. Rather, it is simply a device to increase
investment. As noted above, arbitrary assumptions about hurdle rates beg critical
questions about the effect of uncertainty, changing relative prices and irreversibility
on investment behavior. The approach used provides no insights into investment
behavior; it implicitly assumes that behavior.
The HE/LC scenario depends on an arbitrary assumption about penetration
rates and ignores price effects. The LIEF model "provides a mechanism for
evaluating general investment in conservation technology as a function of energy
prices, capital recovery rates, and other prices." Yet in evaluating the HE/LC
scenario, the study ignores the postulated $25 and $50 carbon prices that are part of
this scenario. Instead it assumes a doubling of penetration rates for new technology
and retirement rates for old capital. The study makes no attempt to demonstrate
that an increase in penetration/retirement rates is economically motivated.
Although no policies are modeled or advocated, the study lists a number of
potentially costly and/or intrusive policies that could promote energy efficiency.
These include accelerated depreciation, rebates or tax credits, regulation and
efficiency standards, pricing and fiscal policies, and "other economic incentive
programs."
TRANSPORTATION
For the transportation sector, the business-as-usual scenario is the Annual
4 A $50 carbon fee would certainly increase investment in energy efficiency, as does the drop in the CRF.
The latter approach is not the right way to model expected relative price increases, however. Again, uncertainty
and irreversibility should be explicitly modeled, making it clear that a high apparent hurdle rate is not the same
as a high discount rate.
4
08/20/97 WED 11:45 FAX 202 6222633
006
Energy Outlook (AEO) reference case, adjusted to reduce the assumed improvement
in light-duty vehicle fuel economy. The efficiency scenario assumes earlier
introduction of advanced fuel economy technology and adds certain key technologies
that are not in the BAU. The high-efficiency/low-carbon scenario postulates future
"breakthroughs" in technology. As with the other sectors, this analysis provides few
insights for technology policy.
The efficiency scenario assumes accelerated adoption of existing technologies, but
provides no reason why this might occur. Unlike the analysis of the other sectors,
the analysis of the transportation sector does not even include any economic
assumptions that might imply its conclusions. As a result, it promises no medium
or longer-term gains.
The HE/LC scenario is even more ephemeral; it requires technological
breakthroughs, primarily in fuel-cell technology. As the report notes, the EFF and
HE/LC scenarios "differ from each other less in effort than in outcome.
In
contrast, because the outcomes postulated in the high-efficiency/low-carbon scenario
require technological breakthroughs, they require a certain degree of luck to be
achieved by 2010." In other words, we do not need to try any harder to achieve the
HE/LC scenario; we just have to be lucky.
The analysis raises the AEO energy baseline, but not the emissions baseline.
Since it raises the AEO energy baseline, the study should also adjust the emissions
baseline. As a result, the savings postulated relative to the AEO baseline would be
reduced.
ELECTRICITY
The analysis of the electricity sector describes how the electricity demands
inherent in the BAU, EFF and HE/LC scenarios can be met with lower carbon
emissions. The BAU scenario is a fully competitive bulk-power market in the year
2010. The demands on this system are then adjusted to reflect the effects on
electricity demand and supply of the EFF and HE/LC scenarios. These results are
used in the sector analyses to evaluate carbon savings attributable to reductions in
electricity consumption. They are also used to evaluate the opportunities for
reducing carbon emissions in electricity generation in response to $25 and $50
carbon prices.
The EFF and HE/LC scenarios predict substantial reductions in electricity
demand from baseline. The two scenarios predict reductions of 9 and 16 percent,
respectively, in end-use electricity demand relative to BAU. In fact, they assume
essentially zero growth in electricity demand between 1997 and 2010. To put this
into perspective, electricity sales increased at an annual rate of 2.0 percent annual
rate so far in the 90s and at more than a 3 percent rate over the past 25 years.
IMPLICATIONS OF THE STUDY
As the above discussion demonstrates, the study is primarily a catalog of
5
08/20/97 WED 11:46 FAX 202 6222633
1
007
potential improvements in energy efficiency. Neither the determinants of these
improvements, nor their implications for energy demand behavior are examined.
Rather, the study provides an accounting of two very stylized scenarios. Without
developing and detailing the relationship between the study's scenarios and the
policy mixes that would have to accompany them, it would be inappropriate to draw
any conclusions from the study about the role of technology, much less the role of
technology policy, in addressing global warming. Although the study provides no
policy recommendations, it does hint at possibilities. Listing them provides some
insight into the potential difficulties in making the scenarios "come true."
Aggressive R&D, both public and private. The study continually refers to the
need for aggressive R&D, but provides no suggestions as to how it could be
fostered and at what cost.5 The EFF scenario is basically an extrapolation of
the Climate Change Action Plan; the likely success of this effort is at best
problematic. Some have suggested a more vigorous effort, similar to the Apollo
project. Although this sounds good, we should remember that the Apollo project
required rechanneling 0.4 percent of the entire GDP of the 1960s into this one
government project. Many of the climate change modeling efforts predict that
reducing emissions levels to 1990 levels in 2010 would not cost much more than
that in the absence of a technology program.
Tax incentives. Investment tax credits, accelerated depreciation, and other tax
incentives are available to spur the development and adoption of energy-saving
technology. This approach has two problems. First, energy-efficiency
investments should not be singled out unless they impose special costs. If they
do, disincentives for using energy are more efficient than incentives for saving
energy. Second, any substantial incentives would have to be "paid for" with
other tax increases and spending cuts. As recent history has demonstrated,
reaching consensus is not easy.
Regulations and standards. Implicit in this study is the idea that regulations
and standards could go a long way toward achieving the EFF and HE/LC
scenarios. The types of standards that would be needed, however, would be
very pervasive and potentially very intrusive. For instance, standards would
have to be applied to building components (windows, insulation, etc.) and
constructions techniques, consumer and commercial appliances, utility and
industrial equipment, etc. If standard setting is a major policy instrument,
achieving the standards could be very costly. Standards work best if they
impose little cost, as the report alleges they often would. Basing policy on this
assumption moves us quickly to the idea that better results depend less on
effort than on luck.
5 The study (arbitrarily) assumes that government costs to promote energy conservation are equal to 7
percent of energy savings. This is very optimistic. For instance, a 10 percent tax credit would cost 10 percent of
the total cost of all qualifying investment, even that which would have taken place in the absence of the credit.
The load factor for explicit government subsidies would be roughly 10 times as large.
6
08/20/97 WED 11:47 FAX 202 6222633
008
Higher prices. The most obvious policy to spur energy conservation is to
increase energy prices. The study presumes a substantial increase in prices in
its HE/LC scenario, but never draws out the implications of higher prices for the
development and adoption of advanced technology. The study points out how
rapidly energy efficiency improves prior to the late 80s and 90s. This is not
surprising, given price trends. As the chart below demonstrates, consumer
energy prices, relative to other prices, grew very rapidly during the 70s and into
the 80s. A commitment to reduce emissions and internal climate costs would
presumably result in substantial increase in relative prices and accompanying
increases in efficiency.
RELATIVE PRICES OF CONSUMER ENERGY
220
Electricity
200
Natural Gas
Gasoline
180
Relative Price (1973=100)
160
140
120
100
80
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
Under almost any feasible scenario that reduces carbon emissions, the pace of
technological advance in energy conservation will increase. The importance and
role of technology are not in question. What is in question is the value of looking at
technology in a vacuum. The 5-labs study provides a plethora of useful information.
It does not present this information in a form that is useful for policymaking,
however. To be useful, it needs to be merged with careful analysis of the
determinants of both consumer and business investment in energy-saving
technology.
7
Review of DOE Labs Study
Unspecified Policies:
No Program Descriptions: The authors do not estimate the costs or even describe the
programs necessary to stimulate the adoption of the new energy-efficient technology they
find could reduce emissions of approximately 200 million metric tons of carbon
equivalent (MMTCE) by 2010. These reductions correspond to about ½ of the reductions
needed to attain 1990 levels by 2010. In the absence of cost estimates this information is
of little use in the evaluation of alternative policy options.
Costs of Programs: Given reasonable assumptions, government programs may cost many
tens of billions of dollars per year above the costs of existing programs to reduce 200+
million tons of carbon. The marginal cost of emissions reductions, including the cost of
the government program, is likely to greatly exceed the permit price. As a result these
programs may be less cost-effective than a cap-and-trade emissions control program.
Luck: The transportation sector requires "luck" in terms of technological innovation to
achieve the projected emissions reductions. Without a permit price, this luck appears
likely only through stringent standards, such as increasing CAFE.
Overestimates Reductions/Underestimates Costs:
Behavioral Changes Ignored: The analysis appears to ignore the behavioral changes that
offset the energy efficiencies promised by the new technologies. For example, more
efficient windows lead to houses with more glass, and more efficient cars lead to more
vehicle miles traveled. Thus these innovations offer real value to consumers, but smaller
energy savings than engineers forecast.
Cost Effectiveness Calculated Using Average, Not Marginal Prices: Many of the
innovations in electrical use appear to be assumed to be cost effective based on an
assumption of average, not marginal electricity prices. The marginal prices may be half
as much as the average prices.
Price Declines Resulting from Reductions in Energy Demand Are Not Taken into
Account: The study assumes a 12% decrease in energy use, but does not account for this
effect on price when calculating cost effectiveness for energy efficient technologies.
Study Double Counts Emissions Reductions Occurring Under Business-As-Usual: The
labs study double counts 22 MMTCE in reductions in the efficiency case that will occur
under the business-as-usual case.
Interactions Ignored, Double Counting "Likely" in Utilities Sector Analysis: The double
counting of dispatching and retooling coal plants to natural gas results in about 9
MMTCE of overestimated reductions.
Industry Sector Analysis Ignores the Costs of Accelerating Retirement.
Excerpt from the President's speech at American University, 9/9/97
"And we also need people who have the confidence in our ability to break new technological and
scientific barriers to stand up and say, you cannot make me believe that we can't reduce
greenhouse gas emissions substantially and still grow the American economy. We could reduce
them 20 percent tomorrow with technology that is already available at no cost if we just changed
the way we do things."
The President's statement reflects the result of a study conducted by five Department of Energy
research laboratories titled Scenarios of U.S. Carbon Reductions. This study, still in draft form,
claims that carbon emissions can be reduced to 1990 levels in 2010 at "net costs to the U.S.
economy [that] are near or below zero in this time frame [1998-2020]" (p. 16, chapter 1, 8/29/97
draft). The Council of Economic Advisers and the Department of Treasury have reviewed this
report and found the economic analyses to be inadequate to support this assertion. The study
suffers two serious flaws. First, it merely assumes "aggressive" and "invigorated" government
policies to stimulate technology adoption, without a discussion of the political feasibility of these
policies or whether these technologies would be voluntarily adopted by private parties. The study
does not provide reliable estimates of the costs of government programs nor does it estimate the
costs of extensive and intrusive new regulations implied, including stringent CAFE standards,
national building codes, and very aggressive appliance standards. This country's experience with
the Climate Change Action Program implies that the government costs of achieving this goal
would be in the billions of dollars annually. Second, the analyses on individuals' and firms'
adoption decisions do not assess economic behavior, but rather invoke a set of-engineering
assumptions that generate substantial underestimates of complete adoption costs. The study
ignores likely individuals' behavioral responses to climate policy (e.g., people drive more miles
when cars become more fuel efficient), implementation costs, and the costs of accelerating capital
retirement, but assumes that individuals live in model houses, drive model cars, and purchase
products manufactured in model factories. The economic literature on technology adoption
indicates that the actual net costs of energy efficient technologies are much greater than predicted
by engineering studies like this study. Scenarios of U.S. Carbon Reductions is an engineering
study, not an economic study. Given these inadequacies, neither CEA nor Treasury has signed off
on the report.
pre-tyto
comment on
President's GCC
Statement
Preliminary Draft
MEMORANDUM
TO:
Jon Gruber
FROM:
Joe Aldy
DATE:
12/8/97
RE:
Umbrella Annex I Trading with neither EU nor Eastern European Participation
If neither the EU nor Eastern European countries participate in full Annex I permit trading
market, the total cost for Annex I countries to comply with a target and timetable increases, but
the U.S., Japan, and Canada are all better off with a smaller Annex I "Umbrella" (trading
between U.S., Japan, Canada, Australia, and FSU countries). Australia has roughly the same
costs (domestic abatement costs plus transfers for emissions reductions abroad) under this
umbrella as under full Annex I trading. Eastern Europe actually benefits under a regime where it
does not participate in the umbrella but it does sell permits with the EU (a European-only trading
regime) relative to full Annex I trading. As the only seller of permits to the EU, Eastern Europe
does not have to compete with cheap permits from FSU countries, and thus can sell more permits
at higher permit prices than under full Annex I trading. The three major buyers of permits in the
Umbrella, U.S., Canada, and Japan, benefit, because as buyers of permits, the loss of a major
competitor means they can buy more emissions reductions in EEFSU at lower permit prices.
Former Soviet Union countries and the EU are worse under this scenario of two trading blocks
(the Umbrella and the European-only trading) than under full Annex I trading. The cost for the
EU increases under European-only trade relative to full trading because it cannot take advantage
of low cost emissions reductions in FSU countries, such as Russia. Former Soviet Union
countries are worse off even though they don't have to compete with Eastern European countries
in the sellers market because the EU would be the second largest buyer of permits under full
Annex I-wide trading. Losing a major buyer decreases total demand for their permits and thus
the price more so than losing competitors contracts the supply and pushes up the permit price.
To illustrate the effects of EU non-participation, I assessed country-specific marginal abatement
cost curves derived from SGM outputs for the 1990 in 2010 target and timetable. The first chart
illustrates the difference in the total economic effects of these two trading regimes. The two
charts that follow show permit prices, domestic emissions abatement, purchases and transfers of
permits on the Annex I market, and total costs of Annex I trading with EU participation and a
trading regime without EU participation.
Umbrella: U.S, Canada, Japan, Australia, FSU
European-Only Bloc: EU, Eastern Europe
Winners with Two Trading Blocs Relative to Full Annex I Trading: U.S, Canada, Japan, Eastern
Europe
Losers with Two Trading Blocs Relative to Full Annex I Trading: EU, FSU
No Difference Between the Trading Blocs: Australia
Preliminary Draft
Difference in Economic Costs of Trading Regimes with and without EU, Eastern European
Participation
Country/Region
Total Costs under
Total Costs under
Change in Costs
Full Trading
Trading without EU,
(- means costs
(abatement cost +
Eastern Europe
decrease w/o EU,
transfers)
(abatement cost +
Eastern Europe
transfers)
participation)
U.S.
$12.0b
$10.2b
-$1.8b
Australia
$0.8b
$0.8b
0
Canada
$1.9b
$1.5b
-$0.4b
Japan
$3.5b
$2.9b
-$0.6b
Former Soviet Union
net gain: $12.3b
net gain: $9.7b
$2.6b
Russia¹
net gain: $7.9b
net gain: $6.2b
$1.7b
Eastern Europe
net gain: $3.7b
net gain: $5.8b
-$1.9b
EU²
$8.1b
$10.6b
$2.5b
ANNEX I, total
$10.3b
$12.2b
$1.9b
abatement cost
Preliminary Draft
Annex I Trading with Full Participation
Country/
Permit
Domestic
Reductions
Domestic
Capital
Total Cost
Region
Price
Reductions
Purchased
Abatement
Flow
Abroad
Cost
U.S.
$41.3
177
202
$3.7b
-$8.3b
$12.0b
Australia
$41.3
11
15
$0.2b
-$0.6b
$0.8b
Canada
$41.3
13
39
$0.3b
-$1.6b
$1.9b
Japan
$41.3
21
75
$0.4b
-$3.1b
$3.5b
Former
$41.3
168
-382
$3.5b
+$15.8b
net gain:
Soviet
$12.3b
Union
Russia¹
$41.3
109
-248
$2.3b
+$10.2b
net gain:
$7.9b
Eastern
$41.3
27
-105
$0.6b
+$4.3b
net gain:
Europe
$3.7b
EU²
$41.3
83
156
$1.7b
-$6.4b
$8.1b
Preliminary Draft
Annex I Trading without EU or Eastern Europe Participation
Country/
Permit
Domestic
Reductions
Domestic
Capital
Total Cost
Region
Price
Reductions
Purchased
Abatement
Flow
Abroad
Cost
U.S.
$33.6
151
228
$2.5b
$7.7b
$10.2b
Australia
$33.6
9
17
$0.2b
$0.6b
$0.8b
Canada
$33.6
12
40
$0.2b
$1.3b
$1.5b
Japan
$33.6
18
78
$0.3b
$2.6b
$2.9b
Former
$33.6
149
-363
$2.5b
-$12.2b
net gain:
Soviet
$9.7b
Union
Russia¹
$33.6
97
236
$1.7b
-$7.9b
net gain:
$6.2b
Eastern
$59.7
40
-118
$1.2b
-$7.0b
net gain:
Europe
$5.8b
EU²
$59.7
121
118
$3.6b
$7.0b
$10.6b
Notes:
1. Russia is calculated as 65% of FSU because its economy in 1995 was 65% the size of the
economies of all FSU countries.
2. SGM models the Western Europe region including 19 countries, 4 of which are not in the EU
bubble. However, the 15 countries in the bubble comprised about 93% of CO₂ emissions in 1990
of the 19 countries in the modeled region. See the attached list of countries to review the
distinctions between the Western Europe region modeled in SGM and the EU bubble.
Preliminary Draft
EU Bubble Countries:
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
United Kingdom
Western Europe in SGM:
EU bubble countries plus
Iceland (1990: 0.6 MMTCE CO₂)
Norway (1990: 14.3 MMTCE CO₂)
Switzerland (1990: 11.6 MMTCE CO₂)
Turkey (1990: 39.7 MMTCE CO₂)
Preliminary Draft
MEMORANDUM
TO:
Jon Gruber
FROM:
Joe Aldy
DATE:
12/8/97
RE:
Annex I Trading without EU Participation
If the EU does not participate in an Annex I permit trading market, the total cost for Annex I
countries to comply with a target and timetable increases, but the U.S., Japan, Australia, and
Canada are all better off without EU participation. The EU and Eastern European and Former
Soviet Union countries are all made worse off by EU non-participation. The cost for the EU
increases if it does not participate because it must achieve all of its emissions reductions at home,
instead of in lower cost countries such as Russia. Eastern European and Former Soviet Union
countries are worse off because the EU would be the second largest buyer of permits under full
Annex I-wide trading. Losing a major buyer decreases total demand for their permits, resulting
in EEFSU countries selling fewer permits at lower prices. All other Annex I countries benefit,
because as buyers of permits, the loss of a major competitor means they can buy more emissions
reductions in EEFSU at lower permit prices.
To illustrate the effects of EU non-participation, I assessed country-specific marginal abatement
cost curves derived from SGM outputs for the 1990 in 2010 target and timetable. The first chart
illustrates the difference in the total economic effects of these two trading regimes. The two
charts that follow show permit prices, domestic emissions abatement, purchases and transfers of
permits on the Annex I market, and total costs of Annex I trading with EU participation and a
trading regime without EU participation.
Preliminary Draft
Difference in Economic Costs of Trading Regimes with and without EU Participation
Country/Region
Total Costs under
Total Costs under
Change in Costs
Trading with EU
Trading without EU
(- means costs
(abatement cost +
(abatement cost +
decrease w/o EU
transfers)
transfers)
participation)
U.S.
$12.0b
$7.6b
-$4.4b
Australia
$0.8b
$0.5b
-$0.3b
Canada
$1.9b
$1.1b
-$0.8
Japan
$3.5b
$2.0b
-$1.5b
Eastern Europe
net gain: $3.7b
net gain: $1.9b
$1.8b
Former Soviet Union
net gain: $12.3b
net gain: $6.2b
$6.1b
Russia¹
net gain: $7.9b
net gain: $4.0b
$3.9b
EU²
$8.1b
$18.9b
$10.8b
ANNEX I, total
$10.3b
$21.9b
$11.6b
abatement cost
Preliminary Draft
Annex I Trading with EU Participation
Country/
Permit
Domestic
Reductions
Domestic
Capital
Total Cost
Region
Price
Reductions
Purchased
Abatement
Flow
Abroad
Cost
U.S.
$41.3
177
202
$3.7b
-$8.3b
$12.0b
Australia
$41.3
11
15
$0.2b
-$0.6b
$0.8b
Canada
$41.3
13
39
$0.3b
-$1.6b
$1.9b
Japan
$41.3
21
75
$0.4b
-$3.1b
$3.5b
Eastern
$41.3
27
-105
$0.6b
+$4.3b
net gain:
Europe
$3.7b
Former
$41.3
168
-382
$3.5b
+$15.8b
net gain:
Soviet
$12.3b
Union
Russia¹
$41.3
109
-248
$2.3b
+$10.2b
net gain:
$7.9b
EU²
$41.3
83
156
$1.7b
-$6.4b
$8.1b
Preliminary Draft
Annex I Trading without EU Participation
Country/
Permit
Domestic
Reductions
Domestic
Capital
Total Cost
Region
Price
Reductions
Purchased
Abatement
Flow
Abroad
Cost
U.S.
$23
101
278
$1.2b
$6.4b
$7.6b
Australia
$23
7
19
$0.08b
$0.4b
$0.5b
Canada
$23
8
44
$0.09b
$1.0b
$1.1b
Japan
$23
12
84
$0.1b
$1.9b
$2.0b
Eastern
$23
15
-93
$0.2b
-$2.1b
net gain:
Europe
$1.9b
Former
$23
118
-332
$1.4b
-$7.6b
net gain:
Soviet
$6.2b
Union
Russia'
$23
77
-216
$0.9b
-$4.9b
net gain:
$4.0b
EU²
$158
239
0
$18.9b
0
$18.9b
Notes:
1. Russia is calculated as 65% of FSU because its economy in 1995 was 65% the size of the
economies of all FSU countries.
2. SGM models the Western Europe region including 19 countries, 4 of which are not in the EU
bubble. However, the 15 countries in the bubble comprised about 93% of CO₂ emissions in 1990
of the 19 countries in the modeled region. See the attached list of countries to review the
distinctions between the Western Europe region modeled in SGM and the EU bubble.
Preliminary Draft
EU Bubble Countries:
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
United Kingdom
Western Europe in SGM:
EU bubble countries plus
Iceland (1990: 0.6 MMTCE CO₂)
Norway (1990: 14.3 MMTCE CO₂)
Switzerland (1990: 11.6 MMTCE CO₂)
Turkey (1990: 39.7 MMTCE CO₂)
T&T:
U.S., Japan, Canada: 2% below 1990
Australia: 5% above 1990
FSU, Eastern Europe: 1990
EU: 10% below 1990
Full Annex I Trading
Country/
permit
domestic
reductions
domestic
transfers
total cost
Region
price
reductions
purchased
abatement
abroad
cost
U.S.
$51.6
215
191
$5.5b
$9.9b
$15.4b
Canada
$51.6
16
38
$0.4b
$2.0b
$2.4b
Japan
$51.6
26
75
$0.6b
$3.9b
$4.6b
Australia
$51.6
13
5
$0.3b
$0.2b
$0.6b
FSU
$51.6
415
0
$5.2b
-$21.4b
net gain:
$16.2b
EU
$51.6
105
218
$2.7b
$11.2b
$13.9b
Eastern
$51.6
112
0
$0.9b
-$5.8b
net gain:
Europe
$4.9b
Two Permit Trading Blocs: Annex I Umbrella and Europe-Only
Country/
permit
domestic
reductions
domestic
transfers
total cost
Region
price
reductions
purchased
abatement
abroad
cost
U.S.
$36.6
159
247
$2.9b
$9.0b
$11.9b
Canada
$36.6
13
41
$0.2b
$1.5b
$1.7b
Japan
$36.6
19
82
$0.3b
$3.0b
$3.3b
Australia
$36.6
10
8
$0.2b
$0.3b
$0.5b
FSU
$36.6
378
0
$3.0b
-$13.8b
net gain:
$10.8b
EU
$101
178
145
$9.0b
$14.6b
$23.6b
Eastern
$101
145
0
$3.4b
-$14.6
net gain:
Europe
$11.2b
Two Permit Trading Blocs: Annex I Umbrella and Europe-Only and 50% Constraint
Country/
permit
domestic
reductions
domestic
transfers
total cost
Region
price
reductions
purchased
abatement
(domestic)
abroad
cost
U.S.
$48
203
203
$4.9b
$3.0b
$7.9b
Canada
$101
27
27
$1.4b
$0.4b
$1.8b
Japan
$119
50
51
$3.0b
$0.8b
$3.8b
Australia
$32
9
9
$0.1b
$0.1b
$0.2b
FSU
$15
289
0
$0.5b
-$4.3b
net gain:
$3.8b
EU
$101
178
145
$9.0b
$14.6b
$23.6b
Eastern
$101
145
0
$3.4b
-$14.6b
net gain:
Europe
$11.2b
Two Permit Trading Blocs: Annex I Umbrella + Global JI and Europe-Only (no JI)
Country/
permit
domestic
reductions
domestic
transfers
total cost
Region
price
reductions
purchased
abatement
abroad
cost
U.S.
$12
50
356
$0.3b
$4.4b
$4.7b
Canada
$12
4
50
$0.02b
$0.6b
$0.6b
Japan
$12
7
94
$0.04b
$1.2b
$1.2b
Australia
$12
4
14
$0.02b
$0.2b
$0.2b
FSU
$12
280
0
$0.4b
-$3.5b
net gain:
$3.1
EU
$101
178
145
$9.0b
$14.6b
$23.6b
Eastern
$101
145
0
$3.4b
-$14.6b
net gain:
Europe
$11.2b
China
$12
170
0
$1.1b
-$2.1b
net gain:
$1.0b
India
$12
21
0
$0.1b
-$0.3b
net gain:
$0.2b
Korea
$12
2
0
$0.01b
-$0.02b
net gain:
$0.01b
Mexico
$12
11
0
$0.07b
-$0.1b
net gain:
0.03b
ROW
$12
30
0
$0.2b
-$0.4b
net gain:
0.2b
US
2010 GDP
9185
Required
Sinks
Elect Res
Scenario
Permit
Domestic
Permits
US
US
US TC
TC/GDP
Cut Under
Price
Reductions
Purchased
Abatement
Capital
($b)
Kyoto
(92$)
(MMTCE)
Abroad
Cost
Outflow
600
0
0
Dom Only
171
600
0
51.3
0.0
51.3
0.005585
600
52
0
Dom Only
146
548
0
40.0
0.0
40.0
0.004355
600
52
33
Dom Only
130
515
0
33.5
0.0
33.5
0.003645
600
104
33
Dom Only
105
463
0
24.3
0.0
24.3
0.002646
600
0
33
Dom Only
155
567
0
43.9
0.0
43.9
0.004784
497
-55
0
10/97 position
148
552
0
40.8
0.0
40.8
0.004447
600
104
0
Dom Only
121
496
0
30,0
0.0
30.0
0.003267
600
0
0
Annex I
48
281
319
6.7
15.3
22.1
0.002401
600
52
0
Annex I
26
187
361
2.4
9.4
11.8
0.001287
600
104
0
Annex I
11
95
401
0.5
4.4
4.9
0.000537
600
0
0
Umb - EU
26
187
413
2.4
10.7
13.2
0.001434
600
52
0
Umb - EU
11
95
453
0.5
5.0
5.5
0.000599
600
104
0
Umb - EU
0
0
496
0.0
0.0
0.0
0
600
0
0
Umb - EU, EE
43
258
342
5.5
14.7
20.3
0.002205
600
52
0
Umb - EU, EE
20
157
391
1.6
7.8
9.4
0.001022
600
104
0
Umb - EU, EE
5
51
445
0.1
2.2
2.4
0.000256
600
0
0
A1 + JI
19
150
450
1.4
8.6
10.0
0.001086
600
52
0
A1 + JI
12
102
446
0.6
5.4
6.0
0.000649
600
104
0
A1 + JI
5
51
445
0.1
2.2
2.4
0.000256
600
0
0
Umb - EU + JI
10
84
516
0.4
5.2
5.6
0.000608
600
52
0
Umb - EU + JI
4
45
503
0.1
2.0
2.1
0.000229
600
104
0
Umb - EU + JI
0
0
496
0.0
0.0
0.0
0
Umb - EU, EE + JI
600
0
0
14
116
484
0.8
6.8
7.6
0.000826
Umb - EU, EE + JI
600
52
0
8
66
482
0.3
3.9
4.1
0.000449
Umb - EU, EE + JI
600
104
0
2
27
469
0.0
0.9
1.0
0.000105
600
0
0
A1 w/ Key LDC
20
150
450
1.5
9.0
10.5
0.001143
600
52
0
A1 w/ Key LDC
12
102
446
0.6
5.4
6.0
0.000649
600
104
0
A1 w/ Key LDC
5
51
445
0.1
2.2
2.4
0.000256
Umb - EU w/ Key
600
0
0
LDC
12
102
498
0.6
6.0
6.6
0.000717
Umb - EU w/ Key
600
52
0
LDC
5
51
497
0.1
2.5
2.6
0.000284
Umb - EU w/ Key
600
104
0
LDC
0
0
496
0.0
0.0
0.0
0
SGM/non-CO2 cost curve analysis
1.
Required
Sinks
Elect Res
Scenario
Permit
Domestic
Permits
US
US
US TC
TC/GDP
Cut Under
Price
Reductions
Purchased
Abatement
Capital
($b)
Kyoto
(92$)
(MMTCE)
Abroad
Cost
Outflow
Umb - EU, EE w/
600
0
0
Key LDC
16
130
470
1.0
7.5
8.6
0.000932
Umb - EU, EE w/
600
52
0
Key LDC
9
72
476
0.3
4.3
4.6
0.000502
Umb EU, EE w/
600
104
0
Key LDC
2
27
469
0.0
0.9
1.0
0.000105
600
0
0
A1 + 20% JI
36
229
371
4.1
13.4
17.5
0.001903
600
52
0
A1 + 20% JI
21
164
384
1.7
8.1
9.8
0.001065
600
104
0
A1 + 20% JI
9
72
424
0.3
3.8
4.1
0.000451
Umb - EU + 20%
0
0
JI
20
157
443
1.6
8.9
10.4
0.001136
600
Umb - EU + 20%
600
52
0
JI
9
72
476
0.3
4.3
4.6
0.000502
Umb - EU + 20%
600
104
0
JI
0
0
496
0.0
0.0
0.0
0
Umb - EU, EE +
600
0
0
20% JI
30
204
396
3.1
11.9
14.9
0.001627
Umb - EU, EE +
600
52
0
20% JI
16
130
418
1.0
6.7
7.7
0.000841
Umb - EU, EE +
600
104
0
20% JI
4
45
451
0.1
1.8
1.9
0.000206
A1 w/ Key LDC +
600
0
0
20% JI
20
157
443
1.6
8.9
10.4
0.001136
A1 w/ Key LDC +
600
52
0
20% JI
12
102
446
0.6
5.4
6.0
0.000649
A1 w/ Key LDC +
600
104
0
20% JI
5
51
445
0.1
2.2
2.4
0.000256
Umb - EU w/ Key
600
0
0
LDC + 20% JI
11
95
505
0.5
5.6
6.1
0.000662
Umb - EU w/ Key
600
52
0
LDC + 20% JI
5
51
497
0.1
2.5
2.6
0.000284
Umb - EU w/ Key
600
104
0
LDC + 20% JI
0
0
496
0.0
0.0
0.0
0
Umb - EU, EE w/
Key LDC + 20% JI
600
0
0
15
123
477
0.9
7.2
8.1
0.000879
Umb - EU, EE w/
600
52
0
Key LDC + 20% JI
9
72
476
0.3
4.3
4.6
0.000502
Umb - EU, EE w/
600
104
0
Key LDC + 20% JI
2
27
469
0.0
0.9
1.0
0.000105
SGM/non-CO2 cost curve analysis
The Effects of Annex I Trading and Ideal Global JI on Russia
Scenario
Permit Price
FSU Permit
FSU TR
Russia TR
FSU TC
Russia TC
Russia
($/ton)
Sales
(billions $)
(billions $)
(billions $)
(billions $)
TR-TC
(MMTC)
(billions $)
100% Paper
$15.8
294
$4.65
$3.02
$0.63
$0.41
$2.61
Tons*
50% Paper
$20.3
215
$4.36
$2.84
$1.10
$0.71
$2.13
Tons
No Paper
$25.9
130
$3.37
$2.19
$1.68
$1.09
$1.10
Tons*
Model: SGM
*
From model runs. 50% paper tons case based on interpolations from constructed marginal abatement cost curves.
Russian revenues and costs are assumed to be 65% of FSU revenues and costs, given that the Russian economy was approximately
65% the size of all FSU countries' economies in 1995.
Total costs are calculated assuming that the marginal abatement cost curve is linear in those sections of the curve.
All dollars are expressed in 1992 $.
These analyses assume that there are no constraints on the ability of other Annex I countries to purchase emissions reductions abroad.
The Effects of Annex I Trading Alone on Russia
Scenario
Permit Price
FSU Permit
FSU TR
Russia TR
FSU TC
Russia TC
Russia
($/ton)
Sales
(billions $)
(billions $)
(billions $)
(billions $)
TR-TC
(MMTC)
(billions $)
100% Paper
$41.3
382
$15.8
$10.27
$3.5
$2.28
$7.99
Tons*
50% Paper
$55
319
$17.5
$11.38
$5.8
$3.77
$7.61
Tons
No Paper
$71.6
251
$18.0
$11.70
$9.0
$5.85
$5.85
Tons*
Model: SGM
*
From model runs. 50% paper tons case based on interpolations from constructed marginal abatement cost curves.
Russian revenues and costs are assumed to be 65% of FSU revenues and costs, given that the Russian economy was approximately
65% the size of all FSU countries' economies in 1995.
Total costs are calculated assuming that the marginal abatement cost curve is linear in those sections of the curve.
All dollars are expressed in 1992 $.
These analyses assume that there are no constraints on the ability of other Annex I countries to purchase emissions reductions abroad.
The Effects of Annex I Trading and Ideal Global JI on Russia
Scenario
Permit Price
FSU Permit
FSU TR
Russia TR
FSU TC
Russia TC
Russia
($/ton)
Sales
(billions $)
(billions $)
(billions $)
(billions $)
TR-TC
(MMTC)
(billions $)
100% Paper
$15.8
294
$4.65
$3.02
$0.63
$0.41
$2.61
Tons*
50% Paper
$20.3
215
$4.36
$2.84
$1.10
$0.71
$2.13
Tons
No Paper
$25.9
130
$3.37
$2.19
$1.68
$1.09
$1.10
Tons*
Model: SGM
*
From model runs. 50% paper tons case based on interpolations from constructed marginal abatement cost curves.
Russian revenues and costs are assumed to be 65% of FSU revenues and costs, given that the Russian economy was approximately
65% the size of all FSU countries' economies in 1995.
Total costs are calculated assuming that the marginal abatement cost curve is linear in those sections of the curve.
All dollars are expressed in 1992 $.
These analyses assume that there are no constraints on the ability of other Annex I countries to purchase emissions reductions abroad.
The Effects of Annex I Trading Alone on Russia
Scenario
Permit Price
FSU Permit
FSU TR
Russia TR
FSU TC
Russia TC
Russia
($/ton)
Sales
(billions $)
(billions $)
(billions $)
(billions $)
TR-TC
(MMTC)
(billions $)
100% Paper
$41.3
382
$15.8
$10.27
$3.5
$2.28
$7.99
Tons*
50% Paper
$55
319
$17.5
$11.38
$5.8
$3.77
$7.61
Tons
No Paper
$71.6
251
$18.0
$11.70
$9.0
$5.85
$5.85
Tons*
Model: SGM
*
From model runs. 50% paper tons case based on interpolations from constructed marginal abatement cost curves.
Russian revenues and costs are assumed to be 65% of FSU revenues and costs, given that the Russian economy was approximately
65% the size of all FSU countries' economies in 1995.
Total costs are calculated assuming that the marginal abatement cost curve is linear in those sections of the curve.
All dollars are expressed in 1992 $.
These analyses assume that there are no constraints on the ability of other Annex I countries to purchase emissions reductions abroad.
Preliminary Draft
MEMORANDUM
TO:
Ray Squitieri
FROM:
Joe Aldy
DATE:
December 3, 1997
RE:
Constraints on Annex I Permit Trading: Paper Tons and Purchase Caps
To assess the effects of constraining the percentage of paper tons EEFSU countries can sell as
well as the percentage of emissions reductions occurring abroad other Annex I countries can buy,
I reviewed model outputs from SGM. Both of these constraints can increase the price of a
carbon permit, depending on the stringency of the constraint.
In most cases, a stringent purchase cap (e.g., no country can buy more than 10% of its emissions
reductions abroad) drives the U.S. permit price (see attached table). For the scenarios with paper
tons and 10% purchase caps, EEFSU countries cannot even sell all of their paper tons. For the
scenarios with paper tons and 25% purchase caps, EEFSU countries do sell all of their paper
tons, and some tons representing actual emissions reductions relative to BAU.
However, constraints on the extent of allowable paper ton sales and loose purchase caps (e.g.,
50%) are driven by the paper ton constraint. In the case of a 50% paper ton constraint and a 50%
purchase cap, non-EEFSU countries buy 49% of their emissions reductions from EEFSU
countries. In the case of no paper tons and a 50% purchase cap, non-EEFSU countries buy 38%
of their emissions reductions from EEFSU countries.
Preliminary Draft
Constraints
U.S. Permit Price
Permits Purchased Abroad by
($/ton)
U.S. (MMTCE)
100% paper tons, no purchase
$41*
202
caps (no constraints)
50% paper tons, no purchase
$55
149
caps
no paper tons, no purchase
$72*
97
caps
100% paper tons, 10%
$93
38
purchase cap
100% paper tons, 25%
$72
95
purchase cap
100% paper tons, 50%
$45
190
purchase cap
50% paper tons, 10%
$93
38
purchase cap
50% paper tons, 25%
$72
95
purchase cap
50% paper tons, 50%
$55
151
purchase cap
no paper tons, 10% purchase
$93
38
cap
no paper tons, 25% purchase
$72
95
cap
no paper tons, 50% purchase
$72
97
cap
*From model runs. All other estimates are derived from assessing the constructed marginal
abatement cost curves depicted in attached graphs.
Preliminary Draft
MEMORANDUM
TO:
Ray Squitieri
FROM:
Joe Aldy
DATE:
December 2, 1997
RE:
The Effects of Trading Constraints on Permit Prices and Income Flows
To assess the effects of trading constraints on U.S. permit prices and income flows, I reviewed
several model runs from SGM. While unconstrained trading would result in minimizing the
compliance costs with binding targets, some have proposed constraining the amount of emissions
reductions allowed to be achieved through international permit trading and joint implementation.
The following table presents the permit prices and the quantity of permits purchased abroad
under various percentage-based constraints.
U.S. Permit Prices for Meeting 1990 in 2010 under Various Trading Constraints
% of Reductions Allowed to
Annex I Trading Only
Annex I Trading +
be Purchased from Other
(permits purchased abroad)
Joint Implementation
Countries
(permits purchased abroad)
100% (no constraint)
$41/ton (202 MMTCE)
$16/ton (312 MMTCE)
0% (no trading, no JI)
$108/ton (0 MMTCE)
$108/ton (0 MMTCE)
10%
$93/ton (38 MMTCE)
$93/ton (38 MMTCE)
25%
$72/ton (95 MMTCE)
$72/ton (95 MMTCE)
50%
$45/ton (190 MMTCE)
$45/ton (190 MMTCE)
model: SGM
Constraints on Trade
This analysis provides four interesting points. First, in an unconstrained world, the U.S. buys
53% of its emissions reductions abroad with Annex I trading and 82% of reductions with JI and
Annex I trading. Note in the second table that the U.S. buys less as a share of reductions than
other Annex I countries (however, EEFSU countries are sellers). Second, any split between JI
and Annex I trading (e.g., no more than 5% through trading, no more than 5% through JI) is
irrelevant to the U.S. permit price so long as the total constraint (e.g., 10%) is less than the
percentage of emissions reductions the U.S. would buy under no constraints. Third, Russia sells
more permits than China under JI (but less than it would with an Annex I trading only world)
because it has so many paper tons. Fourth, any constraint less than 60% implies that EEFSU
countries would not be able to sell all of their paper tons.
Preliminary Draft
Percent of Emissions Reductions Purchased Abroad with No Constraints on Trading and JI
Country/Region
Annex I Trading Only
Annex I Trading +
Joint Implementation
Canada
75%
88%
Japan
78%
91%
Western Europe
65%
86%
Australia
58%
81%
U.S.
53%
82%
model: SGM
Income Flows
Not only do constraints on trade negatively impact the buyers of permits by increasing permit
prices, but they also decrease the flows of income to countries that sell. In a no-constraint world,
the sellers of permits would receive $20 billion in 2010 under Annex I trading and more than $10
billion in 2010 under Annex I trading and JI. However, a constraint of 10% emissions reduction
through foreign purchases would result in income transfers of only $600 million under Annex I
trading and $200 million under Annex I trading plus JI. This 10% constraint results in EIT and
developing countries receiving only 2-3% of the income they would have received without the
constraint.
August 19, 1997
Comments on "Additionality in the Context of Joint Implementation", August 13 Draft
Office of Economic Policy, Treasury Department
1) The central problem with this paper is that it does not sufficiently acknowledge the
fundamentally difficult task of establishing that emissions reductions are incremental. Each of
the approaches proposed involves comparisons to a counterfactual that is not observed, only
modelled. As such, the guarantee of additionality is only as good as the models themselves. The
memo presents no evidence on the quality of the predictions from these types of models, nor a
sufficiently rich discussion of the technical difficulties inherent in applying these types of
modelling exercises in the context of JI.
To see this, compare the approaches listed in this paper to the best possible approach: JI
with binding developing country committments on emissions levels. This simply amounts to
international trading with developing countries included. In such a world, we are guaranteed
incrementality: to claim credit for a unit of emissions reduction, a company in the U.S. will have
to buy a permit in the developing country for one unit of emissions. This will by definition
guarantee that emissions in the developing country drop by one unit, since there is a fixed total of
emissions credits in that country. Thus, additionality is assured, since there is now one fewer
units of total emissions from other sources in the developing country.
Now, compare to this the best possible modelling approach. Under this approach,
engineering specialists draw up a prediction about the future path of generation power sources
(for example) in the developing country. But any prediction is just that, and as such will have
some error. In some cases, the prediction will understate the pace of technological advance in
the developing country, SO that companies will get credit for building a type of plant that would
have been built anyway. In some cases, the prediction will overstate the pace, so that companies
will not build a plant because they are not getting credit. In any case, given that all models make
prediction errors, there will be resulting error rates in our ability to assign JI credit. So there is
no way to guarantee additionality without binding developing country committments.
This is not to say that there is JI is completely non-additional under the proposed
approaches. Indeed, the methodologies suggested are clever and are probably the best that we
can do without committments from developing countries. But while the paper acknowledges
potential problems such as those described above in the fourth paragraph, it then immediately
turns into the fifth to "assuring additionality". A footnote in that paragraph offers the appropriate
caveat, but the implication is that additionality can be assured nonetheless.
This problem can be partially addressed by making three straightforward changes:
a) A new fourth paragraph on the first page should discuss the benchmark case: international
trading. It should bring out the key points made above: that any Л approach which revolves
around modelling baselines can only approach, and can never achieve, the additionality that
would be guaranteed if developing countries were brought into an international trading regime.
b) Footnote 4 should be brought into the text and amplified.
c) Terms like "high accuracy" should be prefaced by "relatively"; these options are the highest
accuracy of those listed, but may be very low accuracy relative to the ideal benchmark of
international trading.
2) Do we have any evidence on how accurate the forecasts of counterfactual technology paths are
likely to be? If we had done forecasts based on available data for the U.S. or some other country
10 years ago, would we have predicted anything like our current pattern of technology adoption
for generation and other activities? This goes to the heart of these type of modelling approaches
to establishing additionality.
3) As CEA and Treasury highlighted in their comments on an earlier draft, different approaches
to modelling the processes of technological diffusion are likely to yield very different answers
for the counterfactual. How will this uncertainty be resolved? This is a particularly salient
question given the "all or nothing" aspect of JI. If there is some penetration of a particular type
of generation, but it has not fully diffused, the company might get no credit at all. This will
provide a particularly strong incentive for firms to promote the engineering estimates that
support their case. How will these pressures be resisted, given the true uncertainty in the
estimates?
One particular logistical difficulty will be deciding which country will be responsible for
determining the counterfactual. If we let the developing countries themselves model the
counterfactual, one could imagine an "engineering bidding war", where each of several countries
engineers compete to make their baseline look the least advanced (thus making their country
more attractive for investment by presenting more opportunity for additionality). This could be
rectified by an objective U.S. or third party engineer, but this might raise a difficult set of
sovereignty issues.
4) Option 3 provides the closest alternative to true additionality through developing country
committments, by measuring changes in sector specific emissions patterns. But once again, it
must be recognized that emissions are projected based on out of sample modelling. How
accurate are our models? Once again, it would be constructive to assess how well existing
models would do at predicted observed emissions history based on data that ended 10 years ago.
5) Options 4 and 5 strike us as the most problematic, since they are the most subjective. Any
option which is strongly influenced by the type of proposal made by the firm, rather than by
objective evidence to support additionality, will simply reward firms that are best at making their
case, not those that are guaranteeing the most additionality. This will lead to huge inefficiencies
("rent-seeking losses") as firms devote substantial resources to making a case look as good as
possible, rather than devoting those resources to the investment itself.
9/18/97
Outputs
Modelers
Target
Timetable
Trading
Permit
Revenue
Burden
BAU
Paper Tons
AEEI
Ramp-up
Time Path
PDV (5%;
GDP in 2010
ID
Scenario
Model
Allocation
Recycling
Sharing
Emissions
or Corre-
2000-2050)
(deviation
Path
sponding
Foregone
from BAU)
Assumptio
Reductions
Consumption
n
SGM1
BAU
SGM,
Battelle
n/a
n/a
n/a
n/a
n/a
n/a
IAT
n/a
1.0
n/a
-->2050,
$121,650 billion
$9,185 billion
-->2100
(BAU
(BAU GDP)
MAGICC
(climate)
consumption)
-10% of
SGM,
Battelle
-10% 1990
stabilize in
Annex I
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
$485 billion
$9,155 billion
SGM9
1990 in
MAGICC
emissions
2010
part.
-->2100
(-$30 billion)
2010
level
(climate)
SGM8
-10% of
SGM,
Battelle
-10% 1990
stabilize in
domestic
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
$980 billion
$9,149 billion
part.
-->2100
(-$36 billion)
1990 in
MAGICC
emissions
2010
only
(climate)
2010
level
SGM10
-10% of
SGM,
Battelle
-10% 1990
stabilize in
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
$50 billion
$9,171 billion
-->2100
1990 in
MAGICC
emissions
part.
(-$14 billion)
2010
(climate)
2010
level
SGM36
1990 in
SGM,
Battelle
1990
stabilize in
Annex 1
auction
lump-sum
no LDC
IAT
PT
1.0
yes
-->2050,
$195 billion
$9,179 billion
2020
MAGICC
emissions
2020
part.
-->2100
(-$6 billion)
(climate)
level
SGM39
1990 in
SGM,
Battelle
1990
stabilize in
Annex I
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$230 billion
$9,172 billion
-->2100
2010
MAGICC
emissions
part.
(-$13 billion)
2010
(climate)
level
SGM3
1990 in
SGM,
Battelle
1990
stabilize in
Annex I
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
$225 billion
$9,172 billion
(-$13 billion)
2010
MAGICC
emissions
2010
part.
-->2100
level
(climate)
SGM18
1990 in
SGM,
Battelle
1990
stabilize in
Annex I
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$255 billion
$9,172 billion
2010
MAGICC
emissions
2010
stabilizes
-->2100
(-$13 billion)
level
at 2030 in
(climate)
2030
SGM,
Battelle
1990
stabilize in
Annex I
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$260 billion
$9,172 billion
SGM21
1990 in
2010
MAGICC
emissions
2010
BAU to
-->2100
(-$13 billion)
2030,
(climate)
level
equal per
capita in
2050
SGM17
1990 in
1990
stabilize in
domestic
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$740 billion
$9,164 billion
SGM,
Battelle
2010
MAGICC
emissions
2010
stabilizes
-->2100
(-$21 billion)
only
level
at 2030 in
(climate)
2030
no LDC
IAT
PT
1.0
no
-->2050,
$665 billion
$9,165 billion
SGM2
1990 in
SGM,
Battelle
1990
stabilize in
domestic
auction
Tump-sum
-->2100
(-$20 billion)
2010
MAGICC
emissions
2010
only
part.
(climate)
level
Battelle
1990
stabilize in
domestic
auction
Tump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$740 bilion
$9,164 billion
SGM38
1990 in
SGM,
2010
MAGICC
emissions
part.
-->2100
(-$21 billion)
2010
only
(climate)
level
PT
1.0
in 2005
-->2050,
$740 billion
$9,164 billion
SGM20
1990 in
SGM,
Battelle
1990
stabilize in
domestic
auction
Tump-sum
LDC
IAT
2010
MAGICC
emissions
2010
only
BAU to
-->2100
(-$21 billion)
level
2030,
(climate)
equal per
capita in
2050
SGM40
1990 in
SGM,
Battelle
1990
stabilize in
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$5 billion
$9,180 billion
2010
part.
-->2100
(-$5 billion)
MAGICC
emissions
2010
(climate)
level
9/18/97
Scenario
Model
Modelers
Target
Timetable
Trading
Permit
Revenue
Burden
BAU
Paper Tons
AEEI
Ramp-up
Time Path
PDV (5%;
GDP in 2010
ID
Allocation
Recycling
Sharing
Emissions
or Corre-
2000-2050)
(deviation
Path
sponding
Foregone
from BAU)
Assumptio
Reductions
Consumption
n
SGM4
1990 in
SGM,
Battelle
1990
stabilize in
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
$5 billion
$9,180 billion
-->2100
(-$5 billion)
2010
MAGICC
emissions
2010
part.
level
(climate)
SGM22
1990 in
SGM,
Battelle
1990
stabilize in
worldwide
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$25 billion
$9,180 billion
2010
MAGICC
emissions
2010
BAU to
-->2100
(-$5 billion)
level
2030,
(climate)
equal per
capita in
2050
SGM,
Battelle
1990
stabilize in
worldwide
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$20 billion
$9,180 billion
SGM19
1990 in
2010
MAGICC
emissions
2010
stabilizes
-->2100
(-$5 billion)
level
at 2030 in
(climate)
2030
SGM35
1990 in
SGM,
Battelle
1990
stabilize in
domestic
auction
Tump-sum
no LDC
IAT
PT
1.0
yes
-->2050,
$660 billion
$9,172 billion
2020
MAGICC
emissions
2020
only
part.
-->2100
(-$13 billion)
level
(climate)
1990
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
yes
-->2050,
-$1 billion
$9,183 billion
SGM37
1990 in
SGM,
Battelle
stabilize in
2020
MAGICC
part.
-->2100
emissions
2020
(-$2 billion)
level
(climate)
SGM6
1995 in
SGM,
Battelle
1995
stabilize in
Annex I
auction
lump-sum
no LDC
IAT
CR
1.0
no
-->2050,
$380 billion
$9,175 billion
2010
MAGICC
emissions
2010
part.
-->2100
(-$10 billion)
level
(climate)
stabilize in
domestic
auction
lump-sum
no LDC
IAT
CR
1.0
no
-->2050,
$425 billion
$9,174 billion
SGM5
1995 in
SGM,
Battelle
1995
2010
MAGICC
emissions
2010
part.
-->2100
(-$11 billion)
only
level
(climate)
SGM7
1995 in
Battelle
1995
stabilize in
worldwide
auction
lump-sum
no LDC
IAT
CR
1.0
no
-->2050,
$30 billion
$9,179 billion
SGM,
2010
MAGICC
emissions
part.
-->2100
2010
(-$6 billion)
level
(climate)
Annex 1
auction
lump-sum
no LDC
IAT
CR
1.0
yes
-->2050,
$410 billion
$9,176 billion
SGM33
1995 in
SGM,
Battelle
1995
stabilize in
2020
part.
-->2100
(-$9 billion)
MAGICC
emissions
2020
level
(climate)
SGM32
1995 in
Battelle
1995
stabilize in
domestic
auction
lump-sum
no LDC
IAT
CR
1.0
yes
-->2050,
$445 billion
$9,176 billion
SGM,
2020
MAGICC
emissions
2020
part.
-->2100
(-$9 billion)
only
level
(climate)
auction
lump-sum
no LDC
IAT
CR
1.0
yes
-->2050,
-$40 billion
$9,180 billion
SGM34
1995 in
SGM,
Battelle
1995
stabilize in
worldwide
part.
-->2100
(-$5 billion)
2020
MAGICC
emissions
2020
level
(climate)
SGM12
Battelle
2010 BAU
stabilize in
Annex I
auction
lump-sum
no LDC
TAT
PT
1.0
no
-->2050,
$55 billion
$9,185 billion
Peak in
SGM,
2015
MAGICC
emissions in
part.
-->2100
($0 billion)
2040
2015; 1990
(climate)
level in 2040
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$75 billion
$9,185 billion
SGM30
Peak in
SGM,
Battelle
2010 BAU
stabilize in
Annex I
auction
2015
MAGICC
emissions in
2040
part.
-->2100
(0 billion)
2015; 1990
(climate)
level in 2040
SGM,
Battelle
2010 BAU
stabilize in
Annex 1
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$75 billion
$9,185 billion
SGM24
Peak in
2015
MAGICC
stabilizes
-->2100
(0 billion)
emissions in
2040
2015; 1990
at 2030 in
(climate)
level in 2040
2030
9/18/97
ID
Scenario
Model
Modelers
Target
Timetable
Trading
Permit
Revenue
Burden
BAU
Paper Tons
AEEI
Ramp-up
Time Path
PDV (5%;
GDP in 2010
Allocation
Recycling
Sharing
Emissions
or Corre-
2000-2050)
(deviation
Path
sponding
Foregone
from BAU)
Assumptio
Reductions
Consumption
D
Annex I
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$75 billion
$9,185 billion
SGM27
Peak in
SGM,
Battelle
2010 BAU
stabilize in
2015
MAGICC
emissions in
2040
BAU to
-->2100
(0 billion)
2015; 1990
2030,
(climate)
level in 2040
equal per
capita in
2050
SGM11
Peak in
SGM,
Battelle
2010 BAU
stabilize in
domestic
auction
lump-sum
no LDC
IAT
PT
1.0
no
--->2050,
$235 billion
$9,185 billion
MAGICC
emissions in
2040
only
part.
-->2100
($0 billion)
2015
2015; 1990
(climate)
level in 2040
SGM29
Peak in
SGM,
Battelle
2010 BAU
stabilize in
domestic
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$270 billion
$9,184 billion
2015
MAGICC
emissions in
2040
only
part.
-->2100
(-$1 billion)
2015; 1990
(climate)
level in 2040
stabilize in
domestic
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$270 billion
$9,184 billion
SGM26
Peak in
SGM,
Battelle
2010 BAU
2015
MAGICC
emissions in
2040
only
BAU to
-->2100
(-$1 billion)
2015; 1990
2030,
(climate)
level in 2040
equal per
capita in
2050
SGM23
Peak in
SGM,
Battelle
2010 BAU
stabilize in
domestic
auction
lump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$270 billion
$9,184 billion
MAGICC
emissions in
2040
only
stabilizes
-->2100
(-$1 billion)
2015
2015; 1990
at 2030 in
(climate)
level in 2040
2030
SGM25
Peak in
SGM,
Battelle
2010 BAU
stabilize in
worldwide
auction
lump-sum
LDC
TAT
PT
1.0
in 2005
-->2050,
-$3 billion
$9,185 billion
2015
MAGICC
emissions in
2040
stabilizes
-->2100
(0 billion)
2015; 1990
at 2030 in
(climate)
level in 2040
2030
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
-$5 billion
$9,185 billion
SGM31
Peak in
SGM,
Battelle
2010 BAU
stabilize in
worldwide
auction
2015
MAGICC
emissions in
2040
part.
-->2100
(0 billion)
2015; 1990
(climate)
level in 2040
Peak in
SGM,
Battelle
2010 BAU
stabilize in
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
no
-->2050,
-$8 billion
$9,185 billion
SGM13
2015
MAGICC
emissions in
2040
part.
-->2100
($0 billion)
2015; 1990
(climate)
level in 2040
SGM28
Peak in
SGM,
Battelle
2010 BAU
stabilize in
worldwide
auction
Tump-sum
LDC
IAT
PT
1.0
in 2005
-->2050,
$1 billion
$9,185 billion
2015
2040
BAU to
-->2100
emissions in
(0 billion)
MAGICC
2015; 1990
2030,
(climate)
level in 2040
equal per
capita in
2050
+10% 1990
Annex I
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$95 billion
$9,181 billion
SGM15
+10% of
SGM,
Battelle
stabilize in
1990 in
MAGICC
2010
part.
-->2100
emissions
(-$4 billion)
level
(climate)
2010
SGM14
+10% of
SGM,
Battelle
+10% 1990
stabilize in
domestic
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$460 billion
$9,174 billion
1990 in
MAGICC
emissions
2010
only
part.
-->2100
(-$11 billion)
2010
level
(climate)
9/18/97
Modelers
Target
Timetable
Trading
Permit
Revenue
Burden
BAU
Paper Tons
AEEI
Ramp-up
Time Path
PDV (5%;
GDP in 2010
ID
Scenario
Model
Allocation
Recycling
Sharing
Emissions
or Corre-
2000-2050)
(deviation
Path
sponding
Foregone
from BAU)
Assumptio
Reductions
Consumption
n
worldwide
auction
lump-sum
no LDC
IAT
PT
1.0
in 2005
-->2050,
$1 billion
$9,184 billion
SGM16
+10% of
SGM,
Battelle
+10% 1990
stabilize in
1990 in
part.
-->2100
(-$1 billion)
MAGICC
emissions
2010
2010
level
(climate)
MM1
n/a
n/a
n/a
n/a
n/a
n/a
IAT
n/a
~T.0
n/a
-->2025
n/a
$9,205 billion
BAU
Markal
DOE
(BAU GDP)
auction
lump-sum
no LDC
IAT
n/a
~1.0
n/a
-->2025
n/a
$9,137 billion
MM2
1990 in
Markal
DOE
1990
stabilize in
domestic
2010
emissions
2010
only
part.
(-$68 billion)
level
MM3
1995 in
Markal
1995
stabilize in
domestic
auction
lump-sum
no LDC
IAT
n/a
~1.0
n/a
-->2025
n/a
$9,152 billion
DOE
2010
emissions
2010
only
part.
(-$53 billion)
level
n/a
~1.0
n/a
-->2025
n/a
$9,197 billion
MM4
1990 in
Markal
DOE
1990
stabilize in
domestic
auction
lump-sum
no LDC
IAT
2020
emissions
2020
part.
(-$8 billion)
only
level
DOE
2010 BAU
stabilize in
domestic
auction
lump-sum
no LDC
IAT
n/a
~1.0
n/a
-->2025
n/a
$9,201 billion
MM5
Peak in
Markal
(-$4 billion)
2015
emissions in
2040
only
part.
2015; 1990
level in 2040
9/18/97
ID
Permit
Permit
Permit
Conc.
Conc.
Year Conc.
Change in
Change in
Emissions
Year
Intl. Trade of
Intl. Trade of
Date
File (h:\jaldy\)
Prices:
Prices:
Prices:
(ppmv) in
(ppmv) in
(550 ppmv)
Temp. (deg.
Temp. (deg.
Peak,
Returns to
Permits, U.S.,
Permits, U.S.,
Received
2010
2025
2050
2050
2100
Reaches 2x
C) from 1990
C) from 1990
mmtce
1990
2010
2050
Run
(Deviation
(Deviation
Pre-Ind. Level
in 2050
in 2100
(year)
(MMTCE), ($)
(MMTCE), ($)
from BAU)
from BAU)
(Deviation
(Deviation
(Deviation
from BAU)
from BAU)
from BAU)
SGM1
$0
$0
$0
502
711
2065
1.06
2.36
no peak:
n/a
n/a
n/a
08/21/97
cea90_~1.xls
2245
(2050)
SGM9
$91
$137
$238
481
645
2074
0.97
2.11
1637
never returns
-180,
-332,
08/21/97
cea90m_~1.xls
(-21)
(-66)
(+9)
(-0.09)
(-0.25)
(2005)
(-$16.4 billion)
(-$79.0 billion)
SGM8
$175
$304
$924
481
645
2074
0.97
2.11
1637
2010
n/a
n/a
08/21/97
cea90m_~1.xls
(-21)
(-66)
(+9)
(-0.09)
(-0.25)
(2005)
SGM10
$33
$37
$45
481
645
2074
0.97
2.11
no peak:
never returns
-332,
-845,
08/21/97
cea90m_~1.xls
(-21)
(-66)
(+9)
(-0.09)
(-0.25)
2060
(-$11.0 billion)
(-$38.0 billion)
(2050)
SGM36
$23
$86
$150
486
656
2072
0.99
2.16
no peak:
n/a
-180
-364
09/10/97
case20-1.xls
(-16)
(-55)
(+7)
(-0.07)
(-0.20)
1714
(-$4.14 billion)
(-$54.6 billion)
(2050)
SGM39
$41
$84
$149
486
656
2072
0.99
2.16
no peak:
never returns
-202,
-364,
09/10/97
case10~1.xls
(-$8.3 billion)
(-$54.2 billion)
(-16)
(-55)
(+7)
(-0.07)
(-0.20)
1714
(2050)
SGM3
$42
$84
$149
486
655
2072
0.99
2.15
no peak:
never returns
-202,
-364,
08/21/97
cea90_~2.xls
(-16)
(-56)
(+7)
(-0.07)
(-0.21)
1714
(-$8.5 billion)
(-$54.2 billion)
(2050)
SGM18
$39
$83
$150
478
565
2091
0.96
1.82
no peak:
never returns
-209,
-362,
08/27/97
case2.xls,
(-24)
(-146)
(+26)
(-0.10)
(-0.54)
1712
(-$8.2 billion)
(-$54.3 billion)
9/4/97 fax
(2050)
SGM21
$39
$83
$150
n/a
n/a
n/a
n/a
n/a
no peak:
never returns
-209,
-362,
08/27/97
case3.xls
1712
(-$8.2 billion)
(-$54.3 billion)
(2050)
SGM17
$108
$188
$582
476
564
2092
0.95
1.82
1550
2010
n/a
n/a
08/27/97
case2.xls,
(2000)
9/4/97 fax
(-26)
(-147)
(+27)
(-0.11)
(-0.54)
SGM2
$110
$191
$582
485
658
2072
0.99
2.16
1637
2010
n/a
n/a
08/21/97
cea90_~2.xls
(-17)
(-53)
(+7)
(-0.07)
(-0.20)
(2005)
SGM38
$108
$188
$582
484
656
2073
0.98
2.15
1550
2010
n/a
n/a
09/10/97
case10~1.xls
(-18)
(-55)
(+8)
(-0.08)
(-0.21)
(2000)
n/a
n/a
n/a
n/a
n/a
1550
2010
n/a
n/a
08/27/97
case3.xls
SGM20
$108
$188
$582
(2000)
$23
$33
486
656
2072
0.99
2.16
no peak:
never returns
-312,
-751,
09/10/97
case10~1.xis
SGM40
$16
(-16)
(-55)
(+7)
(-0.07)
(-0.20)
2101
(-$5.0 billion)
(-$24.8 billion)
(2050)
9/18/97
ID
Permit
Permit
Permit
Conc.
Conc.
Year Conc.
Change in
Change in
Emissions
Year
Intl. Trade of
Intl. Trade of
Date
File (h:\jaldy\)
Prices:
Prices:
Prices:
(ppmv) in
(ppmv) in
(550 ppmv)
Temp. (deg.
Temp. (deg.
Peak,
Returns to
Permits, U.S.,
Permits, U.S.,
Received
2010
2025
2050
2050
2100
Reaches 2x
C) from 1990
C) from 1990
mmtce
1990
2010
2050
Run
(Deviation
(Deviation
Pre-Ind. Level
in 2050
in 2100
(year)
(MMTCE), ($)
(MMTCE), ($)
from BAU)
from BAU)
(Deviation
(Deviation
(Deviation
from BAU)
from BAU)
from BAU)
SGM4
$16
$23
$32
486
655
2072
0.99
2.15
no peak:
never returns
-313,
-752,
08/21/97
cea90_~2.xls
(-16)
(-56)
(+7)
(-0.07)
(-0.21)
2102
(-$5.0 billion)
(-$24.1 billion)
(2050)
$0
n/a
n/a
n/a
n/a
n/a
no peak:
never returns
n/a
n/a
08/27/97
case3.xls
SGM22
$15
$23
2239
(2050)
SGM19
$15
$23
$110
478
565
2091
0.96
1.82
1883
never returns
-316,
-500,
08/27/97
case2.xls,
(-24)
(-146)
(+26)
(-0.10)
(-0.54)
(2040)
(-$4.7 billion)
(-$55.0 billion)
9/4/97 fax
SGM35
$71
$192
$582
484
656
2073
0.98
2.15
1550
2020
n/a
n/a
09/10/97
case20~1.xls
(-18)
(-55)
(+8)
(-0.08)
(-0.21)
(2000)
SGM37
$9
$24
$33
486
656
2072
0.99
2.16
no peak:
n/a
-246
-751
09/10/97
case20~1.xls
(-16)
(-55)
(+7)
(-0.07)
(-0.20)
2101
(-$2.21 billion)
(-$24.78
(2050)
billion)
SGM6
$74
$119
$202
483
648
2074
0.98
2.12
1637
never returns
36,
-122,
08/21/97
cea95_-1.xls
(-19)
(-63)
(+9)
(-0.08)
(-0.24)
(2005)
(+$2.7 billion)
(-$24.6 billion)
SGM5
$62
$131
$317
483
648
2074
0.98
2.12
1637
never returns
n/a
n/a
08/21/97
cea95_~1.xls
(-19)
(-63)
(+9)
(-0.08)
(-0.24)
(2005)
SGM7
$27
$32
$41
483
648
2074
0.98
2.12
no peak:
never returns
-131,
-593,
08/21/97
cea95_~1.xls
(-19)
(-63)
(+9)
(-0.08)
(-0.24)
2073
(-$3.5 billion)
(-$24.3 billion)
(2050)
SGM33
$57
$120
$203
482
648
2074
0.97
2.12
no peak:
n/a
20
-119,
09/10/97
case20~2.xls
(-20)
(-63)
(+9)
(-0.09)
(-0.24)
1599
($1.14 billion)
(-$24.16
(2050)
billion)
SGM32
$51
$131
$318
482
648
2074
0.97
2.12
1550
n/a
n/a
n/a
09/10/97
case20~2.xls
(-20)
(-63)
(+9)
(-0.09)
(-0.24)
(2000)
$33
$41
482
648
2074
0.97
2.12
no peak:
n/a
-122
-592
09/10/97
case20-2.xls
SGM34
$21
(-20)
(-63)
(+9)
(-0.09)
(-0.24)
2072
(-$2.56 billion)
(-$24.27
(2050)
billion)
SGM12
$0
$47
$155
491
n/a
n/a
1.02
n/a
1807
never returns
0, (n/a)
-367,
08/21/97
cea90_~1.xls
(-11)
(-0.04)
(2015)
(-$56.9 billion)
08/27/97
case6.xls,
$153
489
658
2071
1.00
2.17
1755
never returns
-5,
-367,
SGM30
$11
$56
(-13)
(-53)
(+6)
(-0.06)
(-0.19)
(2015)
(-$0.06 billion)
(-$56.2 billion)
9/4/97 fax
SGM24
$11
$56
$153
481
568
2089
0.98
1.84
1755
never returns
is,
-367,
08/27/97
case4.xls,
(-21)
(-143)
(+24)
(-0.08)
(-0.52)
(2015)
(-$0.06 billion)
(-$56.2 billion)
9/4/97 fax
9/18/97
ID
Permit
Permit
Permit
Conc.
Conc.
Year Conc.
Change in
Change in
Emissions
Year
Intl. Trade of
Intl. Trade of
Date
File (h:\jaldy\)
Prices:
Prices:
Prices:
(ppmv) in
(ppmv) in
(550 ppmv)
Temp. (deg.
Temp. (deg.
Peak,
Returns to
Permits, U.S.,
Permits, U.S.,
Received
2010
2025
2050
2050
2100
Reaches 2x
C) from 1990
C) from 1990
mmice
1990
2010
2050
Run
(Deviation
(Deviation
Pre-Ind. Level
in 2050
in 2100
(year)
(MMTCE), ($)
(MMTCE), ($)
from BAU)
from BAU)
(Deviation
(Deviation
(Deviation
from BAU)
from BAU)
from BAU)
SGM27
$56
$153
n/a
n/a
n/a
n/a
n/a
1755
never returns
-5,
-367,
08/27/97
case5.xls
$11
(2015)
(-$0.06 billion)
(-$56.2 billion)
SGM11
$0
$84
$559
489
n/a
n/a
1.01
n/a
1807
2040
n/a
n/a
08/21/97
cea90_~1.xls
(-13)
(-0.05)
(2015)
$12
$99
$563
489
658
2071
1.00
2.17
1729
2040
n/a
n/a
08/27/97
case6.xls,
SGM29
(-13)
(-53)
(+6)
(-0.06)
(-0.19)
(2015)
9/4/97 fax
SGM26
$12
$99
$563
n/a
n/a
n/a
n/a
n/a
1729
2040
n/a
n/a
08/27/97
case5.xls
(2015)
SGM23
$563
481
568
2089
0.98
1.84
1729
2040
n/a
n/a
08/27/97
$12
$99
case4.xls,
(-21)
(-143)
(+24)
(-0.08)
(-0.52)
(2015)
9/4/97 fax
SGM25
$4
$16
$111
481
568
2089
0.98
1.84
1893
never returns
-30,
-500,
08/27/97
case4.xls,
(-21)
(-143)
(+24)
(-0.08)
(-0.52)
(2030)
(-$0.1 billion)
(-$55.5 billion)
9/4/97 fax
08/27/97
case6.xls,
SGM31
$4
$16
$33
489
658
2071
1.00
2.17
no peak:
never returns
-30,
-751,
(-13)
(-53)
(+6)
(-0.06)
(-0.19)
2101
(-$0.12 billion)
(-$24.8 billion)
9/4/97 fax
(2050)
SGM13
$14
$33
491
n/a
n/a
1.02
n/a
no peak:
never returns
0, (n/a)
-752,
08/21/97
$0
cea90_~1.xls
(-11)
(-0.04)
2102
(-$24.8 billion)
(2050)
SGM28
$4
$16
$0
n/a
n/a
n/a
n/a
n/a
no peak:
never returns
n/a
n/a
08/27/97
case5.xls
2241
(2050)
$113
489
662
2071
1.00
2.18
no peak:
never returns
-172,
-339,
08/27/97
casel.xls
SGM15
$17
$56
(-13)
(-49)
(+6)
(-0.06)
(-0.18)
1824
(-$2.9 billion)
(-$38.3 billion)
(2050)
SGM14
$60
$128
$310
488
664
2071
0.99
2.18
1550
never returns
n/a
n/a
08/27/97
case1.xls
(-14)
(-47)
(+6)
(-0.07)
(-0.18)
(2000)
9/18/97
ID
Permit
Permit
Permit
Conc.
Conc.
Year Conc.
Change in
Change in
Emissions
Year
Intl. Trade of
Intl. Trade of
Date
File (h:\jaldy\)
Prices:
Prices:
Prices:
(ppmv) in
(ppmv) in
(550 ppmv)
Temp. (deg.
Temp. (deg.
Peak,
Returns to
Permits, U.S.,
Permits, U.S.,
Received
2010
2025
2050
2050
2100
Reaches 2x
C) from 1990
C) from 1990
mmtce
1990
2010
2050
Run
(Deviation
(Deviation
Pre-Ind. Level
in 2050
in 2100
(year)
(MMTCE), ($)
(MMTCE), ($)
from BAU)
from BAU)
(Deviation
(Deviation
(Deviation
from BAU)
from BAU)
from BAU)
SGM16
$7
$16
$25
489
662
2071
1.00
2.18
no peak:
never returns
-219,
-643,
08/27/97
casel.xls
(-13)
(-49)
(+6)
(-0.06)
(-0.18)
2128
(-$1.5 billion)
(-$16.1 billion)
(2050)
MM1
$0
$0
n/a
n/a
n/a
n/a
n/a
n/a
no peak:
n/a
n/a
n/a
08/26/97
8_26runl.wk4
2066
(2025)
MM2
$148
$192
n/a
n/a
n/a
n/a
n/a
n/a
1586
2010
n/a
n/a
08/26/97
8_26runl.wk4
(2005)
MM3
$136
$146
n/a
n/a
n/a
n/a
n/a
n/a
1600
n/a
n/a
n/a
08/26/97
8_26runl.wk4
(2005)
MM4
$0
$198
n/a
n/a
n/a
n/a
n/a
n/a
1749
2020
n/a
n/a
08/26/97
8_26runl.wk4
(2010)
MM5
$0
$99
n/a
n/a
n/a
n/a
n/a
n/a
1767
2040*
n/a
n/a
08/26/97
8_26runl.wk4
(2015)
c.maccracken @ pnl.gov
10/13/97 01:47:00 PM
Record Type:
Record
To:
joseph e. aldy
CC:
Subject: SGM Results
Joe -
I assume you're not at work today ...
I finished the $50 Safety Valve runs that you requested on Friday. I
have a disk waiting at the front desk to be picked up by your courier.
I will be out Tuesday and Wednesday at the Technology Strategy Workshop
(that I think Jeff Frankel and Adele Morris are attending on Tuesday).
If, for some reason, there is a problem with the data on the disk or if
you have any questions, give Ron Sands a call at 646-7791. He has
copies of the results. Or you can leave me a voice mail message and
I'll get back to you.
The runs on the disk are:
sv5s.xls
$10 tax on Annex I in 2005, $30 in 2010, $50 in
2015 and hold at $50 thereafter (Non-Annex I BAU)
sv6s.xls
$10 tax on Annex I in 2005, $30 in 2010, $50 in
2015 and grow at same rate thereafter (Non-Annex I BAU)
sv7s.xls
$10 tax on Annex Lin 2005. ramp to $50 in 2020,
and hold at $50 thereafter (Non-Annex I BAU)
sv8s.xls
$10 tax on Annex I in 2005. ramp to $50 in 2020,
and grow at same rate thereafter (Non-Annex I BAU)
Enjoy!
Chris