ENERGY LABORATORY
INFORMATION CENTER
I
THE FEA PROJECT INDEPENDENCE REPORT:
REVIEW AND EVALUATION
AN ANALYTICAL
by
MIT Energy Laboratory
Policy Study Group
May 1975
.
This Report was prepared under sponsorship from the Office of
Energy Research and Development Policy, National Science
Foundation, under contract NSF C-1030.
PARTICIPANTS
The following members of the Policy Study Group of the MIT Energy Laboratory
participated in the preparation of this report.
Morris A. Adelman, Professor of Economics
Sidney S. Alexander, Professor of Economics and Management
Martin L. Baughman, Research Associate in Electrical Engineering
Richard A. Charpie, Research Assistant in Physics
Robert E. Hall, Associate Professor of Economics
Ogden H. Hammond III, Lecturer in Chemical Engineering
Jerry A. Hausman, Assistant Professor of Economics
William J. Jones, Research Associate, Energy Laboratory
Paul L. Joskow, Assistant Professor of Economics
Henry D. Jacoby, Professor of Management
Paul W. MacAvoy,
Professor
of Management
David C. White, Ford Professor of Engineering and Director
of the Energy Laboratory
David 0. Wood, Director, Energy Management and Economics Program
of the Energy Laboratory
Martin B. Zimmerman, Research Associate in Management
i
ACKNOWLEDGMENTS
We wish to express our appreciation to William Hogan, James Sweeney,
David Nissen, John Kraft, and other members of the FEA Office of Policy
and Analysis for their efforts in facilitating our review of the Project
Independence Report. We have not always agreed on every point, but there
is no doubt that our report is much the better for their willing cooperation.
ii
OUTLINE
Page
1.
2.
LIST OF FIGURES
vi
LIST OF TABLES
vii
SUMMARY
viii
OVERVIEW OF THE PROJECT INDEPENDENCE REPORT
1-1
1.1
Policy Strategies Studied
1-1
1.2
Project Independence Evaluation System
1-5
Data
1-5
1.2.1
Input Models and Associated
1.2.2
The PIES Integrating Model
1-7
1.2.3
Interpretive Models
1-9
DOMESTIC SUPPLY ESTIMATES
2-1
2.1
2-1
2.1
2.3
2.4
Crude Oil
FEA Forecasting
2.1.2
Alternative Forecasts:
Evaluation
Natural
2-1
Method
2.1.1
Comparison and
2-7
2-8
Gas
2.2.1
FEA Forecasting Method
2.2.2
Alternative Forecasts:
Evaluation
2-8
Comparison and
Coal
2-9
2-10
2.3.1
FEA Forecasting Method
2.3.2
Alternative Forecasts:
Evaluation
2-10
Comparison and
2-14
Electricity Supply
2-15
2.4.1
Supply Forecasts
2-15
2.4.2
Alternative Forecasts:
Evaluation
.iii
Comparison and
2-17
Page
2.4.3
3.
3-1
3.1
3-1
3.3
5.
2-19
DEMAND ESTIMATES AND INTERACTION WITH THE INTEGRATING MODEL
3.2
4.
Financing Expansion
Methodology
of the FEA Demand
Simulation
Model
3.1.1
Description
3.1.2
Inputs To the Integrating Model
3-3
3.1.3
The Use of Regional Demand Functions Within
the Integrating Model
3-5
Evaluation
of the Model
of the FEA Methodology
3-1
3-7
3.2.1
Estimation Problems
3-7
3.2.2
Effect on the Overall Demand Estimate
3-11
Summary Evaluation
3-14
CONSERVATION
4-1
4.1
FEA Conservation
Initiatives
4-1
4.2
FEA's Intended Methodology
4-3
4.3
The Actual FEA Calculations and Evaluation of Results
4-4
ECONOMIC IMPACT OF EVENTS AND POLICIES
5-1
5.1
Impact
5-1
5.2
Long-Run Implications of High Energy Prices and of
Alternative Energy Policies
of the Oil Embargo
5-5
6.
ENVIRONMENTAL
ASSESSMENT
6-1
7.
INTERNATIONAL
ASSESSMENT
7-1
7.1
FEA Estimates of World Oil Supply, Demand, and Price
7-1
7.2
Forces Influencing the Future Path of World Oil Prices
7-3
7.2.1
Net Demand Faced by the Cartel
7-4
7.2.2
Strength
7-7
7.2.3
Conclusions
of the Cartel
7-12
iv
Page
8.
9.
LINKS TO THE PERIOD BEYOND 1985
8-1
8.1
The Period Until 1985
8-1
8.2
The Post-1985 Period
8-4
SUMMARY AND CONCLUSIONS
9-1
BIBLIOGRAPHY
v
LIST OF FIGURES
Page
1.1
Blueprint of the Project Independence Evaluation System
1-6
(PIES)
1.2
Schematic
2.1
Cause-Effect Relationship in Actual Markets
2-5
2.2
Procedure for Evaluating Individual Drilling Projects
2-5
2.3
Regional Cost Function for Coal
2-11
2.4
Structure
3.1
A Sample Regional Natural Gas Demand Functions for 1985,
Using the National Elasticity
3-6
3.2
Regional Demand Functions in 1985 Under Two Price
Trajectories
3-8
4.1
FEA Demand Curves For a Given Product With and Without
a Given Conservation Initiative
4-5
Representation
of the PIES
of the FEA Electric
Power
vi
Integrating
Model
Model
1-8
2-16
LIST OF TABLES
Page
1.1
Assumptions Underlying Basic FEA Strategies
2.1
Exploratory Footage
to 1988 In District
1-3
2-2
Stipulated For the Years 1974
3 Under BAU, and Estimated
Drilling Under Alternative Prices
2.2
Electricity Supply & Fuel Requirements:
A Comparison
of the FEA $11.00 BAU Case With Two Forecasts
MIT Model for 1985
and $15.00
Crude
2-18
From
Scenarios
3-4
3.1
Prices for $7.00, $11.00
3.2
Long Run Elasticities of Demand for Fuels, $11 Scenario
5.1
Changes
5.2
Comparison
6.1
1985 Pollution
7.1
FEA and OECD Estimates of Demand, Indigenous Supply, and
Resulting Imports for Non-OPEC Oil in 1985 at $3, $6,
and $9 per Barrel
7-2
7.2
Reserves, Production, and Capacity for Key Exporters
7-9
8.1
Typical
8.2
Effect of Rate of Return
Eastern U. S.
in Price and Consumption
the Embargo
Period
5-2
DRI Forecasts
5-4
for Two FEA Cases
6-3
of Alternative
Loadings
Over
3-10
Costs of Synthetic
8-2
Fuels
on Cost of Fuel
vii
($/mmBTU),
8-3
SUMMARY
The Project Independence studies carried out by the FEA during the past
year are an important step in the nation's attempt to understand our emerging energy problems and to formulate policies to deal with them. The principal object of this review is the Project Independence Evaluation System
(PIES) which
is the overall
analytical
apparatus
developed
by the FEA to
support their studies.
The system consists of three groups of interrelated models and associated data. The centerpiece of the system is a large linear programming model
which is used to estimate domestic energy consumption, production, prices,
and imports for different regions of the country. This integrating model
uses as inputs estimates from models of domestic demand and production of oil
and gas. Other important inputs include price-sensitive estimates of coal
production, estimates of the availability of other fuels (solar, geothermal,
hydropower, nuclear), information on transportation costs between regions,
and estimates of the associated requirements for equipment, labor, capital,
and water. Submodels of the electric utility and refining sectors are
included in the integrating model itself.
Once the integrating model has been solved for a given year, the results
may be further analyzed to obtain information on macroeconomic and environmental effects; and on resource and financing requirements for the calculated energy production schedule.
The FEA uses the PIES apparatus to evaluate four broad policy strategies that the U.S. might adopt for the next ten years:
(1)
A "Business as Usual" strategy, which assumes the removal of
oil price controls in 1975, and phased deregulation of natural
gas prices.
(2)
An Accelerated Development strategy, involving removal of obstacles
to the development of offshore gas and oil, synthetic fuels, and
nuclear power.
(3)
A Conservation strategy, involving specific conservation initiatives--such as 20 mile-per-gallon auto standards and improved
heating and lighting standards for new homes--and "demand
management" measures which entail increasing electricity usage,
with supply from coal-fired electric power.
(4)
A Demand Management initiative to force the substitution of coal
and electricity
for oil.
Each of the scenarios is analyzed for the years 1977, 1980, and 1985.
The basic external condition that influences the analysis is, of course, the
price of world oil. The FEA study assumes that the world price will converge on some value in the near future, the precise level of that price being
unknown. The comparisons are done under the assumption of world prices of
viii
$7.00 and $11.00
(in 1973 prices)
delivered
to U.S. shores.
The key results of the overall analysis are:
settles at $11.00 in 1973 prices (which is roughly
if the world price
$13 to $14 per barrel
in
today's prices), then by 1985 under "Business as Usual" we will be importing
3.3 million barrels per day (about half of today's level). If the world
price drops to $7.00 per barrel in 1973 prices (or roughly $8 to $9 in
1975 prices), then by 1985 our imports will be up to 12.3 million barrels
day.
per
With conservation or accelerated development measures, these imports
can be reduced
by various
amounts.
Overview of the FEA study
Now since this report is a critical review and evaluation, it does
by its very nature tend to focus on specific points of weakness in the material being reviewed.
It is well
to start,
therefore,
by putting
this work
in context and commenting on the overall effort as a whole. Several points
are worth mentioning. First, at the time the study began, there was no
coherent data base for analysis of the many facets of the U.S. energy sector, its relation to the economy, and the federal and state policies that
influence energy supply and utilization. No doubt PIES is only a step in
the process of creating a data base adequate for federal analysis and monitoring of national
policy;
but it is a critical
step.
Moreover,
a set of
analytical models has been formulated for utilizing these data to forecast
future energy conditions. Heretofore there were scattered modeling efforts,
but nowhere within the government had it all been put together into a coordinated framework for analysis.
No doubt there are differences of opinion about the overall design of
the PIES system (and below we level strong criticism at specific parts of its
current structure). But the fact remains that the various pieces have been
brought into a coherent system which can provide a framework for managing
data, coordinating judgements, and forcing consistency in assumptions.
Having said that, we must look at the work as it stands and evaluate
it from three points of view:
(1)
Did the FEA study illuminate the most important questions, and
did it adopt the proper set of assumptions and conditions to be
analyzed?
(2)
Was the analytical apparatus adequate to the-task?
(3)
Are the correct implications drawn from the analysis?
As one might anticipate,
the reviews
are mixed,
and there
is no clear
answer to the effect "yes, they did it right", or "no, they did it wrong."
None the less, an attempt to answer these questions gives a feel for how
wide a band of error should be put around the FEA estimates, in what directions the possible bias may lie, and where more work must be done in order
to do better in the future. Our list of the most important points to worry
about is the following:
ix
The Oil and Gas Supply Estimates
The supply estimates for domestic oil and natural gas are based on a
modified version of a model developed originally by the National Petroleum
Council. Under this procedure, oil and gas supplies are calculated by assuming the amount
of drilling
that
is profitable
in each of 12 regions
in each
year, multiplying this by stipulated rates of reserves-added per foot drilled
to get total reserves, and then assuming that reserves are produced at a certain rate. At higher oil or gas prices more drilling becomes profitable, and
production rises. It is a method that is almost totally dependent on the
judgement of the analyst feeding in drilling and discovery rates to the
computer program.
There are systematic problems with this analysis. The method has
been applied in a way that appears to underestimate the likely response of
oil and natural gas supplies to price changes. This occurs because, under
the FEA procedure, an increase in price in 1975 brings about increased
drilling only after 1980 or even later. This belies the activity we see
taking place in the domestic petroleum industry today. In particular, the
method seriously underestimates the likely level of exploratory activity for
natural
gas by basing
the expected
drilling
rates on the experience
of the
early 1970's, when gas drilling was dampened by the effects of field-price
regulation.
Taking these considerations into account, one can argue in the case of
oil that the responsiveness of investment to price is underestimated in the
model. On the other hand, it is not clear whether adequate weight was given
to certain opposing influences--in particular, the declining responsiveness
of supply to investment because discovery will continue its decline, and
because improved recovery out of a given amount of oil in place will come
at sharply higher real costs. On balance, then, there is little solid ground
for arguing that the estimates are high or low overall. An MIT model forecasts supplies
very similar
to the FEA results
at $7.00, and other estimates
are scattered above and below it. But the uncertainty is great, and we would
not use the FEA forecasts for policy analysis without considering that the
estimates of, say 11.9 million barrels per day in 1985 at $7.00 per barrel,
can easily
be off by 1.5 million
barrels
either way.
In natural
gas, on the
other hand, the FEA analysis seems unduly pessimistic. Here the error band
is also wide, but would extend from somewhere in the neighborhood of the
FEA estimate
(11.9 million
barrels
per day (oil equivalent)
in 1985 at
$7.00 per barrel) to two or three million barrels per day above this level.
Perhaps as important as the potential errors and biases in the FEA
estimating method is the fact that the most important issue of the day, the
effect of price controls on the supply of these fuels, was not satisfactorily
analyzed. We have argued that the analysis tends to understate the importance of higher prices even in the $7 to $11 range. We also believe that
continued price controls on oil and field-price regulations of natural gas
would have a significant dampening effect on the domestic supplies of these
fuels. Unfortunately, the fact that the study contains practically no analysis at all of the potential significance of price controls, coupled with
supply estimates that show very little response to price, gives the erroneous
impression that price deregulation is not an important issue influencing
x
future U.S. energy sufficiency. We do not believe the FEA intends to convey
this impression, but it is there nonetheless, given the structure of the
analysis, the particular assumptions made, and the scenarios chosen for
detailed analysis.
The Electric Power Sector
One of the very good features
of the PIES
integrating
model
is the way
it handles the electric power sector. The analysis is sound, given its
assumptions. Unfortunately, the assumptions tested in the FEA analysis fail
to illuminate the most critical problems of this sector and one of the key
determinants of its future growth, i.e., the financial health of the investorowned utilities. It is now apparent that without substantial rate increases
allowed by the state regulatory commissions, it is unlikely that they will
be able to raise sufficient capital to expand their systems to the levels
implied in the FEA analysis, or with the technology mix assumed (i.e.,
heavy investments in capital-intensive coal and nuclear units). These
financial difficulties, if they continue, will lead to reduced levels of
system reliability and will reduce the desirability of electricity to consumers. This will curtail demands for this form of energy (and thus call
into question the "demand management" strategy presented in the Project
Independence Report), but may also raise demands for other fuels, most
notably imported oil.
Of course, the FEA report discusses this problem; but it does not analyze
its quantitative significance. The lack of analysis of this issue--its
implications, and what it might be worth to avoid its occurrence--is an
important
shortcoming
in the FEA's
study as it stands.
The Demand Analysis and its Interaction within the Integrating Model
In estimating the future demands for energy in the U.S., the FEA used
a three-step form of analysis whereby (1) aggregate national energy demand
was estimated given a forecast of the average energy price, (2) this overall
BTU demand was split up amount fuels using a separate estimating model, and
(3) national demands for specific fuels were divided amoung regions according to their historical proportions.
When applied
to the data for U.S. energy--clouded
as it is with
regu-
latory interventions and rapid growth in the network of natural gas pipelines--this procedure did not yield results that were consistent with what
one would expect to be the behavior of this sector under alternative prices.
For example, the analysis showed natural gas demand falling in certain
use sectors when prices of distillate oil rose. Since these two fuels are
close substitutes for one another, one would expect the opposite result.
Attempts were made to correct the deficiency (and this effort continues
at the present time), but even given these efforts, the interaction of the
flawed demand model with the integrating framework leads to an identifiable
bias in the results.
xi
In essence, the problem is that, since natural gas demand is assumed
not to rise as oil prices rise, then the price of natural gas is never
driven to levels that are consistent with the high price of the substitute
In effect, the price of natural gas stays at a level appropriate to
fuels.
a world with $7.00 oil even when the price of oil from the world market
This means,
(which determines the domestic price) is assumed to be 11.00.
in turn, that the price of an average BTU in 1985 with $11.00 oil is under-
stated, and the overall demand is thus overestimated.
When these problems
are corrected, we expect the FEA will find that oil demand as estimated
in the November report is biased upward, both due to the upward bias in
overall energy demand, and due to the inaccurate representation of how much
of this total demand will show up as a demand for natural gas.
Another problem that tends to an underestimate of the dampening effect
of higher
oil prices
is the fact that the FEA was unable to take account
of the fact that overall GNP growth will be affected in some measure by
No doubt this is not a phenomenon that anyone has
higher oil prices.
but the fact that it does exist should be kept
modeled very satisfactorily,
in mind when applying the appropriate error range around the FEA's forecast.
The International Assessment
It appears
that
the FEA devoted
the great
bulk of its resources
to the
domestic aspects of the energy problem, and applied only a small fraction
to the international
phenomena
that are the immediate
cause of current
difficulties and the driving force behind their evolution.
sis is based on a set of judgemental
estimates
of oil demand
The FEA analyin the world
and oil supply from non-OPEC countries, which yields a residual demand for
This net demand is then compared with the potenthe exports of the cartel.
tial supply from cartel nations (which is very great, and at a cost far
below current prices) in order to get an idea of how big a problem the car-
tel may have in avoiding a flooding of the market with oil, and consequent
erosion of price. The analysis assumes that the world price will gravitate
to one level or another; it may stay near $11.00 per barrel (in 1973 prices),
These longor more likely it will settle to a price around $7.00 a barrel.
term price scenarios then provide the link between the international assessment and the domestic evaluation discussed above.
this vision of a smooth evolution of prices to some
Unfortunately,
In fact, there are
of reality.
stable value is a serious oversimplification
forces at work in this market which make it more likely that the price will
fluctuate
over time.
For example,
as prices rise there are factors
that
tend to reduce supply and drive prices still higher. Oil-rich exporters
find their revenue needs are easy to satisfy under rising prices, and they
can more easily afford to cut production. Outside the cartel, in those
nations where oil exploitation is in private hands, rising prices present
serious equity problems due to the excess profits that accrue to private
corporations.
Governments
of these countries
are led to impose
tax schemes
which have the side effect of reducing the incentive to expand oil supply.
(Our own struggle
in the U.S. with this issue
xii
is all too evident;
the problem
is duplicated in Canada, in the nations surrounding the North Sea oilfields,
To the extent these phenomena lead to reduced supply, it
and elsewhere.)
becomes easier to maintain high prices, or further increase them.
On the other hand, it is likely that prices eventually will turn down
from current
levels,
for in time high prices
lead to reduced
demand,
to
gradually increasing supplies from outside the oil cartel, and thus to a
sagging demand from the cartel members. Once price begins to erode--perhaps
due to a buildup of excess capacity and an attempt by some cartel members
to compete for a larger share of a depressed market--forces are set in
motion which tend to drive the price down further. Oil-rich countries will
have built up domestic spending programs and high imports under high prices,
and if prices
fall these governments
will
be under strong
pressure
to
increase oil production to pay the bills. Further price shading will be
required to move larger quantities of oil, and so the process feeds on
itself. Naturally, if the cartel should break, and prices fall considerably, immediate efforts would be made to reconstitute the cartel and raise
prices again. There is no inherent reason why, over a short-run period, they
should not once again be successful.
If in fact it is true that this market
and the cartel
structure
that
dominates it are likely to prove unstable, then the world oil price could,
over the period to 1985, fluctuate over a range significantly wider than
the $7 to $11 range used by the FEA as a basic assumption of their work,
and at the very least the price is unlikely to gravitate to a level which
is in fact stable, and which people believe is stable.
In these circumstances there is no reason to expect that a reduction
or increase in import demand by any one country will have any effect on the
world price. This is a persistent notion: one of the major conclusions
in the Executive Summary of the PIR is that our actions to achieve selfsufficiency could have an apprecia-bleeffect in bringing the world price down
to $7 per barrel.
But there
is no analysis
in the FEA Report
to support
this assertion, and we believe it is mistaken.
Conclusions
Considering the state of the data and available models when work began
and the short time available,
the FEA's
Project
Independence
study
is an
impressive accomplishment. It seems clear that the government needs the
in-house capability to do this kind of analysis, and that these efforts should
be continued and improved.
In viewing the results of the work as of today, however, several points
are worth keeping in mind.
(1)
There is considerable uncertainty in the estimates of domestic
supply and demand; net imports, being the residual, is subject to
even greater uncertainty. However, given the assumptions behind
the analysis, the FEA estimates of U.S. import dependence in 1985
xiii
appear to be biased upward. At $11.00 per barrel oil prices,
the U.S. is more likely to be self-sufficient in energy than
the FEA indicates; at lower oil prices, imports are likely to
be smaller than forecast by the current PIES apparatus.
(2)
Due to various shortcomings and difficulties in the PIES analysis, it appears that the likely responsiveness of the U.S. energy
sector to price increases has been underestimated. Problems in
the demand analysis, when corrected, are likely to show a stronger
adjustment to price change, and the particular method used to
estimate oil and natural gas supply tends to underestimate the
effect of price on domestic fuel supply.
(3)
The likely underestimate of supply responsiveness, coupled with
the fact that the analysis does not deal with the effects of
price controls on demand and supply, means that the Report as
it now stands gives an inadequate appreciation of the stakes that
are involved in current policy discussions about price control or
decontrol.
(4)
In the set of PIES results presented in the Project Independence
Report, it is assumed there are no problems of capital availability
that impede desired investments in the energy sector. There are
several points where this assumption might be questioned (and
where, indeed, the FEA study worries about it), but nowhere is it
more limiting than in the case of the electric power sector,
where some of our gravest energy problems arise. The study does
not indicate the degree to which a faltering of investment in
electric power may reduce the use of domestic coal and nuclear
energy and increase dependence on foreign oil.
(5)
The report focuses on policies to deal with an external world
where there may be a threat of short-term market disruption (for
example, through boycott) and a foreign exchange drain if prices
are high, but where the price is reasonably stable and where
investors and consumers have a stable expectation of what it will
be in the future. This means the report as it stands does not
provide the analysis to aid decisions on policy issues--such as
tariffs, import quotas, subsidies and guarantees for synthetic
fuels, etc,--that are required in a world of fluctuating uncertain
oil prices.
xiv
1.
OVERVIEW
In November,
OF THE
PROJECT
1974, the Federal
INDEPENDENCE
REPORT
Energy Administration
completed
its
Project Independence Report, a multi-volume document which presents the
results of a six-month study of the U.S. energy economy. The core of the
FEA effort is a set of engineering process models, econometric models,
and a mathematical programming model, which together have been named the
Project Independence Evaluation System, or "PIES". The purpose of PIES is
to provide an integrated, comprehensive system for evaluating current and
projected energy conditions, and to assess the impact upon these projected
conditions of alternative policy initiatives. The system is intended to
be sensitive to changes in energy prices and to incorporate recent information on projected costs and technologies for energy production and use.
In the sections to follow, PIES and the data used to support it are
subjected to critical review and evaluation. Since it is the nature of a
critique to focus on specific points of weakness in the material being
reviewed,
it is well
to start
by putting
the FEA work
in context
and by
commenting on the overall effort. Several points are worth mention. First,
at the time the study began, there was no coherent data base for analysis
of the many facets of the U.S. energy sector, its relation to the economy
as a whole, and the federal and state policies that influence energy development. Scattered data series existed, many collected by federal agencies;
but for coordinated analysis such as that called for in the Project
Independence study a massive data collection and processing effort had to
be carried out. No doubt it is only a step in the process of creating a
data base adequate for federal analysis of policy in this sector; but it
is an important step. Moreover, a set of analytical models has been formulated for analyzing these data. Heretofore there had been scattered
modeling efforts, both in and out of the government. Indeed, given the
time constraints, much of the PIES system had to be a patching-together of
analytical models drawn from other sources. But nowhere within the government
had it all been put together
into a coordinated
framework.
So although there are differences of opinion about the overall design
of the PIES system (and below we level strong criticism at specific parts
of its current structure) the fact remains that the various pieces have
been drawn together into a coherent system which can provide a framework
for managing data, coordinating judgements, and forcing consistency in
the various assumptions that must be made in any analysis of a system as
complex and interdependent as the energy sector.
1.1
Policy Strategies Studied
The PIES system has been used by FEA to assess four broad strategies
for developing a national energy policy. The assessments, for the years
1977, 1980, and 1985, include:
1-1
1-2
(1)
A "Business-As-Usual"
(BAU) scenario,
in which
the U.S. economy
is projected to adjust to a given price for foreign crude oil
and petroleum products, and assuming only those changes from
current policy which are "certain" to occur. The assumed policies include deregulation of natural gas and crude oil prices.
(2)
An Accelerated Development case (AD) in which the process of
adjustment to a higher foreign crude price is modified by new policies designed to remove technological and institutional barriers
to increased domestic energy production (shift the supply
curve).
(3)
Introduction of energy conservation initiatives designed to
reduce the demand for particular fuels, given a particular set of
fuel prices (shift the demand curves).
(4)
Demand management initiatives designed to force the substitution
of coal
and electricity
for petroleum
(shifts
in both demand
and
supply curves).
The basic assumptions underlying each of these strategies are summarized
in Table 1.1.1 While it is not our purpose to evaluate the strategies
chosen by FEA, it is worthwhile to point out two assumptions underlying the
strategies which severely limit the ability of the FEA analysis to cover
the full spectrum of possible energy futures. First, the assumption of
deregulation of natural gas and crude oil prices in the BAU case means that
FEA has provided no analysis of the implications of continuing the current
policy of controlling prices in this area. In fact, there is strong disagreement as to whether this policy should be changed, particulary considering its income distribution implications.
Secondly, there is an assumption underlying all of the strategies that
the world price of oil will approach smoothly some given real price. Though
it is convenient for analytical purposes, this view may be very misleading.
In Section 7 we consider the implications of this assumption in more detail.
For the present we note that there is a good chance that the world oil price
will not gravitate to some stable value but may oscillate over time in
response to world economic conditions and the fortunes of the oil cartel.
In omitting
this possibility,
the FEA analysis
misses
the opportunity
to
illuminate some of the policy questions of the day, e.g., guarantees against
down-side price risk in order to spur domestic supply.
1
For each strategy an independent assessment is performed assuming
imported crude oil prices of $7.00 and $11.00 (1973 dollars), except in the
case of the demand management strategy. For that strategy the business-asusual assessment is modified via application of assumptions about the extent
of substitution which could be "forced", within technological constraints,
by institutional changes.
1-3
Table 1.1.
Oil
2.
Natural
Gas
Accelerated Development
Assumption
Business-as-Usual
Assumption
Energy
Source
1.
Assumptions Underlying Basic FEA Strategies
Moderatg OCS leasing program
(1-3xlO acres/yr); Prudhoe
Bay development with one
pipeline.
Phased deregulation of
new gas; LNG facilities
in
Alaska.
Same Federal coal land leasing; phased implementation
of Clean Air Act with stack
gas controls; moderate strip
mining legislation.
No licensing changes; added
enrichment and reprocessing
capability.
3.
Coal
4.
Nuclear
5.
Synthetic
No change from current policy.
6.
Shale
No change from current policy.
7.
Geo-
Continued
thermal
leasing programs.
Solar
Continued R & D program.
8.
R & D and Federal
Accelerated OCS leasing in
Atlantic, Pacific, Gulf; expanded Alaskan pipelines and development of NPR #1 and NPR #4.
Deregulation of new gas; addiitional Alaskan pipeline; gas
from tight formations.
Same as BAU with additional
leasing and larger new mines.
Increase of nuclear capacity
15% by 1985 due to streamlined
licensing and siting; additional
uranium availability.
Streamlined siting; financial
incentives.
Additional
leasing; modification
of Colorado air quality stan-.
dards; financial incentives.
Streamlined leasing, licensing,
and regulatory; financial incentives.
Additional R & D and financial
incentives.
Other Assumptions:
9.
10.
11.
Price controls removed by 1975.
Tax laws (depletion allowance) unchanged.
Imported Canadian gas available at $1.20/mcf.
12.
LNG available
at $2.00/mcf.
Same as BAU.
Same as BAU.
Same as BAU.
Same as BAU.
Equipment allocation to achieve
critical levels needed for oil/
gas drilling.
1-4
Table 1.1 (continued)
Demand Management
Assumption
Conservation Initiatives
Assumption
Reduce demand via --
Reduce petroleum demand by --
1.
Mandate 20 MPG auto standards.
1.
2.
Gasoline taxes.
3.
Financial incentives for R&C retrofit.
4.
National thermal standards for
new homes.
5.
National commercial lighting
standards.
6.
Appliance efficiency standards.
Converting growth in industrial
demand
oil/gas
R & D for efficiency
Convert existing utilities to coal.
3.
Make
all new R&C heating,
electric
heating.
No significant
changes
portation sector.
in industrial
processes.
8.
ov-
2.
4.
7.
to coal by
ernment intervention.
Demonstration of efficiency measures
at electric utilities.
I
in trans-
1-5
1.2
Project Independence Evaluation System
The Project Independence Evaluation System (PIES) is organized into
three groups of models. As illustrated in Figure 1.1, the system includes
input models and associated data, a linear programming model which includes
submodels of refinery operations and electric utility generation, and models
to facilitate interpretation of the results produced by the LP model.
1.2.1
Input Models and Associated Data
There are four basic input models to PIES including a macroeconomic
model, an industrial production model, an annual demand model, and a supply
model for oil and gas production. Associated input data include estimates
of coal production at alternative prices, and a major data base of resource
input requirements per unit of activity output.
The macroeconomic
model
used by FEA is the Data Resources,
Inc.
(DRI)
Long Term Growth Model [3]. The outputs from the model used as inputs to
the Demand and Industrial Production Models include macroeconomic and
demographic variables such as the level and distribution of real GNP, the
rates of inflation and unemployment, population, real personal income, and
housing starts.1 The DRI Industrial Production Model [4], using estimates
of the level and distribution of real output from the macroeconomic model,
is used to estimate the Federal Reserve Board Industrial Production indices.
The FEA Demand Simulation Model is a dynamic econometric model which
is used to forecast demands for 47 primary and derived energy products conditional upon assumed energy prices, industrial activity levels, the level and
distribution of real output, and certain technology data relating to energy
consumption. The model distinguishes among fuel and power demands in each
of three major consuming sectors (residential and commercial, industrial,
and transportation) and industrial raw material uses.
In PIES the demand
model
is used to forecast
annual
quantities
demanded,
by census region, and national demand elasticities for the 47 products and
nine prices in the model. The structure of the model and the procedures
by which the model is used in the Project Independence Evaluation System are
reviewed and evaluated in Section 3 of this report.
The Oil and Gas Supply
Model
is an adaptation
of a process
model developed by the National Petroleum Council (NPC).
engineering
The model
1
For a listing of all variables see PIR [8, Table AII-8]. A listing
of all variables used by the Demand Model from the DRI Macroeconomic and
Industrial Production Models, as well as the variable classification for the
Demand Model
itself,
is also given
in the PIR [8, Appendix
II].
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estimates additions to reserves and production levels for 12 supply regions,
given assumptions about crude oil prices, regional drilling programs,
required rate of return on investment, the expected success ratio per foot
drilled, and the projected reserve/production ratio. The structure of the
model and the results presented in PIR are reviewed and evaluated in Section
2 of this report.
While no formal model was developed by FEA to project
coal production levels, a set of production estimates for three different
minemouth prices was developed by a task force of experts. These estimates
and the underlying
methodology
are reviewed
and evaluated
in Section
2 as
well.
The final set of input data in the PIES are resource requirements for
each of the energy production and conversion technologies. The data were
developed for materials and equipment, other capital inputs, labor, water,
and transportation,
as indicated
in Figure 1.1.
Originally the resource requirements data were to be incorporated into
the PIES, together with data on resource availabilities, in order to analyze the possible effect of resource restrictions upon the energy production and consumption process. However, in the results reported in the PIR
these restrictions have not been imposed. Rather, the data have been used
to calculate the resource requirement levels associated with a given production/consumption schedule, and this is followed by a separate analysis of
resource availability to determine if effective resource constraints exist.
Resource requirements data were developed only for energy supply technologies. For an analysis of the implications of excluding resource requirements from the evaluation of conservation technologies, see Section 4 of
this report.
1.2.2
The PIES Integrating Model
The heart of the PIES is the integrating model, a linear programming
(LP) model which, given estimates of regional demands, prices and elasticities, regional supply schedules, and resource input requirements, calculates an energy market equilibrium. The outputs from the model are listed
in Figure 1.1. A schematic representation of the logic of the model is
presented in Figure 1.2. The relation between the demand model and the LP
submodel which incorporates the supply schedules and conversion processes
may be summarized
as follows:
the demand
model
is used to calculate
a
price-quantity coordinate on the demand curve for each of the primary and
derived energy products in the system. Associated with each of these coordinates are measures
of the sensitivity
of the quantities
demanded
to small
changes in each of the prices in the demand model (own and cross price elasticities).
In the first iteration of the integrating model an LP problem is solved
in which the minimum cost schedule of production, distribution, and transportation necessary to satisfy the given demand levels is calculated. Associated with the calculated supply quantities are implicit prices. If these
supply prices differ from the original demand prices, then the solution does
1 -8
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1-9
not represent market equilibrium and a new problem must be structured and
solved. The procedure is to calculate new demand prices, equal to one-half
the difference between the last iteration's supply price and demand price,
apply the own and cross price elasticities to calculate the new demand
quantities,and finally to solve a new LP problem for the new production,
distribution, transportation schedules, and supply prices. This process is
continued until the demand and supply prices are equal, at which point the
energy market is assumed to be in equilibrium. Section 3 or this report
provides a detailed critique of this part of the PIES system.
1.2.3
Interpretive Models
The output from the integrating model is used as input to a number of
submodels which provide interpretation and analysis of results. The first
is a combined interindustry and macroeconomic model, different from the
macroeconomic model used to provide inputs to the demand model, which is
used to reintegrate the energy market with the capital, labor, and financial
markets. However, as is discussed in Section 3 of this report, the adjusted estimates
of the levels and distribution
of real output
are not used to
adjust the initial solution for energy markets.
An environmental assessment model is used to calculate the levels of
pollutants and environmental wastes associated with the energy production
schedules.
The model
is characterized
by an array
of order
15 by 15, indi-
cating the pollutant and waste production levels for each of 15 pollutants
and waste categories per unit of output for each of 15 energy production
technologies. The methodology and results are reviewed and evaluated in
Section 6 of this report.
Although not characterized by a formal model, an important application
of the output results is in the analysis of potential limitations imposed
by the availability of resources. In the PIR independent estimates of the
supplies of the various resources are compared with the requirements calculated from the output of the integrating model. The projection of potential resource supplies to the energy sector is based upon extrapolation
of historical trends in total resource availabilities and shares to the
energy sector, conditioned by examination of the macroeconomic environment
and independent expert judgement.
A final model in the PIES is the International Assessment.
pose of this model is to provide a framework in which the world
The purdemand for
and supply of energy may be analyzed in relation to U.S. domestic energy
conditions. The model draws heavily upon the framework and data developed
for the recent OECD Study [37]. Section 7 of this report reviews and
evaluates the PIR international assessment.
2.
DOMESTIC SUPPLY ESTIMATES
As noted in the previous section, the supply side of the integrating
framework is made up of separate estimates of the likely availability of
domestic
crude oil, natural
gas, and coal by 1985 under a range
of assumptions
about the price of imported oil and other conditions external to the domestic
fuel sector. Each of the supply estimations was supported by a separate
task force study, each of which had its own data collection effort and procedures for modeling and forecasting. In this section we review these efforts,
evaluate the methods used, and indicate the confidence to be placed in the
resulting estimates of supply.
The key energy processing activities--most importantly electric power
production--are part of the internal workings of the integrating model, and
the details of that procedure also are reviewed below.
2.1
Crude Oil
2.1.1
FEA Forecasting Method
The PIR forecasts 11.9 million barrels per day of oil production from
domestic sources at $7 per barrel, and 15.0 million barrels per day at $11
per barrel
in 1985.
This analysis
is based
on an approach
developed
by the
National Petroleum Council (NPC) whereby a computer routine is used to project recent experience. The computer program takes (a) estimates of drilling
in each of 12 regions; (b) estimates of discovery of reserves per foot drilled
in those regions; (c) estimates of drilling costs and (d) a stipulated discount rate 6]. These estimates are used to calculate the present value of
net cash flow for each region separately each year at $7 per barrel.
If the present value at $7 is positive, then all of the stipulated
drilling and discovery for one year takes place in that region. Discoveries
are added up across regions to give total reserves and, given stipulated
production-reserve ratios for each region, total production. Then the same
calculations are made for $11 per barrel. More regions show positive net
present cash flows for a year's drilling at the higher price, so that total
production is forecast to be 3.1 million barrels per day greater at the $11
price than at the $7 price.
The actual pattern of computations across regions and years is formalized
within the computer program. The details of the method can be illustrated
using data for exploratory footage drilled in District 3 from 1974 to 1988
under the BAU case. These data are shown in Table 2.1. Under the FEA method,
the footage shown for a year is either drilled that year if net present value
(npv) is positive, or no footage is drilled, if npv is zero or negative. For
example, 1470 thousand feet are drilled in 1974 if npv is positive or none
is drilled if npv is negative in the calculations. Similarly, 2380 thousand
2-1
2-2
Table 2.1.
Exploratory
Footage Stipulated
For the Years
1974 to 1988 In District 3 Under BAU, and
Estimated Drilling Under Alternative Prices
(a)
Stipulated
Footage
Exploratory
Year
Footage
(Thousands)
1974
1975
1976
1977
1470
1523
1581
1601
1978
1544
1979
1980
1981
1660
1634
1757
1982
1983
1984
1985
1986
1987
1988
1839
1967
2105
2380
2523
2842
2998
TOTAL
(b)
Subtotal
7,719
16,546
29,424
29,424
Drilling Response to Price
Footage
Dri 11 ed
Price
$7
(Thousands)
0
$8
$9
7,719
16,576
$10
29,424
2-3
feet are drilled in 1985, or none at all, depending on whether npv is positive
or not. As the assumed price increases, npv in some years and regions changes from negative to positive, so that footage drilled goes from zero to
stipulated levels, reserves increase, and finally production increases.
The way in which the computer program adds to supply is highly artificial, however. Because drilling costs are assumed to be higher in later
years, the npv of a year's drilling in a region is greater in the early
years. Because of this, the computer code calculates an npv which is positive in early years and negative in later years for low prices in some
regions. For example, npv is positive at a price of $8 per barrel for 1974
to 1978 in Region 3, but negative after 1978; drilling occurs at 1470,
1523, 1581, 1601, 1544, a total of 7719, for the first
five years,
and is
zero thereafter. Additions to supply from price increases thus are assumed
to occur through drilling in later years only. When price increases throughout the period, more drilling occurs and production is added after 1978 because drilling in later years increases from zero to stipulated levels.
For example,
as price in 1974
increases
from $8 to $9 per barrel,
total
drilling in District 3 increases from 7719 to 16,546; but this is entirely
the result of drilling increasing from zero to the stipulated levels only
in the years
1979 to 1983 [10, Exhibit
III-16].
A price
increase
from $9
to $10 has only the effect of increasing drilling in the years 1984 to
1988, from zero to the levels shown in the series above. In fact, the
Oil Task Force Report [10, Exhibit III-16] shows that Region 3 neatly increases
its drilling in five-year packages as prices increase by one dollar. All
the regions do the first few years' drilling when there are increases in
present prices.
This computer routine might make sense for a field, when a full drilling pattern for one year has been laid out, and the only issue is whether
the price level warrants secondary recovery later on. But as a regional
pattern it involves shortcuts in execution that abstract from reality in
several important ways. The conceptually correct "supply function" for oil
at the regional level is replaced with an incorrect "average cost" function.
Important parts of the decision-making process are assumed away--in particular,
feedbacks from net present value to drilling assumptions are left out.
Working with "regions" rather than "wells" for present value calculations
results in aggregation or "summing up" errors. In fact the whole process
in practice is an artifact for what are actually a series of drilling judgements that need no computer modeling assistance; the process is one of "assumptions in" produces "assumptions out" without the benefit of a model's logic
as a deciphering or integrative device. We deal with these problems here
by considering in detail the implications of FEA treatment of drilling
sequences, drilling costs, and uncertainty.
Drilling Sequences
The FEA procedure takes as given a target value for exploratory footage
to be drilled in a region for a given year. The expected success ratio per
foot drilled is also specified. These data, together with crude prices,
2-4
drilling costs, production (equal to a fixed proportion of reserves) and a
discount rate of 10% are used in calculating the net present value (npv)
for the target level of drilling. The decision to actually drill in that
year depends upon whether npv is positive or negative. With npv >0, all
the target footage is drilled. If npv <0 no footage is drilled.
As noted above, the FEA procedure imposes a very unusual restriction
upon the time distribution of exploratory activity. A permar. nt increase in
price from $9 to $10 in 1974 results in increased exploratory activity of
12,848,000 feet in Region 3 all during the period 1984-1988. Thus, ten
years must elapse before the 1974 price increase has an impact upon exploratory activity, and therefore production levels, since the relation between
production and reserves is assumed to be independent of price.
A second difficulty with the FEA procedure involves the relationship
between the geographical level of aggregation and the decision agent used
in the model. The problem may be interpreted by means of Figures 2.1 and
2.2. Figure 2.1 depicts relationships for actual market behavior in the
exploration for reserves. Crude prices and drilling costs determine the
distribution of drilling activities between the intensive (development drilling in old fields) and extensive (drilling in new fields) margins, thereby
determining both the number of wells drilled and the average success ratio
for the region. In turn these variables determine the additions to reserves
from exploratory activity.
Now, firms engaged in exploratory activities may be viewed as ordering
potential drilling projects using the npv calculation described above.
Figure 2.2 depicts the appropriate calculation for evaluating an individual
drilling project. Price of crude, drilling costs, the expected success
ratio and size of find for the project are used in calcuating the npv. The
project will be initiated if npv >0. For the individual drilling project,
Figures 2.1 and 2.2 are consistent. The difficulty arises when the logic
of Figure 2.2 is applied in evaluating an aggregate of the potential drilling prospects
in a region.
There is no way to analyze the appropriateness of stipulated regional
drilling schedules and success ratios since they are not logically derived
from an analysis of the decision process by individual drilling projects as
initiated. In any region there will be many combinations of individual
projects, some with npv >0, which would produce a regional npv <0. Yet in
these cases the FEA procedure will set the drilling activity equal to zero,
thereby contributing to an underestimate of additions to reserves and subsequent production.
Costs
All costs are included in the FEA calculations--except lease rentals.
Given that the drilling in a region is zero or the stipulated level, then
the comparison is between costs at zero and costs at one level of drilling
only in that region. Thus the cost calculation in the routine is average
non-rental costs and price in present value terms. But in competitive
2-5
FIGURE
FIGURE
2.1
2. 2
CAUSE-EFFECT
MARKETS
RELATIONSHIP
IN ACTUAL
PROCEDURE FOR EVALUATING INDIVIDUAL
DRILLING PROJECT
2-6
markets, price will equal marginal expected cost (or the supply curve is
the marginal expected cost curve). The FEA procedure, when taken to the point
where the last region comes in that year with npv slightly greater than
zero, implies
at any price,
that the FEA cost curve
implying greater supply
lies below the marginal cost curve
This FEA curve
at the same price.
is appropriate if "all-or-nothing" choices are being made for all of the
region's drilling, as when the government permits or prohibits all drilling.
curve for analyzing the impact of price changes
But it is not the appropriate
in the onshore regions of the lower 48
at
least
on reserve accumulation,
It results in point estimates of discoveries that are too high at
states.
low prices since there is no intensive drilling beyond the assumed levels
that
"come in" at the lower prices.
But at the same time, the FEA cost calculation shows too little supply
As forecast prices rise, it should be expected that drillat high prices.
ing will increase on the "extensive" margin (in new areas) or the "intensive"
The FEA procedure accounts
margin (in smaller known fields in old areas).
for some increases in these categories, but not in the expected way.
The procedure holds back later years' drilling so that it will occur
only at higher prices. For example, none of the stipulated exploratory
footage is drilled in Region 2 at $7 per barrel, but 12.7 million feet are
drilled at $11 per barrel and 9.6 million feet more are drilled in that
The
region at prices ranging from $12 to $20 per barrel [10, p. III-23].
the
for
drilling
increases occur by taking as given the total lifetime
region, but only completing the last few years' drilling at the assumed rate
at $11 per barrel.
Given these patterns of drilling, there is a significant downward bias
in estimates of the elasticity of production response to price increases.
With very few districts showing any variation from "zero" to "full" drilling, the supply
curve is a series
of discontinuous
steps.
The production
increases at higher prices only occur in later years, so that any price
change in 1975 is assumed by the process to result in drilling
This is mitigated
later, and production some time after that.
ten years
by secondary
and tertiary recovery, which occurs only on another schedule. Since these
are very uncertain, compared to primary recovery, however, they have to be
greatly discounted as the crucial marginal supplies at higher prices. The
elasticities are products of assumptions built into the computer program,
and are not indicative of real-world processes.
Treatment of Uncertainty
Drilling
is affected
not only by the expected
returns
from a well
at
some location but also by expected risk--as measured, say, by forecast
variance
of the returns.
Some locations
are more risky
for drilling
than
others, because they have not been gone over by geophysical research groups
as thoroughly, or because of other factors such as the trap or dome structure,
and interstital fluid movement. No attempt is made in the analysis to
2-7
differentiate regional drilling based on relative riskiness.1
In addition, the FEA computer program assumes that there is no difference between the economics of drilling exploratory wells and production or
development wells. Exploratory drilling activity is undertaken when the
expected value of returns is higher than the expected cost after discounting
returns for significant risk in exploration. The drilling of development
wells involves less risk, and takes place depending on whether it is profitable now to remove oil from the reserve base or to wait and produce it later.
If price goes up, even with little exploratory drilling, production can rise
due to developmental
drilling
in old regions.
This source of supply
in a
five-year period is ignored by the model, even though it is critical for
dealing with problems of supply interruptions in the period 1975-1985.
2.1.2
Alternative Forecasts:
Comparison and Evaluation
There is considerable variation in forecasts of production at $7 per
barrel.
While FEA forecasts
that production
in 1980 will
be 11.1 million
barrels per day, the MIT econometric model forecasts production at 10.6
million barrels [33]. The Lawrence Laboratory Report (done on an NPCderived computer program as well) shows production at 12.5 million, while
the Davidson study shows production at 15.4 million barrels per day [32;5].
Both the high and low forecasts are useful in establishing the range, since
they are based on economic models and historical data (with a minimum of
"stated" values
of critical
parameters).
But the high forecast
is based
on very little research effort, and has to be discounted. Altogether, the
forecasts suggest tentatively that the FEA forecasts at $7 per barrel may
be from half a million barrels high to 1.5 million barrels low.
There are very few forecasts based on prices over the $7 to $11 range.
The forecasts that are available are all judgemental in nature. The time
period of 5 years or more is too long for accurate forecasts to be developed
on the basis of judgement alone. The lack of previous experience over this
range of price changes makes econometric modeling very problematical as
well.
Forecasts from one other important source--the companies carrying on
the drilling--differ widely. This difference, of course, "makes markets"
for exploration and development in this country. But in a recent survey of
a half-dozen sources of information and analysis of exploration within the
industry, we found that there was a tendency to be more pessimistic than FEA
on future supplies. The judgemental forecasters doubted that gains from
lIt has been suggested that risk discounts have been "built into" the
analysis by scaling down the stipulated recovery factors in more risky areas.
If so, only the risk-free discount rate should be used in npv calculations-rates lower than the 10% actually
used.
2-8
secondary recovery, and from exploring new areas in OCS, would be as great
as forecast
by the FEA.
Their concensus
was that the FEA forecast was on
the high side, in contrast to the consensus from computer and econometric
analyses.
Thus
the "error band"
on the low side of the FEA would
be as
large as on that on the high side.
Our-rough judgement is that the error of forecast of the FEA prediction
at either
$7 or $11 per barrel
is more than +1.5 million
barrels
per day in
1985. The forecast process used by FEA understates the elasticity of supply
response to price, but given stipulated drilling it overstates quantity at
low prices. Of course the stipulated drilling may be too high or too low;
judgements on that vary as well, although the "mean judgement" seems to
suggest no FEA bias there. The values of parameters are so arbitrary that,
according to the Oil Task Force Report itself [10] the "range of reasonable
assumptions
could affect
the quantities
predicted
by 1985 by 10 to 40 per-
cent." Altogether, we would not use the FEA forecasts for policy analysis
without considering, as an important part of the analysis, quantities plus
or minus 1.5 million barrels per day.
2.2
Natural Gas
2.2.1
FEA Forecasting Method
The FEA model predicts, with stipulated drilling and discovery rates,
that production of natural gas in the United States will decline slightly
over the next few years, over the entire range of forecast prices [11]. The
computer program generating these predictions is the same as that for crude
oil. But, in contrast with the crude oil forecasts, the stipulated values
of certain important parameters are exceedingly low compared to recent
experience. Model estimates of recoverability of gas are much lower than
of oil production from forecast reserves. Also, drilling is assumed to
increase at 5.75 percent annually and exploration in offshore areas is
assumed to be limited.
These restrictive conditions produce, as "assumption in, assumption
out", estimates of little supply responsiveness to price. Once the range
of 60 cents to 70 cents per thousand cubic feet--now being experienced under
regulation--forecast lower-48 production is between 15.9 and 17.2 trillion
cubic feet in 1985. At (deregulated) prices from 60 cents to $1.10, production increases from 17.2 to 17.4 trillion cubic feet. Because of the
assumed constraints on drilling, the production of natural gas from nonassociated reservoirs increases only by one percent while assumed prices
increase by 60 percent. In effect, drilling assumptions imply an inelastic
supply of natural gas with respect to oil and gas prices.
The FEA computer exercise is a classic example of using a complicated
program to assume certain results. Drilling rates are assumed to increase
at 5 percent per year, as in the earlier NPC study, even though they actually
have been increasing at four times this rate in the last few years. Recent
high drilling rates have been assumed away by the FEA Gas Task Force. At
the same time the Task Force assumes that very recent increases in drilling
2-9
costs hold over the next ten years. The FEA in effect assumes the worst-that FPC price controls, which had frozen drilling for more than a decade,
do make much difference in drilling when removed, but that costs of drilling
stay at present high levels (levels caused in part by the increased drilling ignored
2.2.2
in the FEA analysis).
Alternative Forecasts:
Comparison and Evaluation
The FEA forecast can be compared with those of the econometric gas
and oil model built at MIT for the National Science Foundation (NSF
Grant GI-34936) [33], and with earlier forecasts of the National Petroleum
Council [35]. On the basis of millions of barrels per day oil-equivalent,
the FEA forecasts domestic supply at 9.6 million barrels per day. The
MIT econometric model forecasts supplies of 14.7 million barrels per day
in 1980. The earlier NPC forecasts, under similar conditions, were for
11.5 million barrels. All forecasts assume prices close to $1.00 per thousand
cubic feet for new discoveries in the early 1980's, while oil prices are at
or below $7 per barrel.
It is clear that the FEA is on the low side of
these estimates, by amounts of great significance--the equivalent of 2 to
5 million barrels of oil per day.
The FEA computer program should be useful for indicating effects on the
supplies of gas as oil prices increase over the $7 to $11 range. But the
FEA studies do not show how much more gas would be delivered as oil prices
increase. It is apparent from the MIT model that demands for natural gas
are substantially increased (by 3 trillion cubic feet per annum) as oil
prices rise over this range, so that it can be expected that gas prices
would rise in response to the increased demand. But the FEA model cannot
now be used to track the size and magnitude of the response.
However, it is clear that the FEA model as constructed predicts no
response in gas supplies from changes in either gas or oil prices. This
is contrary to most judgemental forecasts, and even to common sense. The
FEA forecasts too little gas, because constraints on drilling have been
placed without regard to the more recent growing attractiveness of gas discovery projects (due to partial deregulation and higher interstate prices).
The FEA forecast is lower not only than the MIT forecast, but from 1 million
to 2 million barrels per day lower than other widely-known forecasts (the
Ford Energy Policy Project forecasts range from 10.4 to 10.9 million barrels per day [6] and the Lawrence Livermore Laboratory Report shows 11.9
million barrels per day [32]). This range of forecasts is wider than in the
case of oil, and the FEA forecast of gas is below that of others, while in
oil it is in the middle
of those surveyed.
The choice of a higher forecast for gas is critical for the evaluation
of the effects of various policies to "close the gap" between domestic energy
supplies and demands. If the MIT forecast is to be believed, there are the
equivalent of 5 million barrels per day of production over and above those
forecast
in the FEA analysis.
2-10
If a judgemental estimate is used rather than the MIT estimate, the
weight of the forecasts still indicates that gas supply will be above the
FEA forecast. In short, the FEA forecasts are based upon unrealistic conservatism in discovery activity. At the least, the error band for the FEA
forecasts lies from zero to 3 million barrels per day above the forecasts.
2.3
Coal
The major finding of the PIR analysis is an elastic supply curve for
coal. Output is forecast to expand greatly with no pressure on price. The
projections call for constant real prices of coal throughout the 1975-1990
period. The result is puzzling in light of the representational supply
curves depicted in the Task Force Report [9, p. 27]. These curves slope
upward, indicating that higher rates of output are obtainable only at
higher prices. The answer to this puzzle lies in the method by which the
curves are constructed.
2.3.1
FEA Forecasting Method
The Coal Task Force begins by asking what output will be produced in
each region in each period. This assumed output is called the "production
target". The output is then allocated to the different types of mines. A
certain amount is produced by existing strip and deep mines, and the difference is made up by new surface and underground mines.
The Task Force uses engineering cost estimates to determine the minimum
acceptable selling price. Costs are calculated for deep mines producing 1
to 3 million tons per year exploiting coal seams of 4 feet and 6 feet with
conventional or continuous mining techniques, and using either drift,
slope, or shaft entries to the coal. Similarly, surface mine costs are calculated for various ratios of overburden to seam thickness.
The assumed breakdown of output according to mine type, together with
these cost estimates, determines the steps of the regional supply curve,
as shown
in Figure
2.3.
For example,
in Region
3 in 1985,
new strip mines
are assumed to open and produce 100 million tons at a cost of about $9 per
ton. Similarly, it is assumed that deep mines open at a cost of $11 per
ton and produce
50 million
tons.
The important question is what in the model determines the amount of
coal that can be produced by each type of mine. Several possibilities exist.
The length of each step could be determined by reserve constraints. That
is, the lower-cost strip reserves are exhausted first and then further
increments come from deep mines. This is not the case, however. In each
period it is assumed that there are high-cost new underground mines opened
together with new lower-cost strip mines, indicating that the high cost
reserves are brought into production before the low cost reserves are
2-11
S/T 0 N
NEW DEEP MINES
IIII
NEW STRIP MINES
r~~~~~~~~~~I
OLD DEEP MIN ES
OLD
STRIP MINES
OUTPUT
FIGURE 2.3
REGIONAL
COST FUNCTION FOR COAL
2-12
exhausted.1 A second explanation is that short-run constraints cause costs
to rise when output of new mines expands to a certain point. This would
mean there is a short-run supply function as well as a long-run function.
However, the model posits no short-run supply function, and at several
points the Task Force comments that equipment, etc., is assumed to be available.
In fact, in the model
the mix of mines,
and thus the steps,
reflects
an extrapolation of past production trends tempered by judgement about new
developments [9, p. 20]. The key point in the construction of the supply
curves is that deep mines (except in the West) must always be opened to
satisfy demand, and thus the price of coal is always the cost of production
from a new deep mine.
The assumed costs of new deep mines differ slightly among supply
regions. This difference reflects the judgement of the coal task group as
to whether the costs of mining are above or below the national average.
This cost difference between regions remains constant throughout the projection period. The cost depends upon the seam thickness mined. In each
case, the choice of the "incremental" mine was based on judgements about
the characteristics of the mines in the supply region. The result was a
mine somewhere between 48 and 72 inches in thickness, and producing something between 1 and 3 million tons per year.
Having determined that at the margin new deep mines determine the cost
of coal, the FEA then must determine how these costs will behave as output
expands. Two important assumptions are made that affect the forecasts: no
substantial depletion of marginal supplies in the next few years, and constant real factor prices. These assumptions lead to the condition of perfectly elastic supply over the 15-year period; the marginal mines are never
depleted, and never realize higher costs.2
Negligible Depletion
In support of this assumption, the PIR cites reserves of 433.9 trillion
tons
in seams greater
than 28 inches
in tiTckness
at a depth of less than
1000 feet. However, these figures include a great deal of coal not economic
at today's prices. The costs of mining, all other things equal, are inversely
related to seam thickness. Currently, few high-sulfur deep mines are opened
in seams of less than 48 inches thickness. The average is closer to 60
inches for high-sulfur steam coal. More recently available data indicate
1
The Task Force is aware of the anomaly. They offer an explanation
based on transport cost differentials and quality differentials favoring
deep mines. While this is likely to be true in specific instances, these
factors do not systematically favor deep reserves.
2
We
cedure.
and deep
be small
should not push a too literal interpretation of the Task Force proA reasonable interpretation of all this is that both strip reserves
reserves will experience depletion, but the overall effect will
or negligible.
2-13
large amounts of coal in seams of 42 inches or above, though the distribution of reserves in the 48 to 72 inch range is not known. Since the mines
used in the PIR are somewhere
between
48 and 72 inches in seam thickness,
depending on te area, there remains the possibility that depletion could
be significant in certain regions, and that mining of something closer to
42 inch coal may be implied.
Constant Real Factor Prices
Underlying the estimates is the assumption that real wages and productivity are constant. Wages constitute about 35% of coal costs and have been
rising rapidly. The Task Force Report even points out that wages will have
to increase to expand the amount of labor supplied [9, p. 17]. Furthermore, the United Mine Workers can be expected to raise wages as oil prices
increase, making any output level more expensive.
The second area in which rising energy prices will have direct impact
on coal costs is in the transport
sector.
On average,
rail tariffs
account
for 40% of delivered price. Railroads are in a position to increase tariffs
as oil prices increase, since utilities are willing to pay more for delivered
coal. Research at MIT indicates that railroads in the past have charged
relatively higher rates to utilities less favorably situated with regard to
alternative fuels [38]. As these alternatives increase in cost, rates can
be expected to rise. The ICC has jurisdiction over these rates, although
it rarely exercises its authority. In fact, the past performance of this
commission suggests that higher coal rates might be encouraged as a means
of subsidizing less profitable railroad services.
Below we discuss the implications of these factors for alternative
forecasts.
Other Factors Serving to Increase Costs
The question of sulfur in coal was dealt with by assuming that stackgas scrubbing devices are used. This adds to the capital and operating
cost of the electric plant, but allows the use of all coal. There are real
problems: at present, the reliability and usefulness of these devices is
subject to great controversy. Even if this controversy were resolved and
the devices proved, the capacity to produce them in sufficient quantities
by 1980 is surely limited. Consequently, the supply of coal must also consider the supply of low-sulfur coal. At present, low-sulfur deep mines
producing steam coal are being opened in seams 36 inches thick and the
average is about 48 inches. This implies costs much higher than those for
high-sulfur coal. Furthermore, substantial reliance on low-sulfur coal would
force the exploitation of yet thinner seams leading to significant depletion.
A second important policy issue is the question of strip mining.
this model, the effect of a complete banning of strip mining would be
In
2-14
negligible everywhere except in the West where almost all coal is produced
by stripping. This occurs because of the assumption of perfectly elastic
deep reserves. In fact, stripping in the East is superfluous in this model.
The only reason strip coal is produced is that a certain number of strip
mines is assumed to open in each region in each year. If no strip mines
were to open, the price of coal would be unaffected in the long run. The
price is set by the incremental deep mine which is always available at
constant costs.
2.3.2
Alternative Forecasts:
Comparison and Evaluation
In the case of high-sulfur coal, due to its elastic supply the most
meaningful comparison is not what output would be forthcoming at FEA projected prices, but rather what are alternative price estimates for the projected output rates. Rather than compare specific engineering calculations,
we compared forecasts on the basis of the behavior of prices as output
expands over time.
The range in alternative forecasts is due basically to differing assumptions about the behavior of input prices. The National Petroleum Council
projected constant prices as output expanded from 1975 to 1980, at output
levels similar to the FEA [35]. This result, though, depends on productivity increasing to its pre-1969 rate. The FEA forecast assumes no productivity increase in the incremental mine. Thus, using the FEA productivity
assumption in conjunction with the NPC assumption implies a 14% increase in
price above the FEA forecast.
A much wider range is projected by R.L. Gordon [27]. Assuming real
wages maintain their historical trend and productivity increases are moderate, Gordon estimates that prices could increase by as much as 48.5% by
1980. He suggests only the most favorable developments could lead to an
increase as low as 14%. Neither Gordon nor the NPC include transport rate
increase in their estimates. Even a moderate increase of 12% in coal
transport
rates by 1980 would
We conclude
lead to a 4% increase
that the FEA underestimates
in delivered
prices.
prices by at least 18%.
The
upper end of the range is based on very unfavorable developments, so a most
likely estimate of the bias would be in the neighborhood of 25-30%. However,
based upon the general agreement that the aggregate coal supply function is
highly elastic, this significant underestimate of price does not seriously
affect
the supply
of coal.
The major
gap in the model
is the inability
to
deal with the effects of environmental legislation. The key policy questions
in coal supply relate to the effects of strip mining regulation and limitations on the permissible sulfur content of coal. Changes in these regulations
will significantly affect the price of coal in the period under consideration.
2-15
2.4
Electricity Supply
The role of electricity in attaining energy independence is critical.
This is because this form of heating, cooking and illumination can be
provided from the use of coal and nuclear fuels, rather than imported oil,
at roughly comparable (if not lower) costs to the economy.
Thus, higher
growth rates in the consumption of electricity directly reduce the need
for imports.
2.4.1
Supply Forecasts
Forecasts of electricity supply presented in the PIR follow from an FEA
model which is essentially a constrained cost minimizing model. The model
seeks to meet a particular demand or "load requirement" with the least cost
combination of existing and incremental plant capacity. Fuel prices to the
electric utility sector and demands for electricity are exogenous to this
model.
The capital
costs of alternative
types
of generating
equipment,
sys-
tem load factors,1 and annual carrying charge rate 2 and the maximum amount
of nuclear capacity that can be added in any one year are also exogenous
to the model.
Finally, the proportions of new capacity that will be added
to meet incremental load (plus retirements in each supply category--base,
intermediate, and peak) are also specified exogenously. Given the fuel
costs, capital costs and the heat rates associated with each type of plant,
peak, intermediate, and base load requirements are met with the minimum cost
combination of plants. These conditions are illustrated in Figure 2.4.
There are a number of difficulties that arise with the model as presented.
It does not seem to be strictly
appropriate
to specify
exogenously
the capacity factors of peak, intermediate and base load equipment.
given fuel prices,
heat rates, maintenance
costs, etc.,
it would
Rather,
be prefer-
able to construct a merit order of plants economically according to the
actual load. We realize that the FEA has chosen their approach for simplicity, but additional modeling of economic dispatch would increase the realism by making
these "factors"
part of the system equilibrium
(as it now is
in regional and systems center dispatch).
In a similar vein, the exogenous specifications of proportions of new
capacity that will be added as base, intermediate, and peaking capacity is
not consistent with actual planning. Capacity decisions are a result of
forecasts of least cost combinations, so that there are "feedback" loops
as indicated
by the dotted
lines.
Both the types
of plant
and the proportions
lIn addition, the capacity factors at which peak, intermediate, and base
load plant will be run are taken as given.
2
They use 20 percent, which is quite high--17 percent is probably more
reasonable after taking account of various tax benefits even at today's
high interest
rates.
2-16
POSITED CONDITIONS
MODEL OUTPUT
MINIMUM
COST
PLANT CAPACITY MIX
I
]
.~~~~~~~
ro
I
FIGURE
l
I
I
I
-
2.4
STRUCTURE OF THE
FEA
ELECTRIC
POWER MODEL
2-17
of various types of plant capacity that are added are derived endogenously
as an outcome
of long run cost minimization.
It is difficult to tell exactly how sensitive the results of the
stimulation are to these simplifications. We do feel, however, that efforts
could be directed towards having plant utilization and capacity expansion
decisions determined within the model as they should be in a consistent cost
minimizing framework.
There would appear to be at least one unsatisfactory forecast from the
model resulting from these simplifications. In the $11 BAU case, electricity
demand grows at 5.6 percent per year, while capacity grows at 6.3 percent
per year. Exactly why the FEA model behaves in this way is not clear since
no special assumptions regarding load factors, reserve margins, or heat
rates are specified.
But it seems that much too much coal capacity is being
built and run at too low a usage factor--too much to be consistent with
true long run cost minimization. We suspect that this result emerges because
of the modeling simplifications that are discussed above. While the total
coal consumption
figures
approximately 85,000 MW
predicted
by the model
appear
to be accurate,
too much actual coal capacity has been predicted
by the model for 1985. eThis amounts to about $30 billion in excess capital
requirements in 1973 dollars.
In referring to this problem [8, p. 421] FEA
indicates that this difference in growth rates is due to ". . . different
interpretations of historical figures for distributed electricity and the
assignment of transmission losses." Apparently transmission losses were
accounted for differently in the demand model and integrating model. The
effect of this has been to overstate the investment requirements for plants
using the marginal
2.4.2
fuel type,
coal.
Alternative Forecasts:
The MIT electricity
model
Comparison & Evaluation
[1] is conceptually
similar
to the FEA model
except that the simplifications noted above have been avoided as dispatching and expansion decisions are endogenous to the cost minimization routine.
We present two simulations to compare with the FEA results. The first has
fuel cost and capital cost inputs similar to those of the FEA $11 BAU case.
The second is identical to the first except that the costs of coal and oil
burning capacity have been increased to reflect additional outlay for air
pollution control equipment. We call the first the MIT Base Case and the
second the MIT High Air Quality Case. These results are presented for comparison purposes and to examine the sensitivity of the supply results to
small changes in two important variables. The simulations are reported in
Table 2.2.
There are several differences in forecasts worth noting in Table 2.2.
First,
the total electricity
demand
predicted
by the MIT model
is over 10
percent lower for the Base Case and 15 percent lower in the High Air Quality
case than that predicted by the FEA model and nuclear energy consumption
slightly higher. Nuclear energy consumption is slightly higher even though
nuclear capacity is lower in the Base Case because the nuclear plants run
at slightly higher capacity factors in the MIT model. Since electricity
2-18
A Comarison
Electricity Supply & Fuel Requirements:
-.,ompais
. .:
of the FEA $11.00 BAU Case With Two Forecasts From
--
Table 2.2.
for 1985
MIT Model
FEA $11 BAU
Total Capacity
MIT $11-Base
MIT $11-High
Air Quality
922
820
809
456
387
361
327
216
156
Gas
48
67
67
Oil
81
104
137
Peaking
162
151
147
Hydro
100
89
89
Nuclear
204
193
212
3615
3225
3096
1.64
1.16
.87
.55
.42
.46
1.25
1.30
1.43
(KW x 106)
Fossil
Total
Coal
Generation
(KWH x 109)
Fuel Consumgtion
(BTU x l101 )
Coal
Oil
& Gas
Nuclear
(Fossil
equivalent)
2-19
prices are higher in the High Air Quality Case, both electricity demand
and fossil fuel consumption
are lower
than in the Base Case.
Thus,
fossil
fuel consumption by the electric utility industry is very sensitive to the
price sensitivity of electricity demand and the prices expected for electricity.
A comparison of the base cases with the MIT High Air Quality Case is
also of interest. Considerably less coal burning capacity is built, more
oil burning capacity built and both oil and gas burning capacity are used
more intensively in the High Air Quality Case. Since the costs of coal
burning capacity required to meet air pollution requirements were not dealt
with
in detail
in the PIR, this gives
some feeling
for the magnitude
of
the effects on electricity supply decisions of higher air pollution control
costs than are assumed
in the FEA analysis.
These
conditions
may well be
more realistic over the coming decade.
Another uncertainty involves the reliability of nuclear power plants.
Current planning decisions assume that nuclear plant capacity factors will
increase above average historical rates. If capacity factors should fall
far below the anticipated 70 percent level, additional capacity would be
required to meet any level of load. More work should be done on forecasting utilization for those new plants, before any capacity expansion forecasts
are taken seriously.
In summary,
the FEA model
gives
reasonable
results,
but is subject
to
a number of conceptual difficulties. Those appear to lead to over-building
of coal burning capacity and may lead to other difficulties that are not
completely obvious. More important, results of sensitivity experiments of
the FEA electricity supply model to examine the effects of the likely
uncertainties have not yet been reported. We have used the MIT model to
give some feeling for how large the effects might be from small changes in
costs of capacity and in the demand for electricity. The effects are certainly
not trivial
for the 1985 period and are likely to be considerably
magnified in years subsequent to 1985, as lead time constraints become
unimportant and capacity existing in 1974 becomes a smaller proportion
of the total capability. As a result, we would encourage more analysis and
considerable extension of the FEA supply model.
2.4.3
Financing Expansion
The major problem for the electric power industry is finding the
financing to build the minimum cost mix of generating facilities. The Project Independence Report is concerned with the possibility that there may
be financial
problems,
but does not deal in any analytical
way with
the
nature and extent of these problems. But it is now apparent that without
substantial rate increases allowed by the state regulatory commissions, so
as to increase the earnings and cash flow of the electric utilities, it is
unlikely that they will be able to raise sufficient capital to expand their
systems to levels necessary to both meet "minimum cost requirements" and
maintain current levels of system reliability at forecast demands.
2-20
There have been a number of recent studies indicating that this is a
likely set of conditions for the late 1970's-early 1980's. A detailed
review by the Electric Power Financing Sub-Committee of the Federal Power
Commission's National Power Survey shows that a continuation of present
circumstances, without rates of return being increased more than two
percentage points, is impossible [26]. Other studies show that, given
recent cancellations and construction delays, nuclear capacity additions
could fall short of the FEA projections by as much as 30,000 megawatts-more than 15 percent of capacity needs by 1985. Most observers believe
that these nuclear cancellations will be made up in part, mostly by gas
turbines
and overaged
fossil
fuel plants,
so that fossil
fuel demand
will
have to increase beyond the amounts shown in the PIR. The fossil fuel
demand increase could be as much as 1 million barreTs of oil per day
equivalent--a large part of which would have to come from additional imports.
Therefore there is a "feedback" from financial problems largely ignored in
the PIR to the forecasts of the exogenous factors in the electric power
suppTy-system.
Alternatively, plants being deferred or cancelled may not be replaced
at all. A study by Professors Joskow and MacAvoy at MIT shows in preliminary reviews that application of financial analysis to the twelve largest
electric power companies finds most of them with negative earnings per
share and a lack of ability to float any kind of securities in national
capital markets by 1980 [31]. The largest companies in the Midwest and
South will probably not be able to obtain the capital needed for any capacity expansion in 1980 at either the current allowed rate of returns or
rates or return of 12 or 13 percent on equity after taxes. Extending this
study to more large companies would seem to indicate that the country as a
whole may be short as much as 25 percent of forecast capacity additions
in the early 1980's. This will lead to reduced levels of system reliability
and an increasing number of voltage reductions and load curtailments. All
of these reduce the desirability of electricity to consumers and would
greatly curtail demands for this form of energy.
3.
DEMAND ESTIMATES AND INTERACTION WITH THE INTEGRATING MODEL
As described
in Section
1, the FEA Demand Simulation
Model
is used
to
compute the regional demand estimates and national price elasticities which
are inputs to the integrating model. Each solution of the linear program is
based on a particular set of regional demands for various fuels which in turn
is based on certain assumed energy prices. Subsequent solutions of the
overall integrating framework are performed until the system has attained
"equilibrium"
in the sense that the prices
implicit
in the demand
figures
for a particular solution are consistent with the implicit supply prices
of domestic energy sources.
Hence the structure
of the demand model
(as summarized
in the elasti-
city measures) and the detailed mechanisms of the procedure by which the
system iterates to an equilibrium solution are as important to the process
of estimating energy production and consumption levels as the supply functions discussed in Section 2.
3.1
Methodology of the FEA Demand Simulation Model1
3.1.1
Description
of the Model
The model developed by the FEA involves first estimating energy demands
at the national level, conditional upon macroeconomic and demographic variables, energy prices, and technology variables, and then disaggregating to
the Census region level of detail. Fuel and Power demands are estimated
for three major consuming sectors: household and commercial, industrial,
and transportation. Industrial demands for fossil fuels for use as raw
materials are estimated separately 2
The transportation demand equations are based upon differing specifications depending upon the particular fuel. For example, gasoline demand
per capita is a function of gasoline price and income per capita. Demands
for liquified gases and residual fuel oil are functions of prices, but jet
fuel demands are independent of price, depending only upon assumptions
about route miles and load factors.
1
The FEA Demand Simulation Model is described in PIR [8, Appendix II].
Footnote 1 of that index indicates that two technical reports will be published describing the model, including reports by Data Resources, Inc.,
and FEA, but as yet these reports have not been released.
2
Raw material demands are assumed to be a function of industrial
activity levels, lagged consumption levels, and time. Prices are not
included in these equations.
3-1
3-2
The demand equations for the household and commercial and the industrial
sectors employ a common specification. The FEA procedure involves a threestep process:
(1)
Total energy demand. The total demand for energy is estimated
from aggregate time-series data, using an energy price index
(calculated with actual energy shares and prices year to year)
and other variables representing economic and industrial
activity.
(2)
The demand for fossil fuels. The demand for electricity is estimated as a function of its price and other variables. The difference between total fuel and power demand estimated in Step 1
and the demand for electricity is the economy's direct demand
for fossil fuels. The demand for fossil fuels in electrical
generation is taken into account in the electrical generation
sub-model of the integrating framework LP.
(3)
Fossil fuel shares.
fossil
fuel demand
After electricity has been subtracted off,
is divided
into its component
shares.
For
example, in the household and commercial sector six share equations
are used to estimate the shares of seven fuels: anthracite
coal, bituminous
coal,
natural
gas, liquified
gas, kerosene,
resi-
dual fuel, and distillate fuel. The last share, for distillate
fuel, follows from the adding up criterion that fuel shares must
sum to unity. To estimate the shares, a derived demand framework
is used with an econometric specification similar to a conditional
logit probability model. Each energy share is estimated conditional
on its own characteristics
(price)
and the characteristics
of the base fuel, distillate. The prices of other competing
fuels do not directly enter the equation.1
The results of the three-step process are estimates of total national
energy demand, national electricity demand, and national energy demand for
the principal fossil fuels, coal, natural gas, and petroleum
These national estimates are disaggregated down to the level
demand functions at a later point for use in the integrating
1
This econometric
specification
imposes
very strong
products.
of regional
model.
assumptions
on the
structure of underlying demands. For instance, the specification imposes
the restriction that all cross price elasticities with respect to a given
price change are identical. Therefore, the cross-elasticity of anthracite
coal and natural
gas with
respect
to residual
are assumed
to be the same.
An improvement in the demand equations would be to include other prices
beside only the own price and base fuel price in the specifications. Then
the cross-elasticities would not be constrained to have identical values.
3-3
3.1.2
Inputs to the
Integrating
Model
The national (aggregate) demand system forecasts national demands
and own price and cross price elasticities
in each of the three
sectors.
The procedure used is to specify an exogenously given path of energy prices
over the period 1974-1985. National demand forecasts and elasticities
are estimated for each year on the price path. Forecasts of demands and
elasticities are made on the regional level from these national forecasts,
and those forecasts provide the basic demand input data to the integrating
model which solves the system to find an equilibrium. The procedure used
to estimate
the regional
demand
curves
is as follows.
National Demand Forecast.
A set of prices for different energy sources for the period 1973 to 1985
is specified, based on a terminal (1985) price of crude oil (either $7,
$11, or $15 per barrel). The sets of prices used in the PIR analysis are
shown in Table 3.1. The prices in the table for oil products, residual
fuel, distillate, and gasoline are determined from the crude oil price
and by a constant markup assumption. The natural gas and coal prices are
set at values exogenously determined by the analyst. The time path of prices for oil products and electricity between 1973 and the assumed price in
1985 is based on an exponential trajectory, with 90 percent of the 1973
to 1985 price change achieved by 1977, as shown in Table 3.1.
These vectors of energy prices are then used to compute price indices
akin to the ones used in the original
model
estimation.
The shares
of
energy demand do not change over the 1973-1985 period in constructing this
index; 1972 weights are used throughout. Total energy demand for each
year is then estimated from Step 1 of the national demand system using the
total energy demand equations for each sector with values of the independent variables being the composite energy price index and indices of economic
activity, such as disposable income exogenously forecast by a macroeconomic
model. Individual energy product demands are then computed using Step 2
to estimate electricity demand and Step 3 to estimate individual fossil
fuel shares, with the 1973-1985 prices for the separate energy products
being input as independent variables.
Demand Elasticities
Each own and cross price elasticity then is calculated by changing
the price of one fuel at a time by 5 percent and observing the set of
quantity changes each year that result. A separate set of these calculations is done
under the $4, $7, $11, and $15 ultimate
oil price.
For the
household and commercial and the industrial sectors, the quantity change
which is observed under this procedure is composed of two parts: (1) the
change in total energy demand from Step 1 which is a function of the composite fuel index derived from the individual energy prices, and (2) a
3-4
Table 3.1.
Prices for $7.00, $11.00 and $15.00 Crude Scenarios*
Prices for $7.00 Crude Scenario
(1973 Dollars)
1973
4.001
Crude Oil (S/Barrel)
10.44
Coal ($/Ton)
Natural Gas (S/1000 Cu. Ft.)
1.254
Household & Commercial
0.6425
Industrial
4.581
Residual (S/Barrel)
5.584
Distillate (S/Barrel)
0.3971
Gasoline ($/Gallon)
Electricity (/kWh)
Household & Commercial
1.430
Industrial
1.931
1977
1980
1985
7.001
10.44
7.001
10.44
7.001
10.44
0.6423
7.001
9.491
0.4368
1.254
0.6423
7.001
9.143
0.4237
1.254
0.6423
7.001
8.680
0.4063
1.430
1.930
1.430
1.930
1.430
1.930
1 .254
Prices for $11.00 Crude Scenario
(1973 Dollars)
4.001
Crude Oil (S/Barrel)
10.44
Coal ($/Ton)
Natural Gas (S/1000 Cu. Ft.)
1.254
Household & Commercial
0.6425
Industrial
4.581
Residual (/Barrel)
5.584
Distillate (S/Barrel)
0.3971
Gasoline ($/Gallon)
Electricity (/kWh)
Household & Commercial
1.430
Industrial
1.931
9.376
10.44
10.34
10.44
10.86
10.44
1.254
0.6423
9.376
11.87
0.4933
1.254
0.6423
10.34
12.48
0.5033
1.254
0.6423
10.86
12.53
0.4981
1.630
2.200
1.681
2.269
1.708
2.306
Prices for $15.00 Crude Scenario
(1973 Dollars)
4.001
Crude Oil (S/Barrel)
10.44
Coal (/Ton)
Natural Gas ($/1000 Cu. Ft.)
Household & Commercial
1.254
Industrial
0.6425
Residual (S/Barrel)
4.581
5.584
Distillate (S/Barrel)
Gasoline (S/Gallon)
0.3971
Electricity (/kWh)
Household & Commercial
Industrial
1.430
1.931
11.75
10.44
13.68
10.44
14.71
10.44
1.254
0.6423
11.75
14.24
0.5498
1.254
0.6423
13.68
15.82
0.5827
1.254
0.6423
14.71
16.38
0.5897
1.830
2.470
1.932
2.608
1.986
2.681
*Reproduced from PIR [8, Table AII-9].
3-5
change in the fuel shares through Step 3 with the logit fuel split equation.
These own price elasticities and cross price elasticities are then used in
the integrating model to move from the initial approximation to the equilibrium.
Regional Demands
National demand for each fuel is divided into a set of regional demands
and regional prices using coefficients calculated from 1960-1972 data. The
regional share coefficients are calculated using regional value weighted
shares of national demand, and the regional price coefficients are calculated
by using the average relationship of regional to national prices. These
regional share and price coefficients remain fixed over the 1973-1985 period
regardless of changes in relative energy prices. Then, given a regional
demand calculated in this way and a regional price again calculated by a
fixed weight index, the demand curve for the regional price-quantity pair
is fixed by assuming that the demand elasticity is constant over the whole
demand curve and is identical for all regions. Thus, say for the MidAtlantic region, the natural gas demand function is as shown in Figure 3.1.
The regional price (from the trajectory) and quantity (using 1973 weights)
determine the point A, and the slope of the straight line (in logs) is
determined by the national elasticity. The demand functions for all regions
by assumption will have the same slope with their distance from the origin
determined
by the regional
share
and regional
price coefficients.
As can
be seen in Figure 3.1, this assumption of parallel demand curves across
regions is very stringent and likely to be a serious distortion of the
actual situation.
3.1.3
The Use of Regional Demand Functions Within the Integrating Model
Given these regional demand curves (with elasticities) as specified
by the demand model, and given the supply curves (discussed in Section 2),
a Marshallian adjustment process is used to equilibrate the integrating
model. That is, starting with a set of demands which result from the initial price trajectory shown in Table 3.1, the least cost supply distribution
is calculated using the linear program integrating model. The integrating
model produces "shadow prices" which are the implicit marginal prices of the
regional energy supplies. These regional supply prices are compared to the
demand prices on which the initial regional demand quantities were based.
If the prices agree, a regional and national equilibrium has been attained
and no adjustment
is made.
If the prices
differ,
then there
is a two-step
process to approach overall equilibrium. First, a price-half-way in between
the demand and supply price is used to calculate new regional demands using
the national elasticity matrix:
log D = log D
+ M [log P - log P],
where D is the vector of regional demands, P the vector of the new regional
demand prices with P the old price vector. With the new demands, a new
3-6
LOG
PRICE
MID ATLANTIC
PRICE
PAST NPRTH
CENTRAL
WEST SOUTH CENTRAL
FL ANT IC
W^
I
lTIr
-
_AA
|Ad
I
I
FIGURE
3.1
MID ATLANTIC
LOG
DEMAND
DEMAND
A SAMPLE REGIONAL NATURAL GAS DEMAND
FUNCTIONS FOR 1985, USING THE NATIONAL
ELASTICITY
3-7
LP solution
is computed,
and if the model
and data are well behaved,
the
solution should converge to an overall supply-demand equilibrium. If equilibrium is attained, it will be characterized by different regional prices
and energy shares, depending on the different transport costs and the
characteristics of the M matrix.1
Even if equilibrium is attained in the LP solution, there still may
exist a disequilibrium in the system, for the resulting prices may drift
far from the price assumptions that went into the original price index
used in estimating aggregate national energy demand and national price
elasticities. In this case, it would be necessary to cycle back through
the whole demand forecasting model--starting with new trajectories and
computing new demand paths and elasticity matrices. The reason this step
is needed for equilibrium is that the positioning of the regional demand
curves--not only the elasticity, but more importantly, their position in
price-quantity space--depends on the original price trajectory chosen.
This can be indicated
in Figure 3.2, where
DDf
and DDS
are 1985
demand functions resulting from two alternative price trajectories.
Both the position of the demand function and its slope depend on the
prices chosen. Given a regional supply curve, it is very unlikely that it
would pass through the intersection of D1 D' and D2D2. To insure a full
equilibrium once the integrating model provides equilibrium prices for, say,
1985, these prices would need to be used to generate a new set of prices with
new regional demand curves computed. The equilibrium solution of these new
demand curves would be used to form another new price set. If the procedure
converged, a full equilibrium would be attained.
Another similar shortcoming is that once a full equilibrium of the
supply-demand system is found, in principle these results should affect
the level of macroeconomic activity which is used in forecasting total
energy demand. That is, the forecasts of aggregate demand and investment
should be sensitive to factor prices in the economy. Thus if the assumptions used to make the macro forecasts are not consistent with the energy
prices and quantities, serious biases could result. The PIR assumes that
the level of macroeconomic activity remains constant while the world oil
prices varies from $4 to $15. This assumption should be replaced by integrating the macroeconomic model with the energy model, a very difficult
task.
3.2
Evaluation of the FEA Methodology
3.2.1
Estimation Problems
The FEA method for introducing demand into the integrating framework
appears satisfactory in principle, but in practical application, given the
lOutput for the $11 "Business As Usual" scenario by demand region and
products
is presented
in [8, Appendix
IV, pp. 269-275].
3-8
I?
LOG
PRICE
)r
-2
LOG
DEMAND
FIGURE 3.2
REGIONAL DEMAND FUNCTIONS
UNDER TWO PRICE TRAJECTORIES
IN 1985
3-9
data available during the study period, a number of
encountered. 1 Attempts were made to compensate for
that arose in connection with the demand model, but
remain that the overall results must be viewed with
serious problems were
some of the problems
sufficient difficulties
caution.
The essence of the first problem that arose can be seen in Table 3.2,
which presents the own and cross elasticities for the household and commercial sector and the industrial sector.
As can be seen, the model produces
the counter-intuitive result that, in the household and commercial sector,
natural
gas and coal are complements
of residual and distillate
fuels
rather than substitutes for them (that is, the cross elasticities are negative when they would be expected to be positive), so that as the price of
oil rises the demand for natural gas falls in this model.
Even in the
industrial sector, the cross elasticity of coal demand to oil price is
negative, and the cross elasticity of natural gas demand is essentially
zero. 2
Now it is not altogether obvious what all the various factors are that
contribute to this result, but clearly one very likely problem is that
many of the observations
on natural
gas demand are on the supply
rather
than the demand curve. In the estimation procedure, the FEA properly
omitted data from the early 1970's, when markets could no longer be assumed
to be in supply-demand
equilibrium
due to FPC price
regulation.
The esti-
mation of the fuel-split equations used data from the late 1950's and
1960's. During this period natural gas was simply unavailable in many
areas of the country, although markets were expanding rapidly as new
In the months since the PIR was published, the FEA analysts
working on ways to correct some of the problems detailed here.
have been
2
The problem arising in this demand estimation can be seen in the following example considering a change in the demand for fuel oil.
A rise in the
price of natural gas decreases total energy demand (since the price index
rises), but for a given total demand increases the share of residual fuel
oil which is a close substitute for natural gas. Thus the cross price
elasticity of residual demand with respect to natural gas price is:
png . d Res _
RES
d png
where demand
d Tot
d Pindex +
ares d Pindex
for residual
d png
is Res = ares
ares .
T
d png
' Tot, and
po
Res
E
= 1.
It is expected
that the sign of the total derivative is positive, given that residual and
natural gas are close substitutes.
In fact, the FEA demand estimates must
have the first term, the "output or income effect" being large and negative,
for their estimates
show natural
gas and residual
to be complements,
not
substitutes. While in theory the sign of the derivative is indeterminate,
most analysts would find it very surprising that these fuels are complements.
This problem likely arises from the restriction inherent in the demand share
specification that the cross share elasticities are identical across all
fuels for a given change in price of one fuel.
Thus the second term is an
average across all fuels and may not be large enough to give the expected
relationship of substitutes.
3-10
Table 3.2.
Long Run Elasticities of Demand for Fuels, $11 Scenario*
Long Run Elasticities of Demand for Fuels in
tne Household and Commercial Sector 1985, $11 Scenario
ELCH
NGH
BITH
LGH
KH
DFLH
RFLH
PNGHC
PELCH
PBIT
.128
-.444
.602
-. 368
.888
.358
.014
.289
.262
.135
.011
.341
-.618
.012
.137
.005
.001
.110
.009
.099
.008
PDFL
.084
-.063
-1.384
.847
-.029
-.638
-.275
PRF
POTH
.054
-.058
-.147
-.058
-.002
-.047
-.345
.032
.040
.101
-1.605
-.087
.033
.029
Long Run Elasticities of Demand for Fuels in
the Industrial Sector 1985, $11 Scenario
PNGIND
ELCH
NGI
BITI
LGI
KI
DFLI
RFLI
.294
-1.506
.816
1.164
1.956
1.158
1.176
SrGI
1.926
PCI
1.830
PELCIND
-1.356
.324
.008
.008
.016
.008
.008
.016
.016
PBIT
.149
.067
-.593
.171
.622
.225
.593
.369
-.027
-.052
PDFL
PRF
POTH
.056
.128
.029
.085
.152
.076
-.087
-.074
-.128
-1.147
-.076
-.126
-.119
-.179
-.258
-.446
-1.148
-1.092
-1.697
-.437
-.124
-.126
-2.058
-.415
-1.568
-. 257
Long Run Elasticities of Demand for Fuels in
the Transportation Sector 1985, $11 Scenario
PGAS
GAST
LGT
DFLT
RFLT
PNGI
PDFL
PRF
-.355
-. 069
-. 367
-. 258
.191
-. 191
-.758
*Reproduced from the PIR [8, Tables AII-4, AII-5, and AII-6].
3-11
pipelines opened up new markets. As a result, one year there was no demand
in a region and the next year--after the pipeline was opened--there was a
significant change in the fuel share of natural gas, without any change in
relative prices.
If the estimation was regionally disaggregated,
then it
would be possible to introduce the fact that the gas price is essentially
infinite before the pipeline is built to a region, but in an estimation
based on national aggregates this essential fact is obscured, and the result
is that a supposed
estimation
of the demand
curve
is confounded
by estimates
that really are points on a shifting supply curve.
In addition
to the problem
of complementarity
between
gas and oil pro-
ducts, many of the own price elasticities occur because of fuel availability
and locational effects, while in transportation they likely stem from the
problem of disentangling price and income effects in the demand for gasoline.
These problems require careful treatment in any case. However, in a logit
analysis they are difficult to find because shares change very slowly over
time.
Another problem may arise due to the specification of energy demands
in the industrial
sector.
Energy is an intermediate
good,
and the usual
way of dealing with derived or intermediate demand is to estimate final
goods consumption as a function of income and final goods prices, and then
determine demand for factors (e.g., energy) through a production technology
which
is a function
of output
and price
of (all) factors
of production.
It
is legitimate to collapse demand for final goods and the production technology into derived demand for factors; but then the derived demand must be
a function of income and all factor prices. Using only energy prices in
specifying demand constitutes a misspecification because the other factory
prices (e.g., wages, cost of capital, cost of other raw materials) have been
omitted. Ideally, the energy prices would be determined from crude oil,
wellhead gas, and minemouth coal prices by refining and transportation
technologies. While lack of data often precludes correct econometric practice, this consideration would be important in determining the interaction
of energy prices and GNP growth.
3.2.2
Effect on the Overall Demand Estimate
Given the underlying structure implied by the results shown in Table
3.2, it is not surprising
that the initial
demand
forecasts
prepared
by
FEA using the model gave what appeared to be serious underestimates of the
demand
for natural
lIndustrial
gas,
particularly
coal demand
at high oil prices.;
also drops
as oil prices rise,
(For example,
for the same
reason, although the significance of this effect is dampened somewhat
by the fact that so much coal demand
handled in another way.
is in the electric
sector,
which
is
3-12
the model has the equilibrium price of natural gas more expensive with $4
oil than with $11 oil, and more natural gas is consumed with $4 oil than with
$11 oil!)
It is apparent that some considerable effort went into attempts to
correct the problem once the counter-intuitive nature of the results was
seen. For one thing, the elasticity matrix that resulted from the procedure described above was "doctored" to force the model to yield more
reasonable results. Thus, as pointed out in the PIR [8, Appendix, p. 87]
the elasticities of demand to industrial electricity price and household and
commercial natural gas price (Table 3.2) were scaled down by factors of six
and four respectively as part of this process of imposing judgement on the
econometric results. The precise reason for this adjustment, and its
effect on the results, are not known.
Another
form of adjustment
of the model
to this problem
of the dis-
appearance of natural gas demand at high oil prices was in the handling of
the original price trajectories shown in Table 3.1. In this case the
effect on the results is more clear, and damaging. As can be seen in
Table 3.1, the natural gas prices were held constant under all oil price
scenarios
at a price
roughly
equivalent
to $7 per barrel oil.
The endpoint
of the natural gas price trajectory is not raised when oil prices rise to
$11 per barrel for the reason noted earlier, i.e., the natural
falls to unreasonably
low levels when this is done.
gas demand
It is important to notice the effect of this assumption about price
trajectory for natural gas, coupled with the elasticities in Table 3.2
on the solution to the integrating model.
As oil prices rise, natural gas
demand does not rise.
As a result the price of natural gas in the inte-
grating model is never driven away from this starting assumption because,
in effect, gas supply is never driven up onto the inelastic portion of the
supply function.1
In fact in some regions gas prices fall below those
implicit in the vector of initial demands. Three points need to be made
about this set of problems:
(1)
Failure to Achieve BTU Equilibrium
Under the "deregulation"
assumptions
of the PIR, by 1985
sufficient time should have passed so that energy sources which
are nearly perfect substitutes for each other (e.g., natural gas
and distillate) should be in equilibrium with respect to BTU
price (after counting in all transportation and distribution costs).
Using the PIR BTU conversion rates [8, p. A281] and the citygate equilibrium prices for distillate for, say, the Mid-Atlantic
region, the BTU price of distillate is $2.04/million BTUs [8,
p. 273] and the price of natural gas is $1.14/MCF [8, p. A272].
1
This cheap gas is not picked up by the electric power sector because
the model is constrained not to install gas-fired generating capacity.
3-13
Therefore,
a BTU of gas costs
fuel oil.
From elementary cost minimization assumptions, an
industry
only 54% of a BTU of distillate
buying at the city gate should buy only natural
gas.
Household and commercial users, even after allowing for within
city markups and retail delivery costs, should also buy only
natural
gas.
Yet the model
has 3,130 million
BTUs of distillate
being consumed in 1985 in the Mid-Atlantic region. 1
The notion of a BTU equilibrium is a subtle concept. All appropriate costs including transportation, storage costs, etc., plus
the effects of long-term contracts, must be taken into account.
Still,
the most
powerful
notion
of the economic
calculus
states
that close substitutes cannot have greatly different prices.
Thus, even when all the complications are considered, the large
price disparity between, say, distillate and natural as could
not exist in a true equilibrium under deregulation. This consideration must be of extreme importance in determining the role
of alternative fuels such as coal, natural gas, and synthetics
in 1985.
(2)
Overestimation of Overall Energy Demand
Since the natural gas price is never raised above the level shown
in Table 3.1, the price index used in forecasting a national
energy demand is underestimated in relation to what it would be
if the model were yielding something closer to BTU equilibrium,
and thus the aggregate
(3)
demand
is overestimated.
Underestimate of Natural Gas Consumption
The problem
of lost demand
for natural
gas remains,
and in
effect the share of oil (and thus of imports) in overall aggregate demand also appears to be overestimated. As the oil price
rises,
the share of natural
gas must
increase,
not decrease,
as
the PIR forecasts. The PIR in effect continues the natural gas
shortage due to current regulatory policies. To appreciate the
effect of regulation and the size of the natural gas shortage
if it is continued,
the model must
be corrected
so that reason-
able demand forecasts are made.
These problems are critical for policy simulation. In an experiment
suggested by the MIT group in which approximate BTU equilibrium prices
for gas, coal, and electricity for $11 oil are used in the original price
trajectory, the final equilibrium gas price rises 25% above the PIR estimate. Furthermore, equilibrium oil imports are reduced by almost a
million
barrels
a day.
If the cross
elasticity
of natural
gas with
oil
products had the correct sign, it is likely that oil imports would have
fallen even further.
2
The situation
for coal
is less clear due to different
burning
efficiency
and capital cost requirements, but again the price of coal seems well out
of equilibrium even allowing for these additional complications.
3-14
3.3
Summary Evaluation
Due to the complex modeling methodology, it is hard to say what the
effect
of these
problems
is on the final
forecasts.
But at any given
level
of total energy demand, the PIR probably underestimates the amount of
natural gas consumed and overestimates oil products consumed, thus giving
an upward bias to oil import forecasts. Since the oil price is set exogenously, the correct equilibrium quantity of natural gas must increase if
the gas supply
function
is upward
sloping
and if regional
prices are in BTU
equilibrium and natural gas is a substitute for petroleum products.
The effect on total energy demand is much more difficult to disentangle.
Conflicting biases seem to make it impossible to calculate the final bias. 1
However, one prediction may safely be made. The PIR predicts 12.4 million
barrels of petroleum imports per day in the $11 case. Both these numbers
are biased upwards due to the problems in the demand modeling methodology.
Unless one assumes very price inelastic supply curves for coal and natural
gas, and a large underestimate
for total
demand,
both coal and natural
gas
will be consumed in sufficiently greater quantities so that oil imports
will be less than the PIR indicates. Under deregulation and easin of
environmental
standards,
coal and natural
gas will have a larger
share
in
energy consumption than the PIR indicates.
1
Since total energy demand is closely linked to the growth rate of the
GNP which
is assumed
to be the same in the $4, $7, and $11 cases, another
element of uncertainty is introduced.
been
done on the interaction
To date very little analysis has
of increased
energy
prices and growth
of GNP.
4.
CONSERVATION
In the previous section we discussed the FEA analysis of demand,
where "demand" is concerned with the amount of energy that consumers
desire to purchase at some given price. In addition, the PIR outlines
the energy savings that will be realized from the implementation of a
variety of conservation initiatives, including legislative and regulatory actions designed to mandate reductions in energy consumption
beyond those to be expected as a result of higher energy prices. In
this sectionwe review and evaluate this aspect of the FEA methodology
and results.
4.1
FEA Conservation
Initiatives
The PIES provides an analysis of a number of important conservation
initiatives.
In this section,
we summarize
for the $11 scenario
the
initiatives included in the Blueprint, the energy savings associated
with each initiative, and other expected impacts of the initiative.
(1)
Establish a mandatory 20 MPG auto efficiency standard-1.9 quads.
If the sales-weighted average MPG is increased to 20 MPG
by 1985, vehicle
fuel use will
be decreased
19% from the 1985
BAU case. The efficiency standard will have a negligible effect
on vehicle miles travelled (VMT), GNP, and unemployment. New
car sales are expected to be reduced about 3% per year.
(2)
Enact legislation which would substantially increase use
public transit and discourage inefficient use of automobiles -- 1.2 quads.
of
If transit service is improved via legislation and
subsidy, while autos are discouraged via parking fees, tolls,
licensing fees, and gas taxes, then ridership will increase
at least 20% over existing levels and vehicle miles
travelled
(3)
will
be reduced
25% tax credit,
to expire
20% in 1980 and 9% in 1985.
in 1980,
for retrofit
to improve
thermal efficiency of residential buildings -- 0.9 quads.
Estimated government cost for this program 4is $800
million
(4)
per year
in lost tax revenues
by 1980.
Enact legislation requiring federal minimum efficiency
standards for all new residential and commercial construction -1.0 quads.
4-1
4-2
Report
The use of the ASHRAE
as a basis
for
minimum efficiency standards would lead to these savings by
1985; the cost to develop,
implement,
and monitor
the stan-
dards would be $300 million.
15% tax credit,
(5)
expiring
structures -- 0.2 quads.
revenues
would
in 1980,
to retrofit
commercial
Cost in terms of lost government
be $40 million
per year
by 1980.
Enact new legislation requiring mandatory minimum performance
(6)
standards
for new manufactured
appliances
shipped
and sold in
interstate commerce -- 0.5 quads.
Energy
savings
up to a maximum
of 25% of overall
appliance
energy usage would be achievable. Costs to the Federal Government would be $3-5 million per year for research and administration.
Enact legislation mandating lighting standards for commercial
buildings -- 1.4 quads.
(7)
The cost of enforcement would be $25 million annually.
Aggressive conservation program assured by research, development, and demonstration for increased efficiency in industrial
processes -- 1.5 quads.
(8)
Direct governmental costs for RD&D would be $250 million in
1977 and should decrease after that.
Demonstration of energy conserving practices and technologies
in support of amendments to the Federal Power Act -- 0.9 quads.
(9)
Activities to flatten load peaks including alternative
rate structures, cooperative arrangements between transmission
systems with complementary peaking characteristics, and
RD&D in thermal storage devices should reduce end-use demand.
Marketina solar collectors and equipment for waste heat
recuperation could reduce electrical demand. The cost in direct
Federal outlays would be approximately $100 million per year.
FEA also estimates the effects of a demand management strategy which
focuses
directly
upon substituting
coal for oil and gas in utility
and
large industrial uses and on stimulating the use of electricity, rather than
oil and gas, in the residential and commercial sector. This demand management
strategy
is implemented
by forbidding
direct
use of oil and natural
gas
as fuels in new or replacement housing -- all new-buildings would be
Thus a large part of the anticipated growth in petroleum demand in the
industrial sector is converted into coal demand, and utilities are converted from petroleum to coal. No significant change in the transportation
4-3
sector's energy use is expected to occur through 1985, since there is no
possibility of converting transportation vehicles from petroleum to
other fuels. In total, the strategy could reduce petroleum use by
1.0 quads and natural gas by 2.5 quads;
and utilities would total 6.11 quads.
4.2
increased
coal use by industry
FEA's Intended Methodology
FEA's procedure for developing estimates of energy savings through
various conservation iniatives involved the development of special
models for each of the major consuming sectors. Models were developed
for the industrial sector [25], the transportation sector [24], and the
residental and commercial sector [23]. These models were intended to
be sensitive
to the set of conservation
initiatives
so
to be evaluated,
that the various policy instruments could be made explicitly exogenous
variables in the analysis. It was recognized that some initiatives -such as research, development, and demonstration of more efficient
technologies and industrial processes, or demonstration of energy
conservation practices in general -- would be difficult to include in
a modeling framework. However, initiatives such as miles-per-gallon
(MPG) regulation or tax credits to induce investment in insulation
could be explicitly modeled.
If properly specified and estimated, the FEA energy conservation
submodels would essentially replace the econometric demand model described and evaluated in Section 3. However, in the development of
these models the FEA encountered a number of very difficult problems
relating
to model
specification
in a circumstance
involving
the inte-
gration of behavioral assumptions with engineering/process types of
information. As a consequence, the decision apparently was made to
try to develop the conservation models as fully as possible independent
of the national
econometric
demand model,
and then integrate
the two
models to produce demand estimates for each of the conservation initiatives.
This was done in the following way.
First, the same macroeconomic and demographic scenarios were used
in both the national econometric demand model and each of the conservation
models. These data included assuming crude oil proces of $4, $7, and
$11. The conservation models were solved using these input data to
produce independent estimates of the "Business as Usual" demands.
Next, each independent conservation initiative was introduced into the
model, and the resulting model solution compared with the BAU solution
for assumed crude oil prices of $4, $7, and $11. The difference between
the two solutions
at each of the assumed
prices was the estimate
savings due to that specific conservation initiative.
of the
This procedure
4-4
provides a means for disentangling the effects of changes in demand due
to price changes versus changes due to the conservation initiative,
without developing a single demand model which is sensitive both to
prices and to instruments for introducing conservation initiatives.
Of course, there was no reason to expect that the BAU solutions
of the national econometric demand model and those of the conservation
models would turn out to be equal. Since the conservation modeling
effort tended to focus upon the special problems associated with introducing conservation policy variables into a modeling framework, FEA
assumed that the econometric forecast discussed in Section 3 gave the
better estimate of unconstrained demand for .the BAU case. The conservation model estimate of the demand associated with a given initiative
was apparently reconciled with the econometric demand model BAU estimate
in one of two ways. (1) The difference between the conservation model
BAU solution and the initiative solution was subtracted from the national
demand model BAU solution. That is, the conservation model estimate of
the magnitude of the savings was assumed to apply regardless of the
initial level of demand. (2) The percentage reduction in demand
associated with the conservation model solution was taken to apply.
In this case, the national demand model BAU solution was reduced by
this percentage.
In either case, points on the new demand curve, corresponding to
assumed crude oil prices of $4, $7, and $11 dollars, were obtained.
Figure
4.1 summarizes
the relationship
of the two demand
curves
for the $11
scenario. The FEA assumed that the elasticity at each of the three
crude oil prices (as evaluated by the econometric demand model) also
applied to the points on the new demand curve as adjusted for conservation.
The procedure used imposes no restrictions to insure that price elasticities associated with any one of these points will in fact trace out a
demand curve which also passes through the two points associated with
the other two prices. The only condition under which this restriction is
imposed is if the conservation savings are a constant percentage
reduction from the original demands.
4.3
The Actual FEA Calculations and Evaluation of Results
The PIR has "order of magnitude" estimates of the size of energy
savings that may be anticipated following a large-scale commitment to
energy conservation. However, the basis for projecting the expected
savings reflects considerable subjective estimation. The model described
in the Task
Force Reports
[23, 24, 25] were not applied
in evaluating
the initiatives summarized in Section 4.1. In all cases, the Task Force
reports do not present detailed information on the particular initiatives
evaluated in the PIR. This is not to assert that the conservation models
were not used extensively to inform the subjective estimates presented
in the PIR.
However,
the fact remains
that the "positioning"
of the demand
4-5
LOG
PR ICE
DEMAND CURVE FROM NATIONAL
MODEL
ECONOMETRIC
INED BY ADJUSTING
ON WITH
THE BAU
INFORMATIC )N
FROM
F CONSERVATION. CURVE
MODEL
USING NATIONAL
ES
-
LOG
DEMAND
FIGURE
4.1
FEA
DEMAND
CURVES FOR A GIVEN
PRODUCT
WITH AND WITHOUT A GIVEN CONSERVATION
INITIATIVE
I
4-6
curves associated with each of the conservation initiatives for crude oil
price
scenarios
of $4, $7, and $11 is based
on essentially
subjective
evaluation. Our essential point here is that the conservation results
in the PIR cannot be replicated. This is in direct constrast to most other
components of the PIES where estimates can be potentially reproduced by
application of the appropriate model.
Secondly, insufficient information was developed relating to the
investment and social costs associated with a particular conservation
initiative. There are three important consequences of this omission.
(1)
The costs of implementing the iniative cannot be evaluated.
As a consequence, investment levels necessary to implement alternative initiatives cannot be compared among themselves and with investments necessary to increase energy supplies. Such comparisons
are necessary in order to choose a least-cost combination of conservation and supply initiatives to achieve a given import reduction.
(2)
The relationship between the initiatives and the consequent
requirements for non-energy inputs (and their prices) and
the resulting
effect
upon the level
and distributon
of real
output cannot be evaluated. The PIES system includes no capability for assessing the consistency of the energy quantities
and prices, and the associated quantities and prices of investment goods and other inputs, with the assumed level and distribution of real output.
(3)
The procedure by which FEA traces out the demand curves associated with the conservation initiatives under each of the crude
oil price scenarios
seems
incorrect.
Recall that the three
conservation demand curves will coincide only when the conservation initiative produces a constant percentage reduction in
the original demand. Nothing in the FEA procedure ensures that
this restriction was imposed. It would be more appropriate
to estimate the elasticity associated with a segment of the
conservation demand curve by calculating the arc elasticity
between the two continguous points. This would insure that
all the information produced by the conservation models was
incorporated in the conservation demand curve, and would also
insure that a single conservation demand curve was produced.
In summary, FEA's approach to the incorporation of conservation initiatives
into the PIES seems reasonable. However, difficulties seem to have
arisen in implementing the procedure. The conservation models were not
accepted as providing reasonable estimates of the conservation savings,
and so were significantly supplemented, if not eliminated, through
the application of subjective information.
The PIES does not provide a framework within which these subjective
estimates of the impact of selected conservation initiatives can be
evaluated.
5.
ECONOMIC IMPACT OF EVENTS AND POLICIES
Since the Project Independence Report is intended to evaluate various
options for U.S. policy, one critical input to the analysis is the estimation of the larger cost to the economy of the more important policies that
might be adopted to achieve sufficiency, or the possible cost of continued
exposure to the vagaries of the world oil market. Analysis of these matters
is difficult under the best of conditions, and not surprisingly we find this
to be one of the weakest aspects of the PIR effort.
5.1
Impact of the Oil Embargo
Evaluation of the costs of the embargo of 1973-1974 is an important
element of any appraisal of energy policy. Investment in facilities and
programs for protection against future embargoes is justified only if there
is evidence that the economy can be hurt by an embargo. The Project Independence Report contains estimates of the impact of the economy. It concludes
that the cost of the embargo was substantial, and that the adverse effects
continued and even grew after the end of the embargo.
In evaluating this conclusion, it is important to remember that two
events coincided in the fall of 1973. Certain Arab governments imposed restrictions on the quantity of oil supplied to the United States, and simultaneously
raised the price of oil to all customers
by a substantial
amount.
It is important to avoid confusion of the effects of the two events. It
appears that the great bulk of the disruption of the U.S. economy during
and after the embargo was in fact attributable to the price increases and
not to the embargo
itself.
And thus the U.S.
economy
is vulnerable
to
future embargoes only to the extent that they bring about further price
increases by new restrictions on world supply.
It is unfortunate
that the FEA report does not make
this important
distinction, for a review of the materials in the PIR itself supports the
hypothesis that the disruption followed primarily from price increases.
The FEA estimates that oil consumption in the U.S. was 5.8 percent below
trend in the fall of 1973, 13.9 percent below in January 1974, and 16.7
percent below in February. Actual demand fell below trend during the period
because of voluntary and mandatory conservation measures, of uncertainty of
supplies, and because the prices of products rose substantially. With an
elasticity of demand in the short run for petroleum products of -0.2, the
price increases necessary to reduce demand by price pressures alone would
have been 29 percent, 69 percent, and 83 percent, respectively, in the three
periods. The actual price increases for some products were in this range,
though the average was somewhat less, as shown in Table 5.1.
5-1
5-2
Table 5.1.
Changes in Price and Consumption Over the Embargo Period
Nov.-Dec.
1973
Jan.
1.974
Feb.
1974
5.8%
13.9%
16.7%
29.0%
69.0%
83.0%
Gasoline
14.0%
30.0%
37.0%
Kerosene
10.0%
19.0%
42.0%
Distillate (No. 2)
13.0%
34.0%
61.0%
Residual
33.0%
74.0%
127.0%
Percent
reduction
in
actual consumption
below trend
Price increase necessary
to reduce demand by
amount in first row
Actual price increases,
selected products, relative
to September 1973
Source:
Survey of Current Business, 1973-1974 (Various issues).
5-3
Little is known about the quantitative impact of conservation programs
during the embargo; the FEA report contains almost no information on this
subject. It is entirely possible that the combination of price increases
and conservation policies depressed demand to the level of actual consumption,
so that FEO allocation and other quantity controls were not actually necessary. This would be consistent with the observation that products were
generally available in unlimited quantities. No attempt was made or was
needed to enforce restrictions on the consumption of heating oil. Gasoline
was freely available throughout the period in many parts of the country.
Even in the most seriously affected northeastern urban areas, waiting times
for gasoline rarely exceeded
shortfall of 1 or 2 percent.
10 or 20 minutes,
corresponding
to a quantity
Thus there is little evidence that the embargo alone had an important
effect on the U.S. economy. The very real dislocation suffered by the
economy was in the response to the price increases, not the embargo itself.
FEA's estimates of the impact of OPEC's actions are consistent with that
view. They continue to be large well after the end of the embargo, and in
one set of estimates reach their peak a full year after the embargo. Those
estimates, prepared by the Department of Commerce by a method that is not
described
in the PIR, suggest
that real GNP was reduced
by $2.1 billion
in
the fourth quarter of 1973, $10.4 billion in the first quarter of 1974, and
$9.7, $10.2, $14.5, and $15.0 billion in the next four quarters respectively.
Evaluation of these estimates requires a study of the model used to prepare them and the assumptions about fiscal and monetary policy underlying
them--a study which can be undertaken as soon as the method is made known
by the Department of Commerce.
The FEA made a second, larger set of estimates using a very simple
technique. They compared a forecast made by Data Resources, Inc., just
before the embargo (October 24, 1973) to one made well after it (May 21,
1974). They attribute all changes in the forecasts to the embargo. Since
this method takes account of all influences on the economy that changed
over the period, it is clear th-atit measures the combined influences of the
embargo, energy price increases, and events not directly connected with the
OPEC action, such as the tightening of monetary policy during the spring of
1974. Some idea of the magnitude of the errors in this procedure can be
gained by comparing the two forecasts used by the FEA with the actual behavior of the economy and DRI's current forecast for real GNP. These data
are shown in Table 5.2.
By the third quarter of 1974, differences between forecasts (before
vs after embargo) were smaller than errors in forecasts. For the later
quarters, errors in the forecasts dwarf the changes in the forecasts from
October 1973 to May 1974. Many determinants of economic activity change
from one forecast to the next, quite apart from dramatic actions like
those of OPEC. Little confidence can be put in estimates derived from comparisons of forecasts that attribute all of the differences to a single
influence.
The US. economy entered a deep recession after the embargo and price
increase of 1973-1974. Though energy problems are given a large role in
5-4
Table 5.2.
Comparison of Alternative DRI Forecasts
Date of
forecast
73IV
741
7411
74III
741V
751
10-24-73
848.4
851.8
855.7
862.5
869.7
879.9
5-21-74
844.6
831.0
836.2
845.4
855.6
864.2
12-28-74
845.7*
830.5*
827.1*
823.1*
804.4
794.8
*Actual data
5-5
popular accounts of the recession, experts in macroeconomics generally find
that they are of minor importance. The prevailing expert view is that the
current recession is basically similar to earlier recessions in resulting
from a reduction in aggregate demand. Contractionary monetary and fiscal
policies are the fundamental cause of the current recession, in this view.
The embargo and price increase brought about an unusually difficult choice
for policy-makers between high levels of inflation and high rates of unemployment, but they could have chosen a more expansionary policy and thereby
prevented the recession. The recession should be viewed as the method
chosen by policy-makers to deal with inflation (only part of which is attributable to the oil price increase), not an inevitable result of the embargo.
Arthur Okun argues for this interpretation and provides considerable evidence in a recent
paper [36].
Existing macroeconomic models are poorly suited to the analysis of the
impact of energy problems because they are too highly aggregated to deal
in detail with the energy sector and interactions with other inputs and
the prices or quantities of outputs. The disaggregated models do not treat
short-run adjustment in enough detail to make useful estimates.1 Work
should be undertaken to disaggregate the macro-models, and to make the
energy-oriented market or sectoral models more dynamic. This has to be
done before reliable forecasts of the effects of sectoral policies can be
undertaken.
5.2
Long-Run Implications of High Energy Prices and of Alternative Energy
Policies
Over the longer run, to 1985 and beyond, the economy responds more
flexibly and efficiently to large changes in the prices of energy. Workers
laid off from energy-sensitive industries find work in other sectors, new
industrial processes are developed to use more of other inputs and less
energy, and houses, automobiles, and other consumer products are redesigned
to use less energy. High energy prices are much less costly and disruptive
in the long run than in the short run. The FEA's report agrees with other
studies that the total volume of output of the U.S. economy is hardly affected
1
The FEA report does contain a good deal of data on the impact of the
oil price increase on specific industries. According to a study conducted
by the Department of Labor, quoted by the FEA, about 500,000 workers were
laid off as a direct or indirect result of reduced consumption of oil. Most
had been employed in the automobile and related industries. These layoffs
were less than the normal layoffs that occur each week in the U.S. economy,
and did not have an important impact on the national unemployment rate.
Higher energy prices called for a reallocation of resources from energysensitive industries to other industries, and the layoffs and subsequent
re-employment of workers that took place in early 1974 was the working out
of this process. The cost of the sudden increase in energy prices was the
transitional unemployment of workers taking part in the process.
5-6
by high energy prices or by alternative energy policies. According to the
FEA's study (based on models provided by Chase Econometrics Associates and
by Clopper
Almon),
real GNP will
grow at a rate of 3.7 percent
per year
over
the period 1973 to 1985, whether or not a policy of accelerated supply is
adopted,
if the world
price
of oil is $7 per barrel.
At $11 per barrel,
growth would be 3.2 percent per year. A second major study, carried out by
Edward Hudson and Dale Jorgenson of Data Resources, Inc., for the Energy
Policy Project of the Ford Foundation [6] is somewhat more optimistic. It
projects a growth rate of real GNP over the period 1975-1985 of 3.6 percent
per year assuming a continuation of past trends in energy consumption, 3.5
percent if high prices and other influences depress consumption below its
historical path, and the same 3.5 percent even if strong policies keep
energy consumption constant rather than growing at all. Neither of these
studies uses a fully integrated model of energy use and economic growth, so
there may be a considerable margin of error. However, both analysis conclude that there is no fixed relation between energy input to the economy
and total output, so the economy can continue to grow even with substantially less energy.
High energy prices depress the real incomes of Americans even though
they have little effect on real output. This is simply the counterpart of
the dramatically increased real incomes of nations that export oil. Real
wages in the United States are now over five percent below the smooth trend
they followed before 1973.1 The FEA study seems to have overlooked this
effect
altogether.
With oil at $7 per barrel,
they project
a rate of
growth of the real wage of 1.5 percent per year, precisely the same as at
$11 per barrel.
Again,
the lack of integration
of the energy model
into
the macroeconomic mode prevents a satisfactory analysis of the impact of
energy prices on overall prices and wages.
It is generally thought that high energy prices have a differentially
adverse impact on consumers with low incomes. The FEA report presents a
good deal of evidence supporting this view. Families with incomes below the
median spend about 11 percent of their income in gasoline, electricity,
heat, and other forms of energy. The fraction declines with rising income-families with incomes of $12,000 spend a little less than 8 percent on energy,
and those with incomes of $20,000 around 5 percent. It appears to us,
however, that the FEA substantially overstates the distributional effects
of an increase in energy prices. The Energy Policy Project studied the
issue more carefully using a survey of energy consumption made recently.
They conform the FEA's finding that direct consumption of energy does not
rise in proportion to income. However, the EPP study shows that consumption of energy through the purchase of goods that are produced with energy
is twice as important as direct consumption, and does rise more nearly in
1
The ratio of hourly compensation in the private non-agricultural sector
to the consumer
price
index rose smoothly
in the period
1954-1972
at an
annual rate of 2.4 percent. Since the second quarter of 1973, the ratio has
dropped 2.1 percent, while its past rate of growth would have had it rise
by 3.1 percentage
points.
5-7
in proportion.
Further,
both the FEA and EPP studies
suffer
from an impor-
tant technical defect that biases them toward overstating expenditures in
lower income groups and understating them in high income groups. The
lower income groups contain many families who are normally better off but
have suffered a temporary reduction in income. These families consume more
than do the genuinely poor. Similarly, the upper income groups contain
families who are only temporarily well off and cannot consume as much as
the genuinely rich. An important next step in research should be the
adjustment for this bias by methods of budget analysis that are currently
available. It is not at all unlikely that a refined study would reveal
that total energy consumption is the same fraction of income in all groups,
and that an increase in energy prices does not have an adverse effect on the
distribution of income.
6.
ENVIRONMENTAL ASSESSMENT
As was pointed out in Chapter IV of the PIR, environmental goals are
not necessarily consistent, indeed, are sometimes exactly inconsistent with
objectives of reduced dependence on foreign energy resources and a robustly
operating economy. Two indisputable conclusions are drawn in the PIR.
Environmentally, low demand growth is superior to high demand growth and
importing
to the environment
fuel is less detrimental
than producing
it
domestically. The problem, therefore, is one of advancing on the path of
increased economic and energy welfare, while at the same time not sacrificing
"too much" gain in quality of the natural environment, human health, and
safety. There are obviously difficult choices existing at all levels of
decision making--locally, regionally, nationally, and in some cases worldwide. PIR does not deal with these trade-offs. Obviously, action on the
exigent energy and economic problems of the country cannot wait for extensive
and complete analysis of the environmental implications. Neither the techniques
of evaluation nor the data exist in a quality or scale necessary to accomplish
a complete determination of optimal imports and environmental quality. But
very little of what could be done is attempted in the FEA policy analyses.
No conclusions are possible from the results reported.
The analytical approach used by the FEA relates fifteen environmental
residuals to the alternative supply and demand strategies analyzed in the
PIR. The fifteen residuals include:
- Water Pollutants
1.
Acids
2.
Bases (equivalent tons/day)
3.
Total Dissolved Solids (tons/day)
4.
Suspended Solids (tons/day)
5.
Organics or Oil Spills (tons/day)
6.
Thermal
(BTU's/day)
- Air Pollutants
7.
Particulates (tons/day)
8.
Nitrogen Oxides (tons/day)
9.
Sulfur Oxides (tons/day)
10.
Hydrocarbons (tons/day)
6-1
6-2
11.
Carbon Monoxide (tons/day)
12.
Aldehydes (tons/day)
- Solid Wastes
13.
Solids (tons/day)
14.
Fixed land (acres/year)--fixed land is that for which
- Land
alternative
uses are precluded
for many years,
such as
land on which new, permanent facilities are constructed.
15.
Incremental
land (acres/land)--incremental
land is the
maximum acreage that is excluded from alternative uses
at any time prior to reclamation, such as land on which
It is not the quantity of
surface mining has occurred.
land disturbed each day.
Critical to the approach is a set of assumed effluent factors. Each of
these effluent factors (with units of, for example, tons/year of acids emitted
per 1012 BTU's of coal produced from underground mines) related the rate of
emission of each pollutant (or land requirements for the land categories) to
an activity measure in each of the supply or consuming sectors. The activities,
or basic processes, to which individual effluent factors are associated are
consistent with the aggregation of supply and consumption used in the integrating
model. These individual activities include: supply activities: natural gas
(offshore, onsore), oil (offshore, onshore, Alaska, imported), coal (underground
mines, surface mines), and shale oil. They also cover conversion activities
(electricity, coal gasification) and consumption activities: residential and
commercial, industrial and transportation.
For each of the fifteen activities and fifteen residuals listed, an
effluent factor is estimated,' yielding 225 effluent factors. "Pollution
loadings" are then estimated by transforming an energy supply and demand
balance [8, p. 282] into environmental "loadings" of the residuals via this
matrix of effluent factors. The results of this matrix multiplication for
the FEA supply and demand strategies are displayed in the PIR [8, pp. 217-220].
Table 6.1 illustrates some of these results for the two basic FEA scenarios,
$7 BAU and $11 BAU. The numbers presented are nationally aggregated and represent
the rate of emission of the physical quantities noted into the environment.
The development
of the data for the residual
matrix
was jointly
sponsored
by the Council on Environmental Quality, Environmental Protection Agency (or
matrix of effluent factors), and the National Science Foundation, and done by
Hittman Associates, Inc.
6-3
Table 6.1.
1985 Pollution Loadings For Two FEA Cases
$7
BAU
$11
BAU
Water Pollutants
1. Acids (tons/day)
2. Bases
-
(tons/day)
-
31
42
5222
5809
4. Suspended Solids (tons/day)
237
301
5. Organics (tons/day)
296
318
24,509
23,975
2181
2273
8. Nitrogen Oxides (tons/day)
41,804
46,713
9. Sulfur Oxides (tons/day)
47,091
53,657
18,819
18,824
1002
1357
431
392
852
1130
35,597
35,770
3. Total Dissolved Solids (tons/day)
6. Thermal Discharge (Billion BTU'sday)
Air Pollutants
7. Particulates (tons/day)
10. Hydrocarbons (tons/day)
11. Carbon Monoxide (tons/day)
12. Aldehydes (tons/day)
Solid Wastes
13. Solids (1000 tons/day)
Land
14. Fixed Land (1000 Acres/year)
15. Incremental Land
1000 Acres/year)
1501
2668
6-4
The problem with the FEA analysis is not with what was done, but rather
with what wasn't done. First, the data base of effluent factors developed
by Hittman
Associates,
Inc.,
encompasses
more
than that used by the FEA--
effluent factors for ten forms of water pollution were derived, where only
six were used by the FEA, and three occupational health impact factors (for
deaths, injuries, and man-days lost per unit of activity in each supply sector)
were derived, and none of these were used by the FEA. Also, each effluent
factor has associated with it a hardness factor, i.e., a subjective evaluation
of the relative
confidence
that can be placed
in each number.
As might be
expected, there is substantial justification for some, while for others there
are very low confidence levels. The FEA has used the numbers with no qualifications for probability
of accuracy.
Finally,
no analysis
has been done of the
very controversial issues that surround nuclear waste disposals, radioactive
emissions, or nuclear safety.
The substantive policy problem with the FEA analysis, however, goes
beyond criticism of the aggregation levels or particular numbers. The
crucial question in environmental analysis revolves around the identification
and ranking of effects that various supply and demand strategies have on
public health, safety, and the natural environment. The pollution loadings
derived by the FEA are only a first step in an attempt to carry out these
analyses. Some of the effluents they incorporate in their analysis are
much more localized in their effect on ambient conditions than the FEA
analysis provides for. Some have much more harmful effects on the receptor
population than others. The FEA makes no attempt to evaluate these impacts,
either quantitatively or qualitatively. Until the analysis is carried into
this domain, the acceptance or rejection of alternative strategies put forth
by the FEA can only be made for reasons other than the environmental effects.
Finally,
in the integrating
model
no provision
is made
to force
the
scenarios to be consistent with the capacity of the environment to acceptably
absorb the emissions that result. For the most part this reflects the limits
of existing capability to perform systematic environmental analyses in a
systems-oriented
context, and for this the FEA cannot be faulted.
Nevertheless,
concern for the environment is real, and the future policies adopted in the
energy domain will have a large impact upon the condition of the environment.
Both methodologically and empirically, further capability to perform
systematic environmental analysis needs to be developed.
7.
INTERNATIONAL ASSESSMENT
The expected future price of world oil is of critical importance to the
Project Independence studies. To the extent that domestic prices are influenced
by the cost of imports, the world oil price will affect domestic supply and
demand,
and the net demand
for imports.
Moreover,
the world
price,
and its
likely fluctuations in the future, have an important influence on the development
of energy sources, and on the policies needed to assure these developments.
7.1
FEA Estimates of World Oil Supply, Demand, and Price
The FEA study approaches the analysis of this circumstance by dividing
the world into two camps--members of OPEC and everybody else. Demand estimates
for 1985 are made for the non-OPEC
countries;
this demand
is then assumed
to be
partially served by the indigenous supply within each country, or by imports
from some non-OPEC net exporter (e.g., Norway). The residual demand then is
interpreted as a demand for imports from OPEC as a group, and this net demand
is compared with the potential supply from the OPEC countries at various prices.
The net surplus of potential supply over expected demand in the OPEC camp is
taken as an indication
of the degree
of strain
that the cartel will
experience,
and (implicitly) as a predictor of its success in sustaining or raising the
world oil price.
Table 7.1 shows the FEA estimates for the non-OPEC countries.
the OECD study
that preceded
it [37], the FEA analysis
uses prices
As did
of $3, $6,
and $9 per barrel in 1973 prices, (or approximately $3.45, $6.90, and $10.35
at last quarter 1974 prices), at Persian Gulf ports. With transport costs
added, these prices are consistent with domestic U.S. prices of $4, $7, and
$11 per barrel
used elsewhere
in the Project
Independence
studies.
The demand
estimates in the table take account of the likely effect of higher prices on
energy growth. Similarly, the estimates of indigenous supply are based on an
analysis of the responsiveness of suppliers to higher prices, for at higher
prices higher-cost resources become worth exploiting. So, for example, the
OECD estimates of supply and demand for the U.S. come directly from "Base
Case" assumptions in the analysis of the domestic market. Recall that the
"Base Case" assumes price deregulation for oil and other energy resources,
and the FEA analysis shows that supply increases as prices rise from $4 to
$11 per barrel of oil because these prices justify moving farther out along
the cost curves
for domestic
oil and gas.
The FEA estimation
procedure
for
other countries is not explained, but it is reasonable to presume that similar
assumptions were made for all the areas shown in Table 7.1.
The table also shows the OECD
projections
for its member
nations
(i.e.,
the U.S. and Canada, Western Europe, Australia and New Zealand, and Japan).
The OECD estimates of demand are higher than those from the FEA study, but
7-1
.*
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7-2
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7-3
so are the anticipated indigenous supplies. The net result is that the OECD
estimates of net imports are slightly below those prepared by the FEA for
the corresponding area.
The FEA study then estimates that the maximum potential production from
OPEC countries by 1985 is 53.1 million barrels per day, which implies a
potential excess capacity at $11 per barrel of 24.8 million barrels per
day (53.1 minus 28.3). This 46 percent excess capacity is then taken as
"indicative of the degree of OPEC collaboration necessary to maintain current
oil prices" [8, p. 360]. The clear implication is that the $9 price (approximately
$10.35 at last-quarter 1974 prices) is not likely to be sustainable, or at least
it is sustainable only with a high degree of internal organization
and discipline
within the cartel. At the $6 price path the potential surplus is only 9.6 million
barrels today (53.1 minus 43.5), an excess capacity of 18%. This is judged
to be "a substantial surplus capacity...which still requires some cooperative
effort between some OPEC states" [8, p. 360].
7.2
Forces Influencing the Future Path of World Oil Prices
The impression
given by the FEA analysis
is that the world
oil price
may
stay in the range around $9 per barrel, but it is perhaps more likely to
decline because of the pressures noted above to a level nearer $6 per barrel.
These basic price paths form the link between the international assessment
and the entire domestic analysis, which uses this price (converted to a price
for oil delivered to U.S. shores) as the fundamental exogenous condition.
This implicit assumption that the world price will gravitate to one level or
another may well have been essential to the integration of a study as complex
as that undertaken by the FEA. Unfortunately, there is no necessary reason
why the world price should behave in this way. Indeed, over a period of five
to ten years a pattern of fluctuation is quite probable. The implications of
such an outcome for the FEA analysis, and for national policies that may be
derived from it, are sufficiently important that it is worth a brief description
of how this fluctuation may come about.
1
Estimates of 1980 worldwide demand for OPEC oil, in millions of
barrels per day, include the following.
Source
W.J. Levy Consultants
Ford Foundation Project
Brookings Project
OECD
FEA (1985)
Price
(1974 dollars)
Demand
$8
6.89
7
10.50
38
28
33
21
7
6.61
28
44
9.92
Implied
Elasticity
281.1
Obviously, the variation among the four sources assuming 1980 prices
between $6.89 and $8 is much greater than can be explained by the variation
in price; in fact, the highest price goes with the largest quantity.
7-4
The world price will be the result of a struggle among several competing
On the one hand, the history of international
and opposing sets of forces.
cartels reveals an inherent tendency to develop excess capacity and for this
excess to lead to erosion of the cartel price; the basic task of the cartel
On the other hand, there are forces that
is to prevent this from happening.
determine the net demand faced by individual cartel members, and by the cartel
The difference is excess capacity; if it is small, then the cartel's
as a whole.
But to the extent that world demand is
discipline problem is less serious.
reduced by the high cartel price (either due to reduced demand or to increased
supplies from non-cartel sources) the task of cartel discipline is made more
there is no reason
In general
difficult.
for these
factors
to remain
in
balance over time, and so the resulting price is fundamentally unstable.
7.2.1
Faced by the Cartel
Net Demand
In the cartel model used in the FEA analysis, the net demand on the
cartel is simply the residual of world demand less the supplies from all
non-OPEC sources, as shown in Table 7.1.' On the demand side, the FEA and
OECD analyses represent about the best that can be done given the condition
of readily available data bases and analyses. Nonetheless, the results for
world demand in 1985 must carry a wide band of uncertainty. Moreover, the
path from the present to whatever the demand will be in 1985 will not
necessarily be a smooth one. At present, world demand is sluggish due to
recession in key industrial economies; during recovery the rate of demand
growth could be rapid, though no one can predict with confidence when this
may come or with what strength.
In the estimates of indigenous non-OPEC supply there are similar factors
that not only make
1975 estimates
uncertain
but also indicate
that the path
to 1985 may not be a smooth one. Take, for example, the outlook for supply
from those countries in Table 7.1 that have significant petroleum resources.
All the major
ones
(the U.S.,
Norway,
Canada,
and the United Kingdom)
petroleum industries that are essentially in private hands.
private
oil companies
do not respond
to real resource
have
Naturally,
cost in making
their
exploration and production decisions, but to pecuniary costs, or profits
after taxes. And therefore any estimate of likely future output is confounded
by two phenomena: new taxation and rising input prices.
Taxation. The incidence of taxes in the countries listed above varies
taxes to
greatly, but it is clear that it is possible for supplier country
cost
below
price.
render much production uneconomic despite real resource
of
special
problem
have
a
private
oil
sectors
with
In effect, the countries
managing
the adjustment
acceptable way.
This simple
to dramatically
increased
oil prices
in a politically
Even in conditions of unchanging price levels, costs vary
model has some limitations,
as noted
below.
i:1,
7-5
enormously from field to field and even within fields. Hence a price
sufficient to bring in production at the margin means very large profits
earned in low-cost fields. Under normal conditions this may be politically
tolerable, especially where the industry is well enough developed to make
it clear that while some fields earn enormous profits, others make equally
impressive losses, so that the prospective rate of return with which the
whole industry must operate is not necessarily higher than other industries.
In the circumstance of this past year, however, the old political
equilibrium has been disturbed, particularly in areas where there have been
striking successes in oil exploration. Expected production cost may be far
below oil price, and under pre-existing tax systems the return to private
corporations
can be very large.
Generally,
this result
has proved
to be
politically intolerable, and governments are taking steps to alter the tax
system
to capture
as large a portion
of these
rents as possible.
In the normal course of events, one would expect a government to attempt
some kind of graduated tax which would remove most of the "excess profits" but
not affect the scale of output. Crudely oversimplified, this would mean that a
project whose real resource costs were just equal to the price would pay a zero
tax, while a concern making a very large return would pay a much higher tax rate.
Whether such a system could be calibrated finely enough is an interesting question,
but not immediately relevant because it does not appear that this will be
accomplished in the near future in the countries at issue here. Taxes are
not that delicately conceived an instrument.
As a result of these tax changes,
it is quite
possible,
at least
in the
short run, for investment and production to decline as a result of higher
prices in the world market! And, in fact, the most probable estimates of
1980 and 1985 production from some of the most promising areas, particularly
1
the North Sea, are substantially less than would be reckoned by simply
comparing real resource costs with price. The same can be said of Canada;
the U.S.
response
is still
being
hotly
debated
in the Congress.
The Canadian case is an interesting example of how this process appears
to take place. Higher oil prices in 1973-74 resulted in windfall gains for
Canadian producers, and the response was a steep, per-barrel export tax. The
new tax apparently made production unprofitable for a considerable part of
Canadian output, for between March and December 1974 oil output dropped by 24%
from 1.9 to 1.4 million barrels per day. This change made the development of
new producing capacity exceedingly unattractive, which naturally led to a decline
in drilling activity; the number of operating rigs fell from 259 in March to 151
in December, a 48% drop in 9 months. (Meanwhile, the number of rigs operating
in the U.S. increased 20% over the same period.) A drastic decline in drilling
effort insures a corresponding decline in expected reserves. This appears to
have accentuated the fear or "running out of oil," and hence hastened a
restriction on Canadian exports to the U.S. This last step brings further
reductions in production and seems likely to lead to a continuing decline in
Canadian investment and production, at least on the short run.
7-6
These recent developments in national government policy would call for
a reduction in the OECD and FEA estimates of supply from these countries, for
the method
used in constructing
the numbers
shown
in Figure
7.1 does not take
these factors into account. On the other hand these restrictive policies
could change in a matter of months or weeks, again revising the outlook.
Rising Factor Prices. Over the past year, the prices of inputs to
energy supply industries have begun to rise much more rapidly than the
general price level. Evidence of the rate of increase is mostly fragmentary
or anecdotal, but it is impossible to doubt: in particular, project estimates
appear to be escalating at considerably more than 25% per year. Between
1969 and the end of 1973, the implicit GNP price deflator for non-residential
fixed private domestic investment increased by 22 percent. BLS indexes of
oil field machinery,
oil well
casing,
and line pipe increased
respectively
by 18, 27, and 29 percent, or only slightly more. But by December, 1974,
they were above 1969 levels by 60, 85, and 101 percent respectively. The
IPAA index for 19 important materials purchased rose 37 percent, payments to
drilling contractors by 33 percent, in 1969-1973; by late 1974, materials
prices were 64 percent above 1969 [30]. Obviously, the worldwide boom in
hydrocarbon exploration and development must be expected to result in higher
prices
of input
factors
in the short
run.
This is the natural
result of a
circumstance where demand for equipment and manpower rises rapidly but supply
can expand only slowly. Moreover, where some monopoly power is present it
is reasonable to expect this price pressure to be increased by the attempts
of factor suppliers (such as labor) to capture part of the windfall gains
resulting from higher oil prices.
It is not clear, however, what will happen over a period of five or ten
years, when there is time to expand the supply of input factors. In
competitive markets one would expect inflation-adjusted factor prices to
describe a parabola, first rising sharply because of immediate scarcity,
slacking, and then decreasing as bottlenecks are widened and supplies
became adequate, and eventually approaching a new equilibrium level no
higher than the old in terms of relative prices. Furthermore, one should
expect rather important learning effects, especially in offshore and Artic
technology which is now in a rapid state of evolution.
It may be, therefore, that FEA and others are correct in neglecting the
steep rise in factor prices in 1974 when analyzing events to take place out
to 1985. But the fact that this rapid price rise is taking place in the
short run does influence the calculations of oil companies and does affect
the path of development in response to higher oil prices.
As a net result, these changes in factor prices and tax policy, and
uncertainty about their future course, may have a strong influence on the
path by which world net demand for cartel oil will develop over the next
decade. They add to the uncertainty introduced by our lack of knowledge
of the true nature of the resource base worldwide, the rate of growth in
the world economy, and the lack of certainty about what world oil prices
7-7
will be year to year; taken together these influences provide the cartel
with a changing
7.2.2
environment
to which
it must
adapt
if it is to survive.'
Strength of the Cartel
Whatever the net demand for oil from the members of OPEC, there remains
the question of the mechanism of supply and price determination, for supply
definitely has the potential for outstripping demand at current prices,
creating
a world
oil surplus.
To be clear at this point,
it is necessary
to distinguish three kinds of "surplus." One is of actual current production
in excess of sales or consumption. Such a surplus cannot be maintained for
more than a very short period--weeks, or at best months--because it is
physically impossible to store more than a small percentage of the output.
The next concept is that of surplus capacity, i.e., resources developed into
reserves by installation of wells, gathering systems, and transport systems
which permit a given level of output without injury to the producing formations.
Finally, there is the concept of "supply potential" which indicates the amount
of productive capacity which would be renumerative to install, given the
resource endowment.
Cartel Production Capacity. The FEA estimates the supply potential of
OPEC as being 53.1 million barrels daily in 1985. Since current capacity is
not much under 40 million barrels, the estimate is conservative. However,
potential capacity will not be translated into actual capacity unless there
is a reasonable assurance of selling enough of the output at a good enough
price to return the investment. Where the investment requirements are very
low, this need not be a very strong
restraint.
For example,
where
requirements
are $300 per additional daily barrel, then at current Persian Gulf prices, the
investment would be paid back in 30 days. This would assure the maintenance
of a considerable cushion, if the prospective investors are governments who
receive all the prospective returns. Private companies, which bore the risk
but received only a modest fraction of the return, would have no such incentive.
1
The FEA supply figures do not take explicit account of either the Soviet
Union or China, very likely on the assumption that their effect on the world
scene will be small. Here too there is uncertainty, however. For the Soviet
Union it appears that oil resources can only be made into reserves to a limited
extent,
at rising
costs.
This does not seem to be the case with
natural
gas,
where the deposits are apparently very large, but where the limitation is in
available technology, manpower, and materials. If the pace of development were
stepped up, gas resources could serve as a very large scale replacement for oil,
both in the Soviet Union (releasing crude oil and products for shipment) and
also in Eastern and Western Europe.
Regarding China, there seems to be a general consensus that oil deposits are
very large and accessible without any unusual effort or expense, though rapid
development would require a heavy infusion of foreign technology and equipment.
Preliminary indications are that decisions have been made to go ahead with a
substantial oil program, and hence estimates of 2 to 4 million barrels per day
from China, much of it going to Japan, seem reasonable by 1980. By 1985 the
amount could be much larger.
7-8
At any rate, the FEA report has given a seriously misleading impression
in suggesting (doubtless inadvertently) that at current price levels the
OPEC countries will be faced by a huge buildup of actual operating capacity,
with
46% of the total in surplus
in 1985.
What
the calculation
does indicate
is a tendency to develop some level of excess capacity--an expectation that
is consistent with the events of the past year. At the end of 1973, OPEC
daily capacity was approximately 4 million barrels above actual production,
while at the end of 1974 a continuing buildup and stagnant output had brought
it to at least 8 million
barrels
daily,
as shown
in Table
7.2.
The table
presents end-1974 reserves, December output, and December capacity (the
difference being excess capacity), for Canada as well as the members of
OPEC. The production figures are fairly precise, capacity is at best an
approximation. Since roughly 10% spare capacity is needed to take care of
seasonal and irregular fluctuations, it would be nearer the truth to reckon
that the true excess was only about 1 million barrels per day (4 less 3) at
the beginning of 1974 and 5 million at the end. (February excess capacity
is estimated at 4 million barrels per day above that of December, about
12 million barrels altogether.)
It is possible to forecast the production capacity of these key nations
for only a short distance
into the future,
on the basis
of announced
plans
and observed drilling activity and commitments. And, once again, it is
possible for the outlook to change significantly over short periods of time.
For example, there is a general consensus that Iraq resources could be
turned into reserves at least twice as great as current (35 billion barrels)
and which could support a level of output three times current rates of
around 2 million barrels daily. Accordingly, the announced goal of the
government of Iraq of 6 million barrels by 1981 was taken to be altogether
feasible. The FEA projection of 4.8 mbd 1985 is therefore a very conservative
measure of potential. But Iraq had had great difficulty selling its oil
output, since only a minor portion is now transferred through the integrated
channels of the international oil companies. They could sell all their oil
at lower prices, but they have declined to do so. The trade press now
reports that the 1980-1981 goal has been scaled down to 4 million barrels
daily.
In Abu Dhabi,
the goal of 3 million
barrels
daily
in the late 1970's
and 5 million in the early 1980's has been abandoned, and there is a freeze
at the current
2 million
So although
barrels.
it is reasonable
to expect
there will be some
level of
excess capacity in the cartel at any time, there is need for much better
analysis
than has been available
to date in order
to forecast
the magnitude
and distribution of the excess for any distance into the future.
Cartel Discipline. The next key question, of course, is how discipline
is imposed on the cartel under current surplus conditions, and how the structure
of the group
is likely
to evolve
in the future.
As noted
earlier,
the FEA
analysis speaks of the cartel's success in terms of "internal organization and
discipline" and "cooperative effort." Although organization and cooperation
may become
important
issues in the future,
the cartel
does not now depend on
any multi-national production allocation agreements for its current success.
7-9
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7-10
At the present
time, the international
companies
still
appear
to play the
strategic role in limiting output and dividing markets.
Roughly 85% of world oil output still moves through the integrated
channels of these companies, and probably another 5-10% of the OPEC crude
oil is sold by them to independent refiners, public and private. These
companies themselves, reckoning the government take as a unit cost, produce
all they can sell. The companies need not communicate with each other, and
presumably do not. If therefore the producing governments are content to
accept the "solution" that emerges as the haphazard result of the companies'
sales positions, the resulting division of markets is quite stable.
The oil lifted
and either
sold or transferred
by the multinational
companies is proof against any substantial price reduction, because the
companies' margin is or soon will be very small. If their margin does not
exceed 30-50¢, the reduction they make for most favored purchases cannot
exceed some fraction of that amount. This is an additional reason why
maintenance of the multinational oil companies in place as sellers and
refiners of crude tends to insure the continued efficiency of the cartel.
The cartel may face real strain in the near future, however. Some of
the producing nations have truly nationalized, in the sense of investing
their own money
and selling
the oil.
All of them seem to feel a powerful
attraction towards doing so as an assertion of their control of their
resources,
though
there is conflict
on this issue
not just among
the cartel
nations but within every nation. To the extent that producing countries
market their output directly, the opportunities for discrimination increase,
and the cartel is faced with substituting some other form of quantity control.
Though there is little evidence to date of significant erosion, there
are several important channels for discriminatory sales which have been used
extensively in the past by the companies, and which bear watching today.
(1)
Credit
Terms.
As a rule of thumb,
if oil is worth
$10 per
barrel, and short-term interest rates are around 1 percent
per month, then each additional 30 days of credit is worth
10¢ per barrel.
(2)
Tanker Rates. Price discrimination can be achieved by quoting
artificially low tanker rates in order to reach lower delivered
price. With tanker rates from Persian Gulf to Western Hemisphere
or Rotterdam in the range between a low of about $.40 for shipment
in superabundant
VLCC's and a high of about
$2 for shipments
in
small tankers, the possibilities for discrimination would seem
to be as great as $1 per barrel.
1
Some price reductions are being reported, but they appear to represent
the elimination of excessive premia for sulfur and location advantages, with
no effect
on
the cartel
"marker
crude,"
i.e., Saudi Arabian
light.
7-11
(3)
"Downstream" Operations. Producers also can discriminate by
going "downstream" into refining and selling the crude as
products, whether manufactured at home or elsewhere. A
low-cost supplier going downstream could also make longerterm contracts with marketers of gasoline and with users
of heavy and light heating oils, and there are myriad
possibilities for price shading in these circumstances.
Other possible forms of discrimination include exchanges of crude oil
on terms which amount to a price reduction, and also joint ventures whereby
the supplier loans money or takes an equity position much larger than the
share of his receipts. Still another form of discrimination (potentially
the most important) is possible when the operating oil company is paid for
various non-oil services as well. For example, the Saudi Arabian Petroleum
Minister has indicated that Aramco has a profitable
future both in oil and
in non-oil
ventures..
It is easy to grant
a price
rebate to Aramco
in the
guise of higher fees for some non-oil service. A similar circumstance is
offered by the new 3-year sales contract between Kuwait and Shell. Nothing
has been revealed about the payments due Shell for the "commerical know-how"
and "training and other services" it is to provide Kuwait.
These possibilities for discrimination are important because even small
price reductions are a very efficient way of obtaining additional sales,
since they are so large in relation to the refining margin. Given the current
weakness in product markets, many refiners are losing money or barely
covering their variable costs. In the steady state, the U.S. margin
probably need not exceed $2 in order to pay an adequate return. With the
range, therefore, of margins under depressed and sustainable conditions, a
price reduction of 50¢ would make the difference between profit and loss
for nearly all refiners in the consuming countries.'
It is entirely possible that these various forms of discrimination could
grow into a major erosion of cartel price. In this event,'several possible
responses could be expected. There could be an attempt to organize an
allocation mechanism within the cartel to substitute for the role now being
played by the international companies. The history of international commodity
cartels offers a rich store of possible arrangements, though few actually
worked for more than a few years. Failing an effective group control scheme,
Saudi Arabia and other low-population oil-rich countries could take on the
role of balance wheel. Obviously the greater the excess capacity, the more
1
The possibility of producer-government discrimination also has a direct
bearing on security policy for the U.S. If an oil import tariff is enacted,
with an equalizing excise on domestic production, this affords a very strong
competitive advantage for any OPEC nation which wants to sell additional
quantities of crude oil. For example, if the OPEC nations produce approximately 30 million barrels per day in the near future, and market directly as
much as 20%, this would amount to 6 million barrels per day. On this portion,
or approximately U.S. 1974 total imports of crude and products, their power to
discount is unbounded. A tariff plus counterveiling excise may restrict total
consumption by raising the price to consumers, but it does not serve as an
effective barrier to imports.
7-12
severe must be the cutbacks, and there are unknown limits to the tolerance
of any given country. Rising expenditures, commitments, and expectations
tend to lower the threshold of retaliation. But under some conditions of
demand, OPEC and non-OPEC supply, and price, such an arrangement might
suffice for some length of time.
On the other hand, the cartel could collapse completely, even suddenly,
the price falling below $6, which is the lowest price given serious attention
in the FEA study.
In such an event,
attempts
to regroup
and reformulate
the
cartel would have begun even while the collapse was taking place; and if these
efforts were successful, the price could rise again.'
There are various hints, more prominent in the Executive Summary than
in the full text of the PIR, of the need for political cohesion among cartel
countries, or of some decisions being more political than economic. These
hints are too vague for analysis, and are perhaps an unnecessary complication.
The greater the exporters' revenues, the greater their political power, either
on the local or the world scene; hence political goals coincide with economic
ones and need not be made more explicit. Moreover, the willingness of the
Soviet Union to cooperate with cartels during the 1920's and 1930's shows
that even very strong antipathies are no barrier to cooperation.
7.2.3
Conclusions.
Several conclusions follow from this brief survey of the determinants
of the world oil price. First, the concept used in the PIR studies of a
"price path" of $6 or $9 per barrel
over
a ten year
potentially damaging simplification of reality.
on a "$6 world"
and a "$9 world,"
period is a serious
and
The PIR essentially focuses
and the uncertainty
that is dealt with
in
the analysis (albeit implicitly) had to do with the problem of not knowing
which of the two worlds will come about, and with the construction of means
of hedging against guessing wrong. This is not the same thing as worrying
about the implications of living in a "$10 world" with significant probability
that
it could shift
to a "$15 world"
or a "$5 world"
for a few years
and then
back to a "$10 world." The implications of this difference in viewpoint for
domestic supply alternatives, domestic taxation, and international trade
policy are evident.
Second, in a circumstance like this, a reduction or increase in demand
for world oil by any one country or even a group of countries will not
necessarily or even probably have any effect on the world price. This is
a persistent notion which shows up most notably in the PIR analysis of the
effect on world price of increased U.S. imports that might result from the
adoption
of a storage
program
[8, p. 390].
It is, however,
unsupported
analysis and appears unlikely.
1
Moreover, a successful cartel may deliberately cut price to chill
investment in conventional or new energy sources, only to raise it
again later.
by
y_-
·--
8.
8.1
LINKS TO THE PERIOD BEYOND 1985
The Period Until 1985
The PIR and the supporting Task Force reports recognize the restricted
potential for synthetic fuels and alternative energy sources. The report
assumes that under the accelerated supply case synthetic fuels could supply
1.5 million barrels per day by 1985. Two-thirds of this total will be products derived from oil shale. Even this limited contribution, however, could
prove to be overly optimistic.
Experience since the completion of the PIR has led to significant upward
adjustment in cost estimates. Table 8.1 reproduces cost estimates for the
synthetic fuels as of 1973. These estimates were done at MIT and are in
general consistent with the PIR estimates allowing 10% to 12% rate of return
[34, 17]. What has happened since then is illustrated by the experience of
the El Paso Natural Gas Company's coal gasification project. The 1973
capital cost estimate of Table 8.1 is 290-390 million dollars. By early
1975 the cost estimate had reached 1 billion dollars [28]. This large an
increase came about as earlier projections based on bench-scale data were
reevaluated in light of more recent experience. It is not unrealistic to
assume similar increases for the other synthetics. In short, the new technologies represent high-cost alternatives.
Uncertain environmental effects and regulations could further increase
costs. This is compounded by uncertainty with respect to oil prices. Only
if oil prices are expected to remain stable at high levels is commercial
investment likely to be forthcoming. Furthermore, many of the new technologies are unproven. Given these uncertainties, private investors will
demand high rates of return to justify the risk. The 15% allowed for in
synthetics in the policy simulations, and even the 21% return to oil shale
at $11/barrel prices, will be too low. Given the high capital intensity of
the technologies, total costs are very sensitive to the rate of return.
It is shown in Table 8.2 that a required rate of return of 20% increases
costs from $2.73 per million BTU to $3.06 in the case of pipeline gas.
Shale oil and gasification are the most advanced of the new energy
technologies. Uncertainties for less advanced technologies, such as geothermal and solar energy, are even larger. In light of these costs and
uncertainties, pre-1985 commercial development of a synthetic fuels industry or of other new technologies is unlikely. The present activity is
limited to gasification plants planned by regulated natural gas pipeline
companies. These companies are able to roll the high costs of these plants
into their rate base. The real importance of these energy technologies
lies in the post-1985 period. However, because of the long lead time involved
in both research and development, decisions made today will determine the
future options available.
4-
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8-3
Table 8.2.
Effect of Rate of
Return on Cost of Fuel
-
-
$/mmBTU),
-
-
-
M
Eastern U.S.
Rate of Return
Fuel
20%
12%
15%
2.46
2.73
- 3.56
Utility Gas
1.11
1.18
1.39
Liquid From Coal
1.81
1.97
2.48
Pipeline
Source:
Gas
[17], p. 35.
8-4
8.2
The Post-1985 Period
The PIR briefly touches upon the post-1985 period. It projects the
increasing importance of synthetic fuels and new energy technologies. Production of synthetic fuels is projected at 25 million barrels per day by
the year 2010. This scale of operation brings to the fore a series of
questions not considered by the PIR. But only if these questions are answered
in the next few years, will the transition to large-scale production of
alternative fuels be a smooth one.
The very high costs of these sources raises some fundamental issues of
technology assessment. However, the PIR provides no such consideration.
In the first instance, which technologies offer promise? These priorities
must be established in order to develop a coherent research and development
policy. Preliminary research at MIT, for example, indicates that present
high-BTU gasification processes might be too costly to be economic [28].
What should be the government's role in bringing these technologies to the
point of commercialization? What combination, over what time period, of
subsidies and research funds will be necessary? Concomitant with these
economic issues are a series of crucial institutional questions. For
example, is present R & D strategy artificially forcing the synthesis of
fuels in the form which is optimum, not from a long-range point of view, but
for current market structures? Can these new fuels penetrate the present
structure of the energy industries, or is a new set of institutions required
for their smooth introduction?
In short, the links from the pre-1985 period to that point in the
future when synthetic fuels will be used on a large scale are complex. They
involve a set of economic, technical, and institutional factors that receive
scant attention in the PIR.
Yet these issues have to be confronted now if
the transition is to take place.
In summary, the PIR is right about the
limited pre-1985 role of new technologies. And, in pointing to the importance in later periods of these fuels it serves to introduce a series of
unanswered questions of major importance to long-run energy policy.
9.
A key question
SUMMARY AND CONCLUSIONS
is whether
the PIES system was the best way to go about
analyzing the issues raised in the Project Independence studies. The PIES
structure, and the linear programming integrating model on which it was based,
was one of several
ways to set up the problem.
Alternatives
would
have
involved more use of econometrics and simulation rather than the optimizing
approach.
On balance, considering the many objectives the study was to serve, this
cannot be called an improper way to approach the task, although simplifications were called for at some point in order to allow time and funds to
investigate more fully some of the phenomena that are, in effect, assumed
away in setting up the study. For example, much might have been sacrificed
elsewhere in the analysis to develop some set of results on the following
issues:
- oil price controls;
- natural gas price deregulation;
- capital expansion problems in the electric power industry;
- the effect of possible environmental constraints; and
- the implications of fluctuating international oil prices.
Although key issues are yet to be analyzed, and many problems remain to be
ironed out, the method is worth pursuing.
Among the most critical aspects of PIES requiring further research are:
(1)
The supply estimates for domestic oil and natural gas are based
on a methodology that is only a minor improvement over the NPC
model on which they are based, and the results are heavily
dependent on the judgements of the analyst inputting the data.
This work should be replaced by a combination of econometric
models and engineering-geological analysis of this sector. Both
can make economic choice explicit and provide a structure for
testing and validation of forecasts. Engineering-geological
analyses are essential for improved cost and supply functions of
producing from existing oil deposits.
(2)
The demand estimation technique and interaction with the integrating model contain inconsistencies which lead to identifiable
biases in the final results. The three major problems are: use
of the two-level approach to estimate separate energy demands, use
of national demand equations for separate regional demands, and
9-1
9-2
lack of a BTU equilibrium for competing fuels. Given adequate
data, a better approach would probably be to estimate separate
regional demand equations, paying careful attention to fuel
availability and to the substitution possibilities for energy
over
(3)
a period
as long as ten years.
The conservation initiative evaluation is based upon a conceptually
sound procedure, which, however, was not adhered to in the results
presented
in the PIR.
Additional
work
is required
to develop
the
conservation assessment models to the point of inclusion in an
overall, improved demand framework.
(4)
The international assessment is little more than an adding up of
a set of judgemental estimates and contains no evidence of work on
the determinants of supply and demand or the mechanics of cartel
behavior. Several analytical approaches are in existence or under
development, and any further work should be based on some set of
models
of the behavior
of the key participants
in this market.
In effect, the study appears to have devoted the great bulk of its
resources to the domestic aspects of the problem, and applied
only a fraction to the international phenomena that are the cause
of the current problems and the driving force behind their evolution.
The key estimates of net imports of oil under various price conditions
are subject
to greater
uncertainty
than the PIR suggests.
To the extent a
net bias can be identified, it appears that thY-models and procedures used
by the FEA tend to overstate the net imports under various assumed price
conditions. This judgement is due to the combined effects of
- failure to take account of the effect of energy price on GNP
growth;
- problems in the demand model;
- judgements about likely sources of bias in the supply estimates.
On the other hand, to the extent that the price decontrol assumed in the
analysis does not come about, or the assumed growth or generating capacity
does not occur, or the level of development of synthetic fuels is not realized,
there are countervailing influences not accounted for in the analysis.
Finally, the analysis overstates the economic impact on the U.S. of
disruption in world oil markets, such as production cuts or specific embargoes. This bias would tend to overweight the economic costs of dependence
on imported oil. To the extent that this overweighting has a significant
influence
on policy,
it tends to lead the U.S. in the direction
a permanent embargo to minimize the effects of a potential one.
of imposing
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