Electronic copy available at: http://ssrn.com/abstract=2257675
Oil Price Drivers and Movements: The Challenge for Future Research
Hillard Huntingtona, Saud M. Al-Fattahb, Zhuo Huangc Michael Gucwaa, and Ali Nouria
July 2012 (Rev. April 2013)
aEnergy Modeling Forum, Huang Engineering Center, Stanford University, 475 Via Ortega,
Stanford, CA 94305-4121.
bKing Abdullah Petroleum Studies and Research Center, P.O. Box 88550, Riyadh 11672, Saudi
cPeking University, Beijing, 100871, China.
Huntington, Hillard, Al-Fattah, Saud M., Huang, Zhuo, Gucwa, Michael and Nouri, Ali. Oil Price
Drivers and Movements: The Challenge for Future Research (July 2012). Available at SSRN:
http://ssrn.com/abstract=2257675 or http://dx.doi.org/10.2139/ssrn.2257675
Electronic copy available at: http://ssrn.com/abstract=2257675
The complexity of the world oil market has increased dramatically in recent years and new
approaches are needed to understand, model, and forecast oil prices today. In addition to the
commencement of the financialization era in oil markets, there have been structural changes in the
global oil market. Financial instruments are communicating information about future conditions
much more rapidly than in the past. Prices from long and short duration contracts have started
moving more together. Sudden supply and demand adjustments, such as the financial crisis of 2008-
2009, faster Chinese economic growth, the Libyan uprising, the Iranian Nuclear standstill or the
Deepwater Horizon oil spill, change expectations and current prices. Although volatility appears
greater, financialization makes price discovery more robust. Most empirical economic studies
suggest that fundamental values shaped expectations over 2004-2008, although financial bubbles
may have emerged just prior to and during the summer of 2008.
With increased price volatility, major exporters are considering ways and means to achieve
more price stability to improve long-term production and consumption decisions. Managing excess
capacity has historically been an important method for keeping world crude oil prices stable during
periods of sharp demand or supply shifts. Building and maintaining excess capacity in current
markets allow greater price stability when Asian economic growth suddenly accelerates or during
periods of supply uncertainty in major producing regions. OPEC can contribute to price stability
more easily when members agree on the best use of oil production capacity.
Important structural changes have emerged in the global oil market after major price
increases. Partially motivated by government policies major improvements in energy and oil
efficiencies occurred after the oil price increases of the early and the late 70s such as the improved
vehicle fuel efficiency, building codes, power grids and systems etc. On the supply side, seismic
imaging and horizontal drilling as well as favorable tax regimes expanded production capacity in
countries outside OPEC. After the oil price increases of 2004-2008, investments in oil sands, deep
water, biofuels and other non-conventional sources accelerated. Recent improvements in shale gas
production could well be transferred to oil-producing activities, resulting in expanded oil supplies in
areas recently considered prohibitively expensive. The search for alternative transportation fuels
continues with expanded research into compressed natural gas, biofuels, diesel made from natural
gas, and electric vehicles.
Still some aspects of the world oil market are not well understood. Despite numerous
attempts to model the behavior of OPEC or its members, there exists no credible, verifiable theory
about the behavior of the 50 years old organization. OPEC has not consistently acted like a
monolithic cartel, constraining supplies to raise prices. Empirical evidence suggests that members
sometimes coordinate supply responses and at other times compete with each other. Supply-
restraint strategies include slower capacity expansions as well as curtailed production from existing
capacity. Regional political considerations and broader economic goals (beyond oil) are influential
factors in a country’s oil decisions. Furthermore, the economies of OPEC members as well as their
financial needs have changed dramatically from 1970s and 1980s.
This review represents a broad review of economic research and literature related to the
structure and functioning of the world oil market. The theories and models of oil demand and
supply reviewed here, although imperfect in many respects, offer a clear and well-defined
perspective on the forces that are shaping the markets for crude oil and refined products. Much
work remains to be done if we are to achieve a more complete understanding of these forces and the
trends that lie ahead. The contents that follow represent an assessment of how far we have come
and where we are headed. Of course, the entire world shares a vital interest in the many benefits
that flow from an efficient, well-functioning oil market. It is intended and hoped, therefore, that the
discussion in this review will find a broader audience.
Oil prices have fluctuated in a wild roller-coaster ride since 2004. Brent crude oil prices rose from
$29 to $38 per barrel (annual averages) between 2003 and 2004. They rose steadily until 2008,
reaching a record near $147 per barrel in July 2008. This price spike reflected extremely strong Asian
economic growth combined with geopolitical events. Prices collapsed below $33 within the next few
months, as the world economy spun downward into financial disarray. They spurted back to levels
above $80 per barrel in 2010 as the economy in Asia and elsewhere recovered (NY Times, 2011).
Additional upward price increases in 2011 beyond $100 per barrel were created by continued Asian
growth and supply uncertainty mounted with the Arab uprising and the Libyan disruption.
Continued fears about the financial system and future economic growth lingered in August 2011,
causing world oil price to begin retreating again.
These conditions have created massive uncertainty about where future oil prices will be
headed and what factors create these wild price movements. Peak oil arguments abound during an
era when non-OPEC oil production has increased only very modestly despite the record high prices.
Turmoil dominates the political landscape in the Middle East, fueling additional concerns about the
security of oil supplies. Most disconcerting to both oil producing and oil consuming nations has
been the “financialization” of oil, where financial motives and trading permeate oil transactions and
make physical markets appear less important.
This uncertainty creates very significant problems for major oil-consuming countries that are
trying to recover from financial disintegration. But it also raises important concerns for any major
oil-producing country with ample resources. Should it expand capacity to supply growing economies
and at what rate? How much spare oil capacity should it maintain to offset sudden oil-market
surprises--unexpectedly higher economic growth, political unrest in oil-producing regions or major
oil spills in offshore drilling areas? Fundamental factors should be important for both capacity
decisions, but the uncertainty discussed above has eroded the belief that these factors still operate in
the same way as they have in the past.
Capacity expansion influences both long- and short-run market operations. First, greater
capacity allows more future production to meet growing demand. These decisions require an
understanding of long-run market conditions. Second, additional capacity can also build surplus
capacity for market imbalances. These decisions require an understanding of short-run market
conditions. Although the distinction between the short and long run can often be ambiguous, we
define the short term to include horizons of three years or less.
Oil markets have never been easy to understand and projections of future oil prices have
never been consistently accurate. If fundamental supply-demand analysis and oil market modeling
have any benefits, it would appear to be in their ability to organize complex information efficiently
and to provide better understanding of how markets perform. For this reason, we emphasize these
characteristics rather than in their suitability for forecasting.
This paper briefly reviews what is currently known about fundamental factors influencing
the oil market and what are the apparent research gaps from the perspective of a major oil exporting
country. The discussion also includes various broad modeling approaches for representing these
factors. Section 2 focuses on factors that may influence the long-run world oil price path. Section 3
discusses factors that may influence the short-run price path. Section 4 highlights the role of the
world’s largest oil exporter playing in the oil market. Section 5 summarizes the main points with
2. LONG-RUN OIL PRICE DRIVERS AND MODELS
Oil represents a substantial proportion of global energy demand. As the world’s most highly traded
international commodity, oil will continue to play a large role in meeting energy demand in the
future. Over the long-run, the price of oil will be influenced by four large trends: global economic
growth, demand-side technological progress and efficiency gains, new alternative energy sources,
and the changing costs of production. The depletion of easily extracted resources is pushing
production to more technically demanding fields, lower-quality crudes, and more higher cost
operating environments. At the same time, dramatic improvements in technology are expected to
continue to reduce the cost of finding and producing these reserves. Government policies will
change with important impacts on the costs of both petroleum products and competitive energy
sources. Understanding how production, consumption, and the price of oil will change over the
coming decades is of vital interest to both oil-producing and consuming nations, with strong
implications for energy policy, economic growth, climate change policy, and international stability.
2.1 Oil Demand: Drivers and Trends
Generally speaking, when the world economy experiences growth, oil demand will increase. The
existence of this fundamental relationship is uncontested, but its strength varies between regions and
will in future be moderated by many factors with the potential to curb demand, such as fuel-saving
technologies, fuel-switching to different forms of primary energy, and policies designed to constrain
carbon dioxide emissions.
Much of the recent growth in global oil consumption (which rose by 1.5 percent per year
between 1985 and 2008) occurred outside the OECD nations. As a percent of world consumption,
the emerging nations’ share has grown from 37.6% to 44.5% over this period, and developing
economies are expected to continue being the primary drivers of the growth in global oil demand.1
The hypothesized energy and environmental Kuznets curve, which views investments in energy
efficiency as a luxury good that become more affordable and widespread as developing economies
mature and prosper, teaches us that continued strong economic growth in China and elsewhere may
paradoxically work to restrain the growth rate of demand—if only in the longer run.
2.1.1 Growth and industrialization
Per capita oil demand grows at the same rate as the economy in many emerging economies, so long
as other factors like prices do not change. Many countries are experiencing rapid increases in vehicle
penetration and ownership rates as incomes rise. Based on estimates as of 1973, oil income
elasticities exceeded unity throughout the developing regions of the world, and approached two in
the poorest nations. This implies that oil demand should increase at least as fast as GDP in the
developing world, holding constant energy prices and technical progress. In the poorest Asian
nations, oil demand should expand nearly twice as fast as GDP (Medlock and Soligo 2001; Van
Benthem and Romani 2009).
In contrast, per capita oil demand grows more slowly than GDP within the OECD, even
before the impact of potentially rising prices is factored in. Vehicle ownership per person has
stabilized and consumers are beginning to purchase alternative fuel vehicles in these countries.
Gately and Huntington (2002) estimate the long-run income elasticity to be 0.55 in the more mature
OECD countries, implying that oil demand may increase only about half as fast as GDP in the
industrialized portions of the world (again, abstracting from the impact of potential changes in
prices, regulation, and technology).
2.1.2 Oil demand and technical progress
Whereas pure price-substitution implies reversibility, technical progress that is induced by price
increases creates an irreversible and unidirectional effect that is not easily unwound, even when
prices return to previous levels. Several distinct processes drive technical changes that influence oil
demand. The first is ‘exogenous’ change that is largely unrelated to specific changes in the price of
oil or economic conditions. For example, airplane design incorporated significant improvements in
fuel efficiency even prior to the 1970s price shocks. In an ‘endogenous’ process, rising oil prices are
the specific incentive that drives technical change. Automobile companies, for example, revamped
their vehicle fleets after the 1970s to make passenger cars more fuel efficient and, even when oil
prices declined after 1985, those design innovations were never scrapped.
2.1.3 Alternative vehicles and competitive fuels
Limited historical evidence exists by which to measure the strength and potential of inter-fuel
substitution among competing fuels. In many countries, petroleum-based fuels appear to have no
strong or viable competitor for powering transportation. That may be changing as countries have
begun to make commitments to vehicles fueled by compressed natural gas, biofuels, and
electrification. Additionally, companies may increasingly pursue gas-to-liquid processes as a
technological option that substitutes relatively inexpensive natural gas for oil in the production of
diesel fuels. Energy security and climate mitigation policies may accelerate these oil-reduction
2.1.4 Demand response to oil prices
If future oil supplies are expected to be scarcer than today, future oil prices will rise and curb some
of the growth in demand. But, by how much? This question has probably attracted more of the
attention of energy economists than any other issue during the last few decades. A major conclusion
consistent with the findings of most studies is that the longer-run demand response to any gasoline
price increases that occur over the next twenty years is likely to be several times larger than the
short-term response that is initially apparent (Dahl and Sterner 1991; Goodwin, Dargay et al. 2004).
The response of consumption to price is the combined effect of many different decisions.
Utilization decisions impact the gasoline market by reducing traffic activity and the number of miles
driven by households. Over a longer period, household response to higher prices is also magnified
as the vehicle fleet is retired and replaced.
The price elasticity of oil demand seems to be declining lately within the United States, and
perhaps also more broadly within the OECD. Many countries outside of the OECD maintain large
fuel subsidies that impose a wedge between crude and product prices (Arze del Granado et al, 2010).
Removal of those subsidies, which have lately become quite expensive to maintain, would increase
fuel prices to the end-user and thereby reduce future oil demand. The lack of data and estimates for
the emerging countries limits our ability to foresee in more detail how these changes will influence
2.2 Oil Supply Availability and Costs
Despite significant gains achieved via enhanced oil recovery technologies, conventional oil supplies
are diminishing in many fields located outside of the Middle East. Development of unconventional
resources to offset this decline will be very important, but the cost, availability, and scale of
resources like Alberta's oil sands are as yet unknown. At the same time, oil supply prospects, even
from conventional resources, may improve in certain areas. New oil may be discovered in relatively
unexplored regions and reserve appreciation in known resource basins remains an important source
of new additions. Technical progress will probably continue to significantly reduce exploration and
development costs, as well as enhancing safety and security of operations that extend further into
frontier areas. Governments may reduce oil supply barriers by rolling back production royalties and
taxes, and by easing constraints on leasing and acreage.
2.2.1 Resources and geological availability
Oil resources are scattered across the globe in formations with very different characteristics. Based
upon its 2000 world oil assessment, the United States Geological Survey (2003) estimates 1,898
billion barrels of remaining conventional oil and natural gas liquids, excluding cumulative volumes
already produced. These geological estimates are based upon likely discoveries given oil prices and
available technologies prevailing in 2000.
These conventional resources are supplemented by considerably larger volumes of
unconventional resources—heavy oil, oil sands, and oil shale—that require specialized extraction
technologies and significant processing before the oil can be sold. Aguilera, et al (2009) estimate
that the combined volume of conventional and unconventional oil would last for 132 years if
production increased by 2 percent per year.
2.2.2 Resource costs
For economists evaluating market conditions, resource costs rather than total reserves determine
whether scarcity prevails. Many geologic estimates do not distinguish resources that are inexpensive
to extract from those that are much more costly to develop and produce. To fill this gap, a useful
concept is the resource availability curve, a schedule that represents the total known resource base
that could be developed at each successively higher cost level.
Aguilera, et al (2009) derive an availability curve for conventional and unconventional
petroleum resources. They estimate 7 TBOE (trillion barrels of oil equivalent) of conventional
resources and 4 TBOE of heavy oil, 5 TBOE of oil sands, and 14 TBOE of oil shale with average
production costs usually considerably higher than the comparable costs for conventional oil. The
cost estimates for these unconventional petroleum resources are very uncertain and subject to
change. To be useful, any long-run cost estimates should reflect production expanded to scale and
the considerable learning that will accumulate through experience in developing these resources. Oil
prices may well overshoot these long-run cost estimates during intervening years when the additional
unconventional sources are not large enough to meet growing demand.
2.2.3 Oil supply from competitive regions
Producers outside the major exporting countries are generally considered as competitive price takers.
Market prices must cover the marginal cost of producing the last unit of these supplies, including
both the direct expenses and the firms’ opportunity cost of drilling for oil rather than engaging in
another economic activity. If resource depletion is a factor, each supplier will also consider the
opportunity cost of current extraction relative to future production. At higher prices, firms can
justify exploring for and extracting more costly resources, and doing so earlier rather than later.
Two major trends are driving oil supply from regions outside of OPEC: the depletion of
reserves that are easy to extract and the improvement of oil exploration and production
technologies. The combined effects have led to an increase in mega-projects aimed at resources that
were formerly inaccessible, either commercially or technically. Such projects include the Alberta oil
sands, the deep water resources of the Gulf of Mexico, and the pre-salt deposits offshore Brazil.
The major oil exporters are sufficiently large to influence as well as respond to price. They have
market power. However, the extent to which market power has been exercised is less certain. The
previous empirical literature leaves many questions regarding the impact of decisions and actions
taken by OPEC. The data tend to support multiple competing theories, without definitively
excluding any particular behavioral model. Analysts choose their favorite hybrid; they seldom test all
versions. There is clearly room for additional research on the nature of OPEC, and its evolution.
2.4 Long-term Models
The long-run behavior of the oil market has received considerable study through the application of
computer models. Models can be classified by many different criteria, but we find it helpful to
distinguish structural models from computational models. Both approaches take at their core
fundamental microeconomic theories about the objectives, constraints, and behaviors of market
actors. These theories are distilled into a mathematical structure, allowing for interaction between
the actors within a specific market context. The primary distinction between the two categories is
the level of complexity and detail; computational models have significantly more detailed
representations of the market at the cost of model run time. They also have increased data
requirements, and may offer less straightforward interpretation.
Research into the formal modeling of the oil market began largely as a response to the oil
crisis of 1973. The initial goal was to understand the role of OPEC decision making and its impact
on market price. Since that time, as the oil market has changed and the research community has
become more international, structural models have been applied to analyzing a great diversity of
issues involving oil. The major structural approaches include simulation, optimization and game
In simulation models, the behavior of actors in the market is represented by a specific
function contingent on market conditions. This function can be based either on some rule-of-thumb
(such as a target price or target capacity utilization rule), or based on historical econometric estimates
of past behavior. Depending on the researcher’s focus, the behavior of different agents may be
described in varied levels of detail. In general, OPEC is given more complex behavior while non-
OPEC producers follow a simple supply curve, often one that exhibits constant price elasticity. Of
course, the researcher’s goal is to develop rules or functions that are descriptive of actual behavior.
In an optimization model, one agent (at least) actively chooses its behavior to maximize an
objective function (typically profit or welfare). For models of the oil market, the optimizing agent is
generally assumed to be OPEC, or some subset of the organization. OPEC chooses a level of
production to maximize the present value of profits while taking into account how the resulting
price will influence the decisions of competitive producers and consumers. While some models may
have sophisticated representations of the limits to the knowledge available to the optimizing agent,
in many cases the optimizer is given complete foresight of the future path of the market. With the
optimization approach, the researcher seeks to understand what a market player must do to obtain
his best outcome.
In game-theoretic models, two or more agents are assumed to have market power, or at least
some influence on each other’s welfare. They attempt to take actions that are optimal given their
anticipation of what each other will do. That is, each agent is assumed to take into account the
strategic behavior of other actors in the market. A game-theoretic approach may be useful when it is
necessary to explicitly consider the consequences of rivalry and competition between different large
players in the market—for instance when evaluating the incentive for individual OPEC members to
deviate from established production quotas.
Computational models share many attributes with structural models and are largely
distinguished by the sheer number of details included. The complexity of the models makes them
costly to build and maintain, and the level of detail makes it difficult to establish the impact of any
one model choice. However, computational models facilitate certain types of analysis that are not
possible with a structural model: detailed impacts upon individual stakeholders, specific
technological scenarios, and full policy analysis. Moreover, one approach to computational
modeling, so-called computable general equilibrium models, has been used extensively to investigate
fuel substitution opportunities and the broader energy sector impacts of global greenhouse gas
emissions policies. Computational models also facilitate the division of labor in the modeling effort
by dividing the project into distinct sub-modules.
Due to their cost and complexity, computational models are relatively scarce, but with
cheaper computer power they are becoming more common. Still, computational models are typically
confined to institutions such as the International Energy Agency and the Energy Information
2.5 Research Gaps in Long-term Oil Markets
While there has been significant effort representing the long-term behavior of oil markets using
models of all sorts, a great deal of work remains to be done. As new technologies are developed,
demand grows, new kinds of resources are exploited, and relationships in the market change, the
theories and models we apply to the oil market need constant re-evaluation. A few topics stand out
as significant open questions in our understanding of the long-term behavior of the market going
forward: demand behavior, modern OPEC behavior, producer welfare, and resource depletion.
2.5.1 Demand behavior
With the exception of the large computational models, most oil models do not have a very
sophisticated or detailed representation of the demand side of the market. (Understanding demand
dynamics would be useful not only in explaining recent price movements, but also in exploring the
impacts this degree of demand variation has on oil-producing nations. Marked variation, but
especially unpredictability, of demand presumably affects the welfare of producers, not just
consumers, and may change the nature of their capacity investment decisions. Three specific topics
in demand behavior stand out as needing more exploration: the high rate of demand growth in
developing countries, the asymmetric response of oil demand to price changes, and the role of
technology in altering the energy intensity of oil-consuming activities. )
Understanding demand dynamics can be useful not only in explaining recent price dynamics,
but also in exploring the impacts this demand insecurity has on oil-producing nations. Volatility in
demand will have impacts on the welfare for producers and will change the nature of their capacity
investment decisions. Three major topics in demand behavior stand out as needing more
exploration: the high degree of demand growth in developing countries, the asymmetric response of
oil demand to price changes, and the role of technology change in altering the energy intensity of oil-
2.5.2 Security and climate policy
Closely aligned with demand issues is the inclusion of other energy market dynamics that produce
viable substitutes for oil-based products for transportation. Governments are adopting policies to
accelerate the shift consumption away from oil through mandates, taxes and subsidies—all in
response to concerns about energy security and global climate change. To derive meaningful results,
the broadening range of available substitutes for petroleum-based fuels requires the simultaneous
evaluation of multiple fuel markets rather than oil-only analysis.
2.5.3 Modern OPEC behavior
In the late 1970s, OPEC was modeled by many to be a monopolist in the world oil market, and one
author once referred to it as a ‘clumsy” cartel (Adelman 1980). Models developed in late 1970s and
early 1980s examined a number of different theories regarding OPEC’s behavior and market power,
However, OPEC, and its members, have evolved through time and observations gleaned from the
1970s re now outdated.
In the most recent two decades, the global view of OPEC has changed. OPEC is no longer
considered definitively as a cartel that exercises market power by regulating output. Smith (2009)
suggests that OPEC has been restraining investment in new oil production capacity in recent years
and thereby has contributed to higher prices in a market with very rapid demand growth. Although
there is now less research effort to study OPEC’s behavior either econometrically or theoretically
than in prior years, there remains a need for new theoretical models describing OPEC, and these
models should be tested by the detailed data from recent years.
2.5.4 Producer welfare
Many of the market-power models treat OPEC production decisions as if they were made by a
profit maximizing firm or cartel. When trying to understand the impact of OPEC production
decisions on global oil prices and consuming nations, such a formulation may be an adequate
approximation of the decisions made by the organization. However, in reality as sovereign nations,
political as well as economic concerns drive decision making. Oil-producing nations may constrain
prices in order to maintain favorable relationships with other nations or may sell oil at a discount in
their home market to benefit domestic consumers. It may make more sense to view the nations as
maximizing welfare rather than maximizing profit.
Unfortunately, when moving from models that consider profit to ones that try to measure
welfare, modeling techniques increase in complexity and require greater information on the national
economy as a whole. While some models (De Santis 2003) have previously approached this
important question, a great deal of work remains to be done in this area.
2.5.5 Resource depletion
Oil reserves are finite and production will become more expensive and perhaps eventually hit a
‘peak’ (Hubbert 1962). It remains unclear when such a peak will occur and whether it will be based
on a lack of available resources or the lack of sustained crude oil demand. In fact, the threat of peak
oil has loomed over the horizon since the dawn of the petroleum age, but consistent resource
discoveries, unconventional resources and technological breakthroughs have so far managed to ever
expand oil supplies and may continue to mitigate crude resource scarcity for the foreseeable future.
As discussed elsewhere (Smith 2012), it is not even clear that a peak in the production of oil, if it
does occur, would be a harbinger of impending scarcity.
3. SHORT-RUN OIL PRICE DRIVERS AND MODELS
Generally speaking, conclusions regarding the short-run behavior of oil prices are even less settled
than our knowledge of the factors that drive long-term trends. In large part, this is due to the
relatively short history of investigation into short-run fluctuations, as well as recent changes in the
composition and liquidity of short-term oil markets that have only begun to be sorted out.
Modeling short-run changes in the oil market requires different techniques, depending upon
the specific issue under investigation. Financialization, in particular, has made the oil derivatives
market more liquid and perhaps influential, while the number of participants in financial markets has
increased because of hedging and investment opportunities. The use of high-frequency data may be
required to consider all of the relevant details in short-term models, but much of that data is not
available in the public domain. The primary goal of short-term models, of course, is to provide
better understanding of short-term price movements and to inform short-term forecasts. In contrast
with long-term models, short-term models do not usually seek what the future equilibrium path for
oil prices will look like. Instead, they attempt to forecast prices, or price changes, that are expected
to be observed in near future. This is typically attempted with the help of reduced form models that
estimate parameters of statistical models that best describe short-run price movements without
considering the fundamental forces of supply and demand. Short-term models also use the powerful
financial theories of arbitrage and risk-taking in the attempt to infer market expectations from
observed future prices.
3.1 Critical Observations
During the previous decade, the oil market experienced significant short-term upsets, the most
important of which was perhaps the boom-bust price cycle during 2008. That particular episode
challenged the ability of conventional models to provide adequate explanations and forecasts of oil
prices. Many studies have looked to find structural explanations, but there still is no consensus on
the underlying economic causes. In addition to the high levels of price, a higher level of volatility has
also been observed lately in the oil market. For the first time a change of $100 per barrel in only four
months was observed in oil prices (July to November 2008).
These trends are not limited to the oil market; financial activity and turmoil in commodities
markets in general have increased. The volume of investment in commodities index funds, overall
futures market trading activity (as revealed by the open interest in all contract maturities)2, and
correlations among commodity prices (as well as between commodities and equities) have all
increased significantly. Forward curves have at times become substantially flatter, indicating that
futures prices at varying maturity dates are now moving more closely with each other and with the
spot prices. But, financialization may act as double-edge sword. It increases market liquidity and
facilitates price discovery and risk management. However, it creates more opportunities for
unscrupulous traders who would attempt to distort and manipulate futures prices.
Against this backdrop, there appear two overriding challenges for the modeling community.
First is the need to examine whether, as some allege, futures trading causes “artificial” movements in
the spot price of oil, and if so, to trace out the expected remedial effect of alternative regulatory
2 Open interest at the close of each trading day refers to the total number of futures contracts that remain in force over-
night (i.e., not already closed or delivered). For each buyer of a futures contract there must be a seller. From the time the
buyer or seller opens a contract until the time it is settled, that contract counts toward open interest.
reforms. Second is to realize the hope that financial variables can be used to forecast future price
paths more accurately than on the basis of fundamental analysis alone.
3.2 Fundamental Drivers
Certain economic factors have played a fundamental role in recent price changes. Demand and
supply shocks, together with the continuous flow of news and uncertainty that surrounds them, are
the primary drivers underlying short-run oil price dynamics. The impact of these shocks is magnified
by the low elasticities of both short-run oil supply and demand. Hamilton (2009) demonstrates that
under specific assumptions about the elasticities of supply and demand, one can explain the 2008
boom-bust price cycle just by using fundamental supply and demand factors. A caveat is that the
price predictions drawn from such models are extremely sensitive to the specific magnitude of the
presumed elasticities. Nevertheless, short-term supply and demand drivers are believed to be able to
describe most of the observed price changes. This section reviews these fundamental drivers.
3.2.1 Short-term supply drivers
During 2005-2008 available inventories were depleted while major oil-producing countries held low
levels of spare capacity. Considering the inverse relationship between spare capacity and spot oil
prices and the inelastic supply in the short run, this has led to higher price levels.
Short-term supply shocks have also influenced the oil market. The Deepwater Horizon oil
spill in the Gulf of Mexico and the revolution in Libya are two recent examples of such events.
Consider first the deep water Horizon spill. The methods of obtaining liquid fuels are becoming
increasingly reliant on advanced and capital intensive technologies. From deep water drilling, to the
processing of oil sands, to advances in refining, the oil market is changing its risk profile. While
engineers are constantly working to perfect better control systems and reduce the chance of any
failure, the potential for damage from any single catastrophe is increasing. Besides, with the
increasing ‘lumpiness’ of production from the trend in production towards more complex
megaprojects, the supply impact of a single outage (or addition) is increasing, potentially leading to
more price volatility (Skinner 2006).
3.2.2 Short-term demand drivers
The short-run demand for oil is also relatively price inelastic. There are four main reasons for this.
First, oil consumption levels cannot change quickly due to the existing stock of vehicles and other
oil-using equipment. Second, in the OECD countries, oil consumption is less responsive to price
changes because the share of consumers’ energy expenditures as a fraction of their total incomes is
relatively low. Third, oil demand in developing countries is largely driven by steady income growth
and industrialization. And fourth, the demand impact of crude oil price changes are in many cases
offset by government subsidies or taxes.
Macroeconomic news also influences oil prices. As incomes increase and economies expand,
more energy will be used for transportation, heating, and cooling. Hicks and Kilian (2009) utilize a
direct measure of global demand shocks based on revisions of professional forecasts of real GDP
growth. They show that recent forecast surprises are associated primarily with unexpected growth in
emerging economies According to this line of research, markets have been repeatedly surprised by
the strength of this growth.
Furthermore, US foreign exchange and interest rates exert an influence on the price of oil.
The price of oil (in USD) increased by more than 600% from January 2002 to July 2008. The same
increase in terms of the Euro was less than 300%, as the Euro gained strength during that interval.
As this example suggests, depreciation of the US currency may lead or contribute to an increase in
oil prices (which are typically expressed in US dollars). Fluctuations in interest rates influence the
value of oil in the future relative to its value today, which can lead in turn to changes in production,
consumption and storage decisions. Interest rates also change the prices of financial derivatives
3.2.3 News and information signals
In financial markets, price is believed to reflect all publically available information and uncertainties
about the future, at least as a first approximation. Newly released information about future events
will have a proportionate impact on today’s price. All kinds of news are relevant: information
regarding the economic growth of different countries, the prices of other commodities, currency
rates, major countries’ stock market movements, and more. The flow of information can change
prices frequently and sharply. However, to have any impact, the news must be credible.
Previous research shows that not all announcements made by major players in the oil market
(OPEC, IEA, etc.) are credible. To better understand short-run price movements, it is important to
distinguish between relevant, credible announcements and ones that are ignored by the market. An
important step in conducting this analysis is to consider the incentives of the issuers of information:
specifically, whether those objectives are aligned with the truthful revelation of information. A
signaling framework and a forecast model can be used to simulate the effect of new announcements
and analyze their incentives.
3.3 Price Forecasting Approaches
Most short-term oil market models focus exclusively on oil price and its statistical time series
properties. In contrast, structural models explicitly specify and attempt to estimate the impact of
changes in oil demand and/or supply. This distinction means that short-term price models are
mainly limited to the task of forecasting, rather than providing economic interpretation of the sort
required for policy analysis. Despite the rather large number of recent short-term price models that
have appeared in the literature, significant opportunities remain for further study.
3.3.1 Reduced form models
Reduced form models take advantage of financial and structural data and employ econometric tools
to build a model and estimate its parameters. These models are usually applied to forecast a specific
variable (e.g. world oil price). They differ primarily in terms of the complexity of the statistical
structure that is assumed to fit the data. Three contrasting specifications have been used to study oil
price data: autoregressive moving average (ARMA), vector autoregression (VAR), and structural
vector autoregression (SVAR). Each approach has its own advantage and, at the conceptual level,
no one approach is superior to the others. Therefore, the choice among them should be dictated by
the observed statistical properties of the time series involved in the analysis.
If the reduced form models are applied for purposes beyond simple forecasting, however,
serious problems arise. These problems center on the concept and interpretation of “causality,”
which is a term that plays an often misunderstood role in many short-run time-series analyses.
Causality is, of course, central to the study of policy analysis. To be successful, policy makers must
be able to anticipate the consequences of their actions. Will trading limits cause volatility to
decrease? Will producing from the strategic petroleum reserve cause prices to decline? Etc. The
cause and effect implicit in these questions represents something stronger than the statistical
tendency of two variables to move together, which is no evidence that an exogenous change in one
will cause another resulting change in the other. Therefore, it is essential when contemplating short-
term forecasting models to understand that a finding of “Granger–causality,” which is based on
patterns of correlation, neither proves nor disproves that a fundamental causal relationship links one
variable to another. To the extent that fundamental “structure” is added to short-term in the form
of a SVAR, it is also important to keep in mind that the structure that is assumed to link the
variables in a causal chain is typically dictated by convenience, as when a diagonal pattern of variable
exclusions is adopted in order to permit the model to be solved recursively; or, when a priori
constraints are imposed on the size of key parameters to achieve identification of causal relations.
Of course, if the constraints are untested and inappropriate, so may be the causal relations.
In summary, short-term statistical models will continue to flourish, based in part on the
availability of additional high-frequency pricing data and in part due to increased scrutiny of financial
investors in the oil market. It will be imperative for both the producers and consumers of this
research to keep in mind the fundamental limitations of these time-series methods and to tailor their
inquiries to questions that can properly be answered with the tools at hand.
3.3.2 Financial models
Financial models are a somewhat newer brand of oil price models that extend statistical analysis to
some of the newer time series (futures prices and options) with guidance from relevant hypotheses
developed in the theory of finance.
Since options and futures contracts convey information about the future, they have been considered
as a first step in incorporating financial data in oil models. However, futures prices may include a
risk premium that varies through time, and therefore do not represent a simple expectation about
the price that will prevail in the future. It has been shown, for example, that “no change” forecasts
are more accurate than forecasts based on futures prices (Alquist, Kilian et al. 2010).
Pagano and Pisani (2009) document significant time-variation in the risk premium and use
the degree of capacity utilization in US manufacturing and oil inventory levels as proxies for this
variation. They demonstrate how one can find expected prices in the future based on the
combination of futures prices and the risk premium. Thus, if one could model and forecast the risk
premium, when combined with market data, it should be possible to obtain estimates of expected
prices in the future. Given the potential value of this ability, to producers and consumers alike,
further research into determinants of the risk premium seems warranted.
3.3.3 Structural/financial hybrid models
Hybrid models, combinations of structural and financial models, are motivated by the need to
produce short-term forecasts that are more consistent with supply and demand frameworks. These
models are calibrated to base-case forecasts of a long-term model, with outcomes that are adjusted
based on the flow of new market information and short-term economic responses. Relevant new
market information would include price observations from futures markets, forecasts in demand
growth, and supply shocks (e.g. the reduction in Libya’s production during 2011). Hybrid modeling
requires estimates of both short-term and long-term elasticities, with which to simulate price
responses. The model takes information signals as input and generates price and quantity paths as
output. In light of the Efficient Market Hypothesis, the market responds instantly to the new
forthcoming information. Further efforts to incorporate theories of commodities and storage might
lead to models capable of forecasting inventory changes and the movement of futures prices as well.
(See Routledge, Seppi, and Spatt (2000) as an example).
3.3.4 Modeling volatility
Market price volatility can be estimated either from backward-looking historical data or from
forward-looking financial derivatives using implied volatility (Szakmary et al. 2003). Indeed, even for
models where volatility is not of direct concern, a researcher might need to know how volatility and
price shocks lead to changes by consumers and producers. For example, the use and production of
oil is heavily tied to existing capital stock and capacity investments. Price shocks even over a
relatively short time frame can have lasting impacts on demand and supply for years to come
through their impact on capital investment. Monte Carlo methods and artificial neural network
technology could be applied to simulate supply and demand shocks and to estimate the benefits of
major producers adopting strategies that stabilize price—but that is all dependent on first developing
an understanding of how the use of excess capacity and stockpiles influences volatility.
3.4 Analytical/Theoretical Models and Insights
Financial aspects of oil markets are not well explored. Studies are still trying to confirm a range of
theoretical hypotheses about the operation of the financial markets and to identify the most
important financial drivers. These include models that do not try to simulate or forecast the whole
oil market; instead, using partial equilibrium or econometric techniques, they try to understand
short-term market movements more accurately and to distinguish among competing theoretical
During 2000-2008 when the oil prices were increasing, investments in commodities markets
also increased significantly. That triggered the question of whether the price rise of 2008 represented
a financial bubble of some kind. Brunnermeier (2009) defines a speculative bubble as characterized
by the following elements: (1) Prices are higher than the fundamental value; (2) A group of investors
buy the asset based on the belief or sentiment that they can sell it to others later with a higher price;
(3) Such beliefs or sentiments cannot be supported by fundamental factors.
Studies on the role of financialization can be categorized into two groups: conceptual models
and statistical tests. The former type of analysis consists of deductive arguments for accepting or
denying the hypothesis that an increase in financial activity will cause prices to rise more than what
fundamental factors would dictate, and the logical validity of these arguments rests solely on the
underlying assumptions independent of any empirical evidence. The latter type of analysis focuses
on quantitative relationships between trending variables to find statistical patterns of predictability.
A few studies cite conceptual arguments to advance the claim that excessive investment in
commodity index funds might have played a role in creating the bubble. But, conceptual analysis
alone cannot establish the strength or magnitude of the effect. Thus, additional empirical research is
needed to clarify the picture. Certain conceptual relationships remain so far rather inscrutable even
after they have been quantified. For example, Tang and Xiong (2010) find a link between increased
price correlations among different commodities and the growing volume of commodity index
investments. But there is no indication, theoretical or otherwise, that higher correlations are “good”
or “bad.” In any event, elevated correlations are not evidence of a “bubble.” Regarding the
possibility of a bubble induced by financialization, it is well to remember that price movements in
futures markets with rising index fund investment have not been uniformly upward (Irwin, Sanders
et al. 2009). Moreover, Headey and Fan (2008) show that prices of many non-financial
commodities—commodities that were not financialized—displayed similar dynamics as the
financialized commodities, despite having no influx of speculative financial investors. There is
considerable room for additional research into the price movements of all commodities, whether
financialized or not. The parallel movements suggest the presence of some common factors,
beyond financialization, and research is needed to identify and measure the influence of those
factors. It seems likely that any progress in this direction will depend upon a more complete
appreciation of the role of common demand shocks, inventories, and convenience yields.
3.5 Statistical Tests
Researchers commonly perform statistical causality tests to describe the temporal relationship
between speculators’ trading activity, oil price movements, and volatility. As noted above, these tests
using Granger causality establish causality not in a structural sense, but only confirm whether the
observed movement in one variable precedes the changes observed in another variable. The
difference is important: although one might move a picnic inside just before it starts raining, moving
the picnic doesn’t cause the rain. With that caveat in mind, and using non-public data, the
Interagency Task Force on Commodity Markets (2008) study the dynamic relation between daily
price changes and changes in the positions of various categories of traders. They find that some
trader positions can be predicted as a response to price changes but not the reverse. Sanders and
Irwin (2011) find evidence that larger long positions by index traders Granger-cause lower market
volatility. This result is contrary to the popular belief that index traders’ activities increase market
There is some additional evidence on the other side of the argument, and the conflicting
conclusions are an invitation to pursue further both conceptual and empirical research into the
causes of commodity price movements. One example is the group of studies that evaluate whether
statistical characteristics of oil price movements match the pattern of an explosive bubble. In
contrast with explosive bubbles that prevailed for several months in the copper and nickel markets,
Gilbert (2010) finds only weak evidence for an explosive bubble in the oil market, and that appears
to have endured for only a few days in July 2008. But, do we know what caused it, or why it
subsided? We also have a few studies that report some evidence, conceptual as well as empirical,
that financial activities were driving the oil price away from its fundamental value during 2008.
Although fundamental factors are important in his analysis, Einloth (2009) suggests that speculators
may have been building inventories from March to July in 2008, based upon evidence that spot
prices rose further after convenience yields had begun to fall. And, Singleton (2011) finds significant
empirical support that investor flows influenced excess returns from holding oil future contracts of
different maturities, after controlling for a number of other exogenous factors.
In summary, there have been many studies, but as yet no absolute consensus on the causes of
the oil price boom and bust of 2008. Although there exists only limited statistical evidence that the
price cycle represented a speculative bubble caused by an influx of financial traders, the matter
remains the subject of great debate among researchers, policy makers, and the general public. The
value of any further work that helps to clarify this issue would be substantial.
3.6 Prescriptive Models
Short-term modeling is a relatively new approach. Some studies have tried building a theoretical
framework for interactions between the financial markets and the physical markets. These
prescriptive studies usually simplify the details of the actual market and examine various phenomena
that would be expected to occur under certain conditions. Their main goal of this deductive
approach is to understand how the market works rather than forecasting or simulating with high
For example, Deaton and Laroque (1996) and Routledge, Seppi, and Spatt (2000) consider
storage agents in the commodities markets and determine how the levels of inventories should
change with uncertainty and how forward curves should behave in such settings. Routledge, Seppi,
and Spatt interpret the concept of convenience yield as an option that storage agents will exercise at
an optimal time. Allaz (1992) develops a generic commodity market model (1992) to demonstrate
that, depending on the relative strength of the hedging and strategic motives, a producer’s optimal
position in forward markets may be either short or long. Brandts, Pezanis-Christou and Schram
(2008) study of Cournot (quantity) competition and Liski and Montero’s (2006) inquiry into a
potential link between forward contracting and collusion are further examples. The stylized nature
of modeling that lies behind all of these studies invites extensions that explore the robustness of the
findings to more realistic depictions of the agents who trade in these markets.
4. THE ROLE OF SAUDI ARABIA IN THE GLOBAL OIL MARKET
The influence of Saudi Arabia on the global oil market is unchallenged. Saudi Arabia’s role and
decision parameters since the discovery and production of oil in the Kingdom have been determined
by different factors. Al-Moneef (2011) discussed this issue and highlighted four important factors.
The first factor is the size and production life of Saudi Arabia’s oil reserves. For the past fifty
years, Saudi Arabia has the world largest crude oil reserves; equivalent to 20% of the world’s proven
reserves. The second factor is the diversity of Saudi Arabia’s export outlets. Saudi Arabia is
exporting to the U.S., to Europe and to the Far East. This diversity of outlets (and crude types
exported) offers Saudi Arabia marketing flexibility and highlights the international consequences of
its policies. In addition, Saudi Arabia is exporting its oil from two domestic terminals to the world:
the Arabian Gulf, and the Red Sea. The third aspect is the Kingdom’s large crude oil production
capacity. Saudi Arabia maintains large excess capacity available to face supply disruptions and
demand surges. Saudi Arabia’s excess capacity in the past three decades since 1980 averaged 60
percent of OPEC’s (and of the World’s) excess production capacities while its share in OPEC’s and
the world’s production averaged 32 and 12 percent respectively during the period. This unused
capacity averaged 35 percent of Saudi oil production during the 1982-1990 period, 13 percent during
the 1990s and 14 percent in this decade. OPEC’s averages over these three periods were 17, 6 and 4
percent respectively. While the other OPEC members' excess capacities depend on market
conditions, Saudi Arabia made an official policy since the mid-nineties, of maintaining 1.5-2 MBD
excess oil production capacity at all times. Saudi Arabia’s role has been very useful to soften the
impact of major oil supply interruptions, such as the Iran-Iraq war, Iraq’s invasion of Kuwait, the
Venezuela crisis in 2003, hurricane Katrina in 2005 and the Libyan crisis in 2011. These actions
helped lessening oil market volatility and stabilizing oil prices. The fourth facet is the role of oil in
Saudi Arabia’s economy. For the past three decades, oil has represented 35% of Saudi Arabia’s
GDP, 84% of its government revenues and 90% of its merchandise exports. These rates explain the
high interdependence between the Kingdom’s domestic and international oil policies.
These four factors have pushed Saudi Arabia to develop its own oil industry, through its
national oil company Saudi Aramco. The latter was created through the purchase by Saudi Arabia of
the assets of the four American companies operating in the Kingdom. Saudi Aramco was entrusted
with the tasks of managing and developing the hydrocarbon resources of the Kingdom to achieve its
development objectives, execute the government energy policies and develop the technical skills in
Saudi Arabia’s oil policies are geared towards efficiency and sustainability, which involves
stable oil markets and an efficient oil industry able to play a leverage role in the oil sector. In the face
of environment uncertainties, Saudi Arabia is investing in research and development projects such as
research centers, universities and companies.
Regarding the role of Saudi Arabia in OPEC, it has been as equally important for OPEC as
OPEC has been for Saudi Arabia (as suggested by R. Mabro, Oxford Institute for Energy Studies,
2001) The role of OPEC and Saudi Arabia have both evolved in line with the market changes. Such
changes include the diversity of market players, the influence of the financial market on the physical
market, the energy policies of consumer countries, and the climate change as well as energy security
Since the influence of the financial market on the physical oil market is increasing, Saudi
Arabia acknowledged the new market reality and adopted a policy of urging the international
community to exert some regulatory oversight as well as transparency measures over means of
transactions in such markets. In order to stabilize the market, Saudi Arabia has been working with
OPEC and IEA to reach better predictability. The Kingdom is also promoting the strengthening of
the producer consumer dialogue, among other things by strengthening the role of the International
Energy Forum (IEF), created in 2003 and entrusting it to coordinate the Joint Oil Data Initiative
(JODI) to enhance the flow of timely and accurate oil data worldwide.
In the early 1990’s, Saudi Arabia realized that the challenges of climate change would add to
oil demand and supply uncertainties and integrated its climate change policy with its oil policy. Saudi
Arabia considers energy security as a two dimensions concern: supply security, that is: the
availability, diversity and reliability of energy supplies at all times; and demand security, that is: the
predictability, efficiency and growth of energy demand in line with economic growth.
Saudi Arabia is predicted to continue playing a dominant role on the global oil market. The
Kingdom will also continue its efforts to ensure sustainable oil supply to the world with stabilized
long term prices at reasonable levels. At the same time, it will go on with its investments in the oil
and gas sectors to ensure adequate supplies and sustainable economic growth. It will maintain an
excess capacity of 1.5 to 2 MBD at all times in order to face supply crises efficiently. Finally, Saudi
Arabia’s oil policy will be defined in dialogue with other producers and consumers in order to
address together the environmental, investment and price volatility challenges.
The complexity of the world oil market has increased dramatically in recent years and new
approaches are needed to understand, model, and forecast oil prices today. In addition to the rapid
financialization of the oil market, many fundamental structural changes have also affected physical
markets for oil. Financial instruments now communicate information about expected changes in the
underlying fundamentals much more rapidly than in the past, so the implications of both financial
and physical developments are clearly linked.
Casual evidence of the closer relation between financial and physical markets is everywhere.
The prices of long- and short-dated contracts have started moving more closely together. Sudden
supply and demand adjustments, such as faster Chinese economic growth, the Libyan uprising, or
the Deepwater Horizon oil spill, have changed expectations in ways that affect both current and
forward prices. Although volatility appears to have increased, financialization has arguably made
price discovery more robust and expectations more transparent. Most empirical economic studies
suggest that it was expectations regarding fundamental drivers, and their future trends, that shaped
prices during the 2004-2008 cycle, although over exuberant expectations cannot be ruled out
completely on available evidence.
With increased price volatility, major exporters are now considering ways to provide more
price stability, which is needed to improve long-term production and consumption decisions.
Managing excess capacity, primarily within OPEC, but also strategic stockpiles held by major
consuming nations, have historically been important factors for keeping world crude oil prices stable
during periods of sharp demand and supply shifts. To what extent would the expansion of excess
capacity alter market expectations in the current environment? And would the result be greater
price stability in the face of uncertainties regarding the rate of Asian economic growth, the debt
crisis in some EU countries, the restoration of Libyan production, heightened tensions between Iran
and the west, etc.? OPEC can pursue price stabilization strategies more effectively if both the
causes and consequences of volatility are better understood, and if OPEC members coordinated the
use of additional oil production capacity.
Within the context of long-term oil price drivers, the role of Saudi Arabia in the market is
quite important. Maintaining and expanding Saudi crude oil capacity, if undertaken, would provide
supply cushion to lessen oil price volatility. Unfortunately, one does not know the magnitude of
these effects because there is uncertainty about the parameters influencing supply and demand
behavior. History tells us that there have been periods when expansions in Saudi output stabilized
oil prices, for example, in 1991 during the first Gulf war. It also reveals that there have been other
periods when oil prices continued rising despite Saudi expansion (2008 leading up to the financial
crisis). In evaluating any decision regarding the use of excess capacity, it is important to know what
other factors are moving oil prices at the same time. Another important aspect of Saudi Arabia’s role
in the oil market involves continued oil exploration efforts and the development of new fields that
would allow production to keep pace with the growing global oil demand in the long run. Saudi
Arabia’s role also includes the availing of excess capacity that could be released immediately in
periods when oil shortages suddenly emerged in the market.
Apart from the short-run consequences of price volatility, we must learn from the important
structural changes that emerged in oil markets after previous major price increases, because similar
events are likely to happen again in the future. Partially motivated by government policies, the
automobile industry dramatically improved vehicle fuel efficiency in the mid- to late 1970s. Seismic
imaging and horizontal drilling in the early 1980s expanded production capacity in countries outside
OPEC. Recent improvements in shale gas technologies are now being extended to shale oil as well,
resulting in expanded oil supplies in areas recently considered prohibitively expensive. The search
for alternative transportation energy sources continues with expanded research into compressed
natural gas, biofuels, diesel made from natural gas, and electric vehicles. Which of these factors, or
others, will produce the next game-changing impact on the oil industry?
Many fundamental aspects of the world oil market remain unclear. After 40 years of
research, there exists no credible, verifiable theory about the behavior and influence of OPEC. It is
evident that OPEC members do not consistently act like a monolithic cartel. Empirical evidence
suggests that members sometimes coordinate supply reductions and at other times they compete
with each other. Output can be managed either by production in the short-term or by limiting
investment to expand capacity in the longer-term. Clearly, these are complementary strategies, but
how can or should they be coordinated? Regional political considerations and broader economic
goals (beyond oil) also must enter the calculations of each OPEC member country. These influences
have also changed rapidly as the economies of OPEC members have been transformed dramatically
during the past two decades, and financial needs for exporting oil now weigh heavily in their
This paper is based on research supported by King Abdullah Petroleum Studies and Research
Center (KAPSARC) contained in Energy Modeling Forum (2011a, 2011b), which contain a much
more extensive set of references than we could produce here. We would like to acknowledge the
careful comments and review on our previous work by Bassam Fattouh, James Hamilton, James
Smith, Fred Joutz, Majid Moneef, and Awwad Al-Harthi. We also benefitted from the valuable
advice from and discussion with John P. Weyant, Stephen P.A. Brown, James L. Sweeney and
participants at the Oil Metric Forum workshop in Washington, D.C. on September 16-17, 2010, and
the National Energy Policy Institute Conference on OPEC at 50: Its Past, Present and Future in a
Carbon-Constrained World in Tulsa, OK on March 23, 2011. All responsibility for the contents of
this paper belongs to the principal authors, and none of the views and conclusions can be attributed
to any of the above individuals or the King Abdullah Petroleum Studies & Research Center
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