Leave it in the ground? Incorporating the social cost of
carbon into oil sands development∗
Branko Bošković†
University of Alberta
Andrew Leach‡
University of Alberta
February 19, 2017
Abstract
We evaluate the impact of imposing the social cost of carbon on new oil sands projects.
Using data from recent oil sands projects and estimates of the social cost of carbon,
we estimate the minimum prices required to make these projects economically viable.
Our results indicate oil sands are a marginal resource before they incur any carbon
costs. The viability of oil sands then depends on the incidence of the social cost of
carbon, but projects are not likely viable, even under optimistic future price forecasts,
if producers bear most of the costs from life-cycle emissions. We also find an important
interaction between resource royalties and carbon charges: the impact of the cost of
carbon varies with where it is imposed across life-cycle emissions.
Keywords: climate change, social cost of carbon, oil sands
JEL classification: Q3, Q4, Q54
∗
We are grateful to Kirsten Smith for excellent research assistance. We thank seminar and conference
participants at Environment Canada, the Environmental Protection Agency, the University of Winnipeg, the
University of Calgary, Memorial University and the AERE Summer Meetings for comments and suggestions.
Financial support for this work was provided by the Social Science and Humanities Research Council of
Canada Insight Development Grant Program, Grant 430-2014-00275.
†
Alberta School of Business, University of Alberta, Edmonton, Alberta T6G 2R6, Canada (email:
[email protected]).
‡
Alberta School of Business, University of Alberta, Edmonton, Alberta T6G 2R6, Canada (email:
[email protected]).
1
Introduction
The Intergovernmental Panel on Climate Change (2014) estimates that only a small fraction
of existing fossil fuel reserves can be exploited under an emissions budget consistent with
stabilizing climate change at 2o C. Since estimated reserves reflect the quantities of fossil fuels
firms expect to extract in the near future, the IPCC findings suggest that the implications of
stringent future policies aimed at mitigating climate change have not been fully capitalized
into the expected profits of current fossil fuel investments. This disconnect has prompted
fears of a potential financial bubble in the fossil fuel industry, sometimes referred to as the
“carbon bubble.”
While we cannot test the rationality of expectations about future greenhouse gas policy
ex ante, we can examine the degree to which existing reserves are potentially at risk of being
stranded under future climate change policies. We examine a potential candidate for such
an impact – oil sands resources in Alberta, Canada – and test whether this resource would
remain economically viable under climate change policies that internalize the social cost of
carbon, an estimate of the present value of climate change damages from incremental carbon
emissions.
The Canadian oil sands represent an ideal case study of the viability of resource extraction under policy which internalizes the social cost of carbon on new development for three
reasons. First, oil sands have high production costs and, as a result, likely represent one of
the marginal resources in global oil supply. Second, oil sands production generates significant greenhouse gas emissions, and has become a focal point of domestic and international
opposition to activities which exacerbate climate change. Together, these cost and emissions characteristics imply that oil sands projects could be vulnerable financially if subject
to more stringent greenhouse gas policies. Finally, oil sands represent an abundant source
of oil reserves – 170 billion barrels of established oil sands reserves constitute 10% of the
world’s reserves (Alberta Energy Regulator (2016a); BP (2016)) – and so the conclusions we
reach could have important implications for eventual climate change mitigation and global
oil supply under carbon constraints.
We use a discounted cash flow model to calculate the levelized cost of energy from prototypical oil sands projects under carbon prices. We parameterize our model using oil price
forecasts and historic discounts for oil sands products along with cost and productivity
data from new oil sands projects that are currently under development as well as operating
projects. Our model accounts for costs associated with construction, maintenance, operation, and reclamation, as well as revenues from oil sales. We track life-cycle greenhouse gas
1
emissions across production, refining, transportation, and eventual downstream combustion.
Conditional on the extraction technology, an assumed opportunity cost of capital, and value
of the carbon tax, we compute the break-even or trigger price of oil such that lifetime present
value revenues equal costs and then compare this break-even price to existing and forecast
oil prices to evaluate the project’s viability. To quantify the effect of imposing the social cost
of carbon (SCC) on oil sands development, we use the Interagency Working Group on Social
Cost of Carbon (2015) (IWG) estimates, which are a product of an extensive meta-analysis
of existing studies. We impose these carbon costs through an emissions tax which we allow
to differ in coverage and point of application: we allow the tax first to cover production
emissions alone and subsequently to cover all life-cycle emissions, and apply the tax both at
consumption and at production sites.
Our analysis yields three principal results. First, our analysis confirms that oil sands
project are marginal and their viability depends primarily on the future price of oil. In
particular, the break-even prices for oil sands projects are above current oil futures prices,
implying these projects are not viable under current market expectations. However, oil sands
investments would more than recover their opportunity cost of capital under the more optimistic price projections developed by Energy Information Administration (2017), amongst
others. Given the uncertainty of oil price projections, we take these results as confirmation
that oil sands are one of the world’s marginal sources of oil.
Second, we find that internalizing the social cost of carbon has the potential to materially
affect the viability of oil sands projects. We first find that when the cost of carbon is applied
only to production emissions, the likelihood of a material impact on oil sands development is
small. Under Energy Information Administration (2017) price projections, the prototypical
oil sands project remains viable under the entire range of IWG-estimated SCC values, while
under current prices or those predicted by futures markets, the same project is unlikely to be
viable with any greenhouse gas emissions costs imposed. We find more significant impacts
when producers face some incidence of a carbon price applied to life-cycle emissions. When
the incidence of carbon prices falls on producers, the prototypical project we analyze is viable
only if the discount rate used to estimate the SCC is at or above 5%, while an SCC estimated
lower discount rate or an estimate admitting 95th percentile damage estimates would result
in a non-viable project. Thus, we argue that oil sands are potentially significantly exposed
to the so-called carbon bubble – their viability depends on an assumption of limited action
on greenhouse gases or on the costs of those actions being borne largely by oil consumers.
To our knowledge, ours is the first paper to incorporate the IWG-estimated social costs
2
of carbon into the levelized cost of production for any particular source of oil, and offers a
unique focus on emissions through the entire supply chain. Studies that have incorporated
the social cost of carbon into levelized cost estimates have focused mainly on different sources
for electricity generation. For example, Greenstone and Looney (2012) derive estimates for
several electricity generation sources, while Davis (2012) focuses on nuclear power and Baker
et al. (2013) focus on solar power. However, none of these studies focus on the entire supply
chain of inputs to production.
Third, we find that the viability of oil sands development depends on both the relative
incidence of carbon costs on producers and consumers as well as on the point of application
of the tax. The non-neutrality of the point of tax application is due to interaction between
resource royalties and carbon pricing. Specifically, when we apply a tax on life-cycle emissions
on oil sands producers, the impact on oil sands viability is more adverse than the same tax
applied downstream on consumers. This is due to an interaction between the royalties
charged by the government of Alberta on oil sands production and the price of crude oil.
Because royalties in Alberta increase with oil prices, costs which are passed-through from
producers to consumers increases royalty rates, thereby decreasing a project’s profitability
while if a tax is applied downstream on consumers, any costs passed on through lower crude
prices would result in lower royalty rates for producers and a more profitable project all else
equal. Our results in this regard add to existing literature on vertical targeting (see Bushnell
and Mansur (2011) and Mansur (2012)) and the application of border carbon adjustments
on imported fuels (see Fischer and Fox (2012)).
2
Model and data
To undertake our study, we rely on a discounted cash flow model of bitumen production facilities. We parameterize the model to represent the two most common production techniques:
(1) a bitumen mine using paraffinic froth technology, and; (2) an in situ bitumen extraction
facility using steam-assisted gravity drainage (SAGD) technology. Under recently-reduced
industry growth forecasts, mined bitumen production is expected to grow by approximately
680,000 barrels per day by 2035, from current levels of 1 million barrels per day, while production from in situ technology is expected to nearly double from current levels to 2.2 million
barrels per day by 2030 (Canadian Association of Petrolem Producers (2016)). For much of
the analysis, we focus on the in situ project since, even in the industry forecasts, no new
mines are expected for more than a decade – increased production is expected to come from
3
improvements at existing facilities and from facilities already under constructions. However,
we include prototypical mine data for context.
For a given project type, the net present value profit function for an oil sands project is
given by:
Π(Pb , Q, C, K, R, τ, O) =
t̄
X
t=0
1
Pb,t Qt − Kt − Ct Qt − Rt − τt .
1+r
(1)
The key parameters that determine the net present value include revenue from the sale of
bitumen, Pb,t Qt , facility capital costs, K, and operating costs, C, resource royalties and
corporate taxes, R, and carbon policy costs, τ . Each of these revenue and cost streams is
discussed in detail below.1
We report two metrics for project financial viability: internal rates of return and the
levelized cost of oil production, or the trigger price at which a project earns a 10% aftertax rate of return. For our internal rate of return calculations, we solve equation (1) for the
discount rate, r, which leads to a net present value of zero, conditional on project parameters
and oil prices. For levelized costs, we set r to 10% and solve for the constant real dollar
oil price that results in a net present value of zero. This levelized cost is best thought of
in the spirit of the trigger price in Mason (2001) – the expected future oil price at which
an incremental oil sands development would return at least the risk-adjusted opportunity
cost of capital. We also report average real dollar cash flows over the life of the project to
emphasize certain dynamics at play.
The model allows us to assess the impacts of greenhouse gas pricing applied at various
points in the supply chain on the economic viability of oil sands production.
2.1
Data
We use a combination of data from projects operating and currently under construction
to represent state of the art oil sands technology. Where possible, we rely on aggregate
information compiled for multiple projects. Parameter values for the in situ oil sands project
are reported in the first column of Table 1, and are based on data from the Kirby North in situ
project that is under construction, owned by Canadian Natural Resources Limited. Since
the project is not at full production capacity, we use extrapolated performance data based
on top quartile performance for existing facilities from Alberta Energy Regulator (2016c),
1
Where we can do so without confusion, time subscripts have been eliminated.
4
assuming that the project uses 2.5 barrels of steam per barrel of oil produced and that
steam is generated using natural gas in simple cycle steam generators. The second column
of Table 1 reports parameter values for the bitumen mine project. These values are based
on data from the Fort Hills project also currently under construction and majority-owned by
Suncor Limited, supplemented with actual performance data from Alberta Energy Regulator
(2016b) for the Kearl oil sands project, which uses similar technology. Fort Hills and Kearl
are typical of a new generation of mines that will ship diluted bitumen directly to market
without the need for a purpose-built upgrader to produce synthetic crude.
The top-left of Table 1 reports the production and cost parameters for each type of oil
sands project, followed by the production greenhouse gas emissions. Notable differences
between the two projects are the production capacity, measured in barrels of bitumen per
day and the time horizons for the projects. The in situ project is smaller at 40,000 barrels
per day, takes three years to build, and production increases over the next three years to
reach full capacity in year 6, after which it operates for 27 more years before being shut
down and reclaimed. The larger-scale mine produces more than four times as much bitumen
at full capacity, begins production in year 4, reaches full capacity after two additional years,
and has a 50 year lifespan. Combined, these imply that cumulative production from the
mine is almost 10 times greater than the in situ project.
Project cost parameters, shown next in Table 1, confirm that oil sands projects are
expensive to build and operate. The cost to build an in situ facility is $1.44 billion, while
construction costs for a mine are vastly greater, both on a cumulative and per barrel per
day of production capacity, at more than $12 billion. Per-barrel maintenance costs for in
situ and the mine amount to $5 and $3 respectively. The third row of the panel reports
operating costs, which include the labour, energy and other costs associated directly with
production activities – $10 and $16, respectively, for the projects. Maintenance capital is
fixed on a per-barrel basis at $5.00 per barrel for the in situ site and $3.00 per barrel for the
mine, while ongoing capital investment necessary to maintain production is estimated at a
further $9.00 per barrel for the in situ site and $6.00 per barrel for the mine. Reclamation
expenses, including activities to remediate environmental damages, are estimated at $0.25
per barrel for both projects.
These project parameters provide an important sense of the scale and timing issues that
differentiate oil sands from other unconventional production, such as the US light tight oil
which has become so prevalent since 2010. In comparison, a typical light oil well in North
Dakota’s Bakken field might cost $6-8 million to drill and complete, and $15-40 to operate,
5
Table 1: Basic model parameters for mining and in situ projects
with roughly half of the cumulative oil ever to be produced from the well produced in the
first three years, before either oil sands project would have produced its first barrel (Energy
Information Administration (2016a), Energy Information Administration (2016b)).
The bottom half of the left-side panel in Table 1 reports greenhouse gas emissions intensities and policies by project type. Both project types have significantly higher extraction
emissions than conventional light crude oil, which translate to higher life-cycle emissions.
The sum of production, transportation, refining and combustion emissions from the mining
project are 535.4 g/bbl of bitumen produced compared to 574.5 g/bbl for the in situ project,
compared to approximately 500g/bbl for light, conventional crude oil (see Brandt (2012);
Jacobs Consultancy (2009); Charpentier et al. (2011); Bergerson et al. (2012)).2 Given their
respective production capacities and lifetimes, the in situ and mine projects produce about
25 million and 125 million tonnes of cumulative greenhouse gas emissions respectively.
The right hand side of the table specifies the exogenous time trends and fiscal policy
parameters used, as well as the allocation of capital expenditures of each project to different
tax expenditure pools. Because the in situ project relies on drilling wells, a greater share of
the expenditures under this project receive a different tax treatment under the Canadian oil
and gas development expense.
2
Bitumen produced at either facility will have identical emissions downstream of production, so any
differences in emissions are due to production technologies.
6
2.1.1
Prices for oil sands bitumen
Whether calculating the internal rate of return, conditional on price forecasts, or the levelized
cost of oil sands, conditional on the discount rate, it is critical to account for how prices for
oil sands products are determined. Oil sands projects produce bitumen, an extra-heavy
oil that generally does not flow freely at room temperatures.3 In order to model oil sands
project revenues, we develop a relationship between benchmark oil prices (we use US West
Texas Intermediate) and oil sands bitumen value at the production site. Oil sands bitumen
is valued at a discount to benchmark light crudes for both quality and geographic reasons. In
order to ship a barrel of bitumen to market, a much larger amount (usually approximately 1.5
barrels) of diluted bitumen must be shipped, and the diluents used for shipment are generally
higher-value natural gas condensate or natural gasoline. In addition to the added total
volume, diluted bitumen has the pipeline properties of heavy crude and so is charged higher
transportation tolls per unit volume than lighter crudes. Once shipped to a refinery, bitumen
or bitumen blends have lower-value yields than comparable volumes of light crudes and must
be processed using more complex, thermal cracking refineries (Nimana et al. (2016)). Thus,
we would expect long term basis differentials to reflect both the reduced value to refineries
and the increased costs to transport oil sands bitumen. As we describe below, instead of
assuming a linear relationship between the price of West Texas Intermediate (WTI) oil and
the value of bitumen, we present a complete derivation of the pricing relationships. From
doing so, we can more accurately translate impacts of carbon pricing through to the revenue
from production as well as accounting for royalty implications.
To model the revenue from oil sands production in a world with prices on carbon, we begin
with the US dollar price of West Texas Intermediate at Cushing, Oklahoma, Pw , adjusted
for carbon policy impacts by the incidence, ψ, of downstream emissions taxes, tc , applied on
refining, combustion, and transportation emissions for light oil, Ed,l . Higher carbon prices
are expected to lead to lower net light oil prices for producers over the long term, although
the combined impact of both production and consumption carbon prices on oil prices is not
clear. This US-based price for light oil is then adjusted for transportation costs, Tc , and
exchange rates, Fx , to determine the price of light oil in Canadian dollars at the Canadian
3
Some oil sands bitumen is upgraded at the production sites to a synthetic crude oil, which is then shipped
without requiring dilution. Since most new production is expected to be shipped as diluted bitumen, we
focus on it here.
7
trading hub of Hardisty, Alberta, Pc :
Pc =
Pw − ψtc Ed,l
− Tc .4
Fx
(2)
The price of diluted bitumen, Pd , which generally trades comparably to heavy oil blends
at a discount to light oil, is determined in our model as a discount, DH , to light oil. Oil sands
diluted bitumen also has higher processing emissions and so we adjust the price differential
accordingly for potential downstream carbon prices as:
Pd = Pc (1 − DH ) − ψ
tc
(Ed,j − Ed,l ),
Fx
(3)
where (Ed,j − Ed,l ) represents the incremental emissions from combustion, refining, and
transportation from a barrel of diluted bitumen relative to light oil for bitumen produced at
each project type j, where j can be either the mining or in situ project.
Finally, in order to derive a value for bitumen, we need to value the diluent used to blend
bitumen. Let Pp represent the premium for natural gasoline over light crude, a premium
which has averaged 8% over the June 2011-June 2016 time period. The implied value of
bitumen at the production site, Pb , is determined as a function of the dilution ratio, φ,
typically about 30%, the cost of diluent, Pp , the cost of transporting diluent from the trading
hub to the production site, Tp , and the cost of shipping the diluted bitumen from the
production site to the transportation hub, Td .
Pb =
Pd − Td − φ(Pp + Tp )
1−φ
(4)
The relationships described in Equations (2 – 4) determine the value of bitumen at the oil
sands facility as functions of quality and geographic discounts, the Canadian dollar exchange
rate, and the ratio of dilution of bitumen for transport.
In our analysis, we rely primarily on two WTI price series: the U.S. Energy Information
Administration (2017) forecast to 2040 and NYMEX futures prices for 5 years sampled on
November 21, 2016, each escalated at 2% inflation beyond the forecast horizon. We refer to
these as EIA and Current Prices in the paper. The predictions of our parameterized pricing
model using forward curve pricing relative to historic averages are shown in Table 2. The
discounts in Table 2 are lower than long term averages, as the congestion that affected the
4
We need to track the relationship between these prices because oil sands royalties are based on the US
dollar price for WTI at Cushing converted into Canadian dollars.
8
Table 2: Historical and modeled price differentials for Alberta bitumen and diluted bitumen (approximated by the price of the Western Canada Select blend) relative to West Texas Intermediate
pricing. Historical prices from Bloomberg.
North American pipeline network and contributed to larger differentials between 2010 and
2014 (see Oliver et al. (2014), Borenstein and Kellogg (2014)) no longer exists. We implicitly
assume in our benchmark scenarios that pipeline networks remain uncongested. Our forecast
pricing relationships are also generally consistent with forecasts used to evaluate the reserves
of publicly-traded Canadian firms. For example, in the Sproule - Worldwide Petroleum
Consultants (2016) forecasts used to value reserves for Suncor Energy, the largest Canadian
energy company, they assume heavy oil discounts relative to WTI of approximately $16
per barrel between 2020 and 2025. However, these are under a much more bullish pricing
assumption for crude, as Sproule sees WTI prices climbing to $87.50 per barrel by 2025 while
futures market prices remain just above $60 per barrel for the same time period. As such,
in percentage terms, the discounts proposed by Sproule are lower than ours.
Natural gas prices are important input costs, particularly for the in situ project. We also
use Energy Information Administration (2017) and forward curve prices for natural gas, with
a real-dollar discount of $0.50/mmBtu between Alberta prices and Henry Hub prices. The
Alberta Energy Regulator (2016d) and National Energy Board (2016) forecasts that we use
in the paper have associated natural gas price forecasts that we use directly. Where we rely
on crude oil price forecasts from Energy Information Administration (2017), International
Energy Agency (2016a), and McGlade and Ekins (2015), we use forward curve pricing for
natural gas.
Finally, the exchange rate into Canadian dollars is an important determinant of profitability and the adjustment of the Canadian dollar with oil prices provides an important
revenue shock absorber to Canadian oil sands. For forward curve pricing, we rely on the
current futures price for the Canadian dollar to US dollar exchange rate, and assume those
to be constant after the 60 month horizon. The Alberta Energy Regulator (2016d) and
National Energy Board (2016) forecasts that we use in the paper have associated Canadian
9
dollar forecasts that we use directly. Where we rely on crude oil price forecasts from Energy
Information Administration (2017), International Energy Agency (2016a), and McGlade and
Ekins (2015), we use an interpolated value for the Canadian-US dollar exchange rate. This
interpolation is derived using a second-order polynomial approximation of the relationship
between real US dollar West Texas Intermediate prices and the Canadian dollar exchange
rate from 1996 through 2016, with the coefficients from this approximation used to forecast
the exchange rate out of sample.
2.1.2
Policies: carbon regulations, royalties, and corporate taxes
The base case for our study includes the current climate change regulation imposed on
industrial greenhouse gas emissions, the Specified Gas Emitters Regulation, as well as the
proposed changes suggested in the Government of Alberta’s 2015 Climate Leadership Plan.
The current regulation requires facilities to reduce their greenhouse gas emissions intensity
by 20% relative to a facility-specific target based on either observed intensity in the third
year of operations or the 2003-2005 average emissions intensity, depending on whether or not
the facility was in operation prior to 2001. Facilities that exceed their emissions-intensity
requirement must return to compliance with the regulation either through the purchase
of regulated emissions offsets, the purchase or transfer of emissions allowances from other
facilities that have exceeded their emissions reductions requirements, or through a payment
to the government in the amount of $20 per tonne in 2016 and $30 per tonne in 2017. After
2017, and before first production from any new projects, the system will evolve from facilitylevel reduction requirements to industry-level output-based allocations of emissions credits,
with the balance of emissions subject to a price of $30 per tonne, which is currently not
legislated to be indexed to inflation. The oil sands benchmark for output-based allocations
is proposed as top quartile performance for in situ and mining operations respectively. We
augment this base case with policy cases in which a carbon tax is applied to carbon emissions
from oil sands production and, where appropriate, to incremental emissions associated with
oil sands processing and final combustion of refined products.
Fiscal policy for the oil sands occurs in two stages – provincial resource royalties are calculated first and then corporate taxes levied by both the provincial and federal governments
are calculated on profits ex royalty.
The oil sands royalty regime depends on the price of WTI oil converted into Canadian
dollars, which we denote as Pw,t . The regime itself is a two-stage system. Initially, firms
pay a royalty rate, Rg (Pw,t ), on gross revenues. During this stage, the project has not
10
yet reached “payout”, defined as the point where the project has earned a cumulative rate
of return on invested capital equal to the long-term government bond rate, rg . Once the
project has reached the payout state, firms pay the maximum of the gross revenue royalty
rate, Rg (Pw,t ), or a higher rate net-revenue royalty, Rn (Pw,t ). The two-equation system
describing this royalty regime is given by:
Ot =
Rt


 1 if Pt
t=0
1
1+rg
Pb,t Qt − Kt − Ct Qt − Rt (Ot ) − τt ≥ 0 or if Ot−1 = 1

 0 otherwise
= Ot max Rn (Pw,t ) Pb,t Qt − Kt − Ct Qt , Rg (Pw,t ) Pb,t Qt
+(1 − Ot )Rg (Pw,t ) Pb,t Qt .
(5)
(6)
Ot is equal to 1 if the project has reached payout, which is an absorbing state: a facility
cannot return to pre-payout even if future earnings are such that cumulative returns fall
below the government bond rate.
The equations linking oil prices and royalty rates are linear between minimum and maximum values, and are given as follows:



.01 if Pw,t < $55/bbl


Rg (Pw,t ) =
0.01 + 0.08 (Pw,t65−55) if $55/bbl ≤ Pw,t < $120/bbl



 0.09 otherwise


 .25 if Pw,t < $55/bbl


Rn (Pw,t ) =
0.25 + 0.15 (Pw,t65−55) if $55/bbl ≤ Pw,t < $120/bbl



 0.40 otherwise.
(7)
(8)
The gross revenue royalty is at least equal to 1%; when the price of oil is between $55 and
$120 per barrel, the rate increases from 1% to 9% linearly with the price of oil and remains
9% for prices above $120/barrel. The net-revenue royalty, Rn , is 25% when the oil price
is less than $55/barrel, and increases linearly for prices above $55/barrel until it reaches a
maximum of 40% when the price is above $120/barrel.
The system thus provides for significant hedges against increases in operating costs,
including those imposed via carbon taxes, as well as against decreases in net revenues that
may arise from downstream carbon prices. A carbon charge applied across the supply chain
11
would lower the royalty rate if the carbon policy led to lower oil prices than would otherwise
occur, and would also lower the royalty base by both reducing revenue and increasing costs of
production. This implied risk sharing between the resource owner and the project proponent
is important to our later results.
Corporate taxes are payable on profits ex royalty with capital costs deducted over time
according to a declining balance schedule. In each year after production begins, firms may
deduct a percentage of cumulative capital expenses, net of previous deductions, from taxable
income. We divide capital expenses into two potential pools with different treatments. For
the Capital Cost Allowance pool, firms deduct 25% of cumulative un-deducted capital expenses in each period, while the Canadian Development Expense Pool allows 30% deduction
of cumulative, not previously deducted expenses. The shares of total capital expenditure
allocated to each of these pools varies by project type, with the breakdown given in Table 1.
3
Oil sands viability, the social cost of carbon, and
carbon cost-sharing
In this section, we report results from parameterizing our model using the data described
above. We provide three sets of results. First, we report viability metrics for oil sands under
current policies and prices, which we refer to as our baseline scenario. Second, we report the
effects of different values of a carbon tax, which include the social cost of carbon. Third,
we distinguish how these effects differ with the point at which the tax is applied. We report
each in turn.
3.1
Baseline results
Table 3 reports viability estimates, with a breakdown of revenues and costs, of oil sands by
technology under current greenhouse gas policies and two different price scenarios. In the
first price scenario, we report estimates based on November, 2016 futures market prices. In
the second scenario, we report estimates based on price projections by Energy Information
Administration (2017).
The first row of Table 3 reports the internalized rate of return for each project type
and price scenario. In the first column, current prices generate a rate of return for the in
situ project of 7.65%, while the mine does not achieve a positive rate of return. These
returns indicate that, given values for current prices and policies, new oil sands projects are
12
marginal investments at best – the expected revenues from oil production reflected in oil
futures markets are not sufficient to sustain reasonable returns on investment.
Table 3: Oil sands project model results
The Energy Information Administration (2017) price projections, shown in the right-hand
columns of Table 3, generate more favourable rates of return for both oil sands projects. The
rate of return for the in situ project is 14.8% – above conventional hurdle rates for investment.
In comparison to the return under current prices, the Energy Information Administration
(2017) prices generate a positive return for the mine at 7.65%, though this likely still implies
that this project is a non-viable investment as it would be below the opportunity cost of
capital for resource firms.5
The second and third rows of Table 3 report the levelized cost of oil sands either in
terms of the WTI price (the second row) or the price of bitumen before transportation
(the third row). These trigger prices suggest that price expectations would have to increase
by approximately $5 to $30 from average prices observed in mid-2016, to $55 and $79 per
barrel, in WTI prices, respectively for in situ and mining projects to be economically viable
investments.
5
Current weighted average costs of capital for oil sands firms are lower than this value in some cases,
owning to recent negative returns on invested capital.
13
Current growth forecasts for oil sands, whether from industry (see Canadian Association
of Petrolem Producers (2016)), non-governmental organizations (see International Energy
Agency (2016b) and Findlay (2016)) or government (see National Energy Board (2016)
and Alberta Energy Regulator (2016a)) each make clear that a bullish view on long term
prices is needed to underpin significant production growth rates. Forecasts by the International Energy Agency (2016a) in addition to the Energy Information Administration (2017)
shown above, as well as forward-looking reserve evaluations by industry Sproule - Worldwide Petroleum Consultants (2016), all call for higher long term prices than those implied
by current futures prices. In Table 4, we show the changes in returns and trigger prices
for only the in situ project when using prices from the Alberta Energy Regulator (2016a),
Energy Information Administration (2017), National Energy Board (2016), Sproule - Worldwide Petroleum Consultants (2016) and using our base case pricing assumptions. Under a
continuation of current crude pricing, changes in carbon policies are unlikely to materially
impact new oil sands project decisions - new projects are likely to remain uneconomic no
matter the greenhouse gas policy choices made. However, if crude oil prices rebound, as
forecast in the institutional outlooks shown in Table 4, there is the potential for GHG policy
choices to have a significant effect on growth. These prices, in and of themselves, would be
sufficiently high to stimulate significant oil sands growth, but that growth could be nullified
by carbon policies that either reduce oil prices received by producers or increase costs of
production.
This table also shows the impact of the price-dependent royalties discussed in Section
2.1.2. At higher prices, such as in the EIA forecast, oil sands project inflation-adjusted
royalty payments increase by a factor of more than three relative to royalties paid under
current prices. The trigger prices for investment change somewhat across price forecasts due
to underlying prices for natural gas or the Canadian dollar exchange rate.
In Table 4, we also include the carbon prices at which the expected returns from a
project would be reduced to (increased to) 10%, which is a type of levelized, break-even
carbon price. Under current prices and policies, carbon prices would have to provide a net
subsidy equivalent to $62.61 per tonne or $3.77 per barrel to allow the in situ project to meet
conventional investment hurdle rates, while the project would be viable with carbon prices
between $150 and $200 per tonne under each of the other four price forecasts modeled. This
result shows the much more significant dependence of oil sands growth on net revenue from
bitumen sales rather than production carbon prices, however as we will see below, insofar as
carbon prices affect those revenues, they can have a much more significant effect.
14
Table 4: Oil sands project model results under different price forecasts.
3.2
The effect of the social cost of carbon on oil sands development
In this section, we report estimates of the effect of applying a carbon tax valued at the
social cost of carbon. The social cost of carbon (SCC) represents the marginal damage of a
one-tonne increase in CO2 emissions, based on an projection of global emissions over time.
We examine the impact on the extensive margin of oil sands development - if new oil sands
are not viable under a carbon tax equal to the SCC, then it is likely that oil sands represent
a negative net present social value and therefore should be left undeveloped.
While there is a range of estimates of the SCC (see, for example, Stern (2007), Nordhaus
(2011), and Tol (2002a,b), among others), we rely on the Interagency Working Group on
Social Cost of Carbon (2015) (IWG) estimates of the SCC for two reasons.6 The first reason
is because these estimates are the product of an extensive meta-analysis of existing studies.
Second, they are currently used for the evaluation of climate change policy in the United
States as well as in Canada (see Environment Canada (2016)).
An emissions tax, equal to the SCC or other values, could also differ in its scope: the base
6
The state of the art in estimating the SCC is summarized in Committee on Assessing Approaches to
Updating the Social Cost of Carbon; Board on Environmental Change and Society; Division of Behavioral
and Social Sciences and Education; National Academies of Sciences, Engineering, and Medicine (2017).
15
Table 5: Effect of SCC tax on oil sands in situ viability
of the tax could be production emissions alone, or it could be expanded to account for lifecycle emissions, which also includes emissions from refining, transportation, and combustion.
Below, we consider both a tax on production emissions alone and a tax that is based on lifecycle emissions. We focus our analysis on the in situ project as this type of project is more
likely to represent the marginal new development.
Table 5 shows the impact when oil sands production emissions alone are taxed at the
SCC rates, and other prices are unaffected. In the top panel, we calculate rates of return
and trigger prices based on prices and exchange rates from late-2016 forward markets. In
the bottom panel, we calculate the same metrics but using price projections from Energy
Information Administration (2017). In both panels of Table 5, we see project rates of return
eroded from the respective baseline scenarios with current policies in place, as the social
cost of carbon applied through a carbon tax imposes higher average carbon costs than the
current Alberta policy in all cases. The real dollar WTI prices at which a new in situ project
16
Table 6: Effect of full reflection of SCC in both production emissions tax and downstream
oil revenue loss
would be expected to earn a 10% rate of return increases from $54.78, in U.S. dollars, under
current policies and prices to a maximum of $66.13 per barrel. Although this trigger price
is still above current prices, it is well below the price forecast from Energy Information
Administration (2017).
For the most-commonly-used IWG 3% discount rate SCC estimate, the average carbon
emissions costs for the in situ project climb to $75 per tonne in real terms, which translates
to an average $4.54 per barrel in GHG costs. The net impact on project profitability relative
to current prices and policies is a $2.22 per barrel decrease in real dollar cash flow, as
decreased taxes and royalties compensate for over half of the greenhouse gas policy cost.
Given current prices, these results suggest that no new oil sands projects would be developed
under policies that internalize the social cost of carbon emissions from oil sands production
into development.
Under more bullish price forecasts, such as those in Energy Information Administration
(2017) shown in the bottom panel of Table 5, the impacts are potentially material for new
projects. With current GHG policies in place, a new in situ project would expect a rate
of return of almost 15% under the oil prices foreseen by the EIA; this return is eroded to
less than 12% with a carbon tax set at the highest estimate of the social cost of carbon, in
the right-most column.7 Given that these values are close to conventional investment hurdle
7
The difference in average carbon costs between the two simulations is due to the social costs of carbon
being expressed in $US, and a lower-valued Canadian dollar under the Current Prices and Policies scenario
17
rates, the potential exists for policies that internalize social cost of carbon emissions from
production to have an impact on investment decisions and thus future rates of oil sands
production.
Vertically-targeted carbon pricing could have a much larger effect on future oil sands
growth, in particular if the incidence of these prices reduces oil prices or increases heavy oil
discounts. Table 6 expands the carbon tax to emissions associated with refining, transportation, and eventual product combustion, as specified in equations (2) and (3). In this case,
the effect on the in situ bitumen production project is significant. If all of these costs are
borne by the oil sands producer through discounted crude prices, then the project cannot
meet typical investment hurdle rates of 10% at any of the IWG SCC estimates under current
prices and policies, so we do not show these results in detail. Under the more bullish oil
prices of EIA (2017), shown in Table 6, the project meets typical hurdle rates only if the
highest-discount rate estimate of the SCC is used. At the commonly used SCC calculated
at a 3% discount rate, the project essentially breaks-even in real terms, and would require
sustained pre-carbon tax WTI oil prices of $100, in US dollars per barrel, to earn a typical
investment rate of return of 10%. At the higher values of the social cost of carbon, the
project loses money. The most extreme case would not see refineries willing to pay a positive
price for bitumen feedstock.
The crucial assumption in the analysis above is that of 100% incidence of downstream
carbon prices on producer net revenues via lower crude oil prices. In Table 7, we vary this
assumption using EIA (2017) prices and the 3% discount rate social cost of carbon series
from the IWG (2015). Several results in this table are worth further discussion. First, as
is intuitive, the greater the burden of the carbon price falling on producers, the higher oil
prices must be to trigger investment. As such, while the project would likely be viable with
the social costs of carbon emissions internalized at production, it is likely to be viable if
and only if most of the carbon costs associated with refining and combustion are borne by
consumers or if they remain external to both producers and consumers. Second, we can
see the important role played by royalty and tax interaction (a topic we discuss more in
depth below) on the results. In the lower half of the panel, we can see how royalties and
taxes drop along with revenues, resulting in the province effectively sharing in the burden
imposed by the carbon price. Therefore, while the carbon price incidence decreases revenue
by approximately $30 per barrel from production-only to full incidence of life-cycle emissions,
free cash flows drop by a little under $16, as reductions in government revenues absorb half
than under the EIA(2017) scenario. The US dollar carbon costs are the same in both simulations.
18
Table 7: Impact of oil price incidence on life-cycle emissions pricing implications for oil sands
of the impact. Thus, while our model assumes perfect incidence on the revenues of the
oil sands project, the fiscal policy ensures that the incidence of these costs on the project
proponent are buffered. Finally, these results suggest that the point of application matters
due to distortionary fiscal policy. In columns (5) and (6) the total carbon emissions subject
to pricing are identical, as is the applied carbon price, however the price is vertically targeted
and applied at extraction in column (6) versus being applied separated on extraction and
combustion emissions where they occur, which is shown in column (5). We explore this result
further below.
3.3
Does it matter where the carbon tax is applied?
Absent distortions, it should not matter whether a carbon tax is applied upstream or downstream: conditional on the indicidence of the tax, the impact should be the same. However,
a growing literature in economics analyzes the unintended consequences that other policies
have on environmental policies (see Bovenberg and Goulder (2002)). Furthermore, given the
global public nature of greenhouse gas pollution, authors have examined the potential for
jurisdictions to impose policies with impacts outside of their own borders through vertical
targeting (see Bushnell and Mansur (2011) and Mansur (2012)) or through border carbon
adjustments (see Fischer and Fox (2012)). Our analysis suggests an important difference
19
between seeing prices applied on all emissions at production versus in downstream consumption markets, holding incidence constant. This interaction between resource royalties and
emissions prices presents an important caveat to the existing literature on vertical targeting
and measures to extend carbon pricing to non-compliant nations.
In the case of oil sands, the provincial government royalties (see Section 2.1.2) assessed
to recoup some of the monetized wealth from the produced resource have important distortionary interactions with carbon policy. This distortion occurs because the royalties charged
depend on the current price of crude oil and because once cumulative returns exceed the
long-term bond rate royalties are charged on net revenues. Insofar as carbon policies either
reduce revenues through reduced oil prices or increase costs, the carbon policy will alter the
royalty base (either gross or net revenue) as well as the time it takes a project to reach the
payout condition, but this effect will be symmetric across increases in costs or decreases in
revenues. However, if carbon prices are applied at the point of consumption and the incidence
of the tax leads to lower prices for oil then would otherwise occur, this reduces the royalty
rate as well as the base, whereas an equivalent vertically-targeted tax applied at production
with identical incidence would lead to higher crude oil prices than would otherwise occur,
increasing the royalty rate.
For more clarity, consider the bookend cases: 100% incidence on producers or 100%
incidence on consumers of a carbon tax on all life-cycle emissions. If the carbon tax is
applied at production and producers are able to pass through the costs of the consumerside emissions to consumers through higher oil prices, this will lead to higher costs and also
higher royalty rates. If the same tax is applied on consumers, and none of it passed back to
firms through lower producer oil prices, then the royalty rate would not be affected by the
imposition of the carbon price. While both points of application would have the same impact
on the royalty base (they each allow the same net revenue to producers since new carbon
costs are borne by consumers in both cases) the royalty rate charged would be higher in the
case where the point of application were on the firm. The reverse is true if the incidence
falls entirely on producers – if the point of application is the producer, there is an increase
in costs with no change in producer or consumer prices for oil and therefore no change in the
royalty rate. However, if the point of application is consumers, but the cost is passed through
to firms through lower oil prices, then both the royalty base and the royalty rate would be
reduced. With higher (lower) royalty rates, more (less) of the costs of carbon will be borne
by the resource owner as opposed to by the producing firm. As a result, we could see a
case where a new development could be viable for a producing firm with vertically-targeted
20
Figure 1: Impact of oil price incidence on life-cycle emissions pricing implications for oil
sands
carbon prices applied downstream on consumers while the same carbon price, with the same
vertical targeting and eventual incidence, but applied upstream at production would make
the project non-viable.
The degree to which increased carbon costs are offset by decreased royalties will potentially affect project viability under different policies. In Table 7, we report the oil sands
viability metrics based on EIA price projections, a carbon tax equal to the IWG 3% SCC
average estimate, and varying levels of tax incidence as well as points of application. The
difference in rates of return between having extraction versus consumption as the point of
application for the carbon tax, where in both cases the incidence falls entirely on producers,
is five percentage points. While for this example, the realized rates of return are both too
low to justify investment, we do see a material change of almost $10 per barrel in the supply
cost of oil sands due only to the change in the point of application.
We also express the impact of downstream carbon price incidence and the point of application of life-cycle emissions pricing graphically, in Figure 1. Here, we map the trigger
WTI price required to yield a 10% IRR under different assumptions about price incidence
and point of application. Here again, the highest oil price is always required if emissions
are internalized through an upstream charge that cannot be passed through incrementally
to consumers. If the same total prices are applied in the supply chain and again borne by
producers but through lower oil prices, the required oil price to make a project financially
viable is slightly lower. Intuitively, as the incidence shifts more of the burden of carbon
21
pricing to consumers, the lower is the oil price required to see an oil sands project break
even. Finally, we see the impact of carbon pricing coverage - where only emissions for production are covered, the break-even prices are much lower than would otherwise obtain. If
some of the average costs of carbon emissions are offset through output-based allocations of
credits, project economics are improved and the extensive margin is no longer very sensitive
to carbon prices.
For our analysis, we rely on assumed oil price incidence of carbon policy, but we can
also use results from two jointly-modeled oil and carbon prices on oil sands development in
two scenarios consistent with the 450ppm/2o C goal. We use the carbon and oil prices from
McGlade and Ekins (2015) as well as International Energy Agency (2016a) for this analysis.
McGlade and Ekins found that oil sands were likely to be largely shut-in by early in the next
decade, but our results suggest caution in interpreting that result. We run 5 simulations
in this section - the first is our base case, with current prices and policies. We next use
oil and carbon prices from the IEA (2015) and McGlade and Ekins (2015) studies, along
with interpolated Canadian dollar exchange rates, to test oil sands project viability. Finally,
we use the McGlade and Ekins price series to show the importance of the stage of project
development in determining the reaction of producers to the imposition of such a pricing
scenario.
Several results are worthy of note - first, both 450ppm scenarios imply higher real dollar
oil prices than our scenario with current prices. Second, while McGlade and Ekins (2015) and
IEA (2015) each derive similar global outcomes from similar models, the implications we find
for new oil sands projects are starkly different. The IEA scenario’s lower carbon costs and
higher oil prices provide for more competitive oil sands projects than the McGlade and Ekins
prices, and a greenfield project is highly attractive under the overall IEA 450ppm environment. If producers expected the pricing environment modeled by McGlade and Ekins, they
would be almost certain to not sanction the in situ project we model in this table. However,
that conclusion changes if the project is already materially advanced. In cases where either
the project has completed most of its construction or where the project represents the expansion of an existing project, the investment in new oil sands production (forward-looking)
would remain viable. This suggests that, at least projects currently under construction
would continue to operate. Furthermore, under the McGlade and Ekins scenarios, bitumen
revenues would still be well above production costs for existing projects unless other factors
led to significant increases in bitumen price discounts or increases in costs. While McGlade
and Ekins conclude that existing bitumen production would be rapidly shut-in under their
22
Table 8: Viability of oil sands in integrated 450ppm scenarios
modeling assumptions, we find no support for that contention in our work. This is reinforced
by the fact that current forward curve prices represent a similar environment for producers as
the McGlade and Ekins results, and oil sands operations have not seen significant, long-term
shut-ins in response to low prices since 2014.
4
Conclusions
This research presents mixed conclusions with respect to the viability of oil sands projects
when the social costs of carbon emissions are internal to project investment decisions. If
we assume that carbon costs associated with refining, transportation and combustion will
be borne by consumers and not passed back through the supply chain via discounted oil
prices to producers, then oil sands projects remain viable under all but the most risk-averse
interpretation of the social cost of carbon published by the IWG. If, on the other hand, it
is expected that either consumers will be unwilling to pay these costs that will result in
discounted oil prices or if it is expected that policies will impose life-cycle costs directly on
23
producers then new oil sands development would be economically unviable. We also find
that any new development is likely contingent on governments continuing to share GHG
costs implicitly through royalty policies.
Beyond the their relevance to current policy discussion with respect to the carbon bubble, our results have two important, additional economic implications. First, we illustrate
the degree to which expectated, long-run price-incidence of carbon policies will determine
fixed capital investment, and highlight the paucity of data on these long-run impacts. This
incidence is also endogenous to current expectations - if fossil fuel producers expect limited impacts of climate policy on future prices, and thus over-build production assets, this
will impact the price-incidence of future policy. Second, our results illustrate the degree to
which local fiscal and regulatory policies can amplify existing externalities. Our paper thus
contributes to an extensive literature examining the unintended effects when environmental
taxes and other fiscal policies overlap and suggests future work on optimal resource policies
in the presence of priced externalities and vice versa.
24
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