Can a “Switching Costs” Approach
Help Foster International
Agreement?
Michael Barsa
David Dana
Northwestern Pritzker School of Law
Allocating Emissions Reductions Has
Been A Challenge
• Kyoto Protocol
– Nearly uniform reductions (6-8% below 1990
levels) for Annex B parties (with flexibility
mechanisms allowing some of those reductions to
take place outside the country)
– No mandatory reductions for non-Annex B parties
– RESULT: US failed to ratify the treaty, while China
and India were never covered in the first place
Post-Kyoto Proposals Have Been
Fraught With Difficulty
• China has proposed allocating emissions
reductions per capita
– But developed nations like the US will not agree
– Other small developing nations would also likely
not benefit from this approach
• Cap-and-Trade and Global Carbon Tax Efforts
Have Languished
Paris? INDCs Not Sufficient
• Lack of standards
• Lack of results: While almost 87% of global
emissions are covered by countries that have
submitted INDCs (latest data from World
Resources Institute), they will not meet the goal
of keeping average global temps below 2 degrees
C (according to the IEA).
• Too conservative: some countries (like China) are
conservative, only making pledges they know
they can easily meet
Is there another way forward?
• Countries are concerned about costs
• Can we make national targets cost-sensitive?
• How might this work?
Costs
• By costs, we focus on compliance costs only
• We do not focus on full economic costs (i.e.,
overall economic effects of compliance,
including downstream effects on investment,
savings, and employment) because this would
be too complex and contestable
• EPA, too, often refuses to quantify full social
costs and uses compliance costs only, for this
same reason.
What might a cost-conscious scheme
look like?
• Two different models in prior EPA rulemakings
under the Clean Air Act
– The “traditional” model used in the Cross State Air
Pollution Rule (CSAPR)
– The “switching costs” model used in the Clean
Power Plan (CPP)
Traditional Model: Clean Air Act Basis
• The Clean Air Act Section 110(a)(2)(D)(i)(I)
requires State Implementation Plans (SIPs) to
prohibit any source within that state from
emitting any air pollutant in amounts which
will “contribute significantly to
nonattainment” in other states.
Traditional Model
• EPA defined what it means to “contribute
significantly” in part by the amount of
emissions in excess of the reductions that
“highly cost-effective controls” could achieve
• How does this work?
• What assumptions were made about the
shape of the marginal cost curve?
Traditional Model: first attempts
• In EPA’s 1998 nitrogen oxide (NOx) “SIP call” (a
call for a revision to the SIPs), EPA decided
that 23 “significant contributor” upwind states
needed to reduce their emissions by the
amount achievable with “highly cost-effective
controls,” which EPA defined as those that
could be achieved for less than $2000 per ton.
• Result?
• Actual emissions reductions of upwind states
varied depending on variations in cutback costs.
• Those states that had already taken measures to
reduce emissions had to cut back comparatively
less (because the measures left to them were
comparatively more expensive)
• EPA implicitly assumed a traditional rising
marginal cost of abatement curve
CSAPR
• A similar equal cost threshold approach was
carried forward into EPA’s Cross State Air
Pollution Rule (CSAPR) for NOx and SO2.
• Again, upwind states would reduce emissions
by reference to uniform cost thresholds
(uniform within 4 different groups of upwind
states).
CSAPR
• EPA rejected a uniform % reduction rule
because it would punish states that had
previously implemented stringent control
programs and reward those that had not.
• In designing the Transport Rule (the precursor
to the CSAPR), EPA explicitly assumed
increasing marginal costs for reductions of
SO2 and NOx and tabulated projected
emissions at each cost level.
CSAPR
• EPA selected points along the curve and
projected emissions at those levels, and used
air quality measures to determine where the
marginal benefits of increased abatement
would decrease.
• Based on these data, EPA decided what each
upwind state’s emissions budget would be
CSAPR
• Bottom Line: This traditional model of costsensitivity assumed that similar sources faced
a similar rising marginal cost curve, even
though they might be at different points along
that curve, depending on what abatement
measures they already had.
• Equalizing compliance costs translated into
different emissions budgets for each state.
Clean Power Plan
• EPA’s Clean Power Plan (CPP), on the other
hand, is sensitive to costs in a much different
way.
• The CPP is based on Section 111(d) of the
Clean Air Act, which requires EPA to prescribe
regulations that require each state to submit a
plan that “establishes standards of
performance” for existing sources of air
pollution.
CPP
• A “standard of performance” is “a standard for
emissions of air pollutants which reflects the
degree of emission limitation achievable
through the application of the best system of
emission reduction which (taking into account
the cost of achieving such reduction and any non
air quality health and environmental impact and
energy requirements) the Administrator
determines has been adequately demonstrated.”
CAA Sec. 111(a)(1)
CPP
• How does EPA calculate the “best system of
emission reduction” (BSER) for each state?
• It uses 3 “building blocks”:
– Increasing operational efficiency of existing coal
plants
– Shifting electricity generation from coal to natural
gas
– Increasing electricity generation from renewable
sources like solar and wind.
CPP
• For each building block, EPA determines what the
states demonstrably can achieve, taking costs
and other factors (such as health and energy
requirements) into account.
• EPA then translates those building blocks into an
overall state goal for lowering CO2 emissions
from power plants.
• States are free to meet that goal however they
wish—they don’t have to do what the building
blocks assume they can do.
CPP—Operational Efficiency
• For Building Block No. 1 (operational efficiency of
coal plants), EPA assumed that, to a certain
extent, heat rate improvements at coal plants
(i.e., improvements in the amount of energy
required to produce each kWh of energy) would
pay for themselves
• EPA looked at factors such as the best historical
heat rate performance for each EGU, and
calculated the overall potential for heat rate
improvements within each of 4 regional grid
interconnections.
CPP—Operational Efficiency
• These factors are consistent with a traditional
model where we assume steadily rising
marginal costs of abatement
• Indeed, EPA studied various low-cost
measures such as equipment upgrades and
contrasted them with higher-cost “best
practices”—these were largely uniform within
similar types of coal-fired EGUs.
CPP—Demand-side energy efficiency
• The draft CPP had also included demand-side
energy efficiency as a “building block,” but this
was taken out of the final rule.
• However, EPA will still give states credits toward
its emission targets for implementing demandside energy efficiency in low-income communities
• Here, too, EPA assumes a traditional rising
marginal cost of abatement curve, assuming that
future EE programs will be more expensive once
states move beyond the “low-hanging fruit”
CPP—Renewable Energy
• However, when it came to making
assumptions about how much Renewable
Energy (RE) each state could achieve by 2030,
EPA didn’t simply assume a rising marginal
cost curve
• Instead, EPA was sensitive to various regional
and state-specific factors that would make RE
growth more or less likely in that state
CPP—Renewable Energy
• RE includes utility-scale solar photovoltaic,
concentrating solar power, onshore wind,
hydropower, and geothermal
• EPA used the state-level effective RE levels
from state RPS requirements to quantify
regional RE targets to meet by 2030.
• EPA then calculated the constant rate at which
each region would need to increase its
generation each year to meet the target.
CPP—Renewable Energy
• EPA then applies this constant growth factor
(which varies from a low of 6% in the West
region to 17% in the East Central region) to a
state’s pre-existing RE generation
• Thus a state’s historic RE performance acts as
a limiting factor
• I.e., the absolute Mwh targets will be smaller
for states starting with lower absolute
amounts of RE generation
CPP—Renewable Energy
• As a result, state RE growth assumptions
differed widely based on how much a state
could do
• For example, Kentucky, which got 0% of its
energy from renewables in 2012, would be
assumed to get to only 1.9% by 2030, whereas
Nevada, which was at 8% in 2012, would get
up to 19%.
CPP—Renewable Energy
• What EPA is doing here is not simply assuming
that states that hadn’t done much historically
to generate RE had lots of “low-hanging fruit”
to take advantage of.
• Instead, EPA was sensitive to the fact that
differences in natural endowments, grid
connections, and even political capacity
(thought not overtly) might limit what a state
can be assumed to do to “switch” to RE.
CPP—Renewable Energy
• Not surprisingly, some states like NJ
complained that the CPP did not “reward”
states that had already switched to RE (by
lowering their targets) or “punish” those that
had not (by raising their targets)
• But that was the point!
Scaling Up the CPP Model?
• The CPP is consistent with the notion that
where we want to “switch” power generation
to RE, we should not simply assume that
states or nations that haven’t done much can
do more at less cost.
• Sometimes the opposite is true, based on
natural endowments and the costs of building
new infrastructure (which make the marginal
cost curve “lumpy”)
Can A Similar Approach Help Facilitate
Agreement Internationally?
• Recalls David’s and Ken’s work regarding
experimentalist governance and the
advantages of “bottom up” approaches—this
might foster agreement because nations
facing high switching costs might otherwise be
reluctant to agree to anything
• This approach also avoids normatively
intractable debates about whether wealthy
states should do more
Uncertainty: Blessing or Curse?
• The uncertainty about how much emissions
reductions a “switching costs” approach
would mandate might be a blessing in
disguise—assuming that countries could agree
to the relevant factors to be used and trust
the process. Thoughts?
• Like the Montreal Protocol, a “switching costs”
approach is more technically focused on costs
and alternatives
Helps Lower Costs
• Targeting more emissions reductions in states
that can meet such reductions at lower cost
helps to lower overall compliance costs
• Similar gains could be made through an
emissions trading scheme or carbon tax, but
those have not proven feasible so far.
Disadvantages
• Information Costs are high
• Potential perverse incentives—states might
not create clean power infrastructures ahead
of time for fear that a “switching costs” regime
would assign them high reductions as a result
Mitigating perverse incentives
• Not clear politically how strong the perverse
incentives argument is (i.e., states that have
the political will to switch to clean power
ahead of time might not resist higher targets)
• Could give “credit” for previous switching
efforts (like EPA did with future demand-side
EE)
Conclusion
• An approach that is sensitive to switching
costs might be a useful and less politicallycharged way to differentiate between nations
• Even if not the sole basis for new targets, it
could be a factor in the “mix” (which might
also include EE and other factors)