Can a “Switching Costs” Approach Help Foster International Agreement?

Michael BarsaDavid 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 cost-sensitivity 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 demand-side 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 politically-charged 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)