Scheme Selection

CENTRAL CHALLENGE: How to design different carbon pricing schemes to be tested? What are the arguments for and against each scheme? Students can use the World Bank’s FASTER criteria for carbon pricing (see side bar) to evaluate the schemes:

• Fairness
• Alignment of policies and objectives
• Stability & predictability
• Transparency
• Efficiency & cost-effectiveness
• Reliability & environmental integrity

Yale decided to test four carbon pricing schemes, two of which were proposed by the Task Force and two were added by the Steering Committee and the Carbon Charge Team through conversation with stakeholders.

Redistribution Scheme

The first scheme proposed by the Task Force is referred to as the Redistribution scheme. A monthly $40 per tCO2e charge is applied to carbon emissions associated with building energy use. At the end of the fiscal year, Yale returns all of the revenues to the units based on their individual performance compared to the university’s average change in emissions from a baseline. Buildings with percent changes below this average receive a full refund and additional payment that together are more than they were charged, resulting in a net rebate. Those with percent changes above this average receive a refund amounting to less than they were charged initially, resulting in a net charge. The sum of charges and rebates is zero and, as a result, the scheme is revenue-neutral for the university. However, it is not revenue-neutral for the individual buildings and administrative units.

Applying this design to the pilot, the five units in this scheme were compared to the group’s overall percent change in emissions from baseline. Those emitting above this value incurred net charges while those emitting below this value received net rebates. The charges and rebates again added up to zero.

The main advantage of this scheme is that it is revenue-neutral for the university as a whole while still providing incentives for each unit to reduce emissions. In addition, individual units will not bear an exorbitant amount of cost in any given year, which especially benefits those who have relatively small budget.

However, this scheme can allow the total university’s emissions to increase year after year without any penalty, as there was no cap to emissions and units were only compared with their average collective performance. The scheme also lacks simplicity (because the charge/rebate depends on performance relative to others) and predictability (because units are unable to forecast the number by which they will be judged, making it difficult to conduct cost-benefit analysis to inform decision making).

Despite the benefits of revenue-neutrality, participants in the pilot felt that this scheme made them compete against each other and reduced the level of cooperation. They also perceived the scheme as unfair because buildings vary in size, history, and/or use and thus have different marginal abatement costs (meaning more or less expensive reduction opportunities). The unique energy profile of each building makes comparison among them unreasonable.

Target Scheme

The second scheme proposed by the Task Force is referred to as the “Target” scheme. This scheme addresses the simplicity and predictability issues by providing a specific reduction target, which can be universally applied to all buildings or customized for each building. The reduction target chosen for the pilot was 1% below baseline.

Similar to the “Redistribution” scheme, a charge of $40 per tCO2e is applied monthly to units’ building energy use. However, at the end of the fiscal year, Yale returns most of the revenues to each unit based on its individual performance relative to the fixed target (-1% in the pilot) rather than to the university’s average percent change in emissions.

The “Target” scheme thus improves fairness by focusing the competition internally, which was preferred by pilot participants than comparison with their peers. It also establishes a cap on the university’s total emissions. However, this scheme does not guarantee revenue-neutrality. It can result in a deficit or surplus for the university depending on whether the buildings collectively exceed or fall short of the target.

A deficit is not a negative outcome for the centrally-supported units, as it resulted in a small financial reward for the units but significant energy cost-savings for the university. This is because utility costs for centrally-supported units are paid for by the university and are much higher than the carbon rebate. Both a deficit and a surplus are however undesirable outcomes for the self-support units. A deficit would represent a subsidy to the self-supporters for reducing their emissions below the target, while a surplus would represent a tax for increasing their emissions relative to the target. As these units are self-financed and do not receive significant revenue from or pay taxes to the university, these outcomes are challenging administratively.

This scheme is also subject to gamability—units may negotiate to receive a more preferable reduction target. Additionally, to make the scheme completely fair, the target needs to be customized to each unit based on the characteristics of their buildings. Yet this will be too administratively burdensome to be implemented.

Investment Scheme

To simulate the second year of a carbon charge when a portion of the revenues would be returned to the buildings as rebates earmarked for energy efficiency, the Steering Committee added an “Investment” scheme. Five units received an energy efficiency earmark equal to 20% of their baseline carbon charge for spending on self-guided energy actions, which can be educational initiatives or capital investments. This represented a scenario in which all of the revenues from carbon charges are sent back to the units, 20% of which is earmarked for energy efficiency while the rest is returned without restrictions. The scheme aimed to test the effectiveness of decentralizing energy efficiency investment.

The advantages of this scheme are that it guarantees investment on energy efficiency and is somewhat revenue neutral, as a certain percentage or all of the revenues from the carbon charge are returned to the units. However, it has the potential to incentivize overinvestment or underinvestment, as units try to use up or do not want to spend more than the earmarked amount. Decentralized capital investment may also be less cost-effective than centralized investment. For example, a central planner can prioritize energy efficiency investments with the highest net benefits across a portfolio of buildings. The pilot found that the level of energy efficiency investment was lower than expected, but this may have been due to the relatively short duration of the pilot.

Information Scheme

Quality meter data are available at Yale and in many cases are provided to the units. However, the data were buried in departmental budget statements and provided without much context (e.g., in comparison to past energy use or other buildings with similar characteristics), making it difficult to find and interpret them. Furthermore, the realization that the carbon charge would require changes in the budgeting system led to a desire to test an “information only” approach. The need to communicate energy, carbon, and cost information to financial and operational decision-makers, coupled with the desire to isolate the effect of information, led the Steering Committee to add another scheme to the pilot. The five units in this group received a monthly building energy report with a $40 per tCO2e price signal but no financial consequences. The other three schemes in the pilot also received this information report in addition to the financial incentives.

The pilot found that information can be helpful, or at least that energy savings could accompany information provision. In Gilder Boathouse, a building that holds crew operations, the team was motivated simply by the new energy report and reduced their emissions by 20% below baseline during the pilot. However, the overall result for this group showed that information in isolation was insufficient: Only two out of the five units reported “higher” or “much higher” levels of motivation and action. In general, the pilot found that information coupled with incentives was the most effective in increasing motivation for energy action.