Economists frequently tout carbon taxes and cap-and-trade programs as the most efficient ways to reduce carbon emissions because they directly put a price on carbon. At the same time, they often view other forms of regulation that more indirectly price carbon—such as renewable portfolio (output-based) and fuel economy (attribute-based) standards—as less efficient. But the price of fuels and the demand for electricity and vehicles often change. In this uncertain landscape, output and attribute-based regulations could provide needed flexibility to adjust to price and demand shocks. But, is their flexibility enough to outweigh their inefficiencies? A new study confronts this question.

“At the time when a regulator is setting a policy, it’s very hard for them to predict how the price of fuel or the demand for the good might change over the life of the policy,” says Ryan Kellogg, the author of the study and a professor at the Harris School of Public Policy. “This uncertainty makes creating rules with a fixed cap on emissions difficult and risky in the sense that they may either become more expensive or possibly much cheaper than expected, in which case you miss out on low-cost emissions reduction. In a highly-uncertain landscape like this, that uncertainty should be considered when designing a policy.”

In the study, Kellogg uses a simple model of supply and demand for goods that generate carbon emissions, such as vehicles or electricity, and applies the model to both fuel economy standards and the U.S. electricity sector. He discovers that some amount of output or attribute-basing is better than a fixed emission cap when there is uncertainty about future demand for the good’s output or the value of one of its attributes. The larger the amount of uncertainty, the more efficient these types of flexible regulations can be.

The flexibility of the standard becomes especially important in the electricity sector because uncertainty about the future demand for electricity is large. If demand is low or the price of low-carbon fuels is low then there are less emissions being produced. In this case, a fixed emission standard might not be high enough to reduce emissions. But if demand is high or the price of low-carbon fuels is high then a lot of emissions are being produced and the cost of abating them might be too costly under a fixed standard. A standard that changes based on the amount of electricity produced —such as the rate-based standards envisioned by the Obama-era Clean Power Plan—could then potentially out-perform a fixed emission standard or cap in the electricity sector.

In the automotive sector, uncertainty about fuel prices or future demand for vehicle miles traveled is smaller. As a result, the flexibility that comes with fuel economy standards—which regulate emissions based on the size of the vehicle’s footprint with bigger vehicles expected to reduce fewer emissions than smaller ones—is not enough to account for the inefficiencies the system can create. Namely, a recent study found that a size-based system incentivizes automakers to increase vehicle size in order to fall into a less stringent compliance category. A fixed standard, and especially one accompanied with credit training, would likely be the more efficient policy choice.

In both sectors studied, a carbon tax is the most efficient path since the tax eliminates abatement cost uncertainty while avoiding distortions to output or to a good’s attribute. The same is true of an emissions cap that is indexed to outside sources of uncertainty, such as fuel prices or GDP, rather than to a good’s output or attribute.

“Most of the time, a fixed cap would be more efficient than a targeted regulation,” Kellogg says. “An exception is the electricity market, where uncertainty about the demand for electricity is so large that a more flexible standard—such as one where the emissions ceiling can vary with electricity generation—may be the smarter policy choice.”

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