Economic signals achieve energy savings through two mechanisms. First, they affect consumer behavior. For example, consumers might choose to drive less or to turn down their air conditioning in response to a fuel tax. This happens quickly after the policy comes into effect, if consumers are informed about the price changes and respond in an economically rational way.

The second mechanism involves influencing the choices consumers make when buying new products or the decisions companies make when building new equipment and, in turn, the equipment that manufacturers choose to produce and offer for sale. Carbon pricing will increase demand for fuel-efficient equipment, and manufacturers will seek to respond to that demand.

Just as when they are trying to meet performance standards (discussed earlier), businesses will take action to improve their product offerings in response to an economic signal. They need time to invest in R&D activities, to change their manufacturing processes, to alter their supply chain, and to update their marketing materials. Firms need years to fully respond to a price signal that they learn about today.

Even more than with performance standards, there is often uncertainty about the permanence and magnitude of price signals. Tax rates can change dramatically based on the political preferences and economic viewpoint of the government at a given time, and subsidies are ideally structured to phase out as a technology achieves maturity. This uncertainty can interfere with businesses’ plans and reduce the effectiveness of price signals.

For example, suppose a tax on fossil fuels is authorized only for a few years, with the possibility of renewal. A business may decide that it is not prudent to make large R&D investments and retooling factories if the tax might be gone by the time any newly developed products can reach the market. Even if the tax is renewed, and renewed again, the continued uncertainty surrounding each renewal will dampen businesses’ responses to the tax, so it achieves less efficiency improvement than would have been caused by the same tax had it been authorized with sufficient long-term certainty in the first place. The same can be true of subsidies. The U.S. Production Tax Credit is one example of how failing to provide long-term certainty can lead to poor investment decisions.

Similarly, a business with limited knowledge of future subsidy rates must hedge when making investments. If a feed-in tariff for wind power is extended for only a year at a time, a business will not be able to rely on it when deciding whether to commit to the construction of a large wind farm, which would take more than a year to site, permit, and build.

Generally, subsidies should be designed to phase out over time, while taxes should be designed to increase over time. When possible, the endpoint or goal of an economic incentive should be selected and explicitly specified. For example, the goal of a subsidy for wind power may be to help wind power scale to the point where it can compete economically without a subsidy. The long-term goal of a carbon tax may be to fully price in the social cost of emissions and then to remain at that level indefinitely. If a long-term goal is publicly specified, this helps businesses understand policymakers’ intentions and make plans with the benefit of having this endpoint in mind.

One example of a successful incentive phase-down is the California Solar Initiative, which provided a subsidy for residential solar installations that scaled down based on the cumulative installed capacity, with a clear future trajectory and timeline. The program is widely regarded as having been a nearly optimal subsidy policy and for having maximized economic efficiency while helping scale residential solar in California

Economic incentives can be structured in two ways. Either the amount of the incentive can be specified explicitly, or the policy may stipulate a mechanism by which the incentive value is found. In economic terms, the policy assumes a known quantity or a known price, and it uses the market to find the other value. Each mechanism is appropriate in specific cases.

If the price of a given policy objective is known (e.g., the value of the damages caused by emissions—the externality), then a tax or subsidy can be set based on that price, allowing the market to identify the quantity of activity appropriate at that price, and to identify methods to reduce emissions per unit activity. For example, a policymaker may not be able to specify the exact quantity of CO₂ emission reductions in each industry (e.g., cement, chemicals, steel) because they are each unique and complex businesses with differing abatement opportunities.

However, if the policymaker has a good estimate of the harms caused by CO₂ emissions, she can set carbon pricing at that level. Each industry will be motivated to find the most cost-effective ways to reduce its own emissions until any remaining abatement options are more expensive than the tax. From a social economics standpoint, social welfare is optimized at this point (because further emission reductions would be more costly than the benefits they provide).

The second way an economic incentive may be structured is as a price- finding mechanism. If a policymaker knows how much of something she would like to achieve (such as a specific quantity of clean energy on the grid), then a price-finding mechanism can be used to identify the lowest incentive that will achieve that outcome. For example, in a reverse auction, suppliers of a good (such as clean electricity) bid against each other for the lowest subsidy they will accept. The subsidy is set at the lowest level that would achieve a sufficient quantity of clean electricity, based on the amounts each supplier offered to produce at each price

Often there are significant regulatory inefficiencies or permitting challenges that raise costs, increase timelines, or discourage investment in clean technologies. These soft costs can take many forms, such as large paperwork requirements for receiving rebates, burdensome environmental quality studies, or slow permitting processes. In many instances there are good and valid reasons for these requirements.

In the case of vehicle rebates, the government needs to ensure it isn’t paying rebates for any vehicle more than once, and in the case of environmental quality studies, sufficient study is needed to ensure a new project will not harm endangered species, damage people’s homes, or lead to environmental damages. Nevertheless, a tradeoff occurs between regulatory burden and financial attractiveness for clean technology investments.

The government should take steps to reduce these soft costs for projects that promote decarbonization of the economy. Pre-zoning specific areas for specific types of infrastructure can be a promising approach for large clean energy projects. For example, a large area of desert, absent critical wildlife habitat, might be pre-zoned as “solar-ready,” and solar projects in that area can have greatly reduced requirements for project-specific permitting or approvals. Texas’s Competitive Renewable Energy Zones for wind power are a successful example. Another way to lower soft costs is to standardize necessary forms and allow online submission (over the Internet).

Although the methods will vary based on the policy and technology being considered, policymakers should continuously look for ways to streamline processes for clean energy technologies in order to lower their costs and drive deployment

Economic incentives for clean energy should be based on the amount of clean energy that is generated and used, not on the amount of capacity built or money invested to purchase or install clean energy infrastructure. This ensures that the incentive is paid only when these resources are actually used.

A subsidy based on installed capacity risks contributing to three problems. First, it encourages cheaper and lower-quality equipment. An inexpensive wind turbine might have the same rated power output as a higher-quality turbine, but it might break more frequently or be unable to produce as much electricity.

Second, capacity incentives promote installations in areas that may not be ideally suited to capacity growth. For example, they might encourage the placement of wind turbines in areas with worse wind speeds or where there is not sufficient transmission capacity to deliver all of the wind power to demand centers.

Third, a capacity-based subsidy eliminates the incentive to produce as much electricity as possible, because the subsidy is paid based on the size of the installation rather than the amount of electricity it generates.

An economic signal becomes harder to administer and is more prone to leakage—when consumers or businesses affected by the tax purchase goods from other areas without the tax—the further downstream (closer to the final point of sale) it is administered. In many cases an economic signal also can have much greater impact if administered upstream (closer to the point where the product is produced or imported).

For example, a tax on coal administered at the coal mine will make the price of coal higher and induce power plants to switch to other fuels, whereas a tax on electricity based on the amount of coal generation not only is harder to administer but also is less likely to influence power plant operators to switch to other fuels. Therefore, economic signals should be administered as far upstream as possible. Sophisticated upstream actors will then mitigate the impacts of the tax by switching to less expensive options, and only the remaining impacts of the tax will be passed down to consumers via the pricing of goods.

Policies that offer economic signals in the form of subsidies should ensure these incentives are liquid and do not have unnecessary transaction costs. A liquid incentive is one that is easily transferable and is akin to cash. Grants or cash payments are highly liquid, but tax credits are not.

For example, to avoid the appearance of providing subsidies, the U.S. government usually offers tax credits (a reduction of income tax charged on some types of income). Often, the entities who earn the tax credits don’t have enough qualifying income to fully use the tax credits. Therefore, in order to take advantage of the credits, they are forced to partner with tax equity investors, entities that have sufficient qualifying tax liabilities. These entities are generally investment banks and other large financial institutions. Having to partner with one of a limited set of tax equity partners means less of the incentive goes directly to the clean energy developers while raising project costs (finding and negotiating a contract for tax credits is expensive). It would be more efficient to just provide cash payments or grants to the developers.

Ensuring subsidies are liquid and usable by the intended recipient helps to reduce the risk and complexity faced by clean energy projects and ensures government monies are used to subsidize projects most efficiently.