The Energy Policy Simulator (EPS) offers three options for the way in which revenues from the carbon tax policy may be handled. Before discussing these options, it is helpful to have an understanding of the implementation of the carbon tax policy in the EPS.
Overview of the Carbon Tax Implementation
In the EPS, the carbon tax policy can be set separately for each sector. Within an affected sector, the carbon tax increases the cost of GHG-emitting fuels according to each fuel’s CO2e content. (Biomass and liquid biofuels are taxed according to lifecycle GHGs, to give them credit for upstream sequestration of CO2 that occurred during their production; these fuels are not assumed to be carbon-neutral unless lifecycle emissions data show that upstream sequestration equals or exceeds tailpipe emissions.)
All process emissions come from the industry sector (which includes waste management and agriculture). If the industry sector is subject to the carbon tax, the carbon tax is applied both to GHG-emitting fuels and to process emissions (unless process emissions are excluded from the carbon tax by setting the relevant control lever). Taxed process emissions increase the cost of industrial or agricultural production in a similar way to increased fuel costs for these industries.
The carbon tax also increases the cost of certain capital equipment in the transportation, electricity generation, and industry sectors, as a result of the cost attached to upstream emissions that occurred as a result of the manufacture of the equipment.
The tax is not levied on any CO2 that is captured and sequestered via CCS.
Increases in costs (including cost of fuel, cost of process emissions, and cost of capital equipment) are used to calculate a reduction in the demand for goods and services in various sectors, such as the demand for transportation services or the demand for production from the iron and steel industry. These changes in costs also are taken into account by the mechanisms that decide which types of power plants should be built, when high-emitting power plants should retire, and what types of vehicle technologies are preferred by buyers of new on-road vehicles. All of these effects contribute to the emissions reduction that the EPS assigns to the carbon tax.
Representations of Carbon Tax Revenues in the EPS
Although the carbon tax reduces demand for goods and services and encourages shifts to cleaner vehicles and power plants (thereby reducing the quantity of fuel purchased), the financial savings from buying less fuel are smaller than the increased costs of the fuel that is purchased even after applying the carbon tax. The result is that the carbon tax increases net, after-tax spending on fuel.
The EPS supports three different ways that the use of this revenue may be represented.
By default, the carbon tax revenue is assigned to the government. The EPS makes no assumptions about how the government will spend this revenue. There are an infinite number of ways in which the revenues could be spent, and the question of how to spend government revenues is not specifically a question about energy and environmental policy, but rather a question about government budgeting and national priorities that are not limited to the energy system. Therefore, under Option 1, we regard the question of how the revenues are used as out-of-scope of the EPS. It is important to note that positive revenue for government doesn’t imply that government simply sits on the money or burns it in a bonfire; government can use that money to fund services, reduce the national debt, or reduce other taxes. Therefore, under Option 1, increased government revenues should be regarded as a beneficial financial outcome of a policy package.
The EPS offers a set of financial outputs that assume the carbon tax is revenue-neutral. That is, the government returns to society an amount equal to the net revenue generated from the carbon tax. This is calculated by subtracting the carbon tax revenues from the two reported metrics of final policy package cost (change in capital and operational expenditures and total change in outlays). This option does not make any assumption about the manner in which the carbon tax revenue is returned to society: that is, it doesn’t assume it will be used to cut payroll taxes, to reduce income taxes, distributed as a dividend to all citizens, or any other specific mechanism. It merely assumes a dollar-for-dollar return of value, as if it were a direct cash transfer from government to other actors in society. This way of looking at carbon tax revenues may be better than option 1 if you are seeking to minimize the cost of your policy package and want this minimization to represent a “good” outcome for society, because under option 1, higher policy package cost may in fact be the more socially-beneficial outcome, if the carbon tax revenues are used wisely.
The model’s web interface provides “revenue-neutral carbon tax” versions of the “Effects by Policy: CO2e Cost Curve” and the two cost metrics (“Change in CapEx + OpEx” and “Change in Total Outlays”) in the “Financial: Policy Package Cost/Savings” category.
Carbon tax revenues may be used to fund clean energy, efficiency, process emissions reduction, and similar programs. In this case, the programs funded or enabled by the carbon tax are represented by settings of the other policy levers in the simulator, such as energy efficiency standards, promotion of methane destruction, livestock measures, and so forth. Mechanically, this is not much different from creating a policy package that includes a carbon tax along with other policies. The critical difference is that the entire package should be regarded as a single policy, a “carbon tax with smart use of revenues.”
To assess the cost-effectiveness of the “carbon tax with smart use of revenues” policy, look at the revenue-neutral cost outputs (not the standard cost outputs) for the whole policy package, assuming the package contains only the carbon tax and the policies enabled by use of the carbon tax revenues. To see why the revenue-neutral cost outputs should be used, imagine a package of two policies: carbon tax and methane destruction. This is a clear example because methane destruction doesn’t have direct financial benefits (it substitutes flaring for venting). Suppose the carbon tax cash flow changes are +$2 for government and -$2 for all other actors combined. Suppose the methane destruction policy cash flow change is -$2 for industry. If you fund the methane destruction policy with the carbon tax revenues, you’d expect the total cost of this policy package to be $2, because the -$2 suffered by industry is compensated for by the +$2 that government receives. If you use the revenue-neutral outputs, you get this result. If you use the non-revenue-neutral (standard) outputs, you’d see a total package cost of $4, because those outputs look at changes in capital and operational expenses, without giving credit for changes in revenues.
The policies enabled by use of the carbon tax will not automatically incur costs that precisely equal the revenue generated by the carbon tax. If you wish to model a “carbon tax with smart use of revenues” under which the revenues precisely match the funding consumed by the other programs, you will need to set the levers of the programs to be funded to specific levels to cause the costs to line up with the carbon tax revenues. (Recall that the EPS never sets policy levers on behalf of the user. Rather, it relies on the user to set the policy levers, and then it simulates the results of the selected policies. In other words, the EPS is forward-simulating, not goal-seeking. This is because there are an infinite number of ways the policies could be set to achieve any specific goal, including the goal of smartly using a specific amount of carbon tax revenue. There are many considerations that go into this choice, including political feasibility, so one can’t ask the model to make the policy choices- the user has to do it.)
In the web interface, the two “Effects by Policy” graphs (the “CO2e Wedge Diagram” and “CO2e Abatement Cost Curve”) are not set up to group the carbon tax and policies funded by the carbon tax into a single wedge or a single box, so these two graphs may not be useful when assessing the cost-effectiveness of a “carbon tax with smart use of revenues” policy. If using the web interface to model such a policy, it is better to rely on the two “revenue-neutral carbon tax” graphs in the “Financial: Policy Package Cost/Savings” category. However, if you download the EPS, the ContributionTest Python script may be configured to combine the carbon tax with the policies it funds by assigning the carbon tax and the policies funded by the carbon tax revenues the same “group name” (the last item on each policy line). For more on how to use that script, see Testing Policy Contributions and Generating Cost Curves.
Option 3 is best-suited to users who are interested in highlighting the fact that a carbon tax with smart use of revenues on beneficial programs can be more cost-effective at reducing emissions than a revenue-neutral carbon tax.