Green Jobs
Higher energy prices lead consumers and producers to economize their energy use. This will come from a combination of simply producing and using less of the energy-consuming products and activities. The economizing can also come from investing in more energy-efficient products and processes. This latter response is often credited with creating "green" or "green-collar" jobs. These responses have been estimated in the equations of the macro-economic model used for our analysis. Therefore, the job losses reported in this study are over and above any "green" job gains. The net impact of the regulations will be lower employment and less income. The "green jobs dividend" is negative.
Economic Costs of the ANPR
The ANPR affects the economy directly by increasing the cost of using carbon-based energy. These higher costs require consumers and producers to switch to inferior or more expensive substitutes or to simply cut production and consumption.[5]
The economic model employed here treats the proposed regulations like a tax on energy producers. Thus, energy prices increase by the amount dictated by the regulations. The demand for energy responds to higher energy prices both directly and indirectly. The direct effect is a reduction in the consumption of carbon-based energy and a shift, where possible, to substitutes that either do not require the fee or require a smaller one.
The indirect effects are more complex. Generally speaking, the ANPR regulations reduce the amount of energy used in producing goods and services, which restricts the demand for labor and capital and reduces the rate of return on productive capital. This "supply-side" impact exerts the predictable secondary effects on labor and capital income, which depresses consumption.
These are not unexpected effects. Carbon-reduction schemes that depend on excessive regulations, fees, or taxes attain their goals of lower atmospheric carbon by slowing carbon-based economic activity. Of course, advocates of this approach hope that other energy sources will arise that can be used as perfect substitutes for the reduced carbon-based energy.
Our simulation of potential CAA regulations attempts to follow the vision of the authors' proposal. The process is assumed to be unhampered by lawsuits, bureaucratic inefficiencies, or technological bottlenecks. Everything is "by the book."
If we have succeeded in these efforts, then policymakers can expect the following similar economic effects:
Economic Output Declines. The broadest measure of economic activity is the change in GDP after accounting for inflation. GDP measures the dollar value of all goods and services produced for final sale to consumers in the United States during the year. Anticipation of CO2 restrictions causes an initial increase in gross private investment as firms accelerate capital projects to avoid the higher costs of a CO2-constrained economy. In addition, there may be some initial-investment increases from businesses replacing their soon-to-be obsolete energy-intensive capital.
Nevertheless, the net impact on a CO2-constrained economy is negative, since GDP is never higher than in the baseline scenario. Higher energy costs decrease the use of carbon-based energy in the production of goods, incomes fall, and demand for goods subsides. GDP declines in 2020 by $332 billion, in 2025 by $528 billion, and in 2029 by $632 billion. The aggregate income loss for the 20-year period is $6.8 trillion. All figures have been adjusted for inflation to reflect 2008 prices.
This slowdown in GDP is seen more dramatically in the slump in manufacturing output. Again, the manufacturing industry benefits from the initial investment in new energy production and energy-efficient capital, but the manufacturing sector's declines are sharp thereafter.
Indeed, by 2029, manufacturing output in this energy-sensitive sector will be 27 percent below what it would be if the ANPR proposals are never applied. In 2029, the manufacturing output is $1.48 trillion less than the baseline output; that is, when compared to the economic world without the CAA regulation of CO2. This is equivalent to losing more than 80,000 manufacturing firms. Aggregate manufacturing loss from 2010 to 2029 is $10.9 trillion.
Number of Jobs Declines. The loss of economic output is the proverbial tip of the economic iceberg. Below the surface are economic reactions to the legislation that led up to the drop in output. Employment growth slows sharply following the boomlet of the first few years. Potential employment (or the job growth that would be implied by the demand for goods and services and the relevant cost of capital used in production) slumps sharply. In 2015, regulation-induced employment losses exceed 500,000; and they exceed that level for the remainder of the investigated period. Non-farm job losses peak at more than 800,000.
Indeed, in no year after the boomlet does employment under the ANPR outperform the baseline economy where these proposed regulations never become law.

For manufacturing workers, the news is grim indeed. Employment will already be in decline due to increased labor-saving productivity: Our baseline shows that even without additional job-killing regulations, manufacturing employment will drop by more than 980,000 jobs. The ANPR accelerates this decrease substantially: Employment in manufacturing declines by an additional 22.6 percent or 2,880,000 jobs beyond the baseline losses. By 2029, several specific areas of the manufacturing industry will experience particularly harsh employment losses:
- Durable-manufacturing employment will decrease by 28 percent;
- Machinery-manufacturing job losses will exceed 57 percent;
- Textile-mills employment will decrease by 27.6 percent;
- Electrical-equipment and -appliance employment will decrease by 22 percent;
- Paper and paper-product jobs will decrease by 36 percent; and
- Plastic and rubber products employment drops 54 percent.
All employment declines described are in addition to those that occur in the baseline projections.
Other, less energy-intensive sectors, however, do not suffer such decreases. For instance, government employment ends the 20-year period 0.62 percent ahead of the baseline level; professional and business service employment (which includes lawyers) rises by 6.14 percent; and employment in education rises by 8.4 percent more than the baseline.
Because states have different mixes of industries, the job losses are not evenly distributed. The states whose economies are disproportionately dependent on manufacturing, such as Indiana, Louisiana, Wisconsin, Iowa, and Oregon, will be disproportionately affected by the manufacturing job losses.
Incomes and Consumption Decline. Declining demand for energy-intensive products reduces employment and incomes in the businesses producing these products. Workers and investors earn less, and household incomes decline. Reductions in income in these sectors spread and cause declines in demand for other sectors of the economy.
Our simulation captures this effect of higher energy costs: Disposable personal income falls $145 billion below baseline in 2015 and averages $2.6 trillion below baseline over the entire period of 2010 to 2029.
Conclusion
The ANPR proposes an unprecedented expansion of federal ability to regulate CO2 emissions. Its limits on CO2 emissions would impose significant costs on virtually the entire American economy.
Even under a fairly optimistic set of assumptions, the economic impact of the ANPR is likely to be serious for the job market, household budgets, and the economy overall. The effects discussed above in the simulation are the result of restricted energy use only; they do not consider the substantial administrative costs of complying with the new regulations.

The burden will be shouldered by the average American. The regulations would have the same impact on GDP and employment as would a major new energy tax—only worse. In the case of the CAA, increases in costs are set by forces beyond legislative control.
Overall, using the CAA to regulate CO2 would likely be the most expensive and expansive environmental undertaking in history.
David W. Kreutzer, Ph.D., is Senior Policy Analyst for Energy Economics and Climate Change, and Karen A. Campbell, Ph.D., is Policy Analyst in Macroeconomics, in the Center for Data Analysis at The Heritage Foundation.
Appendix A
Methodology
Analysts at The Heritage Foundation and the Global Insight forecasting company employed a wide array of analytical models to produce the micro- and macroeconomic results reported in this paper. This section describes the models and the major steps performed by these analysts to shape the modeling results.
U.S. Energy Model (Long-Term)
Global Insight's U.S. Energy Model has been designed to analyze the factors that determine the outlook for U.S. energy markets. A staff of more than 15 energy professionals supports the model and forecasting effort. The model is constructed as a system of several models that can be used to assess intra-market issues independently of each other. The integrated system is used to produce Global Insight's baseline Energy Outlook and allows users to simulate changes in domestic energy markets.
The U.S. Energy Model is an integrated system of fuel and electric power models and the End-User Demand Model. The solution is achieved through an iterative procedure. Also, monthly models of petroleum and natural gas prices use the framework of the long-term forecast with additional weekly and monthly information to analyze seasonal fuel prices and update the price forecasts on a monthly basis. The major models that comprise the Energy Model and their interrelationships are described below.
End-Use Demand Model. Demand for final-use energy is modeled by sector, fuel, and census region based on the competitive position of each fuel in its end-market. The total demand for energy is estimated as a function of the stock of energy equipment, technology change, prices of competing final energy sources, and economic performance. The initial demand profile by region of the U.S. for each fuel is then integrated with the U.S. Petroleum, Natural Gas, Coal, and Electric Power Models, each of which consists of three major sub-modules—a supply and transformation module, a transportation/ transmission/distribution module, and a wholesale/ retail price module.
U.S. Petroleum Model. The U.S. Petroleum Model uses the world oil price projection from Global Insight's Global Oil Outlook. The model then determines refined petroleum product prices to end-users by adding refining markups, inventory, and transportation costs. For selected products, federal, state, and local taxes are also accounted for in the model.
The U.S. Petroleum Model also provides a baseline projection of U.S. crude and natural gas production that is based on an annual review of data and literature on U.S. reserves, production, and technological progress.
A simulation block for investigating the supply response under alternative assumptions is part of this model. Imported supplies of crude and petroleum products are developed by the difference between domestic production and the sum of the direct consumption of petroleum by consumers and the transformation demand for petroleum by the power sector.
Natural Gas Model. The Natural Gas Model consists of three major sub-modules: a supply module, a transmission/distribution module, and a spot-pricing module.
- The supply module projects production based on analysis of U.S. reserve data, exploratory and development drilling, and technological progress. A simulation block for investigating supply responses under alternative assumptions is part of this module.
- The transmission/distribution module projects cost by customer class.
- The spot-pricing model integrates the results of the End-User Demand Model, the natural gas demand by the power sector from the Electric Power Model, and the embedded supply and transmission/distribution modules to determine producer prices by basin. A conclusive solution is developed through an interactive process.
Coal Model. The Coal Model is a simulation model designed to replicate the market response of this sector under alternative scenarios. Finalized through the interactive process, the baseline market analysis is provided by JD Energy (a coal and power consulting firm) that includes analysis and forecasts of coal production, rail costs, coal flows, and coal prices.
Electric Power Model. The U.S. Electric Power Model is a detailed, regional (census region) model of the power-generation sector combined with a more aggregate module of the regional transmission and distribution sector.
The preliminary demand for regional generation is determined as a function of the demand for electricity determined in the End-User Demand Model, transmission losses, and trade. Generation requirements are met through the capacity module, which projects capacity decisions based on fuel prices, operating and maintenance costs, and technological progress. Usage is projected as a function of the amount of electricity generated and marginal production cost. Through this analysis, a preliminary demand for a specific fuel by the power sector is developed that is finalized in the iterative process.
Energy Balances Model. The Energy Balances Model completes the process. This model provides national and regional summations of energy use across all fuel types and customer classes.
Operation of the Energy Models. The ANPR implies very aggressive carbon-reduction targets between 2012 and 2050. Most proposed legislation allows offsets to achieve the target CO2 reductions. We assume that EPA regulation of CO2 emissions would target actual reductions equivalent to those required beyond the allowed offsets in legislation, such as the Lieberman–Warner bill. That is, we assume that the regulatory regime allows 30 percent of the reductions to come from non-domestic-energy reductions.
Global Insight Long-Term U.S. Macroeconomic Model
The Global Insight (GI) long-term U.S. macroeconomic model is a large-scale 30-year (120-quarter) macroeconometric model of the U.S. economy. It is used primarily for commercial forecasting.
Over the years, analysts at The Heritage Foundation's Center for Data Analysis have worked with economists at Global Insight to adapt the GI model to policy analysis. In simulations, CDA analysts use the GI model to evaluate the effects of policy changes not only on disposable income and consumption in the short run, but also on the economy's long-run potential. They can do so because the GI model imposes the long-run structure of a neoclassical growth model, but makes short-run fluctuations in aggregate demand a focus of analysis.
The Global Insight model can be used to forecast more than 1,400 macroeconomic aggregates. Those aggregates describe final demand, aggregate supply, incomes, industry production, interest rates, and financial flows in the U.S. economy. The GI model includes such a wealth of information about the effects of important changes in the economic and policy environment because it encompasses detailed modeling of consumer spending, residential and non-residential investment, government spending, personal and corporate incomes, federal (and state and local) tax revenues, trade flows, financial markets, inflation, and potential gross domestic product.
Consistent with the rational-expectations hypothesis, economic decision making in the GI model is generally forward-looking. In some cases, Global Insight assumes that expectations are largely a function of past experience and recent changes in the economy. Such a retroactive approach is used in the model because GI believes that expectations change little in advance of actual changes in the economic and policy variables about which economic decision makers form expectations.
Operation of the U.S. Macroeconomic Model
The policy changes implied by the ANPR and implemented in the U.S. Energy Model (as described above) resulted in more than 71 changes in the U.S. Macroeconomic Model. These changes ranged from energy-source variables (such as the price of West Texas Intermediate crude oil, an industry benchmark price series) to the carbon tax rate per ton of coal.[6] These energy-model results were introduced into the macro model in the following ways:
Energy Price Effects. Heritage Foundation analysts used the market price changes in the refiner's acquisition price for oil (West Texas Intermediate) and natural gas prices at the wellhead (Henry Hub) directly from the energy model.
The macro model contains a host of producer prices that are changed through their interaction with other variables in this model. However, the modeled policy changes affect producer prices in the energy sectors directly. Thus, the energy model's settings for these producer prices were used instead of those in the macro model. Technically, energy-producer prices were exogenous and driven by corresponding prices from the energy model. The following producer price categories were affected: coal, natural gas, electricity, natural gas, petroleum products, and residual fuel oil.
We employed a similar procedure in implementing changes in consumer prices. In this case, the variables affected were all consumption-price deflators. Once again, we substituted energy-model settings for these variables for their macro-model counterparts. The following consumption price deflators were affected: fuel oil and coal, gasoline, electricity, and natural gas.
Energy Consumption Effects. Both the energy model and the macro model contain equations that predict changes in demand for energy, given changes in energy prices, but the energy model contains a more detailed treatment of demand. Preferring details over generality, we lined up the demand equations in both models and substituted settings from the energy model for those in the macro model. Specifically, we lined up these demand equations:
- Total energy consumption;
- Total end-use consumption for petroleum;
- Total end-use consumption for natural gas;
- Total end-use consumption for coal; and
- Total end-use consumption for electricity.
One key transformation that took place dealt with the differing demand units used between the two models in calculating residential consumption. The energy model expresses demand in trillions of British thermal units, while the macro model projects demand in billions of constant dollars.
Another key transformation focused on consumer spending on gasoline. The energy model does not contain a separate forecast for spending on gasoline or other motor fuels. To overcome this, we projected the change in consumer spending on gasoline based on the energy model's change in total highway fuel consumption.
Capital Spending. The energy model calculates capital spending by electric utilities in the base case and in the ANPR case. Spending is higher (at least initially) and costlier in the ANPR case because higher-cost power plants are built or because old plants are refurbished. The change in spending was applied to the macro model variable for inflation-adjusted spending on utility investment after conversion to the appropriate base year.
The analysts then calculated the amount of spending that would have been required to produce the same level of electricity capacity had the mix of spending been equivalent to the baseline. The purpose here is to measure the extra resources required for utility construction simply due to the introduction of the resources related to the carbon fee that will produce lower emissions, but which will not produce extra GDP.
Appendix B


[1] The EPA has the authority to regulate all greenhouse gases. The primary GHGs to be regulated are CO2, methane, and nitrous oxide. This paper limits its analysis to the economic impact from the higher energy costs that regulating CO2 would generate.
[2] In Massachusetts v. the Environmental Protection Agency, 549 U.S. 497 (2007), a divided Supreme Court determined that carbon dioxide is a pollutant as defined in the Clean Air Act. This decision gives the EPA the authority, but not necessarily the mandate, to regulate CO2 to prevent global warming or other harmful effects attributed to CO2. Though the EPA has not, as of this writing, made the endangerment finding that would precipitate regulation, the detailed proposals of the Advanced Notice of Proposed Rulemaking can be interpreted to indicate just such an intent. An endangerment finding is very likely to precipitate a cascade of regulatory actions even though the EPA may prefer a more limited response. This study makes the generous assumption that the EPA can limit the scope and speed with which the regulations are implemented.
[3] Examples of the costly existing regulations are the enacted, but not yet in effect, higher Corporate Average Fuel Economy (CAFE) standards, renewable portfolio standards for electricity generation, and stricter building codes.
[4] Global Insight, "Long-Term Forecast 30-Year Overview," October 2007. Heritage Foundation analysts relied on models maintained by Global Insight to develop the economic estimates reported in this paper. The Global Insight model is used by private-sector and government economists to estimate how changes in the economy and public policy are likely to affect major economic indicators. The methodologies, assumptions, conclusions, and opinions presented here are entirely the work of analysts at The Heritage Foundation's Center for Data Analysis. They have not been endorsed by, and do not necessarily reflect the views of, the owners of the Global Insight model.
[5] These adjustments will take place on many dimensions. For instance, consumers may be forced to consume more expensive and less reliable solar and wind energy; consumers may drive smaller, less safe cars; and increased building costs can lead to smaller and more expensive homes.
[6] The specific year-by-year settings are available upon request from the Center for Data Analysis at The Heritage Foundation.