Analysis of the Lieberman-Warner Climate Security Act (S. 2191) Using the National Energy Modeling System (NEMS/ACCF/NAM)


The American Council for Capital Formation (ACCF) and the National Association of Manufacturers (NAM) believe it important to fully and realistically examine the potential costs that enactment of Lieberman-Warner Climate Security Act (S. 2191) would impose on the U.S. economy. It is becoming increasingly recognized that the cost to U.S. consumers and employers of implementing greenhouse gas (GHG) emission reductions is highly dependent on the market penetration achieved by key technologies and the availability of carbon offsets by 2030. Understanding the potential economic impacts at the national, state and individual household levels can help guide choices on climate change policy to minimize the impacts on economic growth and maximize the benefits to the environment. Greenhouse gas reduction policies need to include consideration of impacts on energy security, economic growth, and U.S. competitiveness. This project is designed to assist in this effort.

This analysis was undertaken using the National Energy Modeling System (NEMS) model, the model used by the U.S. Energy Information Administration (EIA) for its energy forecasting and policy analysis. The ACCF and NAM applied assumptions about the cost and availability of new energy technologies, oil prices, and other key factors. The NEMS/ACCF/NAM1 study’s findings indicate substantial and growing impacts to consumers and the economy of meeting the increasingly stringent emission targets through 2030 established by the Lieberman-Warner Climate Security Act.

Among the NEMS/ACCF/NAM study’s findings are:

  • The CO2 emissions allowance price needed to reduce energy use to meet the S.2191 targets is estimated at $55 to $64/metric ton CO2 in 2020, rising to between $227 to $271/metric ton CO2 in 2030.
  • The cost of the allowances raises energy prices for residential consumers by: Natural gas: 26% to 36% in 2020, and 108% to 146% in 2030;
    Electricity: 28% to 33% in 2020, and 101% to 129% in 2030.
  • These and other increased energy costs slow the economy by $151 billion to $210 billion in 2020 and $631 billion to $669 billion in 2030 (in 2007 dollars). This in turn leads to job losses of between 1.2 million to 1.8 million in 2020 and 3 million to 4 million by 2030.
  • Manufacturing slows, the value of shipments falls by 3.2 % to 4% in 2020 under the low and high cost cases; by 2030 the value of shipments falls by 8.3 % to 8.5% under the two cases. The higher energy costs, lower economic activity and fewer jobs in turn lowers average household income by $739 to $2,927 in 2020 and between $4,022 and $6,752 in 2030 (in 2007 dollars).1 The term “NEMS/ACCF/NAM” is used in this report to distinguish NEMS runs conducted in this project from those conducted by EIA.

As noted in a November, 2007 Congressional Budget Office study, Issues in Climate Change:2

“Obtaining allowances—or taking steps to cut emissions to avoid the need for such allowances—would become a cost of doing business for firms that were subject to the CO2 cap. However, those firms would not ultimately bear most of the costs of the allowances. Instead, they would pass along most such costs to their customers (and their customers’ customers) in the form of higher prices. By attaching a cost to CO2 emissions, a cap-and-trade program would thus lead to price increases for energy and energy-intensive goods and services that contribute the most to those emissions. Such price increases would stem from the restriction on emissions and would occur regardless of whether the government sold emission allowances or gave them away. Indeed, the price increases would be essential to the success of a cap-and-trade program because they would be the most important mechanism through which businesses and households were encouraged to make investments and behavioral changes that reduced CO2 emissions. The rise in prices for energy and energy-intensive goods and services would be regressive—that is, they would impose a larger burden, relative to income, on low-income households than on high-income households.”

As mentioned above, the ACCF/NAM analysis investigates the sensitivity of assumptions that have proven in the past to significantly impact the cost of limiting CO2 emissions from energy – particularly the availability of improved technology in the early decades of a long-term effort to reduce greenhouse gas emissions. These assumptions include the availability of nuclear power technology, the availability of carbon capture and storage for more efficient coal and natural gas-based power generation technologies, the availability of wind and biomass technologies, and the availability of low-cost offsets (international and domestic).

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