Notes

Executive Summary

1 Energy Information Administration, Annual Energy Outlook 2005, DOE/EIA-0383(2005) (Washington, DC, February 2005), web site www.eia.gov/oiaf/aeo/index.html.

2 The tax credits for new homes and existing home envelopes were assumed to apply from 2006 to 2008. The credits for new appliances were assumed to apply from 2006 to 2010.

3 The aggregate supply potential of the economy is embodied in a concept identified as potential GDP. Potential GDP reflects the supply potential of the economy at full employment, while real GDP (or actual GDP) reflects the actual economy, which may have unemployed or underutilized resources.

Background

1 See Appendix A for a copy of the letter requesting the analysis.

2 Energy Information Administration, The National Energy Modeling System: An Overview 2003, DOE/EIA0581(2003) (Washington, DC, March 2003). Detailed documentation is available on the EIA web site at www.eia.gov/bookshelf/docs.html.

3 Energy Information Administration, Annual Energy Outlook 2005, DOE/EIA-0383(2005) (Washington, DC, February 2005), web site www.eia.gov/oiaf/aeo/index.html.

4 The tax credits for new homes and existing home envelopes were assumed to apply from 2006 to 2008. The credits for new appliances were assumed to apply from 2006 to 2010.

5 Despite these limitations, there are benefits to representing the efficiency policies in an integrated modeling system, even when some of the policy impacts are assumed. The modeling system provides a consistent energy accounting framework and simulates the energy market impacts that would occur with changes in energy demand. In addition, some of the macroeconomic implications of the policies are captured because of the program impacts on energy consumption and wholesale prices. As a result, the primary implications of the policies on energy imports, carbon dioxide emissions, and potential economic output can be addressed.

6 For example, see American Council for an Energy-Efficient Economy, “The Energy Efficiency Performance Standard: A Fair and Effective Way to Realize the Economic and Environmental Benefits of Greater Energy Efficiency,” web site www.aceee.org/energy/eestndrd.htm.

7 Alliance to Save Energy, “Energy Efficiency in the Electric System” (Washington, DC, May 2004), web site www.ase.org/section/_audience/policymakers/eleceff/.

8 Although the policies are assumed to be national in scope, they probably would be administered at the State level.

9 In this context, energy intensity is defined as delivered energy consumption per real dollar of industrial output.

10 The southern climate standard is assumed to apply to four Census divisions: South Atlantic, East South Central, West South Central, and Pacific. The northern climate applies to the other five divisions: New England, Middle Atlantic, East North Central, West North Central, and Mountain.

11 In modeling the provision, the eligibility criteria were based on efficiency measures relative to the 2000 IECC, as these are the building codes on which the NEMS residential model is based. The detailed building simulations to reflect the 2004 IECC are not yet available to incorporate into NEMS. As a result, there may be some small differences in energy savings and costs with the provision as modeled in NEMS.

Results

13 The aggregate supply potential of the economy is embodied in a concept identified as “potential GDP.” Potential GDP is dependent on (in a production function framework) factor inputs and total factor productivity. Factor inputs include capital stock (business and public fixed capital stock), labor, and energy. The concept of potential GDP reflects the supply potential of the economy at full employment, whereas real GDP (sometimes referred to as actual GDP) reflects the actual economy, which may have unemployed or underutilized resources. Based on each factor’s historical share of input costs, the elasticity of potential output with respect to labor is 0.64 (i.e., a 1-percent increase in the labor supply increases potential GDP by 0.64 percent); the business capital elasticity is 0.26; the infrastructure elasticity is 0.02; and the energy elasticity is 0.07.

14 The individual policy impacts in Table 9 were estimated from model runs with the policies considered individually. For simplicity, the estimates are based mostly on standalone, sectoral model runs of NEMS representing the sector affected by the policy. These standalone runs do not include all the feedbacks and joint effects that occur when the policies are simulated in complete, integrated NEMS runs. In most cases, the combined effects of the policies are somewhat less than the sum of the individual policy impacts; however, the estimates provide an indication of the relative contributions of individual policies.