Residential Demand Module

[1]   The Model Documentation Report contains additional details concerning model structure and  operation. Refer to Energy Information Administration, Model Documentation Report:   Residential Sector Demand Module of the National Energy Modeling System, DOE/EIA-M065(2008),  (March 2009).

[2]    Among the explanations often mentioned for observed high average implicit discount rates are: market failures, (i.e., cases where incentives are not properly aligned for markets to result in purchases based on energy economics alone); unmeasured technology costs (i.e., extra costs of adoption which are not included or difficult to measure like employee down-time); characteristics of efficient technologies viewed as less desirable  than  their  less  efficient  alternatives (such  as  equipment  noise  levels  or  lighting  quality characteristics); and the risk inherent in making irreversible investment decisions.   Examples of market failures/barriers include: decision makers having less than complete information, cases where energy equipment  decisions  are  made  by  parties  not  responsible  for  energy  bills (e.g.,  landlord/tenants, builders/home buyers), discount horizons which are truncated (which  might be caused by mean occupancy times that are less than the simple payback time and that could possibly be classified as an information failure), and lack of appropriate credit vehicles for making efficiency investments, to name a few.  The use of high implicit discount rates in NEMS merely recognizes that such rates are typically found to apply to energy-efficiency investments.

[3]  U.S. Bureau of Census, Series C25 Data from various years of publications.

[4] Sources: U.S. Bureau of Census, Annual Housing Survey 2001 and Professional Remodler, 2002 Home Remodeling Study.

[5] See DAHL, CAROL, A Survey of Energy Demand Elasticities in Support of the Development of the NEMS, October 1993.

[6]  The IECC established guidelines for builders to meet specific targets concerning energy efficiency with respect to heating and cooling load.

[7] The high technology assumptions are based on Energy Information Administration, Technology Forecast Updates-Residential  and  Commercial  Building  technologies-Advanced  Adoption  Case (Navigant Consulting, September 2007).