ImSET 3.1: Impact of Sector Energy Technologies Model Description and User's Guide

This 3.1 version of the Impact of Sector Energy Technologies (ImSET) model represents the next generation of the previously-built ImSET model (ImSET 2.0) that was developed in 2005 to estimate the macroeconomic impacts of energy-efficient technology in buildings. In particular, a special-purpose version of the Benchmark National Input-Output (I-O) model was designed specifically to estimate the national employment and income effects of the deployment of Office of Energy Efficiency and Renewable Energy (EERE)–developed energy-saving technologies. In comparison with the previous versions of the model, this version features the use of the U.S. Bureau of Economic Analysis 2002 national input-output table and the central processing code has been moved from the FORTRAN legacy operating environment to a modern C++ code. ImSET is also easier to use than extant macroeconomic simulation models and incorporates information developed by each of the EERE offices as part of the requirements of the Government Performance and Results Act. While it does not include the ability to model certain dynamic features of markets for labor and other factors of production featured in the more complex models, for most purposes these excluded features are not critical. The analysis is credible as long as the assumption is made that relative prices in the economy would not be substantially affected by energy efficiency investments. In most cases, the expected scale of these investments is small enough that neither labor markets nor production cost relationships should seriously affect national prices as the investments are made. The exact timing of impacts on gross product, employment, and national wage income from energy efficiency investments is not well-enough understood that much special insight can be gained from the additional dynamic sophistication of a macroeconomic simulation model. Thus, we believe that this version of ImSET is a cost-effective solution to estimating the economic impacts of the development of energy-efficient technologies.