Estimating the changes in the distribution of energy efficiency in the U.S. automobile assembly industry

• Published in: Energy economics Vol. 42; pp. 81 - 87
• Main Author: Boyd, Gale A.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.03.2014; Elsevier; Elsevier Science Ltd
• Subjects: Applied sciences; Automobile industry; Best practice; Economic data; Electric energy; Electric power; Energy; Energy economics; Energy efficiency; Energy industry; Energy management; Energy policy; Energy resources; Errors; Exact sciences and technology; Factories; Fossil fuels; Fossil fuels and derived products; General, economic and professional studies; Industry; Manufacturing; Methodology. Modelling; Microdata; Oil; Stochastic frontier; Studies; U.S.A; United States; North America; America; United States > US; Government Policy; L60 Industry Studies; Microdata; Technological Innovation; Other Transportation Equipment; O39 Technological Change; Energy efficiency; Stochastic frontier; Q48 Energy; Manufacturing; General L62 Automobiles; Other Q55 Environmental Economics; Gouvernment Policy; Energy consumption; Energy conservation program; Assembly plant; Fuel consumption; Energy savings; Energy intensity; Innovation; Energy conservation; Technological change; Automobile industry; Electric power consumption; Stochastic Frontier
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2013.11.008

This paper describes the EPA's voluntary ENERGY STAR program and the results of the automobile manufacturing industry's efforts to advance energy management as measured by the updated ENERGY STAR Energy Performance Indicator (EPI). A stochastic single-factor input frontier estimation using the gamma error distribution is applied to separately estimate the distribution of the electricity and fossil fuel efficiency of assembly plants using data from 2003 to 2005 and then compared to model results from a prior analysis conducted for the 1997–2000 time period. This comparison provides an assessment of how the industry has changed over time. The frontier analysis shows a modest improvement (reduction) in “best practice” for electricity use and a larger one for fossil fuels. This is accompanied by a large reduction in the variance of fossil fuel efficiency distribution. The results provide evidence of a shift in the frontier, in addition to some “catching up” of poor performing plants over time. •A non-public dataset of U.S. auto manufacturing plants is compiled.•A stochastic frontier with a gamma distribution is applied to plant level data.•Electricity and fuel use are modeled separately.•Comparison to prior analysis reveals a shift in the frontier and “catching up”.•Results are used by ENERGY STAR to award energy efficiency plant certifications.