In this paper, we measure the energy efficiency in residential energy consumption using a panel dataset comprised of 40,246 observations from US households observed over 1997-2009. We fit a stochastic frontier model of the minimum input of energy needed to meet the level of energy services demanded by the household. This benchmarking exercise produces a transient and a persistent efficiency index for each household and each time period. We estimate that the US residential sector could save approximately 10% of its total energy consumption if it reduced persistent inefficiencies and 17% if it was able to eliminate transient inefficiencies. These figures are in line with the assessment by McKinsey (2008, 2009, 2013) and greater than those indicated by the Electric Power Research Institute (2009). They suggest that savings in energy use and associated emissions of greenhouse gases (and other pollutants) may benefit from both policy measures that attain short-run behavioral changes (e.g., nudges, social norms, display of real-time information about usage, and real-time pricing) as well measures aimed at the long run, such as energy-efficiency regulations, incentives on the purchase of high-efficiency equipment and incentives towards a change of habits in the use of the equipment.
US residential energy demand efficiency and frontier analysis Household data CO2 emissions reductions