The economic efficiency of energy-consuming equipment: a DEA approach

The market for an energy-consuming device offers a range of models that will meet consumers' needs for an energy service with different levels of energy efficiency. A more efficient model is likely to have greater up-front costs, but the increased efficiency will eventually translate into energy cost savings over the device's lifespan. Cost-effectiveness indicators (namely, net benefit and benefit-cost ratio) can be used to assess whether a more efficient model can be a better alternative for consumers. However, whereas these indicators express to what extent the additional benefits outweigh the additional costs, they do not indicate how efficiently each model allocates capital and energy to provide the energy service. They, therefore, lack the economic efficiency dimension of the problem. This paper introduces a data-oriented, non-parametric approach to evaluate such efficiency for a set of alternative models of an energy-consuming device. It relies on data envelopment analysis (DEA) to calculate relative efficiency coefficients. The coefficients establish an input efficient frontier for the energy service provided and indicate the models that provide the energy service at the least cost. DEA is further extended to calculate the highest cost-effectiveness achievable and indicate the most cost-effective alternatives. The approach proves useful to support consumers' decision-making when shopping for energy-consuming equipment, to guide manufacturers when benchmarking the models they produce, and to inform energy efficiency policy-making and program designing.