Analyzing the “energy-efficiency gap”
Authors: Bhardwaj Kanupriya , Gupta Eshita 
Published: October 2017

PurposeThe key purpose of this paper is to quantify the size of the energy-efficiency gap (EEG) for air conditioners at the household level in Delhi. Most of the studies in the EEG tradition broadly define EEG as the difference between the actual and optimal level of energy efficiency. The optimal level of energy efficiency is defined at the societal level (that weigh social costs against social benefits) and the private level (that weigh private costs against private benefits).Design/methodology/approachThe authors base the empirical results in this study on the basis of the primary data collected through in-person interviews of the high-income urban households in Delhi in 2014-2015. The sample of 101 households was collected through purposive random sampling. The survey data include information on type and number of AC possessed, hours of operations, socioeconomic characteristics and awareness and habits of households.FindingsUsing primary data of 101 high-income urban household, the paper finds that average EEG is about 10 per cent of total electricity demand of ACs at the household level. The maximum current saving potential measured as a difference between hypothetical energy consumption, if everyone adopts five star ACs, and actual energy consumption is estimated about 14 per cent of the total electricity demand of ACs. Results from the ordinary least squares regressions demonstrate that individual’s habits, attitude, awareness of energy-efficiency measures and perceptions significantly determine the size of the EEG. Among other things, authors’ empirical analysis shows that information can play a central role in guiding investment in energy-efficient technologies. From the analysis of improving access to understandable information about cost savings, payback period and emission reduction, it is found that full information leads to the significant reduction in the size of the expected private energy-efficiency gap from 10 to 2.98 per cent at the household level.Research limitations/implicationsThis paper tests the significance of non-economic and non-social factors in determining the size of the EEG. Apart from socioeconomic factors such as income, occupation and education, individual’s energy-conserving habits and attitudes, awareness of energy-efficiency measures and perceptions are other important factors found to have a significant negative impact on the size of the EEG. This is particularly important for the designing of information programs by policymakers for promoting energy-efficiency choices in view of the change that is required in the behavior and attitudes of the households.Originality/valueIn this study, authors try to estimate the size of the EEG of ACs for the high-income urban households in Delhi. The private energy-efficiency gap estimated at 10 per cent of the household demand for ACs indicates existing saving opportunity for the private households. It is found that provision of comprehensive information about cost savings, payback period and emission reduction reduces the size of the EEG significantly from 10 to 2.72 per cent at the private level. This highlights the existence of limited and incomplete information in the market about the possible costs and benefits of energy-efficiency investments. This paper tests the significance of non-economic and non-social factors in determining the size of the energy-efficiency gap. Apart from socioeconomic factors such as income, occupation and education, individual’s energy-conserving habits and attitudes, awareness of energy-efficiency measures and perceptions are other important factors found to have a significant negative impact on the size of the EEG. This is particularly important for the designing of information programs by policymakers for promoting energy-efficiency choices in view of the change that is required in the behavior and attitudes of the households.