Switching to more energy-efficient appliances may lead to higher energy demand. This phenomenon is known as the rebound effect, which may lead to less power saving than expected prior to the switch. Using a combination of propensity score matching with the difference-in-differences method, we examine the change in household electricity consumption that may be caused by replacing air conditioners with more energy-efficient ones. Based on the results of our estimations, we calculate the magnitude of the rebound effect for summer and winter. We find that the rebound effect is positive in summer and winter, and the magnitude is higher in winter (7.87% versus almost 100%, respectively). The estimated rebound effect is small in summer, implying that the power-saving effect due to switching to energy-efficient air conditioners is sizable. On the other hand, no power-saving effect due to the switch was found in winter.
Space cooling Space heating Rebound effect Propensity score matching Difference-in-differences
C23 D12 Q41
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This research is supported by the Japan Society for the Promotion of Science [Grant-in-Aid for Young Scientists (B) #26780164; Grant-in-Aid for Scientific Research (B) #16H03006].
Allcott H, Greenstone M (2012) Is there an energy efficiency gap? J Econ Perspect 26(1):3–28CrossRefGoogle Scholar
Chan N, Gillingham K (2015) The microeconomic theory of the rebound effect and its welfare implications. J Assoc Environ Resour Econ 2(1):133–159Google Scholar
Chitnis M, Sorrell S (2015) Living up to expectations: estimating direct and indirect rebound effects for UK households. Energy Econ 52(1):100–116CrossRefGoogle Scholar
Chitnis M, Sorrell S, Druckman A, Firth SK, Jackson T (2013) Turning lights into flights: estimating direct and indirect rebound effects for UK households. Energy Policy 55:234–250CrossRefGoogle Scholar
Davis LW (2008) Durable goods and residential demand for energy and water: evidence from a field trial. RAND J Econ 39:530–546CrossRefGoogle Scholar
Davis LW, Fuchs A, Gertler P (2014) Cash for coolers: evaluating a large-scale appliance replacement program in Mexico. Am Econ J Econ Policy 6:207–238CrossRefGoogle Scholar
Dubin JA, Miedema AK, Chandran RV (1986) Price effects of energy-efficient technologies: a study of residential demand for heating and cooling. RAND J Econ 17:310–325CrossRefGoogle Scholar
EDMC (2016) Handbook of Energy & Economic Statistics. The Institute of Energy Economics, Quantitative Analysis Unit, Tokyo, Japan (in Japanese)Google Scholar
Fischer C (2008) Feedback on household electricity consumption: a tool for saving energy? Energy Effic 1:79–104CrossRefGoogle Scholar
Gillingham K, Rapson D, Wagner G (2016) The rebound effect and energy efficiency policy. Rev Environ Econ Policy 10(1):68–88CrossRefGoogle Scholar
Haas R, Biermayr P (2000) The rebound effect for space heating: empirical evidence from Austria. Energy Policy 28(6):403–410CrossRefGoogle Scholar
Heckman JJ, Ichimura H, Todd P (1997) Matching as an econometric evaluation estimator: evidence from evaluating a job training program. Rev Econ Stud 64:605–654CrossRefGoogle Scholar
Heckman JJ, Ichimura H, Smith JA, Todd P (1998a) Characterizing selection bias using experimental data. Econometrica 66:1017–1098CrossRefGoogle Scholar
Heckman JJ, Ichimura H, Todd P (1998b) Matching as an econometric evaluation estimator. Rev Econ Stud 65:261–294CrossRefGoogle Scholar
Japanese Agency for Natural Resources and Energy (2016) Catalog of energy saving performance in winter (in Japanese)Google Scholar
Khazzoom JD (1980) Economic implications of mandated efficiency standards for household appliances. Energy J 1:21–40Google Scholar
Metcalf G, Hasset K (1999) Measuring the energy savings from home improvement investments: evidence from monthly billing data. Rev Econ Stat 81:516–528CrossRefGoogle Scholar