Abstract
In this paper, we studied differences in the electricity saving rates across households, observed in the summer months of July through September after the Great East Japan Earthquake. To explain what factors carry different influences on the electricity saving rates, we ran panel data regression models using the electricity consumption billing data in the summer months, July through September, over the five years of 2010-2014 for 910 households in the Tokyo and Kansai areas. Specifically, we concentrated on two main explanatory factors: household attributes that include household size and income, and electricity consumption tendencies characterized by average consumption level and its standard deviation. We found that, while some household attributes such as age and floor space have statistically significant linear relationships with the saving rates, households with higher average consumption can have higher saving rates, implying the electricity consumption data acquired by smart meters may be among the key determinants for tailored energy-saving recommendations.