• Energy Research

Abstract Background Rapidly increasing residential electricity demand has made raising energy efficiency an important policy issue in controlling electricity demand. Methods This study uses a stochastic frontier model to estimate the residential electricity demand function and analyse electricity energy efficiency levels and their determinants using regional data on Japan. Results The results confirm the importance of household dwelling types for determining the electricity energy efficiency. Specifically, the findings suggest that household size and floor area are key to electricity savings, but the ageing Japanese society shows a limited relationship with electricity savings. Further, promoting living in areas where the population has aggregated also results in electricity savings. Conclusions The findings suggest that forming urbanised cities and realising multi-polarisation-type national spatial developments might improve electricity energy efficiency and stimulate regional economies.

Controlling the rapid growth of residential energy demand and enhancing energy efficiency are key policy issues in Japan. Thus, this study aims to estimate a residential energy demand function by conducting a stochastic frontier analysis and analyze the regional determinants of energy efficiency. The results indicate that population density and electrification rate foster energy efficiency and exert the same degree of impact. The study also highlights that population concentration has a nonlinear effect on energy efficiency. In other words, when combined with population concentration, the promotion of electrification policies can significantly contribute toward improving energy efficiency in the residential sector and consequently, have a positive effect on Japan’s regional economy.

A balance between industrial pollution and economic growth becomes a major policy issue to attain a sustainable society in the world. To discuss the problem from economics and business perspectives, this study proposes a new use of DEA (Data Envelopment Analysis) as a methodology for unified (operational and environmental) assessment. A unique feature of the proposed approach is that it separates outputs into desirable and undesirable categories. Such separation is important because energy industries usually produce both desirable and undesirable outputs. This study discusses how to unify the two types of outputs under natural and managerial disposability. The proposed DEA approach evaluates various organizations by the three efficiency measures such as OE (Operational Efficiency), UEN (Unified Efficiency under Natural disposability) and UENM (Unified Efficiency under Natural and Managerial disposability). An important feature of UENM is that it separates inputs into two categories and unifies them under the two disposability concepts in addition to the proposed output separation and unification. This study incorporates an amount of capital assets for technology innovation, as one of the two input group, into the measurement of UENM. Then, it compares UENM with the other two efficiency measures. This study is the first research effort in which DEA has an analytical capability to quantify the importance of investment on capital assets for technology innovation. To confirm the practicality of the proposed approach, this study applies the three efficiency measures to a data set regarding manufacturing and non-manufacturing industries of 47 prefectures in Japan. This study empirically confirms the validity of Porter hypothesis in Japanese manufacturing industries, so implying that environmental regulation has been effective for betterment on the performance of Japanese manufacturing industries. Another important finding is that the emission of greenhouse gases is a main source of unified inefficiency in the two groups of industries. Therefore, Japanese industries, examined in this study, need to make their efforts to reduce the greenhouse gas emissions and air pollution substances by investing in capital assets for technology innovation.

To investigate the future trends of energy demand in Japan accurately, it is necessary to clarify the factors that determine the fluctuations in energy demands across regions. Specifically, it is necessary to clarify whether the energy demand fluctuations across regions arise from compositional factors, that is, differences in energy users, or from regionally unique factors. This study analyzes the determinants of energy demand change to clarify the factors that have affected the fluctuations in regional energy demands in Japan, using dynamic shift-share analysis. The results show that the energy demand fluctuations can be explained by compositional effects and regional effects. With regard to the compositional effects, the energy demand growth increased most remarkably in the regions that specialize in residential and commercial activities. However, energy demand did not increase in the regions that specialize in manufacturing activities. With respect to the regional effects, there were constraints on energy demand in big-city regions because of the improved energy intensity achieved through energy conservation. The results imply that having a mixture of industry and civil sector activities in a region potentially flattens out the fluctuations in energy demand changes. This finding suggests that when moderating the change of regional energy demand, it is important to diversify the industrial structure in each region.

PurposeThis paper aims to estimate electricity demand functions in Japan’s residential sector.Design/methodology/approachThe authors use a partial adjustment model and empirically analyze regional residential electricity demand by using data on 47 Japanese prefectures.FindingsThe results reveal that the price elasticity of residential electricity demand during the analytical period (1990-2010) is remarkably different among prefectures, depending on the magnitude of floor space per household. In addition, this study finds that price elasticity is high compared with income elasticity, implying that residential electricity demand changes with rates. Furthermore, an analysis of factors influencing electricity demand in the residential sector shows that increasing electricity demand growth in each region can be attributable mainly to declining electricity rates and increasing number of households.Research limitations/implicationsThese results suggest that monitoring the electricity rates and the number of households is important for forecasting future residential electricity demand at region.Originality/valueThe study considers the impact of the number of households on overall electricity demand and identifies other factors contributing to growth in residential electricity demand. The findings can be used to derive projections for future electricity demand.

This study investigates the impact of population agglomeration and interregional networks on the energy efficiency of the Japanese industrial and commercial sector. The empirical analysis employs a stochastic frontier model and reveals a nonlinear relation between population agglomeration and energy efficiency. External diseconomies prevail until reaching a threshold level of agglomeration; when the threshold is exceeded, external economies come into play. Enhanced accessibility is found to significantly increase energy efficiency. These results suggest that policies aimed at strengthening regional agglomeration and interregional networks can greatly contribute to improving energy efficiency.