Environment-adjusted total-factor energy efficiency of Taiwan's service sectors

This study computes the pure technical efficiency (PTE) and energy-saving target of Taiwan's service sectors during 2001–2008 by using the input-oriented data envelopment analysis (DEA) approach with the assumption of a variable returns-to-scale (VRS) situation. This paper further investigates the effects of industry characteristics on the energy-saving target by applying the four-stage DEA proposed by Fried et al. (1999). We also calculate the pre-adjusted and environment-adjusted total-factor energy efficiency (TFEE) scores in these service sectors. There are three inputs (labor, capital stock, and energy consumption) and a single output (real GDP) in the DEA model. The most energy efficient service sector is finance, insurance and real estate, which has an average TFEE of 0.994 and an environment-adjusted TFEE (EATFEE) of 0.807. The study utilizes the panel-data, random-effects Tobit regression model with the energy-saving target (EST) as the dependent variable. Those service industries with a larger GDP output have greater excess use of energy. The capital–labor ratio has a significantly positive effect while the time trend variable has a significantly negative impact on the EST, suggesting that future new capital investment should also be accompanied with energy-saving technology in the service sectors. - Highlights: • The technical efficiency and energy-saving target of service sectors are assessed. • The pre-adjusted and environment-adjusted total-factor energy efficiency scores in services are assessed. • The industrial characteristic differences are examined by the panel-data, random-effects Tobit regression model. • Labor, capital, and energy and an output (GDP) are included in the DEA model. • Future new capital investment should also be accompanied with energy-saving technology in the service sectors