A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

Honma, Satoshi; Hu, Jin-Li

doi:10.1016/j.energy.2014.10.066

Cited by 67 publications

(45 citation statements)

References 36 publications

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“…Coefficients of wholesale and retail trade industry share are positive and statistically significant only for group 2, implying that rising the share corresponds to lower efficiency. They are the same signs to our previous study (Honma and Hu 2014a). The coefficient of service activities industry share is positive for group 1 in contrast to negative for group 2.…”

Section: Simultaneous Estimates Of Efficiency and Its Determinantssupporting

confidence: 65%

“…Most data sources of the present paper are the same as our previous work (Honma and Hu 2014a). Data on energy consumption are taken from Agency for Natural Resources and Energy (2013), 4 whereas data on economic variables are taken from the Cabinet Office (2013a, b).…”

Section: Datamentioning

confidence: 99%

“…This is because SFA has advantages that it can consider statistical noises and outliers compared with the DEA. Honma and Hu (2014a) is a companion paper of this study, which extends the crosssectional SFA model proposed by Zhou et al (2012) to panel data models and incorporates the technical inefficiency model proposed by Battese and Coelli (1995) into them. Fujii et al (2016) also applies the SFA to estimate the technical and environmental efficiency scores of Japanese manufacturing industry.…”

mentioning

confidence: 99%

“…In order to take into account of technology difference of multiple groups, in this paper, we incorporate the metafrontier technique into the model of Honma and Hu (2014a). In contrast to Huang et al (2014) that take the output-oriented technical efficiencies, we adopt the TFEE as an input-oriented efficiency measure to shed light on energy use.…”

mentioning

confidence: 99%

“…It is advocated by Hu and Wang (2006) using data envelopment analysis (DEA) and is applied to the Asia-Pacific economy (Hu and Kao 2007), Japan (Honma and Hu 2008, 2014a, Taiwan (Hu et al 2012), and OECD (Honma and Hu 2014b). Although the TFEE is originally defined and is measured by the DEA in the above studies, Honma and Hu (2014a) and Hu and Honma (2014) resort to the stochastic frontier analysis (SFA). This is because SFA has advantages that it can consider statistical noises and outliers compared with the DEA.…”

mentioning

confidence: 99%

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A meta-stochastic frontier analysis for energy efficiency of regions in Japan

Honma

2018

Economic Structures

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After the Fukushima Daiichi nuclear disaster on March 11, 2011, energy conservation has been an urgent issue in Japan. After the accident, all 54 nuclear reactors in Japan had been shut down. Nowadays, due to newly introduced more stringent regulation and prospect from the public, only three nuclear plants are at work on March, 2016. Although a new feed-in tariff to promote renewable energy was introduced in July 2012, it cannot fully make up for the shortfall resulting from the cessation of nuclear power generation. Improving energy efficiency is a feasible solution to the current energy issues in Japan. To this end, we need detailed information what factors affect energy inefficiency.Technological modernization is one of the key factors for success in improving productivity and environmental management (Yang et al. 2017). In general, a decision-making unit (DMU) can use not all available technology, but only specific technology given the current physical, social, and human capitals. Policy-makers should distinguish two inefficiencies: One is attributed to operating failures under the existing technology and the other is attributed to an inability to access the best available technology. The former can be resolved by the DMU's effort given the circumstance, but the latter cannot be mitigated without investment to state-of-the-art equipment and management system. AbstractThis paper measures the metafrontier total-factor energy efficiency (TFEE) of 47 regions in Japan for the period 1996-2008, using the stochastic frontier analysis (SFA). The twostep output-oriented SFA approach by Huang et al. (J Prod Anal 42:241-254, 2014) is followed but converted into a two-step input-oriented SFA approach. The metafrontier TFEE is defined as a product of the group TFEE and the technological gap ratio (TGR). The mean group TFEE is smaller than the mean TGR for both the groups, which shows that the energy inefficiency in Japanese regions with respect to the metafrontier comes from primarily operating inefficiency, rather technology gap. The mean metafrontier TFEE of the metropolitan areas is smaller than that of rural areas, implying that the former is energy inefficient than the latter. The mean TGR of the metropolitan areas is also smaller than that of rural areas, implying that many Japanese regions with major cities are far below the metafrontier and still have much room for energy savings.

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Section: Simultaneous Estimates Of Efficiency and Its Determinantssupporting

confidence: 65%

Section: Datamentioning

confidence: 99%