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

机译：台湾服务业经环境调整的全要素能源效率

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摘要

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.
机译：这项研究通过使用输入变量数据包络分析（DEA）方法并假设可变规模收益（VRS），计算了2001-2008年台湾服务业的纯技术效率（PTE）和节能目标。情况。本文通过应用Fried等人提出的四阶段DEA，进一步研究行业特征对节能目标的影响。 （1999）。我们还计算了这些服务领域中的预先调整和环境调整的全要素能源效率（TFEE）分数。 DEA模型中包含三个输入（劳动力，资本存量和能源消耗）和单个输出（实际GDP）。最节能的服务行业是金融，保险和房地产，其平均TFEE为0.994，经环境调整后的TFEE（EATFEE）为0.807。该研究利用了以节能目标（EST）为因变量的面板数据，随机效应Tobit回归模型。 GDP产出较大的服务业有更多的能源过度使用。资本劳动比率具有显着的正效应，而时间趋势变量对EST则具有显着的负效应，这表明未来的新资本投资也应在服务行业中采用节能技术。

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