As a part of national efforts to achieve green development and mitigate GHCs emissions, European industries have perceived the huge potential benefits from adopting energy saving policies and environmental friendly technologies following European as well as country specific policies. A clean and energy saving manufacturing sector has been targeted as a key area for Europe, particularly, since the launch of Energy Efficiency Directives 2012/27/EU and 2018/2002/EU. Thus, building up an energy efficient European industry can benefit European countries to improve their welfare with greater levels of energy independence and security, achieve the underlying objective of cost minimization and face successfully the threat of energy rising prices. Additionally, it can evolve into a valuable asset for reducing CO2 emissions, fulfilling Kyoto protocol and Paris Agreement (2015), enhancing industry competitiveness and promoting economic growth through continual innovation (European Commission, 2011). On the basis of the above mentioned, a detailed estimation of total factor energy efficiency estimates, at a European industry level is essential for policy makers, economists, environmentalists and scholars. Moreover, it is important to evaluate and detect possible factors that affect total factor energy efficiency scores. Less immediate for this research, but equally important from a production theory perspective, is to incorporate in our total factor energy efficiency estimations the presence of CO2 emissions and examine the convergence-divergence hypothesis. Finally, this research aims at enlightening the role of technological heterogeneity and any country hierarchies in the benchmarking process revealing specific idiosyncrasies at national and European level. The adopted methodology operates in three stages. In the first stage we adopt a fully non-parametric approach to perform benchmarking on total factor energy efficiency scores across industries using Data Envelopment Analysis (DEA) and Directional Distance Function (DDF). In the second stage, econometric approaches provide us a concrete evaluation as whether some groups of variables are likely to increase energy efficiency with respect to the different technologies. Finally, in the third stage, we proceed with a convergence analysis for our total factor energy efficiency estimates. Our results are important for the analysis of governmental policies regarding energy efficiency and the environment such as carbon taxes. Regarding total factor energy efficiency, our results reveal that small-scale economies exhibit a persistent high performance. In addition, the results regarding its determinants suggest that path dependence phenomena have a strong presence, revealing technological lock-in, climatic characteristics occurs, while energy mix displays linear and non-linear relationships. Finally, regardless of the method employed, there is a strong evidence of conditional and unconditional convergence for total factor energy efficiency scores.

中文翻译：

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不同技术体制下的欧洲工业能源效率：二氧化碳排放、气候、路径依赖和能源组合的作用

作为实现绿色发展和减少 GHC 排放的国家努力的一部分，欧洲工业已经意识到遵循欧洲和国家特定政策采用节能政策和环境友好技术的巨大潜在好处。清洁和节能制造业一直是欧洲的重点领域，特别是自 2012/27/EU 和 2018/2002/EU 能效指令发布以来。因此，建立一个节能的欧洲工业可以使欧洲国家在更高水平的能源独立性和安全性下改善其福利，实现成本最小化的根本目标，并成功应对能源价格上涨的威胁。此外，它可以演变成减少二氧化碳排放的宝贵资产，履行京都议定书和巴黎协定（2015 年），通过持续创新提高行业竞争力和促进经济增长（欧盟委员会，2011 年）。在上述基础上，对欧洲产业层面的全要素能源效率估算进行详细估算对于政策制定者、经济学家、环保主义者和学者来说至关重要。此外，评估和检测影响全要素能效得分的可能因素也很重要。这项研究不太直接，但从生产理论的角度来看同样重要的是，将 CO2 排放的存在纳入我们的全要素能源效率估计中，并检查收敛-发散假设。最后，这项研究旨在阐明技术异质性和任何国家等级制度在标杆过程中的作用，揭示国家和欧洲层面的特定特质。所采用的方法分三个阶段运作。在第一阶段，我们采用完全非参数化的方法，使用数据包络分析 (DEA) 和方向距离函数 (DDF) 对跨行业的全要素能效得分进行基准测试。在第二阶段，计量经济学方法为我们提供了具体的评估，即某些变量组是否可能提高不同技术的能源效率。最后，在第三阶段，我们对全要素能效估计进行收敛分析。我们的结果对于分析有关能源效率和环境的政府政策（如碳税）非常重要。关于全要素能源效率，我们的结果表明，小规模经济体表现出持续的高性能。此外，关于其决定因素的结果表明路径依赖现象具有很强的存在性，揭示了技术锁定、气候特征的发生，而能源组合则显示出线性和非线性关系。最后，无论采用何种方法，都有强有力的证据表明全要素能效得分有条件和无条件收敛。此外，关于其决定因素的结果表明路径依赖现象具有很强的存在性，揭示了技术锁定、气候特征的发生，而能源组合则显示出线性和非线性关系。最后，无论采用何种方法，都有强有力的证据表明全要素能效得分有条件和无条件收敛。此外，关于其决定因素的结果表明路径依赖现象具有很强的存在性，揭示了技术锁定、气候特征的发生，而能源组合则显示出线性和非线性关系。最后，无论采用何种方法，都有强有力的证据表明全要素能效得分有条件和无条件收敛。