The fluctuations of China's energy intensity: Biased technical change
The fluctuations of China's energy intensity: Biased technical change
复制标题
中国能源强度波动：偏向技术变革
DOI：
10.1016/j.apenergy.2014.06.088
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发表时间：
2014-12-15
期刊：
影响因子：
11.2
通讯作者：
Wei, Yi-Ming
中科院分区：
文献类型：
--
作者：
Wang, Ce;Liao, Hua;Wei, Yi-Ming
中国能源强度的波动引起了许多学者的关注，但考虑官方投入产出表数据质量的研究较少。本文采用基于投入产出表的Divisia方法进行分解模型。由于投入产出表和价格平减指数存在问题，我们首先产生不变价格来缩小投入产出表。然后我们在调整投入产出表时考虑不同部门的不同程度的有偏差的技术变化。最后，我们使用RAS技术来调整输入输出矩阵。然后利用分解模型对我国能源强度的变化进行实证分析。我们比较了有偏差技术变动和无偏差技术变动的分解结果，并对有偏差技术变动的程度进行了敏感分析。分解结果为：2002-2007年，煤炭和电力能源强度增加，其变化主要归因于结构变化，贡献率分别为594.08%、73.88%；原油和成品油能源强度下降，变化主要归因于生产技术的变化，贡献率分别为978.89%、246.95%。敏感分析结果表明，有偏差的技术变化水平变化1%最多会导致分解结果变化0.6%。因此，我们可以得出结论：与无偏技术变化的分解相比，分解结果对有偏技术变化的程度敏感；技术变革的偏向程度可以通过全要素生产率和能源效率变化率的差异来判断。 (C) 2014 Elsevier Ltd. 保留所有权利。
The fluctuations of China's energy intensity have attracted the attention of many scholars, but fewer studies consider the data quality of official input-output tables. This paper conducts a decomposition model by using the Divisia method based on the input-output tables. Because of the problems with input-output tables and price deflators, we first produce constant prices to deflate the input-output tables. And then we consider different levels of biased technical change for different sectors in the adjusting the input-output table. Finally, we use RAS technique to adjust input-output matrix. Then the decomposition model is employed to empirically analyze the change of China's energy intensity. We compare the decomposition results with and without biased technical change and do sensitive analysis on the level of biased technical change. The decomposition results are that during 2002-2007, the energy intensity of coal and electricity increased, the changes were mostly attributed to the structural change and the contribution was 594.08%, 73.88%, respectively; as for crude oil and refined oil, the energy intensity decreased, the changes were mostly attributed to the changes in the production technology and the contribution was 978.89%, 246.95%, respectively. And the results of sensitive analysis shows that 1% variation of the level of biased technical change will cause at most 0.6% change of decomposition results. Therefore, we can draw our conclusions: compared to the decomposition without biased technical change, decomposition results are sensitive to the level of biased technical change; the level of biased technical change can be determined by the difference in the change rate of total factor productivity and energy efficiency. (C) 2014 Elsevier Ltd. All rights reserved.