| 中国人均能源消费水平地区差距的发展与解释——基于Shapley值分解方法 |
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| 引用本文： | 李博,李清彬.中国人均能源消费水平地区差距的发展与解释——基于Shapley值分解方法[J].资源科学,2013,35(6):1194-1201. |
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| 作者姓名： | 李博 李清彬 |
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| 作者单位： | 1. 天津理工大学国际工商学院,天津,300384
2. 国家发展改革委经济研究所,北京,100038 |
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| 摘 要： | 能源作为现代社会发展的重要基础,与中国经济的发展息息相关.而由于资源禀赋、历史基础与自然环境等方面的地区差异性,中国的发展具有较为明显的区域性特征,这种存在于各地区之间的差异性显然也表现在了能源消费方面.本文使用1998年-2009年的中国省级面板数据测度人均能源消费水平的地区差距,考察决定地区人均能源消费水平的城市化水平、城镇居民消费、工业化程度、国有化程度、对外开放程度以及技术创新能力等因素的影响情况,然后运用基于回归的Shapley值分解技术,对中国地区人均能源消费水平差距进行分解研究.分解结果显示:地区固有因素是影响地区差距的最主要因素,接下来依次是城市化水平、城镇居民消费水平、工业化程度、国有化程度、对外开放程度,以及技术创新能力.其中,对外开放程度与技术创新能力是促进地区差距缩小的重要因素.基于研究结果,本文进而探讨了相关的政策含义.
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| 关 键 词： | 能源消费水平 地区差距 不平等分解 Shapley值 |
| 收稿时间： | 2/5/2013 12:00:00 AM |
Development and Explanation of Regional Inequality in Per Capita Energy Consumption in China: An analysis based on Shapley Value Decomposition |
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| LI Bo and LI Qingbin.Development and Explanation of Regional Inequality in Per Capita Energy Consumption in China: An analysis based on Shapley Value Decomposition[J].Resources Science,2013,35(6):1194-1201. |
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| Authors: | LI Bo and LI Qingbin |
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| Institution: | International College of Business and Technology, Tianjin University of Technology, Tianjin 300384, China;Institute of Economic Research, National Development and Reform Commission, Beijing 100038, China |
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| Abstract: | Due to differences in resource endowment, historical base and the natural environment, regional variation in development, and energy consumption, exist across the Chinese economy. Using provincial panel data from 1998 to 2009, we measured district per capita energy consumption inequality across China and the effects of urbanization, consumption by urban residents, industrialization, state-ownership, openness, and technological innovation capacity. Using regression-based Shapley value decomposition, we identified district per capita energy consumption inequality and found that between 1998-2009, provincial per capita energy consumption of China grew steadily and then slowed gradually. Eastern China per capita energy consumption was higher than western China, and the western per capita energy consumption was higher than central China, but inequality is in decline. Factors inherent to each district appear to be the most influential drivers of inequality, including urbanization, consumption by urban residents, industrialization, state-ownership, openness and technological innovation capacity. Openness and technological innovation capacity were found to reduce district inequality. Related policy implications are discussed based on these results. For example, more attention should be paid to narrowing differences in industrialization and the proportion of state-owned enterprise between regions. |
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| Keywords: | Energy consumption Regional inequality Inequality decomposition Shapley value |
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