基于SBM模型的中国钢铁行业能源效率研究

发布时间：2018-01-20 10:33

本文关键词： SBM模型技术效率规模效率全要素能源效率　出处：《东北财经大学》2013年硕士论文　论文类型：学位论文

【摘要】：我国是钢铁生产、消费和进出口大国,已跃居世界第一位,钢铁行业的健康发展对我国国民经济的有序运行发挥着重要的作用。2011年钢铁行业的工业总产值占全国工业总产值的10%,钢铁是机械、建筑、汽车、家电、造船等行业的原料来源,为国民经济的平稳、快速发展提供了非常重要的原材料保障。但是,我国钢铁行业存在着高投入、高消耗、高排放、高污染等问题,造成了大量的资源浪费,也产生了大量的温室气体,破坏和污染了环境。而研究钢铁工业的能源效率问题有助于这些问题的解决,本文即在此背景下,基于SBM-DEA模型对我国的钢铁行业的能源效率进行分析。 DEA模型对社会经济系统的多投入和多产出指标的有效性评价独具优势。它是基于数学规划思想,通过建立线性规划模型来评价决策单元之间的相对效率。在度量和评价相似决策单元(DMU)之间的效率与生产率问题上,DEA方法得到了广泛的应用,已经被证明是十分有效的工具。但是正像Chames等(1978)所批评的那样,DEA的相对效率评价思想要求应该最大化地减少投入,而同时产出则必须尽可能地扩大。但现实生产过程远远没有理想的那样简单,一些生产过程会产生很明显的污染物,这些我们并不希望产生的副产品被称为“非期望产出”。按照常识来讲,我们必须尽可能地减少和控制这些非期望产出,经济效率才有可能达到最佳状态。但是如上所说,传统的DEA模型却只能使非期望产出增加,这与效率评价最初的目的不符,因此就必须对传统的DEA模型进行修正。传统的DEA模型大都依从径向和角度来分析,这样就无法充分考虑到投入产出的松弛性问题,计算的效率值也是不准确的或是有偏的。很多估计环境效率的DEA模型在分析时都忽略了松弛性问题,因此也就忽略了由于不同决策单元投入过多和期望产出不足所导致的经济无效问题,因而也无法综合衡量、比较决策单元DMU的经济和环境效率。Tone于2001年提出了一个直接处理松弛问题的SBM模型(Slacks-based model),则较为完美地解决了如上所说的问题。与传统CCR和BCC模型相比,SBM模型的不同之处在于它把松弛变量直接放进目标函数中,这就解决了松弛问题。此外,SBM模型一般以非径向和非角度的方式测度效率,避免了径向和角度选择差异带来的偏差和影响。本文在具体的分析过程中,将29个地区按照经济、政治、地理等因素划分为七大经济区。利用SBM模型,选取劳动力、资本存量、能源消费作为投入,工业总产值、产品产量、二氧化碳排放量作为产出,估算了我国29个省、自治区、直辖市从1990年到2011年间的钢铁行业的能源效率。研究结论表明在经济发达的环渤海和长江三角经济区内的北京、上海的效率值始终为1,天津、江苏、广东大部分年份的效率数值为1,而处于生产的前沿面,经济相对落后的大西北、大西南地区的青海、海南的全要素能源效率大部分年份的效率值也为1。从经济相对落后的大西北经济区的其余省份,到大西南经济区、中部六省、中等经济发展水平的东北经济区,再到珠江三角洲经济区,全要素能源效率表现出逐渐递增的态势。这说明在各个地区的钢铁行业中,全要素能源效率与地区经济发展水平呈现一种“U型”的关系。最后,本文又对技术效率进行了分解,分解为纯技术效率和规模效率,期望从技术和规模角度找到综合技术效率低下的原因。结论表明钢铁行业能效值既受技术的影响,也受规模报酬的影响。在纯技术效率值为1的情况下,经济落后地区的规模报酬应该递增,经济相对发达地区的规模报酬应该递减。根据实证分析,最后提出政策建议：促进各个产区的产能调整,淘汰钢铁行业的落后产能,促进钢铁行业结构优化调整,鼓励技术创新。
[Abstract]:China's iron and steel production, consumption and import and export power, has been ranked first in the world, the healthy development of steel industry and orderly operation of China's economy plays an important role in the total industrial output value of.2011 in the steel industry accounted for 10% of the total industrial output value of iron and steel, machinery, construction, automotive, appliance, shipbuilding etc. industry sources of raw materials for the national economy stable and rapid development provides the raw material security is very important. However, China's iron and steel industry there is a high input, high consumption, high emissions, high pollution and other issues, resulting in a large waste of resources, but also produce large amounts of greenhouse gases, destruction and pollution. The problem of environment. The energy efficiency of iron and steel industry helps to solve these problems, this paper is based on this background, analysis of the iron and steel industry SBM-DEA model for China's energy efficiency based on.
Evaluation of the effectiveness of the DEA model of multi inputs to the social economic system and multi output index has its unique advantages. It is based on the theory of mathematical programming, through the establishment of a linear programming model to evaluate the relative efficiency of DMUs. Evaluation similar decision making unit (DMU) and measure the efficiency and productivity of the problem, obtained by DEA a wide range of applications, has been proved to be very effective tools. But as Chames (1978) which critics do, relative efficiency evaluation of the idea of DEA requirements should minimize input, while output must expand as much as possible. But the real production process is far from ideal as simple as that, some of the production process can produce the pollutant obviously, we don't want these byproducts called "undesirableoutputs." according to common sense, we must as far as possible to reduce and control the Expected output, economic efficiency can reach the best state. But as mentioned above, the traditional DEA model can only increase the undesirable output, and the efficiency evaluation of the original purpose is inconsistent, so we must revise the traditional DEA model. DEA model is the traditional compliance radial and angle, thus unable to fully consider the input-output relaxation problem, the computational efficiency value is inaccurate or biased. Many of the estimated environmental efficiency DEA model ignores the relaxation problem in the analysis, so it is ignored because of the different decision making units put too much and expected output deficiency caused by invalid economic problems therefore, can not be a comprehensive measure, decision making economic and environmental efficiency of.Tone unit DMU SBM model is proposed to deal directly with a relaxed problem in 2001 (Slacks-based model), is more perfect To solve the above mentioned problems. Compared with the traditional CCR and BCC model, the difference of the SBM model is that it combines the slack variables directly into the objective function, which solves the problem of relaxation. In addition, the SBM model with non radial and non angle to measure efficiency, avoid the size difference and angle to choose the deviation and influence.
Based on the analysis of the specific process, the 29 regions in accordance with economic, political, geographical and other factors are divided into seven economic zone. By using the SBM model, selection of labor, capital, energy consumption as the input, output the total industrial output value, product, carbon dioxide emissions as output, estimated in 29 provinces, autonomous China from 1990 to 2011, the steel industry's energy efficiency municipalities. Research results indicate that the economic zone in the economically developed Yangtze River Delta around Bohai and Beijing in Shanghai, the efficiency value is always 1, Tianjin, Jiangsu, Guangdong, most of the year for the numerical efficiency of 1, and in the production frontier, the economy is relatively behind the great northwest, southwest of Qinghai, Hainan efficiency total factor energy efficiency of most of the year for the value of 1. provinces in the Northwest Economic Zone from the rest of the economy is relatively backward, to the southwest economic area, the six central provinces, in The Northeast Economic Zone economic development level, and then to the Pearl River Delta Economic Zone, the total factor energy efficiency showed a gradually increasing trend. This shows that in the various regions of the iron and steel industry, the relationship between total factor energy efficiency level and regional economic development is a kind of "U". Finally, this article also made the decomposition of technical efficiency is decomposed into pure technical efficiency and scale efficiency, expect to find low technical efficiency from the point of view of technical and scale reasons. Results show that the steel industry energy efficiency value is not only influenced by the technology, is also affected by the return to scale. The pure technical efficiency value is 1, returns to scale in economically backward regions should the increasing returns to scale, the economy is relatively developed areas should decline. According to the empirical analysis, finally puts forward the policy recommendations: to promote all areas of production capacity adjustment of iron and steel industry, eliminate backward production capacity, promote the iron and steel The structure of the industry is optimized and adjusted to encourage technological innovation.

【学位授予单位】：东北财经大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F426.31;F224

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