基于物质流核算的数据包络分析——国内19个主要城市的实证研究

The Efficiency Analysis of Material Flow Account for the 19 Cities' of China

文章介绍了物质流核算的基本思想和数据包络分析的基本方法,在对国内19个主要城市的物质流进行核算的基础上选取相关数据,并综合一些经济统计数据做了DEA分析,对于这19个城市的物质流基本状况进行了评价,为以后的城市循环经济政策制定提供了一种定量的分析工具。文章的主要结论有:(1)我国物质流输入量所带来的经济效益较欧美发达国家明显偏低,我们的先进城市大约相当于欧美发达国家20世纪90年代中期平均利用率的1/4,日本的1/9,这充分说明我国的经济增长方式主要还是粗放式的;(2)多个城市的物质流核算均由于基础设施建设过多导致的物质流动规模十分巨大,这从一个侧面说明了我国很多城市的经济增长对于固定资产建设的投资依赖十分明显;(3)在DEA分析中我们可以看出很大的物质流投入并不能带来同等的GDP和财政收入。

The root of material flow accounting and analysis （MFA） could be traced back to social metabolism theory in 1857, but it was ameliorated by Abel Wolman, Kenneth Boulding, and Donella Meadows studying Industrial Metabolism during 1960s- 1970s. Through to Wuppertal Institute＇s some consummating work since 1990s, such as MIPS, MFA has been broadcast all over the world. The MFA means to account and analysis material flow in economic developing and the base is to compute input and output of material flow and set up an account of input and output so as to optimize material flow management. By using MFA, the inherence of resources and economic developing could be impersonally evaluated and it also can be used to help governments to shape their developing courses. In past, MFA and MFA relevant studies were focus on macroeconomics, such as a country＇s MFA. In recent years, there have been some MFA studies about one city＇s MFA or one industrial MFA. In China, there were some studies about Guiyang＇s MFA （Guiyang is capital of Guizhou Province, in the southwest of China）, Shanghai＇s MFA, Beijing＇s cement industrial MFA and so on. In environmental system research, some mature model and calculation method such as Data Envelopment Analysis （DEA） in the economics might be introduced to do some quantitative analysis of the environment so as to develop a broader science fields. This paper attempts to study synthesizing the above two methods. This paper attempts to study synthesizing the above two methods. The first aim of this paper is to account 19 cities＇ material flow by MFA, which is shown that China＇s economic development is still primarily at the cost of high consumption of resources. The second aim of this paper is to evaluate the efficiencies of 19 cities＇ material flow by DEA. In this paper, we make DEA evaluation based on MFA, quantify the calculation of recycle economy which extensive references, and evaluate the efficiency of MFA, then provide the basis of decision-making for regulatory system of national, regional and urban. Through data envelopment analysis which based on MFA, we can get the following conclusions： 1 ） The use efficiency of our country ＇ s material flow significantly low than developed countries in Europe and the United States, the 19 selected cities basically represent the most advanced level of the productive forces in China, these cities also represent the most advanced level of technology in China, but the most production efficiency city in material flow is Suzhou which only close to the level of 700 Yuan GDP/ tons, it is roughly equivalent to the quarter of average utilization rate of European countries and the United States in the mid-1990s and the ninth of Japan, this is fully demonstrated that China＇s economic growth is still extensive growth;2）Numbers of cities＇ MFA is very high owing to the large-scale movement of material flow caused by infrastructure construction, this is a profile to show that the economic growth rely on the investment on fixed assets in many cities in China is very obvious;3）The share of water consumption in material flow accounting in cities often is the largest part of total material flow, although China is a serious water shortage country, but in fact, the use of water is not savings;4）In DEA analysis, we can see a lot of material flow into can not produce the equivalent GDP and financial revenue, this shows that many cities in the material flow has remained only in the ＂flow＂, it does not transform into physical capital stock and exert greater efficiency in economic development. We can clearly see in DEA analysis, when we use per capita as analysis unit, many cities have fluctuation. From the point of view of the original input data, mostly because of the relatively low per capita income, this is a profile to provide a support for the movement of people.