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Research On Measurement,Causes And Resolution Of Overcapacity In Equipment Manufacturing Industry

Posted on:2019-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:H X WenFull Text:PDF
GTID:2382330545981808Subject:Quantitative Economics
Abstract/Summary:PDF Full Text Request
Equipment manufacturing industry is a material production department that provides production technology and equipment for our national economy and national defense construction.It is also a strategic industry to enhance our comprehensive competitiveness.In recent years,With the rapid development of China's economy,the capacity of equipment manufacturing has also increased significantly.Some problems have been brought by the rapid economic growth,of which the problem of overcapacity is particularly prominent.Overcapacity means in the planning period,the actual output of an enterprise is far less than a phenomenon of potential output.The method of measuring the capacity utilization ratio is quite mixed,It is roughly divided into two categories.One is the direct measure method,it refers to get the capacity utilization level by doing a investigation of the enterprise.However,the method of investigation requires a lot of manpower,material and financial resources,and each of the respondents' explanation of their own behavior preferences and optimality exist disagreement.Therefore,the direct measure method has not been widely accepted by the theorists.The other is the indirect measure method,measuring the potential capacity scale and then compared with the real output to get the capacity utilization.The commonly methods include the production function method,the cost function method,the data envelopment analysis method and so on.For the strong maneuverability of the indirect measure,it is widely accepted by the academic community.After taking a comprehensive consideration of various methods,this paper chooses the method of stochastic frontier production function to measure the capacity utilization of the equipment manufacturing industry.This method not only takes advantage of data availability,but also has a certain economic theoretical basis.By using the stochastic frontier production function method to measure the capacity utilization of the seven equipment manufacturing industry,it is concluded that there is excess capacity in China's equipment manufacturing industry,and the excess is cyclical and structural.The results show that the overcapacity of the equipment manufacturing industry in China is no longer simple,but relatively complex.Based on this,we build a model to find the reasons for excess.Based on the research,the paper finds that the main reason for the overcapacity of equipmentmanufacturing industry is the economic fluctuation cycle(external factors)and technological progress bias(internal factors).From the perspective of external factors,the development of segmentation industry depends on the overall external economic environment.When the external development environment fluctuates greatly,it will inevitably affect the development of sub sectors;from the internal factors,the distribution and input of the internal factors in the industry are the fundamental factors that determine the efficiency of production and the quality of the products.On the basis of the full text,in the light of the capacity utilization of equipment manufacturing industry,this paper put forward matching countermeasures from different levels.At the national level,we should control the overall economic situation and create the external environment for the good development of the subdivision industry;at the industrial structure level,the structural reform of the supply side is fully promoted;at the technical level,we should increase the investment in scientific research,continuously introduce high-tech,and improve the competitiveness of products;at the sales path level,we should carry out the "go out" strategy,actively transfer capacity abroad and expand the international market.
Keywords/Search Tags:Capacity utilization, SFA model, Economic cycle fluctuation, Technical progress biased
PDF Full Text Request
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