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An Empirical Study On The Efficiency Of Industrial Capital Allocation In Jilin Province

Posted on:2019-07-04Degree:MasterType:Thesis
Country:ChinaCandidate:M LiuFull Text:PDF
GTID:2429330548462487Subject:Quantitative Economics
Abstract/Summary:PDF Full Text Request
Capital is an important factor of production.The process of capital allocation has a close relationship with regional economic development.The economic development of a region can be examined from the capital allocation efficiency of the region.In the three major industries,the secondary industry is the core,that is,industry is the core of all industries.The degree of industrial development and efficiency affect the development level and efficiency of other industries and even the whole society.The efficiency of industrial capital allocation can better represent the economic development of the entire society.Jilin Province is an important province in northeastern China.It was an important industrial base in the early days of the founding of New China and made great contributions to the formation of a complete and independent industrial system and national economic system in China.In recent years,the pace of economic development has slowed down,and there have been doubts about the economy of Jilin Province and even the three eastern provinces in the society.Therefore,it is of practical significance to study the efficiency of capital allocation in Jilin Province from the perspective of industry.The article adopts elasticity coefficient method put forward by Jeffery Wurgler,and firstly estimates the industrial capital allocation efficiency of Jilin Province from2006 to 2015.The result shows that the industrial capital allocation efficiency of Jilin Province is 0.165,that is,for every 1% increase in total industrial output value,the investment in fixed assets increases.0.165%.Compared with the existing literature,this result has all improved significantly but is still smaller than that of foreign developed countries.Then,the efficiency of capital allocation in various industrial sectors was measured.The results showed that Jilin was dominated by heavy industry.Then we measured the industrial capital allocation efficiency of Jilin Province foreach of the ten years from 2006 to 2015.The results show that the external economic situation has a great influence on the efficiency of industrial capital allocation.In the global financial crisis in 2008,it was the lowest in nearly ten years;under the influence of China's “four trillion” plan,it reached the highest value in nearly ten years in 2010.There are many factors that influence the efficiency of capital allocation.From the existing literature,the author finds out seven representative factors and studies how each factor influences the efficiency of capital allocation.This paper analyzes the influence of different factors on the efficiency of industrial capital allocation in Jilin Province by adding dummy variables to the elastic coefficient method put forward by Wurgler.The following conclusions are drawn:(1)The proportion of state-owned economy and the proportion of state-owned workers have a negative effect on the improvement of capital allocation efficiency in Jilin Province,but the proportion of state-owned workers will significantly reduce the efficiency of capital allocation;while the share of state-owned economy will not Significantly reduce the efficiency of capital allocation;(2)The increase in government expenditure after deduction of science,education,culture and health will reduce the market's ability to capitalize on capital allocation;(3)The increase in foreign direct investment will significantly increase the efficiency of industrial capital allocation in Jilin Province;(4)Transport infrastructure and The level of education has a positive effect on improving the efficiency of capital allocation in Jilin Province;(5)The higher the development level of the financial market represented by the banking industry,the stronger the improvement in the efficiency of Jilin's industrial capital allocation.
Keywords/Search Tags:Industry, Capital Allocation Efficiency, Panel Data Model, Influencing Factors
PDF Full Text Request
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