| With its abundance and low-priced labor force and an economic development strategy with high investment and export orientation,China has experienced a high longstanding economic growth since China’s reform and opening-up,and China’s average economic growth rate has been up to 10%during 1978 to 2010,but then the growth declined after 2010.Part of the slow-down could been due to the declining ratio of working force population to the total population:which varied from 74.34%at 2010 to 72.18%at 2016.On the other side,the aged population is expanding whose ratio has been rising up yearly from 8.25%at 2010 to 10.12%at 2016.Another reason of the slow-down could also be the reduced return of capital from of the persisiten high investment of "four trillian yuan plan" in deal with the financial crisis in 2008.What is followed is the increasing debt scale of nation and high leverage ratio which may generate many bad outcomes.Thus,facing the New Normal,the economic development that solely depends on factor investment just could not sustain the persistence and high-speed of economic growth.The level of total factor productivity is the main source to the difference of economic growth among countries.And the level of TFP,on the one side,is accounting on the overall technological innovation level of the whole society.On the other side,it depends on the resource allocation of factors among different firms and sectors.So the key motivation for China to increase TFP and release the potential of economic growth is to optimize the resource allocation among firms and sectors so as to reduce the resource misallocation.Thus,departing from the micro and meso perspective,we use theory deduction and empirical research methods to estimate the degree of resource of misallocation in China and its influence on economic growth.We dig into the mechanism from financial friction to resource allocation among firms and the mechanism from financial development to resource allocation among sectors.Specifically,in the micro-level we investigate the resource allocation among different firms before and after the China’s four trillion yuan($585 billion)economic stimulus;in the meso-level,we dig into the degree of misallocation in the process of industrialization among different industry sectors and the relation between the degree of misallocation and industrial economic growth.The main results and findings are listed as below.First,in the micro-perspective,departing from the model of resource misallocation designed by Heish and Kelnow(2009),we further decompose the degree of resource misallocation inside sectors.And we use the database of the Annual Survey of Industrial Firms in China from 1998 to 2013 to re-estimate and analyze the degree of resource misallocation among sectors,the degree of misallocation of labor,the degree of factor-related resource misallocation and the resource misallocation inside sectors as well as their influences to the loss of efficiency.Specifically,we investigate the resource allocation among and inside different sectors before and after the China’s four trillion yuan($585 billion)economic stimulus.Further,we look into the relationship between resource misallocation inside the industry and the characteristics of different industries.We also construct the interaction term using the dummy indicating whether the "four trillion yuan" stimulus policy is implemented and the characteristics of the industry to look into the influence of the“four trillion yuan" stimulus policy and the characteristics of the industry to the misallocation of resource inside the industry.We find,(1)For the whole sample,the overall economic efficiency could move up 115%to 156%if the manufacturing enterprise could reach the peak of efficiency of resource allocation.(2)The degree of misallocation of China has experienced a U curve process with it falls at first and rises up afterwards especially after the "four trillion yuan" stimulus policy from 2008.(3)The degree of misallocation of capital and labor inside different sectors has experienced a U curve trend which falls at first and rises afterwards especially after 2008 when the "four trillion yuan" stimulus policy is implemented.(4)We find that the industry has higher degree of resource misallocation with higher monopoly power of SOEs,smaller of firm scales and larger average age of firms.Second,in the fourth chapter we estimate and analyze the influence of difference of credit constraints to the degree of resource misallocation.Further we dig into how the ownership structure twists the resource reallocation between firms through influencing the credit constraints of firms.Specifically,we first integrate the credit constraints into the model of resource misallocation theory based on the model from Gilchrist,Sim&Zakrajsek(2013)and Heish&Klenow(2009)and estimate the influence to degree of resource misallocation from ownership difference through credit constraint using counter-factual analysis.Further,we use the industrial firm database to measure and estimate the coefficients of labor factor twist,capital factor twist and the overall loss to TFP caused by resource misallocation.We find,(1)Without the difference on credit constraint(the twist of labor factor and capital factor),the overall economic growth could have been improved at least by 6.14%to 17.52%during 1998 to 2013.And after the "four trillion yuan" stimulus policy,the degree of resource misallocation is higher because of the resulting difference of credit constraint.(2)Without the credit cost difference from difference of ownerships,the loss of TFP caused by the difference on credit constraint could have been lowered by 0.334%-0.942%.Although the absolute value is not large,however,the loss has been rising up from 2009 after the implementation of the "four trillion yuan" stimulus policy.(3)The misallocation of labor and capital has experienced the process of falling first and rising up afterwards in the sample period which reaches its bottom in 2008 and surged up from 2009 for both.Third,from the meso-perspective,we in the fifth chapter investigates the relationship between the degree of resource misallocation among different manufacturing industries and manufacturing economic growth.Specifically,we construct the multi-sector model with heterogeneous labor factor and capital factor following the models of Hsieh&Klenow(2009)and Brandt,Tombe,&Zhu(2013).Second,we estimate the degree of resource misallocation of manufacturing industries using the data covering 34 manufacturing industries during 1980 to 2014 and explore the changes during different periods of industrialization.At last,we empirically test the influence of misallocation on manufacturing economic growth in the later period of industrialization.We find that(1)With the ongoing industrialization,China’s economic grows with the pattern of high misallocation and high growth.If the allocation level is optimized among sectors,the whole manufacturing industry could have risen up by 21%to 39%.(2)Although the gap of output of manufacturing sector has large volatility at some point,the overall trend is downward year by year.(3)From the middle period to later period of industrialization,the misallocation would lower the economic growth and the effect intensifies with time goes on.Fourth,from the meso-perspective,the sixth chapter empirically tests the degree of the influence of financial development to the misallocation of China’s manufacturing sector.The financial development and financial intensification could help the industry with high dependence of outside investment and with high technology to raise money by increasing the channels of money collection and also by increasing the probability of getting the investment.By this,it helps to reduce the friction of capital flowing between sectors so as to optimize the allocation status.Specifically,first we use the data of 34 industries from 1986 to 2015 to estimate the degree of misallocation of different sectors following the theoretical model built in chapter 5.Then we use the dynamic panel data model to empirically test the influence of financial development on the misallocation degree of manufacturing sector.We find,(1)The financial development improves the allocation of resource among the manufacturing industries and specifically,the financial development cast more influence on industries with higher outside investment.(2)The financial development plays different roles towards the heavy industry and light industry sectors.The financial development has more power on heavy industry sector which has higher monopoly power and is capital intensive.Based on our findings,we thus provide the implications below.First,to reduce the misallocation among firms and sectors needs the government to further implement the streamline administration and delegate power to the lower levels so as to establish a unified,open and competitive market with order.Second,it is necessary to fully intensive the reform on finance sectors and provide better financial service to serve the manufacturing sector. |
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