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Testing Of The Direction Of Technology Progress And Its Effect On TFP In The Middle-income Stage Of China Industry

Posted on:2016-06-29Degree:MasterType:Thesis
Country:ChinaCandidate:X L XuFull Text:PDF
GTID:2309330467994291Subject:Quantitative Economics
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The middle-income stage is a very important economical stage for developingcountries, it can improve the level of Total Factor Productivity and help thedeveloping countries successfully across the middle-income stage through optimizingthe economical structure, changing the mode of economical growth, improving factorproductivity and technology level and so on. After entering the middle-income stage,in order to across the stage and keep the economic growing continually, the mode ofeconomical growth in our country begin to change, from factors driving to innovationdriving. Innovation is always reflected in the form of technological progress, and thetechnical change includes the neutral technical change and the biased technicalchange, the two affects of Total Factor Productivity in different ways. We canunderstand the dynamic characteristics of technical change and its contribution toeconomical growth by decomposing and measuring the TFP growth rate in themiddle-income stage.Considering the industry is the pillar industry and its importance to our country,In this paper, based on the background of the middle-income stage, we overall theindustry as the research object and divides it into the mining industry, manufacturingindustry and electric power, gas and water production and supply industry. This paperuses Solow residual method and CES production function decomposition method tostudy the change of total factor productivity and the direction technical change from1985to2011,, and also how the biased technical changed the total factor productivity.We focus on the dynamic performance from both of them in the middle-income stage(2001to2011). The results of the study show that:(1) The Total Factor Productivityin industry shows upward trend, and it increased slowly before entering the middle stage, but accelerated after entering the stage;(2) The technical change is biased tocapital in the whole industry and the three industry. And this kind of bias is moresignificant and showed a tendency to expand in the middle-income stage, it indicatesthe technical change occurred in the industry is more helpful to promote the relativemarginal output of capital. For the whole industry, technical change can raise annualaverage of7.6%to the relative marginal output of capital;(3) Biased technical changecannot only affects TFP growth rate directly, but also can be combined with factorconfiguration to affect the TFP growth rate indirectly. As the industry is a capitalintensive industry, and the technical change is biased to capital this abundant factor,so the technical change is matched with the factor structure, both of them play animportant role in promoting the TFP growth rate in the industry.In order to study which factor can affect the direction of technical change, thispaper constructs the structure of factor allocation, technology imitation andadministrative control these three indicators to analyze the three major industries, andthe study shows: the promotion of capital allocation and imitating technology levelwill lead the technical change biases to capital, while improving the level ofadministrative regulation can inhibit the capital biased technology to a certain extentin the industry. This shows the factor allocation, technology imitation andadministrative control can affect the TFP through influencing the direction oftechnical change. Based on the results of this study, we should consider the factorallocation when introducing new technologies, only the technology is matched withfactor allocation can it be made full use of. Similarly, when the economy needs a newtechnology, it should provide appropriate factor in according to the characteristics ofthe introduced technology so as to ensure the basic factor condition of the technology.
Keywords/Search Tags:biased technology progress, the expanded Solow residual method, CES production function decomposition method
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