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Research On The Measurement Of Industrial Structure Altitude And Its Influencing Factors In Sichuan Province

Posted on:2019-07-19Degree:MasterType:Thesis
Country:ChinaCandidate:Y XuFull Text:PDF
GTID:2359330566462950Subject:Theoretical Economics
Abstract/Summary:PDF Full Text Request
Since the reform and opening up,the economy has been developing continuously.At the same time,China has constantly stressed the adjustment and optimization of the industrial structure.The optimization of industrial structure includes two aspects,one is rationalization and one is industrial structure altitude.This paper studies on the basis of the high level of industrial structure.The industrial structure altitude is reflected in the study of the primary industry,the secondary industry,the tertiary industry.That is,how the development of the three industry of the industrial structure is different under the development of industrial structure,so that the overall development of the whole industrial structure is different.The essence of economic development is reflected in the industrial structure altitude.The essence of economic development is reflected in the height of industrial structure,the upgrading of industrial structure can promote the flow of factor resources among the three industries,create new demand,create new economic growth points,and then greatly improve the economic development.At present,Sichuan is in the key period of the adjustment of industrial structure,it is of great significance to study the industrial structure altitude.This paper makes clear on the basic of the industrial structure altitude theory,measure the industrial structure altitude since the reform and opening up of Sichuan province and 21 cities,and the influencing factors of the industrial structure upgrading from supply,demand,policy and other aspects were summarized and provides a theoretical basis,establishes theory based on empirical research.Study of measure the industrial structure altitude,Sichuan province entered the industrialization period since 1997 and completed industrialization by 2015,12 years and 4 years later than the national level respectively.By 2015,6 regions had entered the period of industrialization completion,15 regions haven't been completed yet.Three of five economic zones have entered the period of industrialization completion,and two economic zones have not yet been completed.Based on the comparative analysis of panel data model and quantile regression model,it is concluded that quantile is more accurate and accurate than panel to describe the magnitude and direction of influencing factors on industrial structure.The study found that the strong influence factors of the overall industrial structure altitude are the city development level,the social demand,the human capital,and the weak influence factors are the financial development,the foreign trade and the technological progress;from the regional perspective,the main factors influencing the high industrial structure altitude area are the human capital,the financial development,the city level;the main factors in the middle-high level are the city level,the human capital,the social demand,the foreign trade;the main influencing factors for the low level are the technological progress,the social demand,the city development level.On this basis,this paper puts forward some policy suggestions to promote the development of industrial structure by using the regression results of the quantile.Mainly including: increasing urbanization rate,promoting balanced development among cities;accelerating financial development in high-level areas,stimulating financial development in low-and middle-level areas;stimulating per capita demand and increasing social spending power;improve the ability of independent innovation,increase the technology innovation investment in medium and low level areas;to enhance human capital,increase investment in education to expand foreign trade;expand foreign trade and implement a strategy of opening up high-level areas to low-level areas.
Keywords/Search Tags:industrial structure altitude, measure, quantile regression, influencing factors
PDF Full Text Request
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