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Research On Influencing Factors Of New Urbanization In Jiangxi

Posted on:2018-03-09Degree:MasterType:Thesis
Country:ChinaCandidate:J RenFull Text:PDF
GTID:2359330515493011Subject:statistics
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The new concept of urbanization is put forward by the 18 th National Congress in 2012,it is only 5 years ago.Whether the national urbanization or the provincial urbanization,there are still many questions needing scholars to study it.Jiangxi Province is a big agricultural province,the level of urbanization is needed vigorously to improve.In response to the national policy,the Jiangxi Province government proposed the policy guidance and planning of urbanization in Jiangxi Province: “the new urbanization plan in Jiangxi Province plan period(2014-2020)”,the planning says that Jiangxi Province is in climbing accelerating period of urbanization,the comprehensive well-off Common construction and the ecological construction phase of ascension,Jiangxi Province should seize the opportunity,properly to facilitate the construction of the new urbanization,rising the urbanization rate from 48.87% in 2013 to 60% in 2020,because the urbanization rate reaching to 60% is an important indicator of building the well-off society.There are many complicated evaluation index for the rapid development of urbanization process,in addition to the acceleration of urbanization forward index,it also includes negative indicators that affecting the process of urbanization.In order to guarantying the stability of the urbanization rate increasing,the negative indicators should be included in the evaluation factors for the development of new urbanization,so that making new analysis and research on the influence factors of urbanization.The paper constructs a new evaluation index system and combines with the principal component analysis model to analyze the positive and negative factors of the urbanization.In the first chapter,the paper mainly introduces the theories about the article researching background,the researching significance and the practical significance,the relevant literature review at home and abroad,the researching content framework and the researching methods,then the paper puts forward the possible innovations and deficiencies.The second chapter mainly discusses the new definition on the connotation and standard of urbanization,and defines the concept of agricultural transferring population.The paper also thinks the urbanization should include economic,social population,environment,science and technology and the construction of urban internal pattern,the concept of transferring population should be thought to be generalized and narrow concept,the most fundamental concept is the person who has the urban residential willingness.In addition,the chapter also elaborates the related research theories,including the push-pull Model,the Two-Sector Model,the Ranis-Fei Model,the Migration Model,and the Central Place Theory.The last of this chapter also analyzes the basic mode of urbanization,and the present situation of urbanization of eight domestic cities and five overseas countries' experience.The third chapter firstly analyzes the urbanization present situation of the five big factors,including economic,social population,technology,urban internal structure,and environment status quo,the paper makes use of some historical data analyzing the status quo.Then according to the situation of Jiangxi Province and the related research literature,the positive and negative influence factors of urbanization in Jiangxi Province are analyzed theoretically.The fourth chapter is mainly about the building of influence factor index and the choice of model,this chapter is divided into two sections.The first section expounds the principle of selecting indicators,and building the index system according to the index system of the 13 th Five-Year plan and other scholars' literatures;in the second is the building of the urbanization influence factor model,including the urbanization influence factor analysis model and the urbanization of Jiangxi province agricultural shifting population urbanization willing model,mainly expounds the theoretical basis for the selected models,including principal component analysis model,SEM model,the binary logistical regression model.The Principal component analysis model is used for the urbanization influence factor analysis for dimension reduction and extraction,choosing influence factor.The fifth chapter is gathering the data through the China statistical yearbook,Jiangxi statistical yearbook,the Jiangxi provincial environmental bulletin of indicators,then establishing principal component analysis model,the principal components of the initial indicators are extracted,getting four common factor,further processing and analyzing,getting the empirical analysis results,it shows that technological innovation factors and ecological factors are the most significant factors to the influence of urbanization.This conclusion is in accordance with the age characteristics so that two factors should be included in the new urbanization evaluation.For the urbanization willing analysis of shifting population in Jiangxi Province is using the survey data and combining the binary logistical regression model and SEM model,empirical analysis shows the gender,marital status,the satisfaction of the welfare system are the main significance factors affecting the urbanization willing of agricultural shifting population,and two methods are used for the same research question,it has carried on the advantages and disadvantages compared.Comparing binary logistical regression model with SEM model in the study for willing problem,binary logistical regression model relative to the SEM model is convenient,although SEM model can show the affecting path,but it needs not only the data requirements,and the model need after repeated revision,so that obtaining more reasonable results.The sixth chapter is based on the empirical results in the fifth chapter,getting the related analysis conclusion,and puts forward suggestions on the basis of the conclusion.
Keywords/Search Tags:New urbanization, SEM model, Principal component analysis model, Binary logistical regression model, SPSS
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