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A GWR-based Study On Impoverishment Factors Of Guizhou Province

Posted on:2019-11-04Degree:MasterType:Thesis
Country:ChinaCandidate:G L YangFull Text:PDF
GTID:2439330566473677Subject:Public Management
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Eliminating poverty is the essential requirement of socialism.It become an important guiding ideology for China to enter the building of a moderately prosperous society in all respects since the 18 th national congress of the CPC.Guizhou province is one of the provinces with the largest number of poor people,the widest poverty level and the deepest poverty level.It is the region with the most severe poverty,and the task of poverty alleviation is heavy.Identifying the poverty family and poverty-stricken villages accurately,quantifying the impoverishment factors,and exploring the different influence of factors can help to distinguish the main impoverishment factor of each village.Therefore,we can propose targeted measures to alleviate poverty and achieve targeted poverty alleviation.This paper takes Jianhe county as an example,and uses the village as the research unit.Researching clustering feature by spatial auto-correlation analysis method.It selects 16 factors from natural capital,social capital and human capital refering to actual situation of jianhe county.Carrying out Pearson correlations analysis and singles out 9 main impoverishment factors for Geographically Weighted Regression model(GWR)to estimate regression coefficient of impoverishment.The results show that:(1)The poverty incidence in Jianhe county has significant spatial positive correlation in space,which shows the characteristics of High-High aggregation and Low-Low aggregation.(2)The spatial clustering of poverty incidence can be divided into five types which includes High Poverty Incidence Area,Hypo-high Poverty Incidence Area,Low Poverty Incidence Area,Hypo-low Poverty Incidence Area and General Area.(3)Average slope index acts different effects on each village,such as distance to the nearest highway,proportion of funds lacked.This paper estimates the regression coefficient of impoverishment factors by GWR model,gives quantitative analysis to the factor of poverty at village levels.Asresult,it broadens the way to research poverty,and deepens the spatial poverty theory,achieving the targeted poverty alleviation research.The paper gives poverty elimination countermeasures,poverty alleviation relocation,land consolidation,traffic conditions improving,construction of small towns,and promoting practical skills training and so on.All of about,aiming to provide reference for the relevant departments to carry out poverty alleviation work.
Keywords/Search Tags:poverty incidence, impoverishment factors, geographically weighted regression model, poverty elimination countermeasures
PDF Full Text Request
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