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An Empirical Study On The Evaluation Of Poverty-stricken Counties In Hunan Province And The Factors Of Poverty-making

Posted on:2020-10-11Degree:MasterType:Thesis
Country:ChinaCandidate:T HuangFull Text:PDF
GTID:2439330605475577Subject:Statistics
Abstract/Summary:PDF Full Text Request
How to eliminate poverty is not only an important problem that the People in poor areas to solve at present,but also the inevitable requirement for China to build a well-off society in an all-round way and achieve socialist common prosperity.Hunan province is a large agricultural province in Midwest China.It has a large number of poor people and is widely distributed.It is still the main battlefield of our country's poverty alleviation.In order to do top-level design of poverty alleviation and development in Hunan Province,the overall objectives of Hunan Poverty Alleviation and Development Implementation Outline(2011-2020)as follows: By 2020,the phenomon of absolute poverty will be basically eliminated,and compulsory education,basic medical care and housing will be guaranteed.Realize the comprehensive economic,social and ecological development of poverty-stricken areas,and reverse the development gap.The Outline also designated Xiangxi Prefecture as a important area for poverty alleviation.Xiangxi Prefecture is located in the west of Hunan Province,in the center of the contiguous poverty-stricken area of Wuling Mountain.Wuling Mountain Area Regional Development and Poverty Alleviation Plan(2011-2020)pointed out in the Wuling Mountain area,the poverty area is large,the infrastructure is weak,the level of economic development is low,and regional development is uneven.Different anylysis and views about the factors influencing the poverty may have direct effect on anti-poverty policy and policy implementation.A complete anti-poverty system involved in ecological environment,resources,infrastructure,and social economic condition have obvious local features.It is necessary to deeply analyze the factors affecting the rural poverty in some specific areas,which will be helpful for anti-poverty policy making and finally realizing the harmonious development and common prosperity of urban and rural residents.Fist,In order to research the main factor in Xiangxi,This article collects data from the Statistical Yearbook of Hunan Bureau of Statistics 2011-2016.Based on regional economic and social development,we firstly pick up 19 indexes which can measure and reflect the poverty features in Hunan.Through principal component anylysis of the data,the main reasons affecting its poverty.Combined with the local political economy,humanistic environment,social system and other aspects,it has established an evaluation index for the impact of poverty in the region.The result shows that counties with tough production activity condition,who want to enhance the counties comprehensive strength and get rid of poverty,mainly rely on the development of agricultural technology,more local finance support,more education resources inverstment,better medical treatment.Secondly,Taking Xiangxi autonomous prefecture as example,based on the basic data of poverty situation in each county,a principal component analysis method wascarried out to determine the main role of poverty-reducing factors according to different component matrices.The results show that government funds are the focus of poverty alleviation work,and due to the impact of natural environment,guzhang county,baojing county and other areas have a particularly serious impact.Poverty alleviation should be increased in these areas.Last,cluster analysis and panel data analysis were carried out for 8 counties in Xiangxi.The results of the analysis show that poverty due to illness,lack of funds,and inconvenient transportation are the main factors affecting poverty in Xiangxi.This is basically in line with the lack of medical security in Xiangxi and the current situation in a remote society.It provides a basis for development trends and policy recommendations for poverty alleviation policies.
Keywords/Search Tags:Evaluation index, Poverty Factor, Principal Component Analysis, Clustering Analysis, Panel analysis
PDF Full Text Request
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