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Research On Poverty Alleviation Fund Utilization Efficiency And Influencing Factors In Rocky Desertification Area Of Yunnan Province

Posted on:2021-02-05Degree:MasterType:Thesis
Country:ChinaCandidate:G H LiFull Text:PDF
GTID:2370330623465687Subject:Applied statistics
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Since the reform and opening up,our government has always been committed to the governance of poverty,with great results.However,although the targeted poverty alleviation model has responded to the current mainstream poverty and anti-poverty perspectives,and poverty alleviation funds have been increasing year by year,there are still practical problems that need to be resolved,such as the low efficiency of poverty alleviation funds and the misalignment of poverty alleviation projects.The purpose of this research is to measure the efficiency of the use of poverty alleviation funds in concentrated poor areas,on this basis to find out the key factors restricting the improvement of their efficiency,and put forward targeted policy recommendations.Based on this purpose,from the perspective of the use of poverty alleviation funds,this paper builds two interrelated index systems: one is an index system for measuring the efficiency of poverty alleviation funds,and the other is an index system of factors influencing the efficiency of poverty alleviation funds.Twelve cities in the rocky desertification area of Yunnan Province with typical poverty characteristics were selected as the research object,and the sample period was 2010-2017.With the aid of the "inputoutput" framework of the DEA model,an index system for measuring the efficiency of poverty alleviation funds was constructed from the perspective of "great poverty alleviation",and the sum of special poverty alleviation funds,industry poverty alleviation funds,social poverty alleviation funds,and credit poverty alleviation funds was used as input,The annual number of people out of poverty,the per capita net income of farmers,and the nine-year compulsory education consolidation rate are used as outputs.From the time dimension,the changes in the use efficiency of regional poverty alleviation funds are explored in stages,and the efficiency value calculated by the DEA model is corrected using the Bootstrap method.Secondly,the clustering analysis method is used to divide the comprehensive efficiency value into three levels: relatively low,relatively medium,and relatively high.The ArcGis 10.2 software is used to draw a spatial distribution map of poverty alleviation fund utilization efficiency,and to explore the use of poverty alleviation funds in the district.Spatial characteristics of efficiency.Thirdly,based on themeasurement of poverty alleviation fund use efficiency,the panel regression model is used to explore the key factors restricting the improvement of regional poverty alleviation fund use efficiency,and to explore its impact on poverty alleviation fund use efficiency from specific projects invested by poverty alleviation funds.By quantifying the breadth and intensity of regional poverty alleviation and development,and measuring the impact of the use of poverty alleviation funds on regional poverty alleviation and development,the relative effectiveness evaluation of poverty alleviation funds is completed.The results show that:(1)The Bootstrap method has a better correction effect on the efficiency value of poverty alleviation funds measured by DEA,and the corrected efficiency value can better reflect the actual situation.During the sample period,the efficiency of poverty alleviation funds in the area showed a decreasing trend.The efficiency values did not reach the effective frontier,and there was room for further improvement.The high scale efficiency indicates that the scale effect is good but there are institutional and management reasons,which leads to low pure technology efficiency,which in turn affects the improvement of comprehensive efficiency.According to the scale reward analysis of the decision-making unit,the overall efficiency of the poverty alleviation funds in the district during the sample period showed a trend of decreasing scale reward;(2)The analysis by stages shows that the relative efficiency value of the precision poverty reduction stage is lower than that of the comprehensive poverty reduction stage,because of the deep poverty in the early stages of poverty reduction and development The population is insufficiently targeted;(3)There are obvious regional differences in the use of poverty alleviation funds in the area.Relatively high efficiency places are mostly close to Wenshan City,showing a spatial distribution characteristic that decreases from Wenshan City to the surrounding area.(4)Among the factors affecting the efficiency of the use of poverty alleviation funds in the district,in terms of the allocation and use of poverty alleviation funds,industrial poverty alleviation projects have a significant impact on the 10% significance level,but the coefficient is negative because the industrial poverty alleviation projects have a "time lag effect".During the sample period,the benefits of industrial poverty alleviation projectswere not exerted;in terms of management and technology,the village promotion project has a significant impact on the use of poverty alleviation funds in the region at a 5%significance level,and it has a positive effect.The remaining projects have no significant impact.Finally,based on the results of the measurement of the efficiency of poverty alleviation funds and the analysis of the influencing factors of the efficiency of poverty alleviation funds,this article proposes several policy recommendations to improve the efficiency of poverty alleviation funds in the area.Including: the establishment of a diverse and mutually supportive poverty alleviation and development organization system;actively implementing the ecological industry poverty alleviation model;the poverty alleviation model should realize the transition from developmental poverty alleviation to inclusive governance;Actively implement the "Village Revitalization Strategy".
Keywords/Search Tags:poverty alleviation funds, utilization efficiency, Bootstrap-DEA model, panel regression model
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