In terms of current life style, living and production conditions and hygienic and educational condition, we select 8 indices, such as annual net income of farmers per capita, annual grain yield per capita, total power...In terms of current life style, living and production conditions and hygienic and educational condition, we select 8 indices, such as annual net income of farmers per capita, annual grain yield per capita, total power of agricultural machinery per capita, dropout rate of school children and so on, to establish index system of determining the poor village in North Jiangsu. By selecting Lianqun Village in Suining County of Xuzhou City, Mawa Village in Siyang County of Suqian City, Chuanxing Village in Guanyun County of Lianyungang City, Xiaozhu Village in Hongze County of Huai'an City, Fengda Village in Xiangshui County of Yancheng City as the representative villages, after the discussion and consultation of the masses and the village cadres of all villages, we get the measuring results of weight. Through the field survey, investigation and interview in the selected regions, we get the relevant data, and then we conduct standardization processing, so as to get the index value that can comprehensively reflect the characteristics of poverty. According to the index data that have been standardized, by using participatory poverty index formula for calculation, we get the values that can explain the poverty degree of the respondents. We sequence the representative poor villages in this region according to the poverty degree from high to low, and the result is as follows: Mawa Village, ianqun Village, Chuanxing Village, Xiaozhu Village, and Fengda Village. It indicates that in terms of the operability of theory and technique, the participatory poverty index can better recognize the poor villages, so that it lays solid foundation for rationally and effectively using the limited poverty alleviation resources.展开更多
Poverty is a severe barrier to sustainable human development and a pressing worldwide issue.Understanding how to accurately assess the spatial distribution of poverty in mountain areas has become crucial for ensuring ...Poverty is a severe barrier to sustainable human development and a pressing worldwide issue.Understanding how to accurately assess the spatial distribution of poverty in mountain areas has become crucial for ensuring that governments at all levels take suitable poverty reduction strategies.In this study,the mountain poverty spatial index(MPSI)was created by combining the digital elevation model(DEM),Luojia-1 night-time light imagery,point of interest(POI)data,and vegetation index products.The MPSI was then used to identify the spatial characteristics of poverty at different scales in the hilly area of Ganzhou city,Jiangxi Province,China.Socioeconomic statistics and Google satellite images were used to verify the reliability of MPSI by constructing a multidimensional poverty index(MPI)at the county scale.The results showed that MPSI and MPI have a positive correlation with a correlation coefficient of 0.8934(P<0.001),which indicates that MPSI could be used to identify the spatial distribution of poverty well.Specifically,the smallest distribution of both MPSI and MPI was in Zhanggong District(1.4555 and 0.1894),which indicates that most of the affluent counties were concentrated in the central region of Ganzhou,and the poor areas were scattered in the surrounding areas of Ganzhou.In addition,MPSI accurately identified poverty in mountainous areas with complex terrain in small administrative units,which can provide a more accurate way to monitor the poverty situation in the mountainous areas of China.This study will be useful for providing scientific references for the Chinese government to implement targeted strategies for eradicating poverty with differentiated policies.展开更多
Poverty–stricken populations must be identified precisely in the fight against poverty to implement the strategy of building a moderately prosperous society in all respects by 2020. The analysis based on the househol...Poverty–stricken populations must be identified precisely in the fight against poverty to implement the strategy of building a moderately prosperous society in all respects by 2020. The analysis based on the household survey in 2013 shows that the targeting accuracy is not high based on the standard of income and the accuracy is higher based on the standard of multidimensional poverty index. But the latter still has a low coverage rate. To gradually achieve integration of the rural poverty line and the rural subsistence allowance line, standards applied to identifying households entitled to subsistence allowances should be changed from the standard of income to multidimensional poverty indexes. A unified standard of subsistence allowances and a unified method for identifying related households should be developed. At the same time, coverage and funding of subsistence allowances should be extended and increased to better meet people's basic needs.展开更多
Industrialization is one way to achieve a sustainable route out of poverty.During the implementation of industry-based poverty alleviation projects,rural households’livelihood responses to change are crucial.A strong...Industrialization is one way to achieve a sustainable route out of poverty.During the implementation of industry-based poverty alleviation projects,rural households’livelihood responses to change are crucial.A stronger livelihood response is conducive to multidimensional poverty relief due to industry-based poverty alleviation projects.Effective poverty alleviation can also stimulate stronger household responses.There is a positive cycle between livelihood response and multidimensional poverty relief effects that can help achieve sustainable poverty alleviation goals.Using a synergistic perspective on the relationship between“people–industry–land”,this paper explains the poverty alleviation logic connecting livelihood response,multidimensional poverty relief,and sustainable routes out of poverty by constructing a four-dimensional livelihood response measurement system with three elements of intensity.We analyzed survey data collected from 2363 households from 4 sample counties in 4 contiguous poverty-stricken areas,and measured and compared the characteristics of rural households’livelihood responses and the factors influencing poverty alleviation projects.Rural households’livelihood responses in four sample counties were moderate.The four dimensions of responses were ranked as livelihood strategy response,livelihood space response,livelihood output response,and livelihood capital response.The three intensities indicated that the perception and willingness elements of livelihood response were very similar,but there was a big gap between those elements and livelihood response actions.At the group level,poor households had higher and more consistent livelihood response than non-poor households.External environment factors(such as location,industry type,village organizational ability,and village atmosphere)and internal family factors(such as resource endowment,income sources,health,education,labor quantity,policy trust,credit availability,and social networks)had a significant impact on households’livelihood response.However,this impact varied across different dimensions and had different intensities.This paper proposes a multidimensional poverty relief mechanism and suggests sustainable routes out of poverty.展开更多
基金Supported by Environment and Development Innovative Experiment Project of Xuzhou Normal University (HJ201015Y)
文摘In terms of current life style, living and production conditions and hygienic and educational condition, we select 8 indices, such as annual net income of farmers per capita, annual grain yield per capita, total power of agricultural machinery per capita, dropout rate of school children and so on, to establish index system of determining the poor village in North Jiangsu. By selecting Lianqun Village in Suining County of Xuzhou City, Mawa Village in Siyang County of Suqian City, Chuanxing Village in Guanyun County of Lianyungang City, Xiaozhu Village in Hongze County of Huai'an City, Fengda Village in Xiangshui County of Yancheng City as the representative villages, after the discussion and consultation of the masses and the village cadres of all villages, we get the measuring results of weight. Through the field survey, investigation and interview in the selected regions, we get the relevant data, and then we conduct standardization processing, so as to get the index value that can comprehensively reflect the characteristics of poverty. According to the index data that have been standardized, by using participatory poverty index formula for calculation, we get the values that can explain the poverty degree of the respondents. We sequence the representative poor villages in this region according to the poverty degree from high to low, and the result is as follows: Mawa Village, ianqun Village, Chuanxing Village, Xiaozhu Village, and Fengda Village. It indicates that in terms of the operability of theory and technique, the participatory poverty index can better recognize the poor villages, so that it lays solid foundation for rationally and effectively using the limited poverty alleviation resources.
基金supported by the Science and Technology Program of Jiangxi Provincial Education Department(GJJ180233)。
文摘Poverty is a severe barrier to sustainable human development and a pressing worldwide issue.Understanding how to accurately assess the spatial distribution of poverty in mountain areas has become crucial for ensuring that governments at all levels take suitable poverty reduction strategies.In this study,the mountain poverty spatial index(MPSI)was created by combining the digital elevation model(DEM),Luojia-1 night-time light imagery,point of interest(POI)data,and vegetation index products.The MPSI was then used to identify the spatial characteristics of poverty at different scales in the hilly area of Ganzhou city,Jiangxi Province,China.Socioeconomic statistics and Google satellite images were used to verify the reliability of MPSI by constructing a multidimensional poverty index(MPI)at the county scale.The results showed that MPSI and MPI have a positive correlation with a correlation coefficient of 0.8934(P<0.001),which indicates that MPSI could be used to identify the spatial distribution of poverty well.Specifically,the smallest distribution of both MPSI and MPI was in Zhanggong District(1.4555 and 0.1894),which indicates that most of the affluent counties were concentrated in the central region of Ganzhou,and the poor areas were scattered in the surrounding areas of Ganzhou.In addition,MPSI accurately identified poverty in mountainous areas with complex terrain in small administrative units,which can provide a more accurate way to monitor the poverty situation in the mountainous areas of China.This study will be useful for providing scientific references for the Chinese government to implement targeted strategies for eradicating poverty with differentiated policies.
基金sponsored by "Construction of China’s Income Distribution Database",key project funded by the National Natural Science Foundation of China"Research on China’s Income Distribution and Labor Market",an interdisciplinary construction project launched by Beijing Normal University
文摘Poverty–stricken populations must be identified precisely in the fight against poverty to implement the strategy of building a moderately prosperous society in all respects by 2020. The analysis based on the household survey in 2013 shows that the targeting accuracy is not high based on the standard of income and the accuracy is higher based on the standard of multidimensional poverty index. But the latter still has a low coverage rate. To gradually achieve integration of the rural poverty line and the rural subsistence allowance line, standards applied to identifying households entitled to subsistence allowances should be changed from the standard of income to multidimensional poverty indexes. A unified standard of subsistence allowances and a unified method for identifying related households should be developed. At the same time, coverage and funding of subsistence allowances should be extended and increased to better meet people's basic needs.
基金Financial support from National Natural Science Foundation of China(Grant No.41761022)Science Fund for Distinguished Young Scholars of Hunan Province,China(Grant No.2020JJ2025)+2 种基金Key Program of Social Science Foundation in Hunan Province,China(Grant No.18ZDB031)Platform Program of Key Laboratory of Ecotourism in Hunan Province,China(Grant No.STLV1815)Hunan Provincial Innovation Foundation For Postgraduate,China(Grant No.CX20201061),is gratefully acknowledged.
文摘Industrialization is one way to achieve a sustainable route out of poverty.During the implementation of industry-based poverty alleviation projects,rural households’livelihood responses to change are crucial.A stronger livelihood response is conducive to multidimensional poverty relief due to industry-based poverty alleviation projects.Effective poverty alleviation can also stimulate stronger household responses.There is a positive cycle between livelihood response and multidimensional poverty relief effects that can help achieve sustainable poverty alleviation goals.Using a synergistic perspective on the relationship between“people–industry–land”,this paper explains the poverty alleviation logic connecting livelihood response,multidimensional poverty relief,and sustainable routes out of poverty by constructing a four-dimensional livelihood response measurement system with three elements of intensity.We analyzed survey data collected from 2363 households from 4 sample counties in 4 contiguous poverty-stricken areas,and measured and compared the characteristics of rural households’livelihood responses and the factors influencing poverty alleviation projects.Rural households’livelihood responses in four sample counties were moderate.The four dimensions of responses were ranked as livelihood strategy response,livelihood space response,livelihood output response,and livelihood capital response.The three intensities indicated that the perception and willingness elements of livelihood response were very similar,but there was a big gap between those elements and livelihood response actions.At the group level,poor households had higher and more consistent livelihood response than non-poor households.External environment factors(such as location,industry type,village organizational ability,and village atmosphere)and internal family factors(such as resource endowment,income sources,health,education,labor quantity,policy trust,credit availability,and social networks)had a significant impact on households’livelihood response.However,this impact varied across different dimensions and had different intensities.This paper proposes a multidimensional poverty relief mechanism and suggests sustainable routes out of poverty.
