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  • Special Issue | Multidimensional Poverty and Livelihood Sustainability
    ZHAO Xueyan, LIU Jianghua, WANG Weijun, LAN Haixia, MA Pingyi, DU Yuxuan
    PROGRESS IN GEOGRAPHY. 2020, 39(6): 982-995. https://doi.org/10.18306/dlkxjz.2020.06.009

    Enhancing the livelihood sustainability of out-of-poverty farming households in poor mountainous areas is not only the realistic demand for rural poverty alleviation in the new era, but also the urgent demand of rural revitalization. Taking into consideration livelihood capital, livelihood strategy and livelihood environment, this study established a livelihood sustainability evaluation index system of out-of-poverty farming households, and used the household survey data of the out-of-poverty households in the Longnan mountainous area to evaluate their livelihood sustainability and identify livelihood barriers. The results show that: 1) From river valley, the middle mountain to the high mountain area, and with the passage of time since a household was out of poverty, livelihood sustainability of the out-of-poverty households decreased in turn, and the livelihood sustainability of work-oriented type and agriculture-industry complementary type are higher than other farmers. 2) The proportion of farmers whose livelihood is unsustainable in Longnan mountain area is 28.83%, and the proportion of farming households with unsustainable livelihoods is higher in high-mountain area, traditional farming type, and late out-of-poverty households, while the proportion of farmers who have unsustainable livelihoods is lower in river valleys, agriculture-industry complementary type, work-oriented type, and early out-of-poverty households. 3) Out-of-poverty households with unsustainable livelihoods are all faced with multiple livelihood barriers, and nearly two-thirds of them are faced with multidimensional capital environment barriers and multi-factor barriers. 4) In view of the multiple livelihood barriers faced by the out-of-poverty households with unsustainable livelihoods, targeted multidimensional livelihood intervention should be implemented for different categories of households.

  • Special Issue | Multidimensional Poverty and Livelihood Sustainability
    LIU Qian, CHEN Jia, WU Kongsen, YANG Xinjun
    PROGRESS IN GEOGRAPHY. 2020, 39(6): 996-1012. https://doi.org/10.18306/dlkxjz.2020.06.010

    The poverty alleviation targets have downscaled to the farming household unit in China. Developing and improving the measurement method for multidimensional poverty at the farming household scale has become the key to accurately allocate the resources and improve the efficiency of poverty alleviation. In this study, a comprehensive framework of ability-assets-environment multidimensional poverty assessment was constructed based on human-environment-activities relationship theories. Taking the Qinling-Daba Mountains area as an example, this study measured the multidimensional poverty of surveyed households. Multidimensional poverty households were identified and compared with the designated poor households. The impact mechanism of multidimensional poverty was also explored. Finally, the multidimensional poverty households were divided into different types according to the deprivation dimensions. The research results show that: 1) There were 245 multidimensional poverty households and 239 non-multidimensional poverty households. With regard to the scores of the capacity dimension, the assets dimension, and the environment dimension, there were great differences between multidimensional and non-multidimensional poor households. 2) The majority (84.08%) of the multidimensional poverty households overlapped with the designated poor households. Furthermore, the degree of poverty of multidimensional poor households was deeper in both comprehensive and individual dimensions. 3) The occurrence of multidimensional poverty was mainly influenced by the weakness and deprivation of development ability and production ability of the households, financial and physical assets for activities, geographical locations and conditions of the environment. 4) There were four types of multidimensional poverty households, namely, development deficiency type, compound poverty type, severe living environment type, and comprehensive poverty type.

  • Special Issue | Multidimensional Poverty and Livelihood Sustainability
    ZHANG Jinping, LIN Dan, ZHOU Xiangli, YU Zhenxin, SONG Wei, CHENG Yeqing
    PROGRESS IN GEOGRAPHY. 2020, 39(6): 1013-1023. https://doi.org/10.18306/dlkxjz.2020.06.011

    Poverty has multidimensional attributes, and it has become a consensus to study poverty from a multidimensional perspective according to different social groups and backgrounds. In order to measure the multidimensional poverty situation in the rural areas where the poor population is concentrated in Hainan Province, we expanded the index system based on the exit criteria for targeted poverty alleviation fulfilling the basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, and established a multidimensional poverty assessment conceptual model for rural households in Hainan Province that covers education, health, housing, livelihood, and income indicators. Then, based on household survey data from 3924 households in 70 towns and 134 poor villages of Hainan Province in 2018, we used the double threshold Alkire-Foster (A-F) method to evaluate the multidimensional poverty status of rural households and villages, and then used the geographically weighted regression (GWR) model to analyze the spatial heterogeneity of the influencing factors of multidimensional poverty in villages. The study results show that: 1) The incidence of multidimensional poverty of the surveyed households was 18.22%. But the incidence of multidimensional poverty in villages with severe multidimensional poverty is not necessarily high. 2) The four indicators of farming households' asset status, cooking fuels, family members' diseases, and family members’ highest academic qualifications contribute the most to multidimensional poverty, while the contribution ratio of indicators belonging to the standard of fulfilling basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, as well as income are generally not high. The multidimensional poverty in the contiguous poverty areas in the central and western regions of the province is mainly manifested by poor asset conditions, unclean cooking fuels, high prevalence of disease of family members, and lower education levels. 3) The GWR model analysis showed that as the most important influencing factors of multidimensional poverty, spatial heterogeneity of the estimated coefficients of the four variables, gender of the household head, education level of the household head, ratio of female labor force, and dependency ratio, have very obvious impacts. In general, areas with more female-headed and low-education attainment individual headed households tend to be more prone to multidimensional poverty, and their impacts increased from east to west and from north to south, separately. With an increasing trend from north to south, the effect of the proportion of female labor force is negative and that of the dependency ratio is positive, which reflects the typical regional characteristics of weak labor force and relatively more industrious women in Hainan poverty-stricken areas.

  • Special Issue | Multidimensional Poverty and Livelihood Sustainability
    QI Wenping, WANG Yanhui, WAN Yuan, HUANG Tao
    PROGRESS IN GEOGRAPHY. 2020, 39(6): 1024-1036. https://doi.org/10.18306/dlkxjz.2020.06.012

    Establishing a multi-objective development evaluation system for poverty-stricken households to realize the accurate identification and dynamic monitoring of relative poverty under different development goals has become an urgent need of poverty alleviation and development in the new stage of rural poverty alleviation. Taking into consideration the strategies of targeted poverty alleviation, rural revitalization, and sustainable development, this study designed a "goal fulfillment degree" Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS) multi-objective development evaluation model that reveals the development level and development gap of poverty-stricken households under the short-, medium-, and long-term goals, and detected the influencing factors of poverty reduction of farming households at different development levels based on geographical detector. Taking Fugong County, Yunnan Province as the study area, the results show that: 1) At present, there is a large number of farming households in the study area that are still in absolute poverty, and there is still a great pressure to tackle the poverty problem. Therefore, comprehensive poverty alleviation is the most urgent development goal of Fugong County. Farming households that are out of absolute poverty are still in relative poverty and have high poverty vulnerability. They are still far from the average development level of rural residents nation-wide and in the province. Therefore, the task of preventing and alleviating relative poverty in Fugong County is arduous. 2) Under the short-term goal, the main factors contributing to poverty are the number of years of education for the labor force, sanitary toilets, safe housing, per capita net income of the family, and family health; under the medium- and long-term goals, compared with the national and provincial levels, the main development weaknesses are per capita net income of the family, education for the labor force, and safe housing. 3) Affected by infrastructure, terrain, economic geographical location, natural resources, and traffic location, the spatial distribution characteristics of poor farming households at different development levels are very different. The lower the development level of farming households, the stronger the spatial heterogeneity, and the greater the impact of geographical environment. The research results can provide efficient technical decision-making support for the implementation of national precision poverty reduction strategies, rural revitalization strategies, and sustainable development strategies.