Poverty Groups Identification and Assessment of Poverty Alleviation Programs in Rural China

DOI

10.2991/assehr.k.200428.040How to use a DOI?

Keywords

rural China, rural poverty, poverty alleviation programs, accusation rule, k-medoids clustering, multiple factor analysis

Abstract

This study analyzed the outcomes of 194 individuals living in rural poverty in Guizhou Province using data obtained from a poverty alleviation information system together with several machine-learning tools. First, four dimensions were abstracted from a multiple factor analysis: family background and work condition, self-development, regional context, and health status and labor capacity. Second, five heterogeneous groups were identified through k-medoids clustering based on the above dimensions. The results showed that the most significant differences among poverty groups were related to health status and household size. The effectiveness of poverty alleviation programs for the different poverty groups was then evaluated. By employing association rule mining, we showed that education assistance is effective in poverty groups in relatively ‘good’ condition but not in others, whereas the ‘Minimum Living Standard’ program failed in all groups, particularly when it was the sole program. Thus, our study indicated that additional targeted alleviation programs should be implemented to address the needs of different poverty groups, especially in terms of education assistance, medical care, and medical prevention programs.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zeng Zhen
AU  - Zhu Mengxian
PY  - 2020
DA  - 2020/05/01
TI  - Poverty Groups Identification and Assessment of Poverty Alleviation Programs in Rural China
BT  - Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)
PB  - Atlantis Press
SP  - 174
EP  - 189
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200428.040
DO  - 10.2991/assehr.k.200428.040
ID  - Zhen2020
ER  -