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Using VPI to Measure Poverty-Stricken Villages in China

Author

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  • Yanhui Wang

    (Capital Normal University
    Louisiana State University)

  • Yefeng Chen

    (Capital Normal University)

Abstract

Revealing the comprehensive poverty levels and spatial diversities of poverty-stricken villages is a prerequisite for “Entire-village Advancement” anti-poverty policy of China. In response, we build a multidimensional poverty assessment model from the perspective of spatial poverty, adopting VPI (village-level poverty index) to examine multiscale and multidimensional situations and characteristics of poverty-stricken villages in rural China, then adopting spatial geostatistics to explore their multidimensional and multiscale spatial point pattern distribution. Further, we also introduce LSE model to examine their poverty types. Our tests show that, Firstly, the validity and reliability of the VPI model can be justified in terms of village-level targeting ratio and policy-coverage ratio. Then, the poverty level of poverty-stricken villages follows a normal-right distribution, presenting an “olive” structure with a shape of “large middle, and small at two ends”, poverty levels and poverty sizes of different counties obviously increasing from east to west, and different classifications of counties also representing different poverty levels. On the other hand, there exists three kinds of multi-scale poverty clusters among different contiguous destitute areas, namely, clustering-randomness-dispersion, randomness-clustering and dispersion/randomness distribution. Villages with poverty type of three-factor dominance account for over 50 % of the total villages, their poverty are mainly caused by harsh geographical environment, disadvantaged production and living conditions, and poor labor forces. This research helps know well about the relationships among different villages from the multiscale and multidimensional views, so as to provide decision basis for optimal development and reorganization of the poverty-stricken villages in rural China, which is of vital practical significance to make overall arrangement of rural development-oriented poverty elimination and to boost new round of precise poverty elimination and new countryside construction.

Suggested Citation

  • Yanhui Wang & Yefeng Chen, 2017. "Using VPI to Measure Poverty-Stricken Villages in China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 833-857, September.
    • Handle: RePEc:spr:soinre:v:133:y:2017:i:3:d:10.1007_s11205-016-1391-5
    DOI: 10.1007/s11205-016-1391-5
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    3. Zhixi Xu & Zhongliang Cai & Shufan Wu & Xinran Huang & Ji Liu & Junying Sun & Shiliang Su & Min Weng, 2019. "Identifying the Geographic Indicators of Poverty Using Geographically Weighted Regression: A Case Study from Qiandongnan Miao and Dong Autonomous Prefecture, Guizhou, China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 947-970, April.
    4. Guo, Junping & Qu, Song, 2021. "Multidimensional and Relative Poverty in Rural China: Evidence from Micro-Level Data of 6145 Households," 2021 Conference, August 17-31, 2021, Virtual 315040, International Association of Agricultural Economists.
    5. Yuewen Jiang & Yanhui Wang & Wenping Qi & Benhe Cai & Chong Huang & Chenxia Liang, 2022. "Detecting Multilevel Poverty-Causing Factors of Farmer Households in Fugong County: A Hierarchical Spatial–Temporal Regressive Model," Agriculture, MDPI, vol. 12(11), pages 1-21, November.
    6. Yuewen Jiang & Chong Huang & Duoduo Yin & Chenxia Liang & Yanhui Wang, 2020. "Constructing HLM to examine multi-level poverty-contributing factors of farmer households: Why and how?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    7. Guo, Junping & Qu, Song & Zhu, Tiehui, 2022. "Estimating China’s relative and multidimensional Poverty: Evidence from micro-level data of 6145 rural households," World Development Perspectives, Elsevier, vol. 26(C).
    8. Yanhui Wang & Shoujie Jia & Wenping Qi & Chong Huang, 2022. "Examining Poverty Reduction of Poverty-Stricken Farmer Households under Different Development Goals: A Multiobjective Spatio-Temporal Evolution Analysis Method," IJERPH, MDPI, vol. 19(19), pages 1-21, October.

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