Research on Multidimensional Relative Poverty Measurement of Rural Left Behind Children and Its Influencing Factors Based on Big Data Samples

DOI

10.2991/978-94-6463-064-0_9How to use a DOI?

Keywords

AF method; multidimensional relative poverty; influencing factors

Abstract

This paper measures the multidimensional relative poverty of rural left behind children based on the big data samples of the 2018 China family tracking survey (CFPS), and empirically studies the influencing factors of multidimensional relative poverty of rural left behind children by using logistic model. The results show that: (1) the incidence of relative poverty of left behind children in rural areas in four indicators of physical development, parental companionship, clean water and household energy is prominent, all of which are above 40%. (2) With the increase of the critical value k of multidimensional relative poverty, the incidence of multidimensional relative poverty and multidimensional relative poverty index (H and m) of rural left behind children show a downward trend. (3) Individual characteristics, family population endowment, family resource endowment and social capital have different effects on the multidimensional relative poverty of rural left behind children.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Meng Lei
AU  - Tianhui Zhuang
AU  - Feng Qiu
PY  - 2022
DA  - 2022/12/27
TI  - Research on Multidimensional Relative Poverty Measurement of Rural Left Behind Children and Its Influencing Factors Based on Big Data Samples
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 71
EP  - 80
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_9
DO  - 10.2991/978-94-6463-064-0_9
ID  - Lei2022
ER  -