Proceedings of the 2016 International Conference on Humanities and Social Science

Dynamic Research on China's Gini Coefficient

Authors
Xiaohui Hai
Corresponding Author
Xiaohui Hai
Available Online January 2016.
DOI
https://doi.org/10.2991/hss-26.2016.98How to use a DOI?
Keywords
Gini coefficient, Grouping weighting method, Income gap.
Abstract

Based on the grouped data of resident income in Statistical Yearbook, the paper calculates the China’s Gini coefficients of urban, rural and national residents in the ten years from 2002 to 2011 according to the characteristics of income data of urban residents and rural residents, and finally analyzes the Gini coefficients of urban, rural and national residents calculated, to come to the conclusion that the Gini coefficient of resident income breaks through the warning line and keeps highly stable, which reflects the wealth gap of China’s residents in the current stage is still in the process of developing from a rational gap to an excessive gap, but there is no polarization.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 International Conference on Humanities and Social Science
Series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2016
ISBN
10.2991/hss-26.2016.98
ISSN
2352-5398
DOI
https://doi.org/10.2991/hss-26.2016.98How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Xiaohui Hai
PY  - 2016/01
DA  - 2016/01
TI  - Dynamic Research on China's Gini Coefficient
BT  - Proceedings of the 2016 International Conference on Humanities and Social Science
PB  - Atlantis Press
SP  - 579
EP  - 583
SN  - 2352-5398
UR  - https://doi.org/10.2991/hss-26.2016.98
DO  - https://doi.org/10.2991/hss-26.2016.98
ID  - Hai2016/01
ER  -