Academic Journal of Humanities & Social Sciences, 2025, 8(2); doi: 10.25236/AJHSS.2025.080208.
Zihan Liu
School of Business, Xi'an International Studies University, Xi'an, Shaanxi, China
This study examines digital financial inclusion's impact on relative poverty in Shaanxi Province using county-level data from 2014 to 2021. Results show it significantly reduces poverty through coverage and usage depth, with stronger effects in district and county-level regions than cities. Spatially, poverty decreased overall but persists in remote mountainous areas due to natural and infrastructural constraints. Ankang and other Qinba mountain areas face multidimensional risks, including inadequate healthcare, education, and agricultural inefficiencies. Recommendations include regional differentiation strategies, investments in healthcare and education, industrial and agricultural modernization, and dynamic poverty monitoring to achieve sustainable poverty reduction through multidimensional policy coordination.
Digital inclusive finance; Relative poverty; Risk of falling back into poverty
Zihan Liu. Digital inclusive finance and relative poverty at county level in Shaanxi province: measurement, evolution and risk of returning to poverty. Academic Journal of Humanities & Social Sciences (2025), Vol. 8, Issue 2: 50-58. https://doi.org/10.25236/AJHSS.2025.080208.
[1] Huang Qian, LI Zheng, Xiong Deping. The effect of digital financial inclusion on poverty reduction and its transmission mechanism [J]. Reform,2019,(11):90-101.
[2] CAI Hongyu, Yang Chao. Digital financial inclusion, credit availability and relative poverty reduction in China [J]. Theory and practice of finance and economics, 2021, and (4) : 24-30.
[3] Zhou Li, LIAO Jinglin ,ZHANG Hao. Digital financial inclusion, credit availability, and poverty reduction: micro-evidence from a Chinese household survey [J]. Economic Science,2021,(01):145-157.
[4] Liang Bang, Li Xiaolin. Digital financial inclusion, poverty alleviation and income distribution: Empirical analysis from Chinese micro-data [J]. Shanghai finance, 2021, (5) : 12- 24.
[5] Zhang Xinjie, Wen Fengrong, Zhang Wuwei, et al. Effect of Digital inclusive finance on increasing income and reducing poverty: An empirical analysis based on data from 17 cities in Shandong Province [J]. Scientific Decision,2022,(09):1-19.
[6] Luo Zhenjun, Yu Lihong. Digital pratt &whitney financial, multidimensional poverty and poverty reduction effect [J]. Journal of statistics and decision, 2022, 38 (11) : 11-15.
[7] Guo-xian bao, Yang Hu. Chinese problems and early warning mechanism research in China [J]. Journal of lanzhou university (social science edition), 2018 46-48 (6) : 123-130.
[8] Zheng Ruiqiang, Cao Guoqing. Chinese out of poverty population, influencing factors, mechanism and risk control [J]. Journal of agriculture and forestry economic management, 2016 (6) : 619-624.
[9] Fan Hesheng. Research on the construction of early-warning mechanism for returning to poverty. Research on Socialism with Chinese Characteristics,2018,(01):57-63.
[10] Ma Shaodong, Wan Renze. Multidimensional poverty perspective of Chinese origin in ethnic minority areas and the countermeasures study [J]. Journal of guizhou minorities research, 2018, 33 (11) 6:45 - 50.
[11] Xie Y T, Yang J. Policy effect of full medical insurance coverage on reducing poverty due to illness [J]. Journal of Beijing Normal University (Social Sciences Edition),2018,(04):141-156.