Data-Driven Modeling of the Impact of Internet Inclusive Finance on the Urban-Rural Income Gap in the E-Commerce Era

Ying Song,
Li Tan,
Yafei Wang,
Lu Li,

Abstract


In modern society, in which e-commerce is advancing rapidly, conventional finance has begun to adopt the internet, and digital inclusive finance activity has emerged. In the e-commerce era, the use of massive data to digitally evaluate important issues remains promising. Against this background, this paper proposes a data-driven modeling framework for the impact of inclusive internet finance on the urban-rural income gap in the e-commerce era. Q1-2: Specifically, using 2011-2017 panel data on 204 prefecture-level cities in China, this paper visualizes statistical features needed to evaluate the rationality of the initial data samples. Then, the study sets up five basic explanatory variables and five control variables and establishes two regression models to map the relationship between the feature variables and the urban-rural income gap. Using several parameter estimation methods to fit the model parameters, the paper examines the impact of inclusive finance on the urban-rural income gap from multiple perspectives. Finally, based on the data-level analysis results, the paper proposes policy suggestions.

Keywords


E-commerce, Urban-rural income gap, Internet inclusive finance, Data-driven modeling, Multivariant regression

Citation Format:
Ying Song, Li Tan, Yafei Wang, Lu Li, "Data-Driven Modeling of the Impact of Internet Inclusive Finance on the Urban-Rural Income Gap in the E-Commerce Era," Journal of Internet Technology, vol. 23, no. 6 , pp. 1377-1388, Nov. 2022.

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