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The impact of digital finance on household consumption: Evidence from China

Open access
Li, Jie, Wu, Yu, Xiao, Jing Jian·2020·Economic Modelling

Abstract

Abstract Using panel data from the China Household Finance Survey (CHFS) in 2013, 2015, and 2017 and the digital inclusive finance index developed by Peking University, this study examined impacts of the digital inclusive finance on household consumption and explored its mechanisms. Results suggest that the digital inclusive finance could promote households consumption. A heterogeneity analysis showed that households with fewer assets, lower income, less financial literacy and in third- and fourth-tier cities experienced larger facilitating effects of digital finance on consumption compared to their counterparts. For consumption categories, digital finance was positively correlated with food, clothing, house maintenance, medical care, and education and entertainment expenditures. In terms of consumption structure, digital finance mainly promoted the recurring household expenditures rather than the non-recurring expenditures. Further analyses based on the mediating model found that online shopping, digital payment, obtainment of online credit, purchase of financing products on the internet and business insurance, were the main mediating variables through which digital finance affected household consumption.

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Metadata

Authors
Li, J., Wu, Y., & Xiao, J. J.
Venue
Economic Modelling
Publisher
Elsevier BV
Published
2020-03
Volume
86
Pages
317-326
ISSN
0264-9993 (ISSN-L)
OpenAlex
W2973338680
Cited by
952
References
2
FWCI
69.14
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The impact of digital finance on household consumption: Evidence from China. https://app.cochat.ai/papers/10.1016/j.econmod.2019.09.027
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Li, J., Wu, Y., & Xiao, J. J. (2020). The impact of digital finance on household consumption: Evidence from China. Economic Modelling. https://doi.org/10.1016/j.econmod.2019.09.027

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.