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Evaluating the influence of digital financial inclusion on financial crises and economic cycles: a Bayesian logistic regression insight

Dinh Le Quoc et al.

Journal of Financial Regulation and Compliance2025https://doi.org/10.1108/jfrc-10-2024-0206article
AJG 1ABDC B
Weight
0.64

Abstract

Purpose This paper aims to examine the impact of Digital Financial Inclusion (DFI) on three key economic aspects: banking crises, economic expansion and economic downturns across 93 countries from 2004 to 2017. Design/methodology/approach Bayesian Logit regression models provide important insights into how DFI influences these economic factors. Findings The findings show that DFI has a modest positive effect on banking crises (coefficients: 0.002–0.027), but rapid growth could increase crisis risks if not regulated. DFI positively impacts economic expansion (coefficients: 0.003–0.012), supporting growth at reasonable levels. For economic downturns, DFI has a negative effect, potentially reducing recession risks, though the impact is small. Regionally, DFI helps mitigate banking crises and downturns in Africa, Latin America and Asia, but in Europe, it slightly increases risks, suggesting potential instability if not properly managed. Originality/value The study provides original insights into the nuanced effects of DFI on banking crises, economic expansion and economic downturns across different regions, offering valuable policy recommendations based on these findings.

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https://doi.org/https://doi.org/10.1108/jfrc-10-2024-0206

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@article{dinh2025,
  title        = {{Evaluating the influence of digital financial inclusion on financial crises and economic cycles: a Bayesian logistic regression insight}},
  author       = {Dinh Le Quoc et al.},
  journal      = {Journal of Financial Regulation and Compliance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/jfrc-10-2024-0206},
}

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Evidence weight

0.64

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.67 × 0.4 = 0.27
M · momentum0.95 × 0.15 = 0.14
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.