Evidence map›Paper›PMID 39170403›Full record

ArticleHeliyon2024

Digital financial inclusion and household financial vulnerability: An empirical analysis of rural and urban disparities in China.

Jianhe Liu, Yuan Chen, Xuanyu Chen, Bin Chen

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jianhe LiuSchool of Finance, Zhejiang University of Finance and Economics, China.
Yuan ChenSchool of Finance, Zhejiang University of Finance and Economics, China.
Xuanyu ChenSchool of Finance, Zhejiang University of Finance and Economics, China.
Bin ChenSchool of Finance, Zhejiang University of Finance and Economics, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent times, a notable increase in the leverage ratios among numerous households across China has been witnessed, culminating in heightened household financial vulnerability. Concurrently, the sphere of digital inclusive finance has witnessed rapid advancement, establishing itself as a crucial mechanism for Chinese households to counteract financial risk shocks. This research article meticulously constructs an ordered regression model, anchored in micro-level data from household surveys, to delve into the influence and operative mechanisms of digital inclusive finance on the vulnerability of household finances. Empirical findings from this study robustly indicate that the evolution of digital inclusive finance significantly mitigates the household financial vulnerability. A thorough mechanism analysis reveals that digital inclusive finance primarily curtails household financial vulnerability through several avenues: it notably enhances financial literacy, augments the income derived from household financial assets, and elevates contributions to commercial insurance. Intriguingly, a heterogeneity analysis underscores that the impact of digital inclusive finance is more pronounced in reducing financial vulnerability amongst households registered in rural areas and those with lower income levels. This article contributes to the expansion of the theoretical framework concerning household financial vulnerability, offering insightful guidance and policy implications for addressing financial vulnerability concerns and forestalling macro-financial risks.

Indexed as

Digital financial inclusionFinancial riskFinancial vulnerabilityHousehold financial vulnerability

Identifiers

PMID39170403
PMCPMC11336744

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.