MétaCan
Menu
Back to cohort
Record W4403865973 · doi:10.3390/jrfm17110487

Credit Choices in Rural Egypt: A Comparative Study of Formal and Informal Borrowing

2024· article· en· W4403865973 on OpenAlexvenueno aff
Sarah Mansour, Nagwa Samak, Nesma Gad

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsBusiness

Abstract

fetched live from OpenAlex

Access to finance is essential for fostering financial inclusion, improving household economic well-being, and stimulating economic growth. However, if not prudently managed, it can become a double-edged sword, increasing the risk of over-indebtedness, particularly among low-income households. This paper investigates the borrowing behavior of rural households in Egypt, exploring whether it is motivated by the optimization of intertemporal consumption or reflects deeper financial vulnerabilities. The study enhances our understanding of rural households’ financial behavior in Egypt and contributes to the literature by introducing perceived general self-efficacy as a key behavioral factor. The paper employs a quantitative methodology using a probit analysis of the Egypt Labor Market Panel Survey to explore the factors affecting the demand for formal loans, informal borrowing, and Rotating Saving and Credit Associations (RoSCAs). The results show that informal credit plays a dominant role in meeting rural households’ financial needs. A significant positive relationship between formal and informal credit suggests they are complementary. Elderly, married, less educated, and poorer individuals are more likely to seek both forms of credit, with employment stability being a key differentiator. Self-efficacy also has a significant positive effect. No significant regional differences are observed, except in the case of informal borrowing, with rural households in Upper Egypt showing less reliance, suggesting that social image may influence financial behavior in this region. The results suggest that demand for credit is driven by economic and financial vulnerability of rural households. The paper highlights key policy implications. First, to enhance participation in formal credit market, credit policies should offer more affordable, tailored credit relevant to starting a business rather than financing consumption, part of which is conspicuous. Second, the low self-efficacy among the rural poor suggests a need for policies that combine credit access with financial literacy and debt management support to prevent over-indebtedness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.243
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of risk and financial managementSame topicMicrofinance and Financial InclusionFrench-language works237,207