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Record W4409409828 · doi:10.1080/23322373.2025.2470595

Does financial literacy enhance banking transactions among rural people with access to bank accounts? Insights from a field experiment in Ghana

2025· article· en· W4409409828 on OpenAlexfundno aff
Yaa Afi Osei, Helena Barnard, William K. Derban, Dominic Essuman

Bibliographic record

VenueAfrica Journal of Management · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
FundersUniversity of PretoriaInternational Development Research Centre
KeywordsFinancial literacyBank accountBusinessField (mathematics)Financial inclusionFinancial systemLiteracyAccountingEconomicsFinanceFinancial servicesEconomic growthPayment

Abstract

fetched live from OpenAlex

Bank account usage is a fundamental indicator of financial inclusion. Across sub-Saharan Africa, various stakeholders actively work to improve access to banking. This study uses motivation, opportunity and ability theory, with self-efficacy as a boundary condition, to theorize the relationship between financial literacy and usage of a mobile-based, zero-cost bank account. In a field experiment with young adults in rural Ghana – a typical population for such interventions – multi-wave data from 142 individuals show that neither financial literacy nor its interaction with self-efficacy improves bank account usage. Follow-up surveys and interviews reveal other motivation- and ability-enhancing factors (i.e. income, and the need for bank accounts) that condition the causal relationship tested in the study. The study’s findings clarify the boundaries of the existing literature on the link between financial literacy and financial inclusion, while offering policymakers valuable insights into the conditions necessary for financial inclusion interventions to achieve the desired outcomes.

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)0.000
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 score0.338
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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