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Record W4283651790 · doi:10.3390/jrfm15070284

Causal Effects of Financial Education Intervention Aimed at University Students on Financial Knowledge and Financial Self-Efficacy

2022· article· en· W4283651790 on OpenAlexvenueno aff
Manuel Salas Velasco

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial literacyFinanceIntervention (counseling)MediationSelf-efficacyTest (biology)Financial analysisDebtPsychologyBusinessPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Based on a randomized controlled experiment among final-year undergraduate students, we provide an assessment of the treatment effects of financial education intervention focused on debt-financed graduate education decision-making. Specifically, this study finds positive treatment effects on both college seniors’ objective financial knowledge and subjective financial knowledge and self-confidence (i.e., perceived financial self-efficacy). Individual financial well-being is thought to be enhanced by improved financial knowledge test scores and perceived financial self-efficacy. In addition, we carry out a causal mediation analysis to investigate the extent to which objective financial knowledge plays a mediating role in the effect of financial education treatment on the intervention outcome (perceived financial self-efficacy). The mediation proportion, the proportion of treatment effect on outcome explained by the intermediate variable of financial knowledge, is around 21%, which is important. Thus, policies that aim to improve financial capabilities among college students through financial education programs should be aware that financial literacy is a significant antecedent of (a prerequisite for) financial self-efficacy.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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.

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

Citations24
Published2022
Admission routes1
Has abstractyes

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