Does financial knowledge affect borrower discouragement among various social categories? Evidence from the United States
Bibliographic record
Abstract
Abstract A deficiency in financial knowledge often precipitates costly financial choices, affecting consumers' behavior and decision‐making. We delve into how financial acumen influences borrower discouragement by utilizing data from the U.S. Federal Reserve's Survey of Household Economics and Decision‐Making (2017–2022). Discouraged borrower describes creditworthy individuals who, despite a genuine need for credit, avoid applying due to anticipated rejection. Our research reveals that financial knowledge diminishes the likelihood of borrower discouragement after controlling for various societal groups. However, when we estimate the model separately, its impact is not uniform across these societal segments. Specifically, our study uncovers that the effects of financial knowledge are different on gender, race, and occupational status. Further analyses of various subgroups confirm that race and occupational status are consistent predictors of borrower discouragement, even when accounting for financial knowledge. These insights underscore the importance of providing targeted financial education to address these disparities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".