The Effects of Financial Knowledge, Skill, and Self-Assessed Knowledge on Financial Well-Being, Behavior, and Objective Situation
Bibliographic record
Abstract
The effects of certain abilities on financial outcomes have been debated for several years. Some argue that financial knowledge is key to financial success, while others have found financial skill and self-assessed knowledge are more important. This study contributes to this debate by providing a descriptive analysis, whereby regression is used to study the simultaneous effects of financial knowledge, financial skill, and self-assessed knowledge on financial well-being, financial behavior, and objective financial situation. Although our methodology does not allow us to determine if relationships are causal, we show that self-assessed knowledge has little to no relationship with financial well-being, may have contrasting relationships with components of objective financial situation, and is weakly associated with good financial behaviors. Financial skill has the strongest relationship with financial well-being and financial behaviors, as well as some components of objective financial situation. Despite having a relatively weak (compared to financial skill) association with financial well-being and financial behaviors, financial knowledge has the strongest relationship with many components of objective financial situation.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".