Gender differences in financial knowledge overconfidence among older adults
Bibliographic record
Abstract
Abstract This study explores gender differences in financial knowledge overconfidence among older adults using the 2016 Health and Retirement Study. We find that older females have relatively lower objective financial knowledge than do older males, while they evaluate themselves to be as financially knowledgeable as older males. Further, several measures of overconfidence in financial knowledge are higher in older females than older males. A number of robustness checks, including a propensity score matching method, use of a polygenic risk scores, and a test of reproduction using the Survey of Consumer Finances corroborate these gender differences. Results from decomposition analyses of overconfidence indices show that relatively lower crystallized intelligence of older females is one of the main reasons that widens the gender gap among older adults. Lower likelihoods of attaining a college education degree and being in a relationship are additional contributing factors that explain the gender gap. This study provides insights into understanding the gender gap in financial knowledge and its implications for government education or intervention programs to support older adults' wellbeing in retirement.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".