Financial Literacy, Financial Resilience and Participation in Securities Markets: Evidence from Portugal
Bibliographic record
Abstract
Using a unique multi-wave dataset from nationally representative surveys in Portugal (2015, 2020, and 2023), this study extends the household finance literature by examining the mechanisms linking financial literacy to capital market participation. We propose and test a moderated mediation framework, arguing that the relationship is channeled through the mediating roles of financial resilience and self-efficacy and is contingent upon sociodemographic moderators. Our findings reveal a decline in average financial knowledge between 2015 and 2020/23, with persistent gaps across socioeconomic groups. Empirical results from count, logit, and ordered logit models provide strong evidence for partial mediation; financial literacy significantly enhances a household’s financial resilience, which in turn is a strong positive predictor of participation in stocks, bonds, and mutual funds. Furthermore, we find that perceived financial knowledge is a more powerful direct driver of participation than objective knowledge. Crucially, these pathways are powerfully moderated by income and education, highlighting that socioeconomic status is a fundamental boundary condition for converting knowledge into investment behavior. The results challenge simplistic direct-effects models and suggest that policy initiatives aimed at boosting market participation, such as the Portuguese National Plan for Financial Education, must look beyond knowledge dissemination to also foster financial resilience, self-efficacy, and address structural inequalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".