Financial literacy and financial well-being of Australian consumers: a moderated mediation model of impulsivity and financial capability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This study aims to test a moderated mediation model for a twofold purpose. First, to examine the mediating role of financial capability (FC) in the association between financial literacy (FL) and financial well-being (FW). Second, to analyze if non-impulsive future-oriented behavior (NIB) moderates the associations of FL with FC and FL with FW. Design/methodology/approach The authors use the PROCESS macros in IBM SPSS Statistics to test the moderated mediation model and analyze the 2016 wave of the Household, Income and Labor Dynamics in Australia Survey. Findings The empirical analysis shows that FC partially mediates the association between FL and FW. Furthermore, the moderated mediation analysis shows that NIB strengthens the associations of FL with FC and FL with FW. Specifically, the positive associations of FL with FC and FL with FW significantly increase for those consumers who score high on NIB. Practical implications The findings have implications for the financial services industry. Professional financial planners can positively improve the ability of consumers to deal with their financial matters by highlighting the importance of FL and NIB. Social implications The study findings suggest educating consumers to discourage impulsive behavior and encourage them to create financial plans as it will enhance their ability to conduct financial tasks efficiently, improving their FW. Originality/value To the authors’ knowledge, this is the first study to assess a moderated mediation model, which examines the role of FC as a mediator variable and NIB as a moderator variable in the association between FL and FW.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it