Managing Household Finances: How Engaging in Financial Management Activities Relates to the Experiential Well-Being of Americans
Bibliographic record
Abstract
This study examines how engagement in financial management activities influences well-being using nationally representative data (N = approximately 30,000) from the U.S. Bureau of Labor Statistics’ American Time Use Survey and its associated Well-Being Modules. The current study estimates ordered probit models for several measures of experiential well-being, which consider how meaningful an activity is for a household and how happy, sad, tired, in pain, and stressed respondents felt during the activity. Controlling for a standard set of demographic and socioeconomic factors, the econometric results indicate that households report lower utility gains (lower happiness, greater sadness, and higher stress) when engaging in financial management activities relative to other activities. Furthermore, the results suggest increases in household time allocated toward performing financial management activities is associated with a lower (higher) likelihood of being very happy (very stressed) compared to other activities. The findings strongly indicate that households perceive financial management activities as vexing, reinforcing the need for financial stewardship support to promote household well-being.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".