Cash-Flow and Savings Practices of Low-Income Households: Evidence From a Follow-Up Study of IDA Participants
Bibliographic record
Abstract
ABSTRACT Understanding how low-income households manage their finances is critical to designing effective antipoverty interventions. This study used data from a 2008 follow-up survey of 326 low-income households in Hawaii who participated in an Individual Development Account (IDA) intervention from 1999 to 2005. Self-reported cash flow (five items) and savings (four items) practices were explored using latent class analysis. Three latent classes were produced: Class 3 managed cash flows and saved (n = 166; 51%); Class 2 managed cash flows but did not save (n = 73; 22%); and Class 1 struggled to manage cash flows and save (n = 89; 27%). Using ordinal regression, psychological sense of mastery was positively and significantly (p < .01) related to being in a higher class membership (b = .14; OR = 1.15). IDA participation had no association with latent classification. The key finding is the heterogeneity among low-income financial management practices and the importance of providing individualized services. Future longitudinal research is needed to understand how IDA participation affects financial practices in the short term and long term.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".