Five Steps to Planning Success. Experimental Evidence from U.S. Households
Bibliographic record
Abstract
While financial knowledge has been linked to improved financial behavior, there is little consensus on the value of financial education, in part because rigorous evaluation of various programs has yielded mixed results.However, given the heterogeneity of financial education programs in the literature, focusing on "generic" financial education can be inappropriate and even misleading.Lusardi (2009) and others argue that pedagogy and delivery matter significantly.In this paper, we design and field a low-cost, easily-replicable financial education program called "Five Steps," covering five basic financial planning concepts that relate to retirement.We conduct a field experiment to evaluate the overall impact of "Five Steps" on a probability sample of the American population.In different treatment arms, we quantify the relative impact of delivering the program through video and narrative formats.Our results show that short videos and narratives (each takes about three minutes) have sizable short-run effects on objective measures of respondent knowledge.Moreover, keeping informational content relatively constant, format has significant effects on other psychological levers of behavioral change: effects on motivation and self-efficacy are significantly higher when videos are used, which ultimately influences knowledge acquisition.Follow-up tests of respondents' knowledge approximately eight months after the interventions suggest that between one-quarter and one-third of the knowledge gains and about one-fifth of the self-efficacy gains persist.Thus, this simple program has effects both in the short run and medium run.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".