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Record W2891927658 · doi:10.3386/w20203

Five Steps to Planning Success. Experimental Evidence from U.S. Households

2014· preprint· en· W2891927658 on OpenAlexaboutno aff
Aileen Heinberg, Angela Hung, Arie Kapteyn, Annamaria Lusardi, Anya Samek, Joanne Yoong

Bibliographic record

VenueNational Bureau of Economic Research · 2014
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersU.S. Social Security Administration
KeywordsRespondentNarrativePsychological interventionQuarter (Canadian coin)Financial planSample (material)FinancePopulationValue (mathematics)Actuarial sciencePsychologyComputer scienceEconomicsPolitical scienceDemographySociologyGeography

Abstract

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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. 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.275
GPT teacher head0.464
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2014
Admission routes1
Has abstractyes

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