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Record W3122634326 · doi:10.3386/w20073

The Wealthy Hand-to-Mouth

2014· article· en· W3122634326 on OpenAlexaboutno aff
Greg Kaplan, Giovanni L. Violante, Justin Weidner

Bibliographic record

VenueNational Bureau of Economic Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBusinessPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The wealthy hand-to-mouth are households who hold little or no liquid wealth (cash, checking, and savings accounts), despite owning sizable amounts of illiquid assets (assets that carry a transaction cost, such as housing or retirement accounts). We use survey data on household portfolios for the U.S., Canada, Australia, the U.K., Germany, France, Italy, and Spain to document the share of such households across countries, their demographic characteristics, the composition of their balance sheets, and the persistence of hand-to-mouth status over the life cycle. The portfolio configuration of the wealthy hand-to-mouth suggests that these households may have a high marginal propensity to consume out of transitory income changes, a prediction for which we find empirical support in PSID data. We explain the implications of this group of consumers for macroeconomic modeling and fiscal policy analysis.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.162
GPT teacher head0.436
Teacher spread0.273 · 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; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
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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