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Record W3122019021 · doi:10.3386/w28383

Household Wealth Trends in the United States, 1962 to 2019: Median Wealth Rebounds... But Not Enough

2021· report· en· W3122019021 on OpenAlexfundno aff
Edward N. Wolff

Bibliographic record

VenueNational Bureau of Economic Research · 2021
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersYork University
KeywordsEconomicsDemographic economics

Abstract

fetched live from OpenAlex

Median household wealth shot up by 21.2 percent in real terms between 2016 and 2019, as asset prices continued to rebound.However, 2007 still remains the watershed year, and median wealth was down 20.4 percent relative to 2007, though mean wealth more than fully recovered.There was a modest remission in wealth inequality, with the share of the top one percent down by 1.4 percentage points, that of the top 20 percent down by 1.0 percentage points, the Gini coefficient down by 0.008, and the mean wealth of the top one percent also down by 1.9 percent.The homeownership rate finally rebounded a bit, by 1.2 percentage points, to 64.9 percent.The stock ownership rate advanced by 0.4 percentage points to 49.6 percent, though still down from its 2001 peak.Though the mean debt of the middle class rose by 10.7 percent in real terms, the debtincome and debt-net worth ratios remained largely unchanged.The black-white gap in mean net worth remained unchanged, as did the Hispanic-white wealth gap.The wealth of households under age 35 continued to deteriorate in both absolute and relative terms between 2016 and 2019.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.168
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.267
GPT teacher head0.452
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations47
Published2021
Admission routes1
Has abstractyes

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