Inheritances and the Distribution of Wealth or Whatever Happened to the Great Inheritance Boom? Results from the SCF and PSID
Bibliographic record
Abstract
Using data from both the Survey of Consumer Finances (SCF) and the Panel Study of Income Dynamics (PSID), we found that on average over the period from 1984 to 2007, about one fifth of American households at a given point of time received a wealth transfer and these accounted for about a quarter of their net worth. Over the lifetime, about 30 percent of households could expect to receive a wealth transfer and these would account for close to 40 percent of their net worth near time of death. However, there is little evidence of an inheritance "boom." In fact, from 1989 to 2007, the share of households in the SCF reporting a wealth transfer fell by 2.5 percentage points. The average value of inheritances received among all households did increase but at a slow pace, by 10 percent, but wealth transfers as a proportion of current net worth fell sharply over this period, from 29 to 19 percent. We also found, somewhat surprisingly, that inheritances and other wealth transfers tend to be equalizing in terms of the distribution of household wealth. Indeed, the addition of wealth transfers to other sources of household wealth has had a sizeable effect on reducing the inequality of wealth.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".