Capital Income Flows and the Relative Well-Being of America's Aged Population
Bibliographic record
Abstract
One way to assess the effectiveness of a nation’s pension system is to measure its success in bringing the incomes of the aged close to those enjoyed by the nonaged. The comparability of income estimates for the aged and nonaged depends, however, on the relative accuracy of the income reports for the two populations. Unfortunately, some income items that are particularly important to the elderly, including occupational pensions, income derived from financial assets, and returns on homeowners’ net equity in their principal residence, are either unreported or significantly underreported in household surveys. In this paper we assess the effects of unmeasured and underreported income flows on the relative incomes of the aged and near-aged. We use survey data from the March Current Population Survey and the Survey of Consumer Finances. The latter survey contains information on wealth holdings as well as income. Using our broadest definition of income, which includes the return on net equity in an owner-occupied home and the predicted annuity flow from a household’s financial assets, the incomes of aged households in the middle of the old-age income distribution appear to be similar to those of nonaged households in the middle of the nonaged income distribution. In the top and bottom one-quarter of the old-age income distribution, incomes under the broadest income definition are substantially higher than those of nonaged households in the equivalent position of the income distribution. This income pattern diverges sharply from the one that would be inferred under the Census Bureau’s standard money income definition, which shows that aged households have noticeably lower incomes than the nonaged.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.000 |
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".