How Household Portfolios Evolve After Retirement: The Effect of Aging and Health Shocks
Bibliographic record
Abstract
In this paper, we study how the portfolios of elderly U.S. households evolve after retirement, using data from the Health and Retirement Study (HRS).In particular, we investigate the influence of aging and health shocks on a household's ownership of various assets and on the dollar value and share of total assets held in each asset class.We find that households decrease their ownership of most asset classes as they age, with the strongest evidence for principal residences and vehicles, while increasing the share of assets held in bank accounts and CDs.Consistent with prior studies, we find that the death of a spouse is a strong predictor of selling the principal residence.However, we find that widowhood also leads households to sell vehicles, businesses, and real estate and to put money into bank accounts and CDs, and further that other health shocks have very similar impacts.Finally, we explore why health shocks affect asset holdings and find that the effect of a shock is greatly magnified when households have physical or mental impairments.This suggests that factors other than standard risk and return considerations may weigh heavily in many older households' portfolio decisions.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".