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Record W4300943262 · doi:10.3386/w12391

How Household Portfolios Evolve After Retirement: The Effect of Aging and Health Shocks

2006· report· en· W4300943262 on OpenAlexaff
Courtney Coile, Kevin Milligan

Bibliographic record

VenueNational Bureau of Economic Research · 2006
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHealth and Retirement StudyEconomicsDemographic economicsEconometricsGerontologyMedicine

Abstract

fetched live from OpenAlex

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.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.173
GPT teacher head0.420
Teacher spread0.247 · 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 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

Citations22
Published2006
Admission routes1
Has abstractyes

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