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Enregistrement W127380083

Research on Pensions and Social Security

2000· article· en· W127380083 sur OpenAlexaboutno aff
Alan L. Gustman, Thomas L. Steinmeier

Notice bibliographique

RevueEconstor (Econstor) · 2000
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueRetirement, Disability, and Employment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSocial securityPensionQuarter (Canadian coin)Health and Retirement StudyRetirement ageIncentiveOrder (exchange)EconomicsActuarial sciencePopulationDemographic economicsWork (physics)Labour economicsFinanceGerontologyDemographyMedicineSociologyGeography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Thomas L. Steinmeier [*] Pensions and Social Security are fundamental parts of saving. They each account for about a quarter of the $500,000 in total wealth held on average by families approaching retirement age. [1] Pensions have a large effect on retirement incentives as well. A man with a defined benefit (DB) pension plan who works in the year before qualifying for early retirement on average will find his benefits increased by about 60 percent of one year's pay. For a woman, the increase amounts to about one-third of a year's pay. [2] Accordingly, it is necessary to have accurate measures of pensions and Social Security in order to measure the wealth of those entering retirement, to understand saving and retirement behavior, and to determine the true impact of policies meant to influence saving and retirement. The Health and Retirement Study To further our understanding of pensions, Social Security, and their effects, we recently helped to develop and analyze data from the Health and Retirement Study (HRS). [3] The HRS, originally fielded in 1992 as a panel survey of 12,652 individuals from households with at least one member born in 1931-41, now has added additional cohorts (age groups) so that it is representative of the U.S. population over the age of 50. Crucial to our work, the HRS has collected pension Summary Plan Descriptions (SPDs) from the employers of two-thirds of those in the original survey who were covered by a pension in 1992. The HRS also collected detailed descriptions of pensions from this group's employers on previous jobs. Also central to our work, 80 percent of the survey respondents granted permission to the HRS to obtain their earnings histories from the Social Security Administration. Social Security records were linked successfully for 95 percent of those granting permission, or 75 percent of the HRS sample. The HRS cohort is an interesting group to study: they are the group closest to retirement age and the first covered by Social Security to learn that the present value of their benefits will fall below the present value of their taxes paid. [4] Thus, the HRS data can teach us a great deal about: retirement incentives; the relationship of pensions and Social Security to total saving and retirement outcomes; complexities in behavior beyond those incorporated in the simple lifecycle model; and the relationship between pension and Social Security policies and the distribution of benefits plus behavioral outcomes. Distributions of Pensions, Social Security, Wealth, and Lifetime Earnings From the HRS data, we have learned a great deal about the distribution of total wealth and its components -- including pensions and Social Security -- and about how they vary with lifetime earnings, for households and for individuals. Contrary to the general impression, pensions are distributed widely among households. Although only half of the employed individuals in the HRS have a pension, three-fourths of HRS households were covered by a pension at one time, and two-thirds of HRS households own the rights to a pension or pension income. In 1992, pension wealth was worth $191,000 per HRS household with a claim on a pension. Moreover, less than 10 percent of pension wealth has been lost because covered respondents have cashed out their benefits after leaving a pension covered job. The share of family wealth held as pensions increases with family lifetime earnings, rising from less than 5 percent of total wealth for those in the bottom 10 percent of lifetime earners, to 30 percent of total wealth for those in the 75th to 95th percentiles of lifetime earners. [5] Although men hold pensions that are much more valuable than the pensions held by women -- for example, at age 55, men hold DB pensions worth $200,000, while women's holdings are $108,000 -- the differences are explained largely by differences in earnings. Benefit-earnings ratios are actually higher for women with DB plans than men: for example, at age 60, benefit-earnings ratios are 20 percent for women and 16 percent for men. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,064

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0030,005
Études des sciences et des technologies0,0020,002
Communication savante0,0020,003
Science ouverte0,0000,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0190,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,202
Tête enseignante GPT0,439
Écart entre enseignants0,236 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2000
Routes d'admission1
Résumé présentoui

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