Notice bibliographique
Résumé
BACKGROUND: Like most of other developed countries, Canada experienced baby boom in the 20 years after World War II. With the eldest baby turned 65 in 2011, it is expected that a considerable number of people will retire in coming years and consequently, retired people will soon constitute a significant part of Canadian population. In this context, an interesting question would be how retirement impacts mental health. This question is related to the well-being of the retired population as well as to over all health care expenditures. AIMS: The major objective of this study is to examine the impact of retirement on mental health as measured by the Short Form Depression Scale. This study further conducts separate analyses to examine whether the impact of retirement on mental health differs between males and females, and among different education and income groups. METHODS: This study uses large scale Canadian National Population Heath Survey (Longitudinal Component) data and adopts fixed effect method and fixed effect instrumental variable method to deal with possible endogeneity problem. RESULTS: After controlling for unobserved individual specific heterogeneity, the study found that retirement has an insignificant impact on depression. As a robustness check, the study utilizes logit, conditional fixed effect logit, and fixed effect instrumental variable regression on a dichotomous variable representing depression and found that retirement has an insignificant impact on depression. The study further examined this issue using different subgroups based on gender, education and marital status, and again found that impacts of retirement on depression are not statistically significant. IMPLICATIONS FOR POLICY: Though the coefficients are statistically insignificant, however, most of the results are economically meaningful since the magnitudes are relatively large, implying very large effects. The effects of retirement on mental health appear to be complex and multidimensional; however, based on the FE-IV models, most of the effects seem to suggest that there may be some increase in depression symptoms. The findings of this study will have important policy implications. If retirement worsens mental health, then policy encouraging retirement may actually increase health care expenditures. On the other hand, if retirement improves mental health, then such policy will likely to decrease health care expenditure. Studies based on data from Canada and other OECD countries suggest that the provisions of social security programs themselves often provide strong incentive to leave the labor force early. The finding of this study that retirement has negative impact on mental health in Canada will imply that current Canadian policy of encouraging early retirement is likely to increase mental health care expenditure. IMPLICATIONS FOR FURTHER RESEARCH: There are a number of ways to extend this study. Depending on the availability of data, future studies can focus on sub populations: voluntary retiree/ involuntary retirement, early retiree/ late retiree and complete retiree/ partial retiree. Future study can also conduct more detailed analysis by including variables such as previous job characteristics, voluntary activity during retirement and family characteristics.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».