Essays on Disability and the Labour Market
Notice bibliographique
Résumé
My dissertation consists of three chapters about the effects of disability and disability policy.\nThe second chapter analyzes the variation in labour market outcomes across disabilities by representing disability as a bundle of characteristics. Rich with information on the characteristics of a disabling condition, I use the Participation and Activity Limitation Survey to compare the relative importance of each {characteristic} and their interactions on employment, wages, hours worked, and annual employment income. The disability {characteristics} include the type of activity limitation, number of limitations, timing of onset, severity, and persistence. I find substantial cross-sectional variation in labour supply, wages, and annual earnings across the activity limitations. Severity is most predictive of labour supply, while persistence/ duration of disability is predictive of all outcomes. Cognitive types of disabilities have more impact on wages than physical. Lastly, I find the timing of onset has important implications for wages and annual income. My results are consistent with disabilities that onset by age eighteen inflicting additional wage penalties through reduced skill accumulation.\nThe third chapter uses Canadian survey and administrative tax data to estimate the effect of disability types in the ten years after onset on the level and composition of personal income. I distinguish disability types based on reported limitations to daily activities and group them into physical, cognitive, or concurrent (both). I find substantial heterogeneity in the effect on personal income across types. Following onset, people with cognitive disabilities experience larger and more permanent declines in employment and market income than those with physical disabilities. Those with cognitive disabilities receive similar increases in total government transfers and fewer transfers from programs designed for disability. Instead, this group offsets some of the decline in market income with transfer programs that target families. Finally, the estimated effect of concurrent disabilities on market income and government transfers appears to be additive as it equals the sum of the effects of physical and cognitive disabilities.\nThe fourth chapter observes that individuals with an early-onset (before age 18) disability attain less education than their non-disabled counterparts. This equates to an eighteen percentage point gap in post-secondary attainment between these populations in Canada. This gap relates to how disability affects the cost and return to investing in education and the availability of additional income through social insurance. I build and estimate a structural life-cycle model of education and labour market choices to analyze the effect of social insurance on education investments for early-onset individuals. I focus on two social insurance policies in Canada: social assistance (SA) and disability insurance (DI). Using linked Canadian survey and administrative tax data to estimate the model, I reproduce the education gap, life-cycle employment rates, and attachment to SA and DI. I find the effect of disability on the accumulation of human capital accounts for two-thirds of the education gap. However, 18.6\\% of the gap is related to disincentives from social insurance policies, mainly from added benefits in SA available for beneficiaries with disabilities. Through counterfactual experiments, I find decreasing the value of SA poses an insurance-incentive trade-off for early-onset individuals. Instead, post-secondary grants for early-onset individuals increase their educational attainment, employment, and improves welfare. Moreover, this policy helps pay for itself through added tax revenues and reduced dependence on SA.
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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».