Essays on Population Economics, the Economics of Population Aging and Health Economics
Notice bibliographique
Résumé
The three chapters of this dissertation analyze topics within the realm of population economics, the economics of population aging and health economics. Chapter 1: Between 1990 and 2019 Manitoba, Newfoundland and Labrador, Nova Scotia, Ontario, Quebec, and Saskatchewan passed or amended legislation allowing physicians to split income with family members via Canadian-Controlled Private Corporations; three provinces (Alberta, British Columbia and New Brunswick) allowed for this before 1990 (we exclude Prince Edward Island and the three territories). For some, there are large financial benefits from income splitting which can exceed $50,000 CAD per year. We use a difference-in-differences model to estimate the effect of not allowing physicians to split income on the net interprovincial migration of physicians to provinces that enacted income splitting rules after 1990. The annual net migration flow to these provinces increases on average by 21% lower when they allow for income splitting compared to when they did not. This equates to nearly 0.3% of the average physician workforce per year. Our results have implications for economic policy and provide information about the utility functions of physicians: it is suboptimal if Canadian provinces design legislation/policy with the intention of poaching physicians from one another; and physicians impose a large cost onto their former healthcare systems and patients when they migrate. Presumably, for those who move as a result of the policy (the increase in the flow), the utility derived from income splitting’s financial benefit outweighs the value of such costs in the physicians’ utility function. Chapter 2: I contribute to the political economy and cost-benefit analysis literatures pertaining to Covid-19 public health measures (PHMs). Specifically, I address how individuals’ net-present-value (NPV) of these policies varies with age across the Canadian population, and how that variation influences the political economy of the PHMs. Deaths per 100k persons from Covid-19 vary markedly across jurisdictions within the USA and Canada, as well as between these two countries. The USA had nearly three times more deaths per capita than Canada – partially due to stricter and better respected PHMs in most Canadian provinces than in most American states. Significant economic costs are associated with these PHMs; and a broad body of literature exists to measure the macro and microeconomic implications of these policies. It is also clear that mortality due to Covid-19 strongly depends on age. Bergstrom and Hartman’s (2008) framework, which employs population projections and lifetables to estimate the political support for public pension reform, is adapted to this context. Assuming individuals’ support for PHMs depends on their expected personal NPV, then the benefits of PHMs are the expected value of life-years saved from not contracting the Covid-19 virus and the costs account for the expected lost income due to the unemployment caused by the PHMs as well as the value of forgone consumption/leisure. From an individualistic perspective, the results indicate the majority of Canadians should support the Covid-19 PHMs. Chapter 3: I explore the possibility that population aging is contributing to slower economic growth through changes in household consumption decisions. I estimate, empirically, the relationship between the basket of goods consumed by aggregate households and their median age. Recently, Cravino, Levchenko and Rojas (2022) analyzed data from the United States and found a positive relationship between the age of households and the share of consumption they dedicate to services. Using household consumption data on 12 countries - which includes both developing and developed nations - the relationship between the fraction of household consumption attributed to services and the Old Age Dependency Ratio (OADR) is estimated. Conditional on GDP per capita, I observed that households consume a larger share of services as the population OADR increases. The additional expenditure is concentrated on hospitality and restaurants, and to a lesser extent, transportation and privately obtained health care.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,002 |
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.
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 source (Gemma direct ou Codex distillé), 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 ».