Essays in Macroeconomics and Labour Mobility
Bibliographic record
Abstract
This thesis consists of three distinct chapters. The first chapter delves into the effects of tuition hikes on students’ choice of majors in the United States. Traditionally, passion, interests, and talents have been the primary factors influencing high school graduates’ decisions when choosing a major in college, without much concern for job prospects or the ability to repay student loans. It may be time to reassess this approach. Since the Great Recession, public universities in the United States have experienced a significant increase in tuition fees, leading to notable shifts in students’ choice of majors. The STEM (Science, Technology, Engineering, and Mathematics) fields have gained popularity, with the share of STEM degrees awarded rising from 16% in the academic year 2009-10 to 43% in 2015-16, according to the National Center for Education Statistics (NCES). Conversely, the proportion of degrees awarded in the arts and humanities (ARTS) has significantly declined, with a 5% decrease in 2015 compared to the previous year and nearly a 10% decrease from 2012 (Jaschik ,2017). This decline in humanities and liberal arts degrees poses a significant issue for policymakers and universities in the United States, often leading to the discontinuation of certain programs. Building upon the previous work of Ionescu (2009), who examines the effects of financial aid policies on enrollment decisions and default rates, my research focuses on the costs associated with investing in higher education borne by students and optimal decisions in terms of major choices. The second chapter of my research focuses on estimating the substitutability between public and private consumption in Canada. Using annual data from Statistics Canada, I estimate a model in which the annual data for government and private consumption from the Canada’s National Statistical Agency is fitted into a constant elasticity of substitution (CES) consumption function. Through cointegration tests and estimation results, I have identified an Edgeworth complementarity between public and private spending in Canada, suggesting that they are interdependent and exhibit a close relationship. The third chapter analyzes interprovincial migration of skilled workers in Canada. It aims to explain the out-migration of skilled workers in Quebec as skilled workers exodus has a serious impact on the tax revenue and productivity. Although Quebec attracts students with high ability each year, as it hosts some of the best English-speaking universities in Canada, many of these individuals choose to leave the province after finishing their studies. This exodus is often due to language barriers that hinder their integration into the Quebec labour market. Retaining anglophone graduates in the province after they obtain their diplomas has become one of the most challenging problems faced by the Quebec government over the past decades. Notably, Quebec is the only province that has experienced net out-migration every year since 1963, and it has the highest out-migration. The issue has been a real problem for policymakers as the province experiences losses through out-migration of its potential skilled workers. This paper shows that the out-migration of skilled workers not only result in a loss of tax revenue but also contributes to Quebec’s debt-to-GDP ratio exceeding the recommended 45% threshold set by the International Monetary Fund. To explain Canadian interprovincial migration, I have constructed a model calibrated to Canadian economies and conducted policy simulations to identify effective strategies for retaining skilled workers.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".