Three essays on health and labour economics
Bibliographic record
Abstract
The dissertation consists of three essays. The first essay examines a dynamic effect of diabetes on employment. The second essay uses a broader measure of health and investigates its interaction with employment. The third essay explores a dynamic effect of education on hourly wage. The first essay investigates the diabetes effect on employment in Canada. The data is taken from the National Population Health Survey and men and women between age 25 and 64 are analysed separately. In contrast to the previous static studies on the effect of diabetes on labour market outcomes, this essay uses a dynamic model to identify the impacts of diabetes on employment in Canada. Results show that diabetes has a positive but insignificant effect on employment for men. The effect of diabetes on employment for women is negative and significant. The results confirm the signs and significance of diabetes coefficients estimated by static studies; however, the numbers are much smaller. Particularly, precise estimates of diabetes effect on employment would be helpful for policy makers to know the economic burden and design the appropriate policies. The second essay uses a broader measure of health to explore the relationship with employment. In contrast to previous static Canadian studies on the impact of health on labour market outcomes, this essay estimates a dynamic model using simultaneous equations to obtain more precise model specification for the interaction of health and labour market outcome. Results show that there is a high state dependency in employment and health for both men and women. Moreover, there is a highly significant and positive effect of health on employment for both men and women. As a result, health policies that have positive and direct effects on health can have positive and indirect effects on employment. The third essay investigates the return to education using a dynamic approach in Canada. This essay uses the longitudinal Survey of Labour and Income Dynamics and estimates the dynamic model for men and women between the age of 25 and 64 separately. In contrast to the previous static Canadian studies on the return to education, this essay estimates a dynamic Mincer model through a system GMM method to obtain more precise model specification for the return to education. Results demonstrate that the hourly wage is highly persistent for both men and women between age 25 and 64. The results also show that the return to schooling is increasing at the beginning of the working life for both men and women compared to a constant return to schooling by static Mincer function. Identifying the return to education can be useful for policy makers to decide on education expenditures and finance schooling programs.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".