Three essays on lifecycle analysis
Bibliographic record
Abstract
This dissertation consists of three independent essays using dynamic lifecycle analysis. In the first essay a general equilibrium model is constructed to study the macroeconomic effects and welfare implications associated with eliminating mandatory retirement in Canada, both in the long and the short run. Political feasibility is examined by measuring the popular support that this type of policy might have under two labour market scenarios: in transitions in which the wage rate clears the labour market and transitions with a sticky wage and youth unemployment. The second essay studies the welfare cost and distributional effects of a change in the pennanent rate of inflation in a model that incorporates both residential and nonresidential capital. The framework is a dynamic general equilibrium lifecycle economy populated by heterogeneous individuals with respect to age, income and homeownership status. A numerical analysis is provided based on parameter values from the U.S. economy. The results show that the burden of inflation is unevenly distributed across income groups and hurts low income individuals more than high income individuals. This outcome arises from a number of characteristics and tax provisions available in the housing market. In the third essay the Keynesian framework and the lifecycle model are combined to study the transitional effects of an exogenous shock on savings held by inhabitants of a small open economy. The focus is on studying impulse responses from the shock and convergence to a new equilibrium under different demographic scenarios. The results show that negative asset shocks are associated with a larger response of the aggregate demand in populations with a higher proportion of middle age and older consumers. However, when compared with economies with a stationary population, the larger initial reduction in demand is followed only by milder changes in transition.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".