Economic Motives and Migration: The Canada-US Experience
Bibliographic record
Abstract
After tax wages differ considerably across countries, providing strong economic incentives for individuals to migrate. Increasing political integration and regional trade agreements facilitate international labor mobility, making these economic motives more important relative to the costs of migration. We undertake an empirical analysis using economic incentives to explain the migration of college-educated Canadian workers to the United States in the 1980’s. We develop an overlapping generations model of migration with heterogenous agents. We calibrate the model to match the total flow of young, collegeeducated Canadian workers to the US from 1980 to 1990. The model delivers a rich set of predictions regarding the migration choices of agents differentiated by income and age. We use the calibrated model to answer policy questions related to migration, such as the effects of Canada harmonizing her tax code to the US tax code. We find that tax harmonization can reduce the migration of college-educated Canadians by 42%. However, the decline in migration among the top quintile of workers is only 33 %.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".