A GLOBAL VIEW OF CROSS-BORDER MIGRATION
Bibliographic record
Abstract
This paper evaluates the global welfare impact of observed levels of migration using a quantitative multi-sector model of the world economy calibrated to aggregate and firm-level data. Our framework features cross-country labor productivity differences, international trade, remittances, and a heterogeneous workforce. We compare welfare under the observed levels of migration to a no-migration counterfactual. In the long run, natives in countries that received a lot of migration—such as Canada or Australia—are better off due to greater product variety available in consumption and as intermediate inputs. In the short run, the impact of migration on average welfare in these countries is close to zero, while the skilled and unskilled natives tend to experience welfare changes of opposite signs. The remaining natives in countries with large emigration flows—such as Jamaica or El Salvador—are also better off due to migration, but for a different reason: remittances. The welfare impact of observed levels of migration is substantial, at about 5% to 10% for the main receiving countries and about 10% in countries with large incoming remittances.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".