Do Imports Increase Unemployment? Empirical Estimates That Are Not Model Dependent
Bibliographic record
Abstract
Some Ricardian models would predict a fall in unemployment with trade liberalization. In contrast, the Heckscher-Ohlin model (Stolper Samuelson Theorem) would predict trade liberalization would cause a fall in wages for labor scarce countries, resulting in greater unemployment if there are wage rigidities. The choice of which theoretical model is used affects the empirical results obtained. This paper produces estimates of the change in unemployment due to a change in imports that are not model dependent. The estimates produced are total derivatives that capture all the ways that imports and unemployment are correlated. I find that unemployment increases with increased imports for Austria, Greece, Japan, Portugal, South Korea, Slovenia, and Sweden, but that unemployment decreases with increased imports for Australia, Belgium, Canada, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Latvia, the Netherlands, New Zealand, Norway, Poland, Slovakia, Spain, the UK, and the US.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".