The Economics and Politics of Revoking NAFTA
Bibliographic record
Abstract
We provide a quantitative assessment of both the aggregate and the distributional effects of revoking NAFTA using a multi-country, multi-sector, multi-factor model of world production and trade with global input-output linkages. Revoking NAFTA would reduce US welfare by about 0.2%, and Canadian and Mexican welfare by about 2%. The distributional impacts of revoking NAFTA across workers in different sectors are an order of magnitude larger in all three countries, ranging from -2.7 to 2.26%in the United States. We combine the quantitative results with information on the geographic distribution of sectoral employment, and compute average real wage changes in each US congressional district, Mexican state, and Canadian province. We then examine the political correlates of the economic effects. Congressional district-level real wage changes are negatively correlated with the Trump vote share in 2016: districts that voted more for Trump would on average experience greater real wage reductions if NAFTA is revoked.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".