The Global Impact of Trump 2.0 Tariffs, with a Special Focus on India
Bibliographic record
Abstract
The study uses a computable general equilibrium (CGE) model based on GTAP-11 database to access the potential global impacts of the Trump 2 tariff regime. It simulates a series of unilateral US tariff hikes on China (60%), Mexico and Canada (25%), India, Western Europe and BRICS nations (20%). The General Equilibrium results show nominal GDP growth and welfare gains for the US at the expense of its leading partners, specially Canada, Mexico, and China. If retaliatory tariffs are imposed, some countries (e.g., India, Brazil, Russia, South Africa and Western Europe) can partially mitigate losses or gain modestly. However, trade war results in global welfare and GDP declines. US-India trade deal could offer mutual benefits and partially offset losses. Ultimately, the study highlights the beggar-thy-neighbour nature of protectionism and underscores the importance of multilateral, rule-based trade systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".