World Economic Prospects Monthly | Global
Bibliographic record
Abstract
Tariffs likely to spark a sharp slowdown, but not a recession ◼ We continue to expect the US tariff hikes will trigger a slowdown in global GDP growth from 2.8% last year to a sluggish 2.3% in both 2025 and 2026.While we think the US economy will suffer a bigger hit to growth than other major economies, we don't think that the US tariff hikes spell an end to US economic exceptionalism.By 2026, the US is likely to head back towards the top of the growth pack.◼ It's still too early to get a reliable assessment of the initial impacts of the US tariff policy changes from recent economic data.Survey-based activity indicators generally softened in April, but don't point to widespread panic around the globe.For instance, the JP Morgan global manufacturing PMI eased to 49.8, but it is only just into contractionary territory and was weaker during most of H2 2024.It's never wise to draw too much from a single data point, particularly the survey-based indicators which have generally been a poor gauge of economic trends since the pandemic.◼ Our baseline forecasts remain conditional on similar tariff assumptions to a month ago.We assume that tariffs on Canada and Mexico will remain in the mid-to-low teens until H2 next year, when we anticipate a new USMCA trade deal will be agreed and bring tariff rates back to around 2%. Tariffs on the rest of the world, excluding China, are anticipated to remain around 10%. ◼ In response to signs that both the US and China might be willing to negotiate on tariffs, we anticipate a lower path for tariffs imposed by the US and China on each other.The average effective US tariff rate on China is anticipated to come down to around 90% over the next month or two and eventually fall to 60%, in line with Trumps' presidential campaign pledge.◼ However, tariffs of that size remain punitive, and we don't anticipate this will provide much of an economic boost to either economy.For China, this will particularly be the case if policymakers scale back any stimulus designed to insulate the economy from the US tariff hikes. Chart 1: Any underperformance of the US economy isn't expected to last
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.442 | 0.467 |
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".