World Economic Prospects Monthly | Global
Bibliographic record
Abstract
Outlook remains resilient despite mounting risks ◼ As Donald Trump's inauguration as US president approaches, there has been little additional clarity regarding the exact nature of the policies he will pursue in office.We still expect world GDP growth will pick up to 2.8% this year and 2.9% in 2026, following an estimated 2.7% expansion in 2024.But risks to our outlook remain high, reflecting uncertainty about both the scale and timing of changes to US fiscal, tariff, and migration plans.◼ Recent news continues to suggest that the US economy is performing strongly, and we expect this resilience to continue thanks to solid fundamentals for consumer spending and investment.We remain sceptical that ongoing actions by Chinese policymakers will be enough to prevent a further modest slowdown in growth this year.Activity in Europe may gain some momentum after a poor 2024, but the broad picture is still one of relatively lacklustre growth.◼ Our baseline forecast continues to assume that the US imposes tariffs on a select group of economies targeted at specific sectors, which are anticipated to come into operation around the end of this year.The moderate adverse growth effects of these measures will initially be more than offset by looser US fiscal policy.◼ Risks are still skewed towards more extensive or a faster implementation of tariffs.Even so, Trump is unlikely to be willing or able to carry out his threat to raise tariffs on China, Mexico, and Canada on the first day of his presidency.Indeed, we continue to see the risk of blanket tariffs on all imports to the US as unlikely.Extra targeted tariffs compared to our baseline are plausible, but the risk of tariff shifts that are a gamechanger for US and global growth prospects remains low.◼ The other key recent development has been the renewed surge in bond yields.At the time of writing, US, UK, and German 10-year government bond yields were at least 50bps higher than at the start of December.Despite the sharp moves in yields we are sceptical that inflationary pressures are building, we think it mainly reflects a pick-up in term premia in response to greater uncertainty.Further increases in yields would be needed for fiscal policies to be recalibrated.Chart 1: The world economy is expected to maintain the steady pace of growth seen in 2023 and 2024
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.323 | 0.318 |
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".