World Economic Prospects Monthly
Bibliographic record
Abstract
Overview: world GDP growth to pick up further in 2018 ▀ Recent developments suggest that the solid performance of the world economy is being maintained and that the omens for 2018 are positive. So we have raised our global GDP growth forecast for 2018 slightly from 3.0% to 3.1% – a little stronger than the 2.9% rise we expect this year and the best result since 2011. ▀ Global GDP probably expanded by 0.8% in Q3 for the second quarter running, which would mark the best six‐month growth performance since the post‐global financial crisis rebound in 2010. It is too soon to make strong judgements about the exact pace of growth in Q4, but as yet the business surveys and trade indicators show no obvious sign of a slowdown in the recovery or world trade growth. ▀ In response to the ongoing positive tone of the data, we have raised our 2018 GDP growth forecasts slightly for several economies, including the US, China and the Eurozone, in turn lifting our 2018 world growth forecast to 3.1%. We expect the recent healthy pace of trade growth to carry over into next year and have raised our world trade growth forecast for 2018 from 3.7% to 4.2%, before a modest slowdown to about 4% in 2019. ▀ Based on this and some modest upward revisions to our oil and commodity prices forecasts for 2018, prospects look more favourable for commodity exporters and economies that are heavily integrated into global manufacturing chains in both the advanced world and emerging markets. ▀ Political uncertainties remain a downside risk. But economic risks may be tilted to the upside, as we see only a gradual response by central banks to the favourable economic backdrop. Another upside risk is that the US government unleashes a €1.5trn fiscal boost, which is rather larger than assumed in our baseline. This could lift US growth in 2018 to 3% or so and would have spillovers for the rest of the world and make our baseline forecast for both trade and investment growth to slow look too cautious. But beyond next year, the real impact is more ambiguous as it would be likely to trigger a faster pace of tightening by the Fed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.375 | 0.439 |
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".