World Economic Prospects Monthly
Bibliographic record
Abstract
Overview: Higher inflation tempers the growth outlook ▀ A deterioration in the near‐term outlook for China and the squeeze on real incomes from higher CPI inflation, particularly in advanced economies, have triggered a further downgrade to our GDP forecast. We expect world GDP growth of 5.7% this year, down 0.1pp from a month ago, before a slowdown to 4.5% in 2022 from 4.7% seen last month. ▀ We do not consider the issues facing Evergrande likely to be a catalyst for a major financial crisis in China. But weakness in real estate construction looks set to undermine near‐term economic prospects while electricity shortages and production cuts are hampering manufacturing. In response, we have cut our China GDP growth forecasts for both 2021 and 2022 by 0.4pp to 8.0% and 5.4% respectively. ▀ Meanwhile, the economic impact of the recent surge in energy prices will vary across economies. In many EMs, government price controls will lessen the inflationary impact but at the same time will either place greater pressure on public finances or lead to energy shortages. ▀ Pass‐through to inflation in the advanced economies is expected to be greater. While we have nudged down the outlook for consumer spending, the hit is expected to be tempered by a faster return of household savings rates to more normal levels. ▀ Although we have raised our world inflation forecast again, to 3.6% in 2022 from 3.3% last month in response to recent events, we do not think this marks the start of a higher inflation regime. At the margin, we now see a slightly faster pace of monetary policy tightening in the US — where we have brought forward the first interest rate hike to end‐2022 — the UK, Canada and a few EMs. But in advanced economies we still see little evidence of significant second‐round inflation effects, suggesting that inflation should still drop back as supply chain issues are gradually resolved.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.313 | 0.381 |
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".