World Economic Prospects Monthly
Bibliographic record
Abstract
Overview: Diverging fortunes across the Atlantic ▀ We have revised up marginally our 2017 world GDP growth forecast to 2.8%, reflecting the boost from a relatively broad‐based strengthening in global trade. However, at a regional level the picture is quite mixed, with several upgrades in Europe but a more cautious outlook for the US in 2018. ▀ Global indicators continue to point to robust and stable activity in the world economy. The manufacturing PMI held steady in Q2, while the services index had the best quarter in over two years. ▀ We have lowered our forecast for oil prices to $45 in H2 2017 and $45.5 in 2018, in line with current spot prices. The change reflects not only increased output in the US but weak demand from OECD countries. This is being reflected in a lower forecast for consumer prices in several economies. ▀ The Eurozone is expanding at the fastest pace in a decade, leading to a dramatic shift in sentiment in the short term. This has led us to raise our 2017 GDP forecast again to an above‐consensus 2.2%. Despite the strong economic momentum, recent communications from the ECB have prompted us to revise our monetary policy call. We expect bond purchases to be reduced to €40bn a month from the start of 2018 and then reduced to €20bn a month in H2, with QE ending at end‐2018. ▀ Despite the stronger global environment, the US remains stuck at a 2% growth rate. Our short‐term forecast remains unchanged but we have downgraded our 2018 outlook on the back of sizable reduction in the envisaged fiscal stimulus package, from a previous $1.2 trillion to $500bn. In light of our lower growth and inflation forecasts, we now see the Fed raising rates only twice before the end of 2018. ▀ A renewed fall in oil prices and more hawkish signals from central banks in advanced economies may worsen the external backdrop for emerging markets (EM). Meanwhile higher global bond yields could dampen capital flows to EMs, although lower inflation from weaker oil prices will lead to attractively high real rates in many of them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.366 | 0.405 |
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".