Rising infection rates threaten to derail economic recovery
Bibliographic record
Abstract
Economic activity in Austria has been sharply curbed by the ongoing COVID-19 pandemic. During the first-wave lockdown, the OeNB’s weekly GDP indicator registered a decline of economic output by one quarter. After the exit from lockdown, the GDP gap narrowed very rapidly, amounting to –3½% compared to previous year levels in the first half of October. Among the hardest-hit sections of the economy, tourism benefited from markedly stronger domestic demand during the summer, which limited the year-on-year decline in overnight stays to 15% in July and August. Meanwhile, the travel alerts newly issued by a number of countries for Austria since mid-September have been taking their toll, though. For October, real-time data on card payments already point to a 40% decrease in overnight stays. In contrast, export performance has been improving, mirroring the slight upward trend in the production sector. By September, the decline in goods exports had dropped to a small percentage according to the OeNB’s export indicator. Looking ahead, the ongoing rapid rise in infection rates constitutes downside risks to growth, however. While the GDP forecasts for 2020 (about –7%) are fairly solid given strong third-quarter performance, the recovery projected for 2021 may turn out to be below the range currently expected (+4½ to +5%). The recovery in the labor market has already been slowing down. Registered unemployment exceeded the year-earlier mark by 71, 000 unemployed individuals by mid-October and thus a mere 30% of the peak measured in April, but unemployment has been shrinking at a decreasing pace. The early warning system for impending layoffs implemented by Public Employment Service Austria points to more layoffs coming in the weeks ahead. Inflation has been highly volatile in 2020 so far, reflecting energy price fluctuations as well as one-off effects (fashion clearance sales started later usual) and price measurement problems. In September, HICP inflation came to 1.3%. In line with the OeNB’s inflation forecast of September 2020, HICP inflation is expected to run to 1.4% in 2020 and to climb to 1.7% in 2021.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".