Austria's economy set to grow by close to 3% in 2018
Bibliographic record
Abstract
Economic growth in Austria peaked at the end of 2017. The first half of 2018 saw a gradual return to average growth. According to the most recent figures of the OeNB’s Economic Indicator of September 2018, this trend is set to continue in the second half of the year. Based on its quarterly forecasting exercise, the Oesterreichische Nationalbank (OeNB) expects real GDP in Austria to rise by 0.6% in the third quarter and by 0.5% in the fourth quarter of 2018 (quarter on quarter; adjusted for seasonal and working-day effects), and thus to remain above the long-term average growth rate of 0.4% until year-end. Thanks to particularly strong growth early in the year, the predicted growth rate for 2018 as a whole is 2.8%, slightly higher than in 2017. External economic uncertainties such as the further course of international trade conflicts and the Brexit negotiations represent a downside risk to the present forecast. Inflation is expected to remain on a steady course over the next few years. The OeNB forecasts a HICP inflation rate of 2.2% for both 2018 and 2019, followed by a slight decline to 2.0% in 2020. The fact that inflation is set to remain above 2% for the time being can be attributed mainly to favorable economic trends and robust growth in unit labor costs. HICP inflation is not expected to slow until 2020, when crude oil prices are likely to decline. Falling rates of inflation in the energy products market are expected to be largely balanced out by rising inflation rates in the services sector over the forecast horizon. As a result, core inflation (excluding energy and food) is projected to rise from 2.0% in 2018 to 2.3% in 2019 and level off at 2.2% in 2020.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.017 |
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".