MétaCan
Menu
Back to cohort
Record W1480623022

Cyclical Recovery Making Slow Progress

2002· article· en· W1480623022 on OpenAlexaboutno aff
Ewald Walterskirchen

Bibliographic record

VenueMonographien · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)RecessionTurning pointBusiness cycleEconomicsSeasonal adjustmentPoint (geometry)Demographic economicsEconomyGeographyMacroeconomicsPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

Responses by firms in the regular WIFO business survey have signalled an upturn in Austrian industrial activity for almost half a year. In April and May, judgements on current business conditions have not improved further. Nevertheless, prospects for the next few months remain positive. The international recession has been overcome. An upturn is under way, although its strength is yet uncertain. In the USA, real GDP picked up markedly both in the fourth quarter 2001 and in the first quarter 2002, supported by a decidedly pro-active policy stance. In western Europe, early expectations were somewhat disappointed, as the EU economy stagnated in the first quarter. While last year's downturn in the EU was highly synchronised with that in the USA, the indications for a rebound this year are less clear. Still, all leading indicators point to a recovery. In Austria too, confidence in the business sector has been growing for months. In particular, production expectations and other forward-looking indicators are rated much more positive, although the overall sentiment has improved no further in April and May. According to provisional calculations, manufacturing output in the first quarter matched the year-earlier level, while construction activity fell sharply in the winter season. The steeper the cyclical downturn in a sector, the more marked is also the negative seasonal profile. In the first four months of the year, some 7, 000 jobs (–3¼ percent) were lost in the construction sector from the previous year. Retail (excluding motor cars) and wholesale trade both edged up by ½ percent in volume in the first quarter, but the slump in car sales (–5 percent in real terms) dragged the sector's value added down below the year-earlier level. Passenger car purchases react rather strongly to short-term variations in incomes and costs (oil prices). Even stronger, however, are cyclical fluctuations in business investment. The latter remained sluggish in the first quarter, leading to a nominal decline by 11 percent year-on-year in imports of machinery and transportation equipment in January and February combined. Tourism, on the other hand, continued its positive trend in the winter season, with earnings rising by 4½ percent at current prices. Inflation is abating gradually. In April, the rate edged down to 1.8 percent, mainly due to an easing of prices for vegetables, price cuts for mobile telephones and of lower energy costs compared with last year. In an international comparison, Austria claims a high rank in terms of price stability: on the Harmonised Consumer Price Index, prices went up by 1.6 percent, compared with 2.4 on average for the euro area. While in some countries the changeover to euro cash money may have added to inflation, that has not been the case in Austria. As could be expected, no turnaround is as yet visible on the labour market. Official statistics give a total of 3, 155, 600 dependent employees for May, 5, 500 more than one year ago. However, this figure is less relevant for the cyclical analysis, as it includes non-working recipients of child-care benefits whose job contracts have not been terminated. The adjusted figure of jobholders (excluding child-care benefit receivers and people in military service) went down by 11, 600 year-on-year in May. The decline has been somewhat stronger than on average in the first four months of the year. Job losses in manufacturing (–13, 000 in April) and construction led to an increase in unemployment benefit payments, whereas those in transportation (postal service, telecom, railways) and the public sector were accommodated mainly by transition into retirement.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.006

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.

Opus teacher head0.053
GPT teacher head0.319
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueMonographienSame topicRegional Development and PolicyFrench-language works237,207