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Record W1999322013 · doi:10.1177/0027950108096583

Housing market downturns and Euro Area growth

2008· article· en· W1999322013 on OpenAlexaboutno aff
Ray Barrell, Tatiana Fic, Sylvia Gottschalk, Iana Liadze

Bibliographic record

VenueNational Institute Economic Review · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGerman Economic Analysis & Policies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsConsumption (sociology)RecessionInflation (cosmology)SlowdownQuarter (Canadian coin)Percentage pointReal gross domestic productAgricultural economicsDemographic economicsMonetary economicsGeographyMacroeconomicsEconomic growth

Abstract

fetched live from OpenAlex

The Euro Area economy grew by 0.8 per cent in the first quarter of this year, and is proving more resilient than anticipated in our April forecast. We were then expecting a markedly less robust outturn of an increase of 0.4 per cent. However, despite this positive start, we still anticipate a downturn in the Euro Area's year-on-year economic growth. After peaking at 2.9 per cent in 2006, real GDP growth is projected to slow down to around 2 per cent over the forecast period. Sluggish domestic demand and diminishing contributions from net trade both contribute to this downturn. Household consumption is forecast to expand by 1 per cent in the short term, down from 1.6 per cent in 2007. Consumption growth is expected to be considerably weaker than in 2007 due to accelerating inflation and the slowdown in the growth of housing wealth, particularly in France, Ireland and Spain as well as elsewhere. Moreover, real disposable income growth is expected to slow down from 2 per cent in 2007 to about 1¼ per cent this year. Nominal wages are expected to rise by 3½ per cent on average this year, and HCP inflation is likely to pick up strongly to slightly more than 3¾ per cent per annum, 1½ percentage points above the level of last year.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.074
GPT teacher head0.254
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2008
Admission routes1
Has abstractyes

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