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Record W3125342394

European household credit markets continue to fall: Key findings from the ECRI Statistical Package

2013· article· en· W3125342394 on OpenAlexaboutno aff
Ales Chmelar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinance, Markets, and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsDeleveragingHousehold debtDebtDemographic economicsEconomicsBusinessFinance
DOInot available

Abstract

fetched live from OpenAlex

The ECRI Statistical Package 2013, Lending to Households in Europe has revealed that European households registered a second consecutive year of falling real values of loans: 2012 followed the historical first drop recorded in 2011. While debt reduction proceeds across the continent, deleveraging to disposable income and to GDP remains limited due to unequal and sluggish recovery. The year 2012 was therefore one of stagnation in household-credit markets. Aggregate housing loans in the EU registered negative real growth rates, illustrating long-term problems in the overall economy. Together with record-low interest rates on housing loans in some countries, this finding reflects lower consumer confidence and the increased strain on households’ medium-term income. While this year’s degree of credit reduction in the EU overall has not been as significant as in previous years, Euro Area (EA) households registered a bigger drop in household credit than in 2011, underlying the prevailing economic problems of last year. At the same time, the EA periphery continued to reduce its household debt by record levels. The stagnation is also present in the normally rather resilient Central and Eastern European countries where the credit reduction extends beyond the former periphery to Poland and Slovenia. Households in Hungary, Eastern Balkan countries and in the Baltic states continued to reduce their debt exposure significantly throughout 2012. The Key Findings relate to the more detailed ECRI 2013 Statistical Package covering 38 countries: the 27 EU member states, three EU candidate countries (Croatia, Turkey and the Former Yugoslav Republic of Macedonia), the EFTA countries (Iceland, Liechtenstein, Norway and Switzerland) and four key global economies (the United States, Australia, Canada and Japan). The purpose of the package is to provide reliable statistical information that allows users to make meaningful comparisons in time and between these countries.

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)0.007
metaresearch head score (Gemma)0.034
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.016
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.005

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 head0.022
GPT teacher head0.184
Teacher spread0.162 · 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
Published2013
Admission routes1
Has abstractyes

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